Bringing Health Care Online: The Role of

Information Technologies

September 1995

OTA-ITC-624

GPO stock #052-003-01433-5
Recommended Citation: U.S. Congress, Office of Technology Assessment, Bringing

Health Care Online: The Role of Information Technologies, OTA-ITC-624 (Washington,

DC: U.S. Government Printing Office, September 1995).
iii

oreword

nformation technologies are transforming the way health care is delivered. Innovations such as computer-based patient records, hospital information systems, computer-based decision support tools,

community health information networks, telemedicine, and new

ways of distributing health information to consumers are beginning to

affect the cost, quality, and accessibility of health care. Changes in the

health care delivery system, including the emergence of managed health

care and integrated delivery systems, are breaking down the organizational barriers that have stood between care providers, insurers, medical

researchers, and public health professionals. Old distinctions between

clinical health information and administrative health information are

gradually eroding as new health care delivery patterns emerge that are

supported by, and in some cases reliant on, the widespread use of networked computers and telecommunications.

Bringing Health Care Online: The Role of Information Technologies

discusses the synergy between information technologies and new trends

in the health care delivery system as health care is brought online. It identifies some of the opportunities to improve health care delivery through

increased use of information technology, and discusses some of the conceptual, organizational, and technical barriers that have made its adoption so uneven. The report identifies key technologies and shows how

they are being used to communicate clinical information, simplify administration of health care delivery, assess the quality of health care, inform the decisionmaking of providers and administrators, and support

delivery of health care at a distance.

OTA appreciates the assistance of the project advisory panelists,

workshop participants, and contractors, as well as the many other individuals who participated in the study. OTA values their perspectives and

comments; the report is, however, solely the responsibility of OTA.

ROGER C. HERDMAN

Director
iv

dvisory Panel

Clement McDonald

(Chair)

Distinguished Professor of

Medicine

Indiana University School of

Medicine

Indianapolis, IN

June Abbey

Director of Research

Institute of Innovation

Shadyside Hospital

Pittsburgh, PA

Stephen Deutsch

Professor

Labor Education and Research

Center

University of Oregon

Eugene, OR

Elliott Fisher

Associate Professor of Medicine

Dartmouth Medical School

Hanover, NH

Bonnie Guiton Hill

Dean

McIntire School of Commerce

University of Virginia

Charlottesville, VA

James Hazelrigs

Executive Director

Medical Database Commission

State of North Carolina

Raleigh, NC

Susan Horn

Senior Scientist

Institute for Health Care Delivery

Research

Intermountain Health Care

Salt Lake City, UT

James Hunt

Distinguished Professor

Health Sciences Center

University of Tennessee

Memphis, TN

Nancy Milio

Professor of Health Policy &

Administration

University of North Carolina

Chapel Hill, NC

Lori Muhlstein*

Market Manager, Health Care

Bell Atlantic Corp.

Falls Church, VA

John Nyman

Associate Professor

Institute for Health Services

Research

University of Minnesota

Minneapolis, MN

Madison Powers

Senior Research Scholar

Kennedy Institute of Ethics

Georgetown University

Washington, DC

Jane Preston

President

American Telemedicine

Association

Austin, TX

Marsha Radaj

Vice President, Operations

Wisconsin Health Information

Network

Brookfield, WI

William Reed

Quantum Health Resources, Inc.

Indianapolis, IN

Bert Tobin

Executive Vice President

Benton International

New York, NY

Bradley Ware

Fairfax, VA

________________

*Until December 1994

Note: OTA appreciates the valuable assistance and thoughtful comments provided by the advisory panelists. The panel does not,

however, necessarily approve, disapprove, or endorse this report. OTA assumes full responsibility for the report and the accuracy of its

contents.
v

roject Staff

Peter D. Blair

Assistant Director, OTA

Industry, Commerce, and

International Security Division

Clyde Behney

Assistant Director, OTA

Health, Education, and

Environment Division

Andrew W. Wyckoff

Program Director

Industry, Telecommunications,

and Commerce Program

James W. Curlin

Program Director1

Industry, Telecommunications,

and Commerce Program

Sean Tunis

Program Director

Health Program

Karen G. Bandy

Project Director

Jean E. Smith

Assistant Project Director

William Creager

Contractor/Congressional Fellow

David Klingman

Senior Analyst

Laura Stricker

Research Analyst2

ADMINISTRATIVE STAFF

Liz Emanuel

Office Administrator

Karry Fornshill

Secretary

Diane Jackson

Administrative Secretary

Karolyn St. Clair

PC Specialist

PUBLISHING STAFF

Mary Lou Higgs

Manager

Chip Moore

Production Editor

Bonnie Sparks

Electronic Publishing Specialist

Chris Onrubia

Senior Graphic Designer

CONTRACTORS

Aspden Associates

Collin Canright

Health Economics Research, Inc.

The Orkand Corp.

Phoenix Planning & Evaluation,

Ltd.

Project HOPE, Center for Health

Affairs

________________

1Through September 1994

2Through June 1994
vi

1 Introduction, Summary, and Options 1

Challenges and Opportunities for Information

Technologies 2

Trends in the Health Care System 5

Congressional Interest 9

Report Summary 10

Other Applications 23

2 Information Technologies for

Transforming Health Care 29

Islands of Automation 30

The Life Cycle of Health Information 34

Key Technologies for the Emerging Health Information

Infrastructure 42

Sharing the Common Pool of Data 68

Policy Issues and Options 73

3 Networks for Health Information 79

Administrative Simplification 80

Administrative Activities in Health Care 83

Provider Administrative Activities 83

Exchanging Information Between Providers

and Payers 84

Linking Health Care Providers With Suppliers 93

Pharmaceutical Industry EDI 94

Community and Regional Networking 95

Costs and Cost-Effectiveness 103

Policy Implications of Electronic Health

Information 109

Policy Considerations for Congress 118

4 Using Information Technology to Improve

the Quality of Health Care 123

Clinical Decision Support 124

Performance Assessment 142

Conclusions 152

ontents
vii

5 Telemedicine: Remote Access to Health

Services and Information 159

Telemedicine’s Potential Effects 160

Telemedicine Applications 165

Telemedicine Issues 177

Telemedicine Policy Options 187

APPENDICES

A Workshop Participants 193

B Reviewers and Contributors 195

C Applications of Clinical Decision Support

Systems 197

D Executive Branch Telemedicine

Activities 201

E Electronic Health Information

Sources 207

F Boxes, Figures, and Tables 213

G Abbreviations and Glossary 215
Introduction,

Summary,

and

Options

nformation technologies are transforming the way health

care is delivered. Innovations such as computer-based patient records, hospital information systems, computer-based

decision support tools, community health information networks, telemedicine, and new ways of distributing health information to consumers are beginning to affect the cost, quality,

and accessibility of health care. The technologies that support

these applications—relational databases, network communications, distributed processing architectures, optical disk storage,

and others—are used today by some health care providers and

payers. Yet information technology is often found in isolated

“islands of automation” in health care provider and payer institutions. Despite the incorporation of high technology into almost

every other aspect of clinical practice, information technologies

have not been fully embraced.

Meanwhile, transformations in the way health care is delivered

are creating new opportunities for innovative applications of information technologies. The health care delivery system is currently undergoing many changes, including the emergence of

managed health care and integrated delivery systems that are

breaking down the organizational barriers that have stood between care providers, insurers, medical researchers, and public

health professionals. These barriers have supported a clear demarcation between clinical health information and administrative

health information and reinforced a long-standing distinction between treatment of disease and preservation of health. These distinctions are gradually eroding as new health care delivery

patterns emerge that are supported by, and in some cases reliant

on, the widespread use of networked computers and telecommunications. | 1
2 | Bringing Health Care Online: The Role of Information Technologies

This report discusses the synergy between information technologies and new trends in the

health care delivery system as health care is

brought online. It identifies some of the opportunities to improve health care delivery through increased use of information technology, and

discusses some of the conceptual, organizational,

and technical barriers that have made its adoption

so uneven. The report identifies key technologies

and shows how they are being used to communicate clinical information, simplify administration

of health care delivery, assess the quality of health

care, inform the decisionmaking of providers and

administrators, and support delivery of health care

at a distance.

CHALLENGES AND OPPORTUNITIES FOR

INFORMATION TECHNOLOGIES

The technologies used for collecting, distilling,

storing, protecting, and communicating data are

widely used throughout American industry. In the

health care industry, however, their application

has been limited to scattered islands of automation, usually limited to discrete departments within hospitals. Computers are widely deployed, but

not widely connected. Clinical and administrative

health information are rarely commingled. Both

types of health information are still stored and

conveyed primarily in paper form. Health information is rarely converted to digital form and

shared among the clinics and primary care offices

where most health care occurs, the hospitals and

critical care units where most health care dollars

are spent, or the population-based health services

that address community-wide health issues. Computers are typically used to organize and administer specific, limited types of health information,

but are not linked into an infrastructure that might

allow broader efficiencies or higher quality health

care.

Figure 1-1 shows the level of adoption of some

selected information technology applications as

reported by chief information officers (CIOs) of

primarily large health care institutions. As the

figure indicates, almost 70 percent of those responding have introduced electronic systems for

submitting insurance claims, and more are in the

process of adopting them. Technologies that allow

communication between computers at disparate

locations, for example physician-hospital data

networks or enterprise-wide networks, are being

adopted or planned by a substantial number of

these institutions as well. Computer-based patient

record (CPR) systems, which are difficult to implement because they require such close integration between many different systems, are at least

in the planning process, according to 50 percent of

responding CIOs, but so far only about 20 percent

consider that they have CPRs operating at least

at an experimental level. When asked which

technologies they were currently evaluating conceptually for future implementation, the two most

frequently mentioned by CIOs were community

health information networks and telemedicine.1

The health care delivery system has several

unique characteristics that discourage the spread

of information technologies. Health professionals

perform a wide variety of tasks including rapidly

changing combinations of “hands-on” care, inductive and diagnostic thinking, detailed recordkeeping, patient education, and communication

with colleagues. Most of the hardware and software approaches that address one of these aspects

of medical practice intrude unacceptably on some

other aspect: computers are not yet as useful, ubiquitous, and handy as the stethoscope and other

common medical technologies. In addition, medical practice is extraordinarily complex and it

changes rapidly. Systematizing even the process

of performing medical procedures, much less rationalizing the language and scientific knowledge

underlying those procedures, is an almost intractable problem. Despite the ongoing efforts of standards-setting bodies, no unified conceptual model

exists that is powerful enough to construct the

mapping between the information that must be

1 College of Healthcare Information Management, Telecommunications in Health Care Survey, 1994 (Ann Arbor, MI: 1994), pp. 20-21.
Chapter 1 Introduction, Summary, and Options 3

Electronic claims submission

Voice mail for staff/physicians

Physician/hospital data networks

General telecom services

Ask-a-nurse/referral service

Enterprise networks

Answering services

Alpha pagers

Data processing services

Home emergency alert

Telecommuting

Interactive voice response

Computer-based patient record

Teleradiology

Distance learning (satellite)

Handheld computer devices

PCs

Community health information networks

Picture archiving & communication

Home monitoring

Distance learning (video)

Telemedicine

Voice mail for patients

Telepathology

,

■ Adopte d

❏ Planning to adopt

I I I

0 20 40 60 80 100

Percent

SOURCE: Center for Healthcare Management Information, Telecommunications in Healthcare Survey, 1994 (Ann Arbor, Ml. 1994)

stored in computer databases and medicine as it is

practiced. In a sense, there is not yet a consensus

about what information should be kept in computer-based patient records or how it should be described, organized, and indexed.

Apart from the complexity of clinical knowledge and practice, there are structural reasons that

discourage implementation of information

technologies in health care settings. In addition,

many communities have only a few hospitals or

major insurers. The cooperation necessary to interconnect medical information within a horizontal layer of the health care system may be seen as

anticompetitive and subject to antitrust regulation, or it may be hindered by organizations that

regard their internal information systems as competitive advantages and accumulated patient records as corporate assets.

Information technologies tend to flatten organizations and may not mesh well with the rigidly

defined job roles and hierarchical structure of current medical practice (see box l-l). Many types of

organizational changes will emerge throughout

the health care system if information technologies

are widely adopted. In other industries, changes

associated with the introduction of information

technologies have included large reductions in the

demand for some types of workers (e.g., mid-level

managers and bank tellers), increased responsibilities for workers in jobs that traditionally involved little decisionmaking (line workers in

manufacturing industries), and an increase in

4
4 Bringing Health Care Online: The Role of Information Technologies

Increased use of information technology will continue to affect the jobs of the 10 million Americans

who work in health care. This workforce is currently growing at about 3.9 percent per year. Changes in

the structure of health care delivery are affecting the composition of the workforce. For example, hospital employment, while it still represents half of people employed in health care, is the slowest growing

sector at 1.7 percent per year. Home health care however, is growing at about 18 percent annually,

although it still accounts for only a small portion of the workforce.1

This report does not analyze the changes that information technology might bring to jobs in health

care, or the effects that these changes might have on the quality of the work environment. These would

be fruitful areas for future research. In general, it appears that information technology applications

could reduce the need for some types of work and could redefine some job roles.

For example, electronic data Interchange (EDI), defined as the application-to-application exchange

of business documents, is increasingly being used to carry out medical payments and other administrative transactions between health care providers and insurance payers. Application-to-application

means that computer programs at different firms exchange information and complete transactions directly, without human intervention. Physicians’ office staffs, for example, often notice a decrease in the

number of telephone calls they make and letters they write after being linked with Insurers through online systems. Much of the potential savings foreseen through “administrate simplification” of the health

care payments process comes from reduced personnel costs.2 The systems currently being implemented do not totally eliminate human intervention, and within many provider and payer organizations some

of the employee time saved by automated payment systems will be spent on other tasks. Nevertheless,

a Iikely outcome of widespread use of electronic medical payments IS the elimination of some jobs in

both provider and payer organizations.

(continued,)

1 U S Department of Commerce, U.S. Industrial Outlook, 1994 (Washington, DC: 1994), pp. 42-1 to 42-6

2 See, for example, Workgroup on Electronic Data Interchange, 1993 Report (Hartford, CT and Chicago, IL October 1993),

p 7-30

competition for local experts from nonlocal health care reflect the ability of computer netsources (discount stockbrokers, for instance).

Similar changes are likely to occur for health professionals, along with a redistribution of status,

responsibilities, and remuneration associated

with the various health disciplines.

Information technologies not only redefine

jobs, but they may have more subtle ramifications

as well. The widespread adoption of integrated information systems will challenge the legal system. Information technologies facilitate alliances

between geographically separate parties. Thus,

they may challenge the existing structure of state

medical licensing and malpractice laws, as well as

“pen and quill” laws that require paper-based

medical recordkeeping. Consolidations and mergers among the many companies offering managed

works and digital telecommunications to act as a

nervous system that can connect previously independent parts of the health care delivery and administrative systems, forming new bodies known

as integrated delivery systems. These new corporate structures may pose antitrust questions as

they challenge traditional providers of health care

in isolated markets.

Information technologies diffuse decisionmaking and responsibility y because they are developed,

maintained, and employed by a variety of people.

Physicians—who have held unique positions of

status and compensation, as well as legal responsibility and risk, under the traditional systems of

licensure and malpractice law—may be put in the

uncomfortable position of being solely responsi-
Chapter 1 Introduction, Summary, and Options 5

Information technology also can change job roles. For example, when physicians place medication

orders at a computer terminal, they take on a data entry task that might previously have been done by a

ward clerk, a pharmacist, or a pharmacy clerk. With proper design, the technology can help integrate

this task with others the physician performs—retrieving information about the patient’s condition, looking up the proper dosage and use of medications, or making judgments and decisions about additional

tests and treatments. Whether data entry is an additional burden, or an integral part of an improved and

more efficient process for rendering care, depends on a wide variety of personal, institutional, hardware, software, and interface design factors.

In some cases, role changes are induced by other organizational changes in which information

technology IS a facilitator. For example, one way that health care organizations are reducing costs IS by

redesigning work so that tasks once done by high-cost personnel are now done by lower cost personnel. For example, much primary health care previously done by physicians is now being done by physician extenders like physician assistants and nurse practitioners. In some hospitals, work previously

done by licensed and registered nurses is now done by nursing aides—sometimes labeled patient care

technicians, 3 while nurses take on the role of managing a team of caregivers.4 This trend IS typical of a

“reengineering” movement in hospital management known as patient-centered care or patient-focused

care—as opposed to department-focused care. Computer technologies—including computer-based

decision support tools and treatment protocols, online patient information systems, patient monitoring

devices, and teleconferencing systems—can support and assist people giving care in these new ways.

SOURCE: Office of Technology Assessment, 1995.

3 Wall Street Journal, Feb. 10, 1995, p. 61.

4 M.L. Parsons and C.L. Murdaugh, Patient-Centered Care, A Model for Restructuring (Gaithersburg, MD Aspen Publishers,

1994)

ble for implementing complex policies resulting

from a mix of research findings, technical

constraints, and business priorities. Networked

information technologies may pose new challenges to the traditional legal assumption that consumers are adequately protected against poor

quality of care through the ability to file lawsuits

against their providers, and alternate guarantees of

high-quality care may need to be designed to replace the current legal remedies.

Finally, information technologies are expensive to implement and their benefits may be difficult to directly measure, even when all parties are

happy with the results. This may delay their deployment in an industry whose sophisticated technological base is seen by some to be a driving

force in making health care more expensive.

TRENDS IN THE HEALTH CARE SYSTEM

❚ Aggressive Cost Management

A major concern for providers, payers, policymakers, and consumers alike is the rising costs of

delivering care. Health care expenditures increased from 5.9 percent of gross domestic product in 1965 to 13.9 percent in 1993.2 Total

expenditures for health care in 1993 were $884.2

billion. Government sources pay for about 43 per2 Katharine R. Levit et al., “National Health Expenditures, 1993,” Health Care Financing Review, vol. 16, No. 1, fall 1994, pp. 247-294.
6 | Bringing Health Care Online: The Role of Information Technologies

cent of this total; the federal government alone

pays nearly 32 percent. Health care is also a major

segment of the economy, employing approximately 10 million people, about 2.6 million of

whom do primarily administrative work.3

As the costs of health care have continued to

rise, there have been concerns in government and

in the industry itself about how to contain and reverse the increase. In the 1990s, particularly in the

103d Congress, a number of proposals were made

for far-reaching reforms in the health care industry. At the same time, within the health care and

insurance industries, many initiatives to control

costs are already under way. In fact, perhaps due in

part to these efforts, the growth rate of health care

costs appears to have slowed during the 1990-93

period.

One of the major influences in the health care

industry has been the growth of managed health

care. “Managed care” is a somewhat nebulous

term, but generally refers to a “system of managing and financing health care delivery to ensure

that services provided to managed care plan members are necessary, efficiently provided, and appropriately priced.”4 Managed care organizations

use a number of techniques to control access to

providers, contain costs, manage utilization of resources, and ensure favorable outcomes for patients.

The number of people enrolled in managed care

plans has increased dramatically in the past 20

years. By 1992, enrollment had grown to over half

of all employees covered by employer group

health insurance.5 As shown in box 1-2, the concept of managed care has expanded to include

many types of health plans and delivery systems.

Many traditional fee-for-service health insurance

plans (those that reimburse members for health

care payments) are also using at least some care

management techniques to manage their costs.

❚ Integration of Health Services

Health care has historically been a very fragmented industry. Routine medical care, crisis

medical care, medical insurance, medical research, and management of public health typically

have been handled by entirely separate organizations in business, government, and universities,

and a large number of intermediary institutions as

well. There are more than 1.2 million health care

providers—ranging from solo practitioners to

1,000-bed hospitals—and they are often isolated

in separate corporate entities from the more than

3,000 private insurance payers that distribute payments for health care services. The providers and

insurance companies are further isolated from the

medical research community, government health

care agencies, and public health organizations. A

network of private-sector intermediaries has

formed to facilitate the complicated relationships

between the various organizations. It is unlikely

that any of these entities will be willing to collect

or organize data that save money or effort for some

other organization, but deliver the intermediary no

immediate benefit; systemic savings may be irrelevant in a vertically fractured industry.

Some of this fragmentation may be reduced

with the current trend toward vertical and horizontal integration of providers and payers into systems that offer the full “continuum of care” to

covered populations. An integrated delivery system is one that brings together hospitals, primary

care providers, nursing homes, home health care

providers, pharmacies, and other services into a

single system through purchase, merger, joint

venture, contract, or other means. As hospital ad3 U.S. Congress, Office of Technology Assessment, International Comparisons of Administrative Costs in Health Care, OTA-BP-H-135

(Washington, DC: U.S. Government Printing Office), September 1994.

4 Marrianne F. Fazen, Managed Care Desk Reference (Dallas, TX: HCS Publications, 1994), p. 149.

5 U.S. Congress, General Accounting Office, Managed Health Care: Effect on Employers’ Costs Difficult To Measure, GAO/HRD-94-3

(Washington, DC: U.S. Government Printing Office), October 1993.
Chapter 1 Introduction, Summary, and Options 7

Managed care can refer to both the elements of managing care and the institutional structures within

which care is managed, To some, managed care means the use of management tools such as preadmission certification (for ensuring that only members who need hospital care are admitted to the hospital), concurrent review (ensuring that necessary and appropriate care is delivered during a hospitalization), or financial Incentives or penalties for both providers and plan members. To others the term is

equated with alternative delivery systems that are variously known by names such as health maintenance organization (HMO) or preferred provider organization (PPO).

In contrast to traditional fee-for-service or indemnity insurance plans where the insurer simply reimburses the insured individual for incurred health expenses and has no direct relationship with the providers of care, managed care organizations create a direct relationship between the insurer and the

provider of care, Whether physicians are salaried employees or contractors, they have a relationship

with the managed care plan wherein they give up some clinical and financial autonomy to that organization. The consumer who joins a managed care plan also surrenders some freedom of choice. The HMO

or PPO in turn takes on a managerial role with the hope of containing costs and enhancing the quality of

care.

One concept used in certain forms of managed care is cavitation. Under capitated payment systems, providers receive a set payment per patient per period, regardless of the amount of services they

provide Providers who exceed their budgets will suffer losses. A second concept common to managed

care is the limitation on the patients’ choice of providers. Some plans only allow patients to choose from

a panel of providers associated with the plan (“closed panel”). Others permit patients greater flexibility,

but require patients to pay a higher share of costs when using outside providers. While the concepts of

capitation and Iimitations on the patient’s choice originated with early HMOs, they are now pervading

the whole health care industry, and many insurance plans, including traditional indemnity plans, may

include these features to some degree. Some managed care organizations have tighter controls—both

over payments and over patient-provider relationships; others maintain looser controls. Closed-panel

HMOs are generally the most restrictive, while independent practice associations (IPAs)—HMOs where

physicians work under nonexclusive contracts and may also have fee-for-service patients—are less so,

as are PPOs.

Managed Care and Cost Savings

According to recent studies, care management techniques reduce health care costs, primarily

through the reduced use of services. For example, the Congressional Budget Office (CBO) reports that,

compared to indemnity plans, closed-panel HMOs reduce the use of medical services by about 196

percent and IPAs reduce use by about 0.8 percent. The combined average effect of all HMOs is a reduction in services of 7.8 percent when compared with the current mix of indemnity plans. 1 Less restrictive types of managed care have not shown such significant reductions, according to CBO.

SOURCE: Adapted from U.S. Congress, Office of Technology Assessment, Understanding Estimates of National Health Expenditures

Under Health Reform, OTA-H-594 (Washington DC: U.S. Government Printing Office, May 1994), p. 76

1 U.S. Congress, Congressional Budget Office, The Effects of Managed Care and Managed Competition (Washington, DC Congressional Budget Office, 1995)
8 | Bringing Health Care Online: The Role of Information Technologies

missions and inpatient days have declined because of cost control efforts begun in the 1980s,

many hospitals have entered these other lines of

business. Some integrated delivery systems are

being organized by insurers or managed care organizations.

❚ Increasing Value of Digital Information

New patterns in health care delivery are enhancing

the value of clinical health data and creating incentives for collecting and disseminating health

information electronically within and between organizations. As managed care organizations grow

and fee-for-service care wanes, doctors and other

practitioners have both a financial interest in delivering low-cost care and incentives for documenting and analyzing their care practices.

Administrators in Health Maintenance Organizations (HMOs) and integrated delivery systems

have long sought to reduce transaction costs (after

an initial investment in equipment and software)

by computerizing internal communications and

automating communications with suppliers and

other business partners. In addition, they have a

vested interest in understanding the clinical details of how care is delivered in order to efficiently

manage resources. 

For example, it is possible to use administrative

records alone to limit overuse of optometry services by approving eye examinations purely on

the basis of elapsed time since the last exam. However, care can be more prudently and perhaps compassionately managed by considering not only the

time of the last billing, but also the clinical record

of that visit and other health information about the

patient. Were the previous results normal, or did

they indicate a problem? Does the patient have

any other conditions that might warrant frequent

eye examinations? Could the current complaint be

due to an adverse reaction to a prescribed medication and, hence, warrant a visit to the prescribing

physician rather than an optometrist? This finegrained analysis of clinical records is contingent

on standardization and digitization of clinical records because paper records are generally inadequate for these purposes.

Finally, the government has a stake in helping

to develop inexpensive, standardized approaches

to information exchange so it can effectively fund

medical research, manage widespread public

health problems, reduce its administrative costs,

and reduce the cost of the health care it purchases

and provides through Medicare, Medicaid, veterans’ care, and employee insurance programs. An

indication of the magnitude of this interest is the

designation of health care applications as a key

component of the National Information Infrastructure (NII) by the Administration’s Information Infrastructure Task Force (IITF). Appointed

by the President, the IITF is comprised of highlevel representatives of the federal agencies that

play a role in developing and applying information and telecommunications technologies. The

IITF’s Committee on Applications and Technology coordinates efforts to develop, demonstrate,

and promote applications of the NII and develops

and recommends technology strategy and policy

to accelerate its implementation. One part of this

committee is the Health Information and Applications Working Group. This group is again divided

into subgroups in the categories of telemedicine,

consumer health information, standards, and

emergency medicine.

These private and governmental interests in

digitizing health information in order to manage

costs and integrate delivery of health services are

manifest in a slow but perceptible trend toward

standardization of health care information and optimization of care delivery. These processes are

occurring on many levels. The medical and computing communities are slowly developing: a)

lexicons for consistently describing medical care,

b) consensus standards for exchanging medical

data between computers, and c) models for how to

collect and organize medical information digitally. Protocols for standardizing delivery of care and

metrics for measuring the quality of health care

services are being developed, as well as decision

support systems that may increase the efficacy of

medical decisions. And throughout the health care

delivery system, innovative applications of in-
Chapter 1 Introduction, Summary, and Options | 9

formation technologies are being studied, tested,

and implemented.

CONGRESSIONAL INTEREST

Recognizing the changes occurring in both health

care and telecommunication technology and their

relevance to the congressional agenda, the Chairman of the Senate Committee on Labor and Human Resources asked the Office of Technology

Assessment (OTA) to conduct a study on the impacts of information technology on the health care

system. The request was supported by the Chairman of the House Committee on Energy and

Commerce.6

Recently, there have been numerous legislative

initiatives addressing aspects of incorporating information technologies into the delivery of health

care. In the 103d Congress, several comprehensive health care reform bills were introduced,7 and

this pattern has continued in the 104th Congress.

These bills seek to restructure various aspects of

the payment and insurance framework of the

health care industry, but, in addition, they often

specify procedures for simplifying administration

of health care delivery through the use of information technologies. For example, several recent

bills direct the Secretary of the Department of

Health and Human Services (DHHS) to adopt uniform standards for various medical data, based on

the work of standards committees accredited by

the American National Standards Institute and on

the advice of groups such as the Workgroup for

Electronic Data Interchange and the ComputerBased Patient Records Institute.8

The bills call for standards for:

1. defining common sets of data elements to be

stored electronically in patient records,

2. performing administrative transactions,

3. assigning uniform patient and provider identification numbers,

4. assigning codes to medical procedures and descriptions,

5. applying electronic signatures, and

6. ensuring patient privacy and data security.

Most bills specify the adoption of the standards

by DHHS within two years or less, and, following

the adoption, provide various measures designed

to encourage rapid adoption of the standards by

nearly all health care providers. These measures

may include direct incentives, such as requirements that all health plans implement the standards for all transactions, or indirect incentives,

such as requirements that all transactions regarding Medicare patients be filed electronically. The

incentives may also be provisional: they may direct the Secretary to assess whether sufficient

numbers of health plans are utilizing the standards

and to require full participation, should it prove to

be cost-effective. Most bills include exceptions

for small hospitals and those that can show they

are in the process of installing an adequate information system. Some of the bills override state

laws requiring the maintenance of paper-based patient records.

Several bills seek to establish national or state

databases of health information for quality assessment purposes, control of fraud, or tracking disease patterns.9 Other bills would authorize grants

6 This committee is now known as the House Committee on Commerce.

7 Two examples are U.S. Congress, Senate, S. 1757, Health Security Act, and S. 1494, Health Care Information Modernization and Security

Act of 1994 (Washington, DC: U.S. Government Printing Office, 1994).

8 U.S. Congress, House of Representatives, H.R. 1200, American Health Security Act of 1995 and H.R. 1234, Basic Health Care Reform Act

of 1995 (Washington, DC: U.S. Government Printing Office, 1995); and U.S. Congress, Senate, S. 7, Family Health Insurance Protection Act

(Washington, DC: U.S. Government Printing Office, 1995).

9 U.S. Congress, House of Representatives, H.R. 798, Veterans’ Benefits, Title 38 U.S.C., Amendment (Washington, DC: U.S. Government

Printing Office, 1995), and H.R. 1200 and S. 7, ibid.
10 | Bringing Health Care Online: The Role of Information Technologies

for rural telemedicine efforts10 or establish a telemedicine commission to formulate plans for

widespread implementation of telemedicine.11

Finally, there have been efforts in both the 103d

and 104th Congresses to reform and deregulate

telecommunications.12 Such reforms may affect

the price of telecommunications services and,

therefore, help determine the feasibility of incorporating telecommunications into health care delivery on a large scale. In addition, current bills

have certain direct influences on health care, including a requirement that prices for telecommunications service to rural health care providers be

comparable to those for urban providers.13

REPORT SUMMARY

❚ Scope of the Analysis

In chapters 2 through 5, this report discusses some

of the challenges and opportunities for using information technology to improve the health care

system. First, it addresses the potential impact of

information technologies on health care delivery

and introduces a variety of technologies that are

being used to collect, organize, and share clinical

information needed for providing patient care.

The report then explores the exchange of health

information for administrative purposes among

the many stakeholders including providers, payers,

employers, consumers, and government agencies.

It discusses how the quality of health care might

be improved by providing health care professionals with high-quality information and decision

support tools at the point of care. Finally, the report explores the potential for addressing the

needs of those in rural or other underserved areas

through telemedicine.

Advanced information technologies offer an

array of other possibilities for influencing delivery of health care services. It was impossible to address all applications in this report. Those selected

were viewed as having the most potential for decreasing costs and improving quality and access in

health care. Particular emphasis is placed on administrative simplification, quality assessment,

and telemedicine, as specified by the congressional committee requesting the report. The report also

briefly mentions the potential for telecommunications to assist consumers in becoming better informed and more involved in decisions affecting

their health care, and points to the need for additional study. Emerging applications of information technology, including remote surgery and

virtual reality applications, were not considered,

nor were issues related to the reform of medical

education to include greater use of information

technology. These are, however, fertile areas for

future research.

Before computers were introduced into the

health care delivery system, clinical and administrative records were kept separately in paper form,

patient utilization of services was rarely scrutinized systematically, and clinical information was

seldom exchanged between business organizations (or even among the various clinicians an individual might see). Thus, paper-based technologies and common organizational policies worked

along with various state laws to provide an ad hoc

level of protection for individual privacy that is

clearly inadequate in the emerging world of com10 U.S. Congress, House of Representatives, H.R. 851, Rural Telemedicine Act of 1995 (Washington, DC: U.S. Government Printing Office,

1995), and U.S. Congress, Senate, S. 7, op. cit., footnote 8.

11 U.S. Congress, House of Representatives, H.R. 426, National Committee on Telemedicine Act (Washington, DC: U.S. Government Printing Office, 1995).

12 U.S. Congress, House of Representatives, H.R. 3626, Antitrust and Communications Reform Act of 1994; Antitrust Reform Act of 1994

(Washington, DC: U.S. Government Printing Office, 1994), and U.S. Congress, Senate, S. 1822, Communications Act of 1994; Telecommunications Equipment Research and Manufacturing Competition Act of 1994, and S. 2111, Telecommunications Services Enhancement Act of 1994

(Washington, DC: U.S. Government Printing Office, 1994).

13 U.S. Congress, Senate, S. 652, Telecommunications Competition and Deregulation Act of 1995 (Washington, DC: U.S. Government

Printing Office, 1995).
Chapter 1 Introduction, Summary, and Options | 11

puterized patient records, integrated delivery services that operate on a nationwide basis, and

instant electronic messaging. New combinations

of legislative protections and technical safeguards

will be necessary to protect individual privacy as

health care information is computerized and standardized. These issues are discussed briefly

throughout this report, but were discussed in detail in the OTA report Protecting Privacy in Computerized Medical Information.

14

The issues and policy options that emerge from

each chapter of this report are briefly summarized

in the sections that follow. First, however, two key

themes are introduced that echo throughout the

chapters. These are cost containment and standards development, and they reflect congressional

concerns about containing health care costs and

enabling administrative simplification that are

manifest in the bills of the 103d and 104th Congresses.

❚ Cost Containment

Reducing the cost of delivering health care is perhaps the prime motivation for congressional interest in exploring the use of information technology.

Anticipated cost savings are based on analogous

reductions in transaction costs for industries such

as banking—which built information infrastructures supporting automated teller machines and

point-of-purchase credit card verification—and

on the increase in productivity and product quality

in domestic manufacturing industries associated

with just-in-time inventory control, continuous

quality improvement, and other techniques that

are highly dependent on information technologies. Although similar efficiencies and improvements may be possible within the health care

system, the magnitude of the savings is very difficult to predict for several reasons.

Most cost containment predictions maintain

the traditional fault line between administrative

information and clinical information. Administrative processes include activities such as transmitting and processing claims, utilization review,

purchasing supplies and tracking inventory, paying bills, managing internal finances, negotiating

contracts, complying with regulations, and controlling quality. Administrative costs of providing

health care have been estimated at between $108

billion and $135.1 billion per year in 1991,15 or

between 12 and 15 percent of the health care bill.

Estimates of annual savings that could be realized

through increased use of information technology

in administrative functions have ranged from $5

billion to $36 billion,16 or enough to reduce administrative costs between 0.5 and 3.6 percent.

These estimates, discussed in more detail in

chapter 3, may be somewhat optimistic because

they assume rapid adoption of electronic data interchange and high rates of market penetration

that do not appear to be materializing. The deeper

problem with such predictions is that they are

often based on merely converting all transactions

within the existing system of fee-for-service

health care to electronic form. However, the shifting landscape of health care delivery patterns cannot be treated as a perturbation within a more rapid

process of digitizing health information. Such

digitization did not happen over the past two decades despite the availability of increasingly capable computer and telecommunication systems;

indeed, several organizational and technological

impediments (discussed in chapter 2) make it likely that widespread digitization will happen only in

14 U.S. Congress, Office of Technology Assessment, Protecting Privacy in Computerized Medical Information, OTA-TCT-576 (Washington, DC: U.S. Government Printing Office, September 1993).

15 Allen Doubloon and Matthew Bergheiser, “Reducing Administrative Costs in a Pluralistic Delivery System Through Automation,” prepared by Lewin-VHI for the Healthcare Financial Management Association, Apr. 30, 1993.

16 Project HOPE, Center for Health Affairs, “Estimating the Cost-Effectiveness of Selected Information Technology Applications,” unpublished contractor report prepared for the Office of Technology Assessment, March 1995.
12 | Bringing Health Care Online: The Role of Information Technologies

synergy with the progressive adoption of managed health care practices and development of integrated service delivery systems.

A second class of economic considerations

concerns the effectiveness of encouraging specific

information technology implementations. These

are of concern to Congress for purposes of guiding

procurement decisions and research priorities. In

recent years, the field of economic evaluation of

medical technologies has expanded rapidly. Rising spending on health care has stimulated the use

of formal techniques such as cost-effectiveness

analysis and cost-benefit analysis to assess the

cost and health effects of using particular medical

technologies.

Cost-effectiveness analysis (CEA) has emerged

as the most popular technique for economic evaluations. CEA involves a structured, comparative

evaluation of two or more health care interventions. Analyses are designed to show the relationship between resources used (costs) and health

benefits achieved (effects) for given technologies

or programs. In CEA, the cost per specified health

effect, such as lives saved or quality-adjusted lifeyears saved, is calculated for particular technologies or programs. If the ratio is measured similarly

for different technologies or programs, the cost

per effect can be compared. Formal CEA involves

a number of explicit steps, including:

1. identifying the perspective of the study,

2. identifying the competing interventions,

3. defining costs,

4. defining effects,

5. discounting future costs and effects to their

present value,

6. adjusting for quality-of-life factors,

7. analyzing the incremental costs and consequences of one option over another, and

8. examining uncertainties underlying

the analysis.

In cost-benefit analysis (CBA), the net costs of

an intervention are compared with the net savings:

the benefits of a program or technology are expressed entirely in monetary terms. Because the

benefit of medical technology generally involves

health effects such as life-years saved, CBA requires that these effects be valued in monetary

terms. One of two techniques—the human capital

approach or the willingness-to-pay approach—is

generally used to measure benefits. The human

capital approach considers the value of a human

life by estimating an individual’s projected future

earnings. The willingness-to-pay approach considers how much individuals are willing to pay for

a reduction in the risk of death or illness.

Applying the formal techniques of CEA and

CBA to information technology applications in

health care is difficult for a number of reasons.

Some of the difficulties are general to all medical

technologies: the competing alternatives for a

technology are not always known; a technology

may be cost-effective in some patient groups and

not in others; technologies constantly undergo

change; there are no standards on how to define

costs (e.g., whether and how to consider indirect

costs such as productivity losses, or intangible

costs such as pain and suffering); there are no standards regarding the length of patient followup

time to consider; analysts differ in their use of

methodologies by which to adjust health effects

for quality-of-life factors; and there are many uncertainties underlying such analyses. A general

problem with CBA involves trying to place a

monetary value on reductions in mortality or morbidity.

Beyond these general difficulties, evaluating

information technologies presents some unique

problems. It is difficult to conduct comparative

studies because system features and levels of service vary widely across institutions and users. In

addition, many applications have been in existence only a short time. Information technologies

and applications change frequently, making analyses difficult—and making even some well-conducted analyses quickly obsolete. In general, it is

difficult to identify and quantify appropriate

costs, savings, and health effects. For most evaluations of information technology, direct costs

would include equipment and operating costs, the

value of the technician’s time, and the cost of

maintaining equipment. However, it is hard to accurately identify and quantify indirect costs such
Chapter 1 Introduction, Summary, and Options | 13

as productivity gains or losses. In general, it is

very difficult to tie the use of information technologies to health consequences.

As a result of these limitations, most existing

economic evaluations do not constitute formal

cost-effectiveness or cost-benefit analyses. Instead,

most have attempted to estimate savings in terms

of productivity gains to the system. Some have

also speculated about how various applications

will ultimately influence patient care. The design

and scope of such analyses vary widely across

studies, as does the level of rigor.

Congressional Options

Recognizing that implementation of information

technologies will bean incremental process, Congress may wish to attempt to evaluate the possible

systemic savings associated with implementation

of information technologies in a way that recognizes the shifting patterns of health care delivery.

Alternatively, Congress could evaluate, for administrative purposes, the costs and benefits of

implementing various specific technologies or

sets of technologies. These are difficult challenges. However, should Congress wish to pursue

such analyses, it could direct agencies or congressional support services to implement one or more

of the following options:

Analyze systemic savings that might

be associated with implementation of information

technologies and related changes in health care delivery systems using realistic estimates for the pace of implementation.

Conduct or fund research to evaluate

the costs and effectiveness of individual information

technologies, such as order-entry systems, clinical protocols, and electronic interchange of claim and payment information.

 Evaluate the potential for synergies between information technologies by funding research in

the implementation of multiple simultaneous applications in test and control facilities.

Establish baseline data for the costs of

current information structures in the health care delivery

system so that future implementations can be objectively evaluated.

Given these possibilities for cost-benefit analyses and systemic cost analyses, it should be noted

that some stakeholders who contributed to this assessment indicated that rigorous cost-benefit or

cost-effectiveness analyses would not play a major role in their decisions to implement information technologies. Rather, these technologies and

systems of technologies were considered by many

stakeholders to be as fundamental and as immune

to cost-benefit analysis as the telephone: adoption

of the technologies would be necessary to remain

competitive in the health care industry.

■ Standards Development

The second major theme that recurs throughout

this report is the central role of standards development for systematizing the compilation and exchange of health care information. One value of

digitized health information is that it can be manipulated quickly and accurately by computers

without human intervention. The accuracy, speed,

and cost of machine-processing are adversely affected by novelty, diversity, and frequent changes

in the rules. Until standards are in place and compliance is widespread, costly activities—such as

maintaining multiple formats for health care information, dealing with exceptions, and developing new interface software as new proprietary

approaches to managing health information become fashionable—will continue to offset some

potential savings of processing health care records

and transactions electronically.

Standards development is an ongoing process.

A number of organizations are working on standards for the content and format of electronic

health information. Standards for the format of

billing and core insurance transactions are well

developed, and the Health Care Financing Administration (HCFA) has adopted some of them.

Another area of standardization that could facilitate electronic transactions is a system of unique
14 | Bringing Health Care Online: The Role of Information Technologies

identifiers for individuals, providers, and sites of

care. At present, each provider uses its own numbering system, which can create confusion when

health information is exchanged between different institutions.

The development of technical standards is primarily a private-sector activity. However, it could

be accelerated through federal participation in developing standards that would encourage information exchange and protect the privacy of

participants in the health care system, and through

expeditious implementation of such standards in

all federal health care matters as a catalyst for

their adoption by the private sector. This should

not be construed as a call for federal agencies to

independently establish standards for implementing information technologies—such efforts would

almost certainly fail to meet the needs of various

stakeholders. Rather, federal agency participation

in existing standards activities would preempt duplicative development of federal regulations and

requirements. Further discussion of standards appears in individual chapters of this report.

❚ Information Technologies for

Transforming Health Care

The potential for new computing and telecommunications technologies to reduce the cost of delivering health care, while facilitating broad structural changes in the health care industry, may presage

a rapid expansion in the application of information technologies to the health care system. Chapter 2 charts the technological and organizational

factors that will help guide the path of that expansion should it occur.

Policy Issues

Many of the practical frustrations encountered by

participants in the health care system can be traced

to the inability of current information systems to

provide accurate, timely information where it is

needed in the health care process. Poor information mobility has become an impediment to efficient delivery of high-quality health care. This

impediment becomes more prominent, expensive, and problematic for health care delivery organizations as they grow larger and more

complex. One approach to solving this problem is

to liberate health information from its traditional

paper medium by creating, transmitting, and processing it through more flexible electronic means.

Electronic information can be used again and

again, in different forms for different purposes. It

can be reformatted easily and transmitted cheaply

once the infrastructure to do so is in place.

Chapter 2 identifies the broad currents of information flowing within the health care system,

and then describes various approaches to computerizing clinical information within hospital and

ambulatory care units. One portion of this clinical

information is the patient’s medical record, which

has conventionally been kept as a thick folder of

paper forms and films. The chapter describes the

design of paper recordkeeping systems and the

reasons they are inadequate for documenting care

in an integrated health care delivery organization.

It discusses ways that this information might be

digitized and then disseminated (with appropriate

security measures) through standardized communications protocols.

A diverse suite of key computer and communication technologies supports the digitization

and dissemination of clinical records. The chapter

describes technologies for: a) capturing data as

it is generated by caregivers and the machines

they use to monitor and treat the patient; b) compressing, storing, securing, and retrieving data;

c) networking and telecommunications technologies sharing information; and d) refining data and

comparing data streams so computers can support

medical decisionmaking. Insight and wisdom

must somehow be culled from an overwhelming

flood of bits and bytes.

This suite of advanced information technologies is also the context for discussions in subsequent chapters of the report that address

administrative health data management, quality

assessment and decision support, and delivering

health care services and information at a distance.

Congressional Options

Many of these core technologies have been developed by the private sector for nonmedical pur-
Chapter 1 Introduction, Summary, and Options | 15

poses and will be adopted within the health care

system as needed. Nonetheless, Congress may

wish to consider certain policy options that could

encourage harmony in how that adoption proceeds.

Support standards-setting activities.

Congress could direct relevant agencies to supply personnel to actively participate in standardssetting meetings. This would proactively obviate

any federal regulatory activity that might be at

odds with consensus standards by making sure

that government interests are represented within

the standards-setting process. Congress could

also provide financial support for the process, including funding research support to help resolve

any technological roadblocks that impede standards development. Congress could also direct

federal agencies to set aggressive schedules for

implementation of consensus standards in their

own health care delivery and administrative activities as a catalyst for similar private-sector action.

Fund and coordinate research efforts to

overcome specific technological barriers.

These efforts could include research into human-computer interface technologies for use in

health care settings and research into large-scale,

open architecture implementations of information

technologies in health care settings.

Coordinate federal efforts to implement

health care information technologies.

The agencies or committees charged with this

coordination could:

1. establish procedures for expediting approval

and distribution of medical software;

2. establish mechanisms (or support similar private-sector efforts) for reviewing and disseminating clinical protocols;

■

advise Congress on specific needs of the medical, technical, and consumer communities with

respect to legislation establishing regulations

and policies pertinent to information technologies; and

set national standards for patient and institutional identification numbers and security procedures to be used with patient records.

Networks for Health Administration

Chapter 3 explores the exchange of health

information among the many stakeholders—providers, payers, employers, consumers, and government agencies—particularly for administrative

purposes.

Policy Issues

As part of a larger effort to reduce costs, improve

quality of care, and improve access to health care,

efforts to effect administrative efficiency through

greater use of electronic commerce in health care

are an important component. Today, about 75 percent of hospital claims are submitted electronically, the vast majority of these being Medicare

claims submitted to HCFA. Physicians submit

some 47 percent of their Medicare claims electronically, but only about 16 percent of total

claims. 17 

. Between some payers and providers, the

process of billing and being paid has been totally

automated, with the organizations exchanging

electronic claims, remittance advice (documents

that explain how much of the claim is paid), and

electronic funds transfers. However, such levels

of automation are still unusual. Electronic claim

services help providers deal with the multitude of

different formats and requirements of payers.

They offer software and services for translating

and reformatting claims and other electronic

transactions among the 400 or so different systems in use.

Compared with a paper-based system, it appears that electronic information reduces costs for

some users. Most of the estimates for savings re17 “Automated Medical Payments Statistical Overview,” Automated Medical Payments News, Feb. 8, 1993, p. 3.
16 | Bringing Health Care Online: The Role of Information Technologies

sulting from the use of information technology are

based on cost reductions in payer-provider transactions resulting from automation in a fee-for-service environment. Managed care organizations

can have equivalent transactions that presumably

will cost less using information technology. However, the major savings that are expected to accrue

from managed care come from better management

of both resources and patient and clinician behavior—for example, reduction of unnecessary services. Information technology should assist in this

as well. For example, having up-to-date patient records available at the point of service should reduce duplicate testing or the provision of

nonallowed treatments. While it has been argued

that information technology fosters better management, actual evidence of its contributions to

cost reduction in this area is difficult to find.

Community health information networks

(CHINs) facilitate exchanges of clinical or administrative data among providers and payers in a particular community or region. CHINs can help

offset the lack of standardization by providing

translations and interfaces between incompatible

computer systems used by different network subscribers. Some networks, often called CHMISs

(Community Health Management Information

Systems), may also maintain a repository of administrative information for use in performing

outcome research and quality assessments of providers and insurance plans in the community. At

this point it is not clear whether community networks, which offer service to competing providers

in the community, will survive as more vertically

integrated health care organizations build proprietary information networks.

While exchanging health information electronically offers advantages, it also raises fears that

privacy and confidentiality of health information

may not be protected. Many consumers already

fear that too many people have access to their

health information. Most information needed for

health care administrative transactions comes

ultimately from the patient record. Clinical information in coded, abstracted form becomes administrative information. The provider attempts

to capture, either through manual or automated

means, everything that is done for the patient during a stay or visit, and to document information

about resource utilization and costs in order to

prepare an appropriate bill. Electronic patient records are under development in many locations

throughout the country. In addition to technological and organizational barriers, there are a number

of regulatory and legal barriers to complete implementation of electronic patient records, including

conflicting state laws and regulations about how

patient records must be maintained and the way

privacy and confidentiality of records should be

protected.

Health information is not limited to the patient

record. Rights of patient access and procedures for

protection of privacy and confidentiality are not

clearly defined for secondary and tertiary users of

health information (e.g., payers, researchers, and

organizations maintaining health data repositories) under federal or most state laws. While most

health care is local, in that people usually see caregivers in their own communities, health information often needs to cross state lines because the

payer, provider, patient, and/or employer may be

in different states.

Congressional Options

Savings may be available to the health care system

as a whole as a result of universal implementation

of electronic medical payments. However, at current implementation rates, universal compliance

may not be achieved for some time, if ever. Getting started with electronic commerce requires a

solid organizational commitment and a significant investment in equipment, software, process

redesign, and education, but some organizations

have weak financial incentives to make the investments needed to institute electronic payments.

Others are forging ahead, unwilling to wait for

standards. The health care industry in the United

States is not organized as a “system” with a central

focus or consensus on how to deal with systemwide problems. The different parts of the fragmented system have diverse incentives, and

efforts by participants to control costs in their own

area can tend to increase costs elsewhere. However, these shifted costs are so subtle and spread
Chapter 1 Introduction, Summary, and Options | 17

over so many participants in a complex system

that they are difficult to quantify.

The federal government has provided some

leadership in helping the health care industry

move toward greater use of electronic information, and may wish to continue this leadership

role. There are three major areas in which government action might be considered: 1) providing

leadership in the adoption of standards for electronic medical payments and other transactions

and exchanges of health information; 2) establishing a system of unique identifiers for people, providers, and payers; and 3) establishing a more

consistent regulatory environment for interstate

exchanges of health information.

Continue to influence the standardization of health care information primarily through the federal government role as a major insurer.

The Health Care Financing Administration’s

(HCFA’s) adoption of claims submission standards, along with incentives such as faster payment of electronic claims, has already been

instrumental in encouraging some payers and providers to begin use of electronic payment systems.

Require the adoption of industry-developed standards for core electronic transactions, including minimum and maximum data sets, and set

timetables for their implementation.

If it is believed that HCFA’s influence alone

will not ensure high enough levels of participation

in a standardized electronic health payment system, then a more active federal role may be considered. A corollary to this option may be:

Charge a government agency with responsibility and authority to set standards and data definitions for administrative transactions in consultation

with industry groups, and to manage changes to standards over time; alternatively create an agency or commission for this purpose.

Establish a system of unique identifiers

for patients, providers, and sites of care.

A national system of electronic commerce for

health information will operate more smoothly if

there is a better system for uniquely identifying

participants in that system, both to prevent duplication and loss of information and to facilitate

coordination of benefits when multiple providers

and payers are involved in a patient’s care. Because of its national reach, the federal government

may be in the best position to establish systems of

identifiers.

In order to create a consistent legal and regulatory environment for electronic health information, Congress may wish to consider the following

options:

Encourage the passage of uniform

state legislation with regard to privacy and confidentiality allowable storage media, and standards for health

information.

A number of industry groups have been working with state governments to encourage adoption

of uniform legislation, and the Department of

Health and Human Services has been assigned the

lead role in designing model state privacy laws.

An alternative or supplement to this option may

be:

Establish federal legislation and regulation regarding privacy and confidentiality of medical information, storage media for patient records, and

standards for storage and transmission of medical information.

Additional federal legislation may be necessary as a framework for state legislation, or to replace state laws, if the process of revising

legislation on a state-by-state basis is seen as ineffective or too time-consuming.

Charge a government agency with responsibility to oversee the protection of health care

data; provide ongoing review of privacy issues; keep

abreast of developments in technology security measures, and information flow; and advise Congress

about privacy matters in the area of health care information.
18 | Bringing Health Care Online: The Role of Information Technologies

Because of the importance of privacy and confidentiality to the public, the continually changing

uses for health information, and the constantly

changing nature of threats to privacy and confidentiality, it may be necessary to establish one organization as an ongoing locus of responsibility.

❚ Improving the Quality of Health Care

Chapter 4 finds that advanced information

technologies—computer-based patient records,

structured data entry, advanced human-computer

interface technologies, portable computers, automated data capture, online query, knowledgebased information systems, and computer

networks—can potentially improve the quality of

health care by enhancing clinical decision support, and by improving data for assessing both the

effectiveness of health services and the performance of health care providers and insurance

plans.

Information technologies could facilitate faster

and easier collection of information about the patient and the health problem at hand. Portions of

that information could be entered by clinicians at

or near the point of care, captured directly from

diagnostic and monitoring equipment, or entered

by the patient prior to care. Technologies such as

relational databases with online query could support faster and easier search and retrieval of previously collected information about the patient, as

well as information from local or remote knowledge bases. Development of computer-based clinical protocols and other forms of clinical decision

support systems (CDSSs) that apply decision

rules and other knowledge-based approaches to

information about the patient and health problem

at hand could recommend diagnoses, tests, treatments, and preventive care. They could also lead

to more rigorous construction and analysis of

measures of service effectiveness and performance of providers and plans. Computer networks, high capacity telecommunications,

advanced human-computer interface technologies, and improved graphics software could lead

to more flexible organization and display of this

information as appropriate for individual clinicians, and more rapid and widespread dissemination of the results of performance measures to

various parties.

Empirical evidence demonstrating the ability

of these technologies to achieve these goals is limited, mixed, or incomplete. Moreover, concerns

have been raised about possible adverse effects on

the quality of health care arising from these

technologies, including:

1. incorrect parameters or criteria, or omitted or

altered steps, in CDSSs that could lead to inappropriate care;

2. excessive reliance on monitoring equipment

and CDSSs, which could undermine the ability

of clinicians to exercise professional judgment

in nonroutine cases and reduce the interpersonal aspects of patient care (the “quality of caring”); and

3. the temptation to use readily available administrative data for assessing the effectiveness of

specific health services or the performance of

providers or insurance plans.

If the data are incomplete or inaccurate, the results could be misleading.

Policy Issues

The private sector has been largely responsible for

the development and application of information

technologies in clinical decision support and performance assessment of health care providers and

insurance plans. The federal government’s role

has mainly involved:

1. developing information systems and performance measures for its own health insurance

and health care delivery programs, most notably Medicare;

2. funding of intramural and extramural research

and demonstration projects; and

3. participating in voluntary standards-setting activities with private-sector organizations.

All of these activities in both the private and

public sectors are likely to continue, with some increasing and others decreasing. In an era of budgetary and regulatory restraints, however, major

new government initiatives, such as funding for
Chapter 1 Introduction, Summary, and Options | 19

technology development or mandated regulation

of clinical information systems, are unlikely. It

can be argued that this is appropriate—in other

words, that the federal government should not interfere in private market decisions regarding the

selection of new technologies or their applications.

On the other hand, the federal government—

specifically HCFA—is responsible for ensuring

tight the quality of health care rendered to Medicare and Medicaid beneficiaries.18 Recent efforts

to move more beneficiaries into managed care

have underscored quality concerns, given the expectation that cavitation creates an incentive for

underservice. 19 Several policy issues regarding

the potential impact of information technology on

the quality of care delivered to Medicare and Medicaid beneficiaries deserve the attention of federal

policymakers.

The foremost issue is the extent to which clinical information systems actually change clinical

practice patterns and patient outcomes, and whether those changes are beneficial to providers and

patients. Empirical research on this issue remains

limited, mixed, or incomplete, and more solid evidence regarding these impacts needs to be obtained. To pursue such research, Congress could

consider the following options.

Congressional Options

Maintain or increase funding for intramural research and extramural grants and contracts to

private-sector organizations for research and demonstration projects designed to:

develop and test the reliability and validity of

various methods of measuring and assessing

(with risk adjustment) the performance of providers and health plans;

develop, implement, and evaluate specific systems of risk-adjusted performance indicators;

■ evaluate the effectiveness and safety of clinical

information systems, including CDSSs.

Maintain or increase funding for HCFA

to develop and evaluate performance assessment

methods and systems suitable for Medicare and Medicaid enrollees, using intramural research and extramural grants and contracts to private sector organizations

for research and demonstration projects as needed.

Assign the task of coordinating the development and evaluation of performance assessment

methods and systems and clinical information systems

to a single federal agency.

Reduce funding for development and

evaluation of performance assessment methods and

systems and clinical information systems, and direct

HCFA to employ performance assessment methods

and systems developed and evaluated in the private

sector with minimal adaptation.

Until more solid evidence is available regarding the effectiveness and safety of existing clinical

information systems and the reliability and validity of performance assessment systems, more drastic action—such as mandating the testing and

certification of ail such systems—is probably not

justified. Legal questions regarding who should

be held liable in situations in which such systems

lead clinicians to make decisions that harm patients are probably best left to the courts to resolve.

Assuming that clinical information systems are

found to be effective and safe in terms of their impacts on practice patterns and patient outcomes,

the next set of issues focuses on the most efficient

means of developing and implementing those systems.

One issue regarding government involvement

in the development of standards and technology

concerns the classification and coding of health

services. Many major payers currently employ

18 The state governments share responsibility for the Medicaid Program with the federal government.

19 Given a fixed payment per plan member, providers may be tempted to minimize the volume and/or intensity of services rendered for each

patient.
20 | Bringing Health Care Online: The Role of Information Technologies

two separate systems for coding health services:

ICD-9-CM 20 for billing by inpatient hospitals and

other institutional providers, and CPT-421 for

“professional” billing by clinicians and other noninstitutional providers and suppliers.

For payment and other purposes, services rendered by a clinician in an inpatient setting must be

coded using both of these systems, creating additional costs for providers. For many services,

however, the codes in ICD-9-CM cannot be

equated (“crosswalked”) with those in CPT-4 because of substantial structural differences between

the two coding systems. Moreover, both

ICD-9-CM (Vol. 3) and CPT-4 have serious technical limitations, such as overlapping and duplicative codes and inconsistent and noncurrent use of

terminology. Most importantly, neither has adequate room for expansion, so both are running out

of codes as new services are created or different

uses of existing services are distinguished. In addition, neither system provides sufficient clinical

detail to support the creation of the kinds of databases required to accurately assess patient outcomes using advanced information technologies.

Citing these and other problems, the National

Committee on Vital and Health Statistics, an advisory body to the Secretary of Health and Human

Services, has recommended developing a unified

classification and coding system for health care

services. 22 However, in 1994, even HCFA reaffirmed its intention to continue this dual coding

system policy in its Medicare and Medicaid programs, despite the substantial barriers this poses

to efficient information processing and analysis.

Provide additional funding for intramural and extramural research on the feasibility of developing a single classification and coding system that

could be applied to all health care services performed

by all providers in all settings.

Establish a new executive branch program to develop a unified service classification and

coding system.

Once a unified service classification

and coding system is developed, mandate that all federa/ agencies that manage health insurance and health

care delivery programs use that system in those programs.

Provide minimal funding for monitoring

and facilitating private sector development of a unified

service classification and coding system.

■ Telemedicine: Remote Access to Health

Services and Information

Telemedicine can be broadly defined as the use of

information technology to deliver medical services and information from one location to another. The use of telecommunications to deliver

health care services and exchange information is

not new. Chapter 5 discusses how recent technological advances—such as fiber optics, integrated

services digital networks, and compressed video

—have eliminated or minimized some of the

problems (e.g., poor quality images and slow

transmission speeds) that limited earlier applications.

Currently, there is much interest in the potential

of telemedicine to lower costs, improve quality,

and increase access to health care, especially for

those who live in remote or underserved areas. Pilot tests are also under way to test the feasibility of

delivering a variety of services directly to consumers in their homes.

20 Practice Management Information Corp., International Classification of Diseases, 9th Revision, Clinical Modification, Fourth Edition,

1993 (Los Angeles, CA: 1993).

21 American Medical Association, Physicians’ Curreny Procedural Terminology, 1994 (Chicago, IL: September 1993).

22 U.S. Department of Health and Human Services, Public Health Service, National Committee on Vital and Health Statistics, The National

Committee on Vital and Health Statistics, 1993 (Washington, DC: May 1994), pp. 8-10,54-75.
Chapter 1 Introduction, Summary, and Options | 21

Although there are no studies that prove the

cost-effectiveness of telemedicine, in some cases

it would seem to have the potential to reduce costs

for some participants. For example, telemedicine

can eliminate the time and wages lost at work and

traveling expenses incurred when specialists and/

or patients have to travel for consultations. In addition, keeping patients in their own communities

can increase revenues for local hospitals and decrease the cost to patients. The cost of a bed in a

community hospital is considerably less than in a

large medical center. Costs might also be reduced

by staffing hospitals and clinics with allied health

professionals, such as nurse practitioners and physician assistants, who would deliver services

where there is no resident physician. Overall costs

also could be lower using telemedicine if it allows

patients to be seen earlier, thus preventing the

need for later, more costly care. Using telecommunications to deliver services directly to the

home would also reduce the costs of travel, as well

as the pressures on clinics, emergency rooms, and

doctors’ offices.

In the short term, however, costs could increase. Telemedicine could add an extra step to the

process if the patient still requires referral to a

larger medical center. If it improves access to care,

there may be increased use of health services as

more people take advantage of their availability. If

reimbursement for telemedicine services becomes

widespread, the system may be vulnerable to

abuse through overuse or fraudulent claims. Cost

is not the only criterion, however. It is important to

consider the “value” of delivering services to

those who might otherwise not get them at all because of their physical location.

Telemedicine can increase access to health care

for populations in rural or inner city areas. It can

do so by making these areas more attractive to

health care providers by giving them immediate

electronic access to up-to-date information and resources, specialists for consultative purposes,

continuing medical education, and other colleagues. Enabling local hospitals to remain economically viable by keeping patients in their own

communities is another benefit for access, as well

as for the economic stability of the community.

Telemedicine appears to have the potential to

improve the quality of care, but this has not yet

been proven. It can provide faster, more convenient treatment and minimize the disruption of the

patient’s life. By reducing the need for referrals,

the continuity of patient care is ensured. The quality of care may be better for a patient who has the

benefit of family support in the local area. For providers, ready access to information to help them

make more informed decisions will improve the

quality of the care they deliver. Electronic access

will help them stay up to date and enable them to

receive continuing medical education credits

without leaving their communities. Some believe

that the establishment of clinical practice guidelines for telemedicine could help to provide a

more consistent level of care.

While telemedicine has been practiced for 30

years, its current iteration is still in the early stages

of development. It will take a number of years before it is used widely enough and evaluated sufficiently in terms of its effectiveness and efficiency

for definitive statements to be made about its

overall value and recommended uses. Like all new

technologies, there will be impacts that cannot be

anticipated in advance. Rigorous evaluation studies are needed to determine telemedicine’s potential benefits, and such research is currently being

supported by a number of federal agencies. The results should provide policymakers with the data

they need to make decisions about the efficacy of

telemedicine. Proposed federal budget cuts, however, are likely to have a negative impact on telemedicine research efforts.

Policy Issues

While the use of telecommunications in delivering health services has great potential, it also

raises a number of issues that need to be resolved

if telemedicine is to thrive. In general, patient consultations using telemedicine are not reimbursable (except for teleradiology and telepathology).

This will have a negative effect on its diffusion until HCFA promulgates a national policy. One of

the reasons for HCFA’s reluctance is the fact that

there is a lack of research available to support the
22 | Bringing Health Care Online: The Role of Information Technologies

safety, efficacy, clinical utility, and cost-effectiveness of telemedicine.

Another issue is the cost of the telecommunications links required for telemedicine. In many rural areas, the communication infrastructure is

unable to support the bandwidth necessary to

carry the signals for telemedicine using two-way

interactive video. In addition, the costs of connections between local and long-distance telecommunication carriers can pose a significant barrier

to telemedicine projects. Under the existing tariff

structures, telephone calls placed to locations inside the local access transport area boundaries are

often more expensive than those placed outside

the same service area.

Telemedicine raises some difficult legal and

regulatory issues as well. Remote diagnosis and

treatment across state lines could bring different

laws and regulations into play. A previous OTA

report found that the present legal scheme does not

provide consistent, comprehensive protection of

privacy in health care information, whether it exists in a paper or computerized environment.

Clearly the privacy implications for telemedicine

will continue to receive careful scrutiny. Physician licensing becomes an issue because telemedicine facilitates consultations without respect to

state borders and could conceivably require consultants to be licensed in a number of states. This

would be impractical and is likely to constrain the

diffusion of telemedicine projects. Telemedicine

may, in fact, decrease the threat of malpractice

suits through improved recordkeeping and databases, and the fact that taping the consultations

will automatically provide proof of the encounter.

However, it may also raise other liability issues,

such as the lack of a “hands-on” examination by

the consultant.

Congressional Options

Responsibility for telemedicine policy is shared

among federal, state, and local lawmakers, and

many of the decisions affecting the diffusion of

telemedicine are influenced largely by the private

sector. Federal efforts to reform both the health

care and telecommunications systems, each traveling its separate path, will have an effect on telemedicine’s progress.

Implementation of telemedicine is likely to

proceed with or without federal support as providers recognize its benefits to their practices. However, federal government support will be required

if it is to benefit those who need it the most—

people living in rural and inner-city areas where

market forces are unlikely to provide the services

needed. In a time of tight fiscal constraints and

shrinking research budgets, federal funding provided will need to be carefully monitored to ensure it is being used wisely. If Congress wishes to

encourage the diffusion of telemedicine to help

solve the disparities in health care availability, it

can have the most impact in the areas of research

funding and reimbursement for telemedicine consultations. The two are closely connected, in that

formulating a standard reimbursement policy is

dependent on obtaining satisfactory answers to

many of the questions raised about telemedicine’s

efficacy and cost-effectiveness. Congress may

wish to:

Continue to support demonstration and

evaluation projects.

The research currently under way is crucial to

answering many of the questions about the benefits of telemedicine. To ensure that projects are

sustainable when funding ends, agencies need to

build in certain requirements. This is currently

achieved by requiring that grantees make a financial investment in the project, often through

matching funds. Many of the current funding opportunities for telemedicine projects focus on rural areas. Telemedicine also offers potential for

solving some of the problems of inner-city health

facilities. After assessing these needs, Congress

could target support for depressed areas where the

needs are great and a limited investment might be

highly leveraged.

Because the data that would support a uniform

reimbursement policy for telemedicine consultations are not yet available, HCFA is moving slowly and deliberately in accumulating the necessary

information on which to base a sound decision.
Chapter 1 Introduction, Summary, and Options | 23

This seems a prudent strategy. Experimenting

with reimbursement in a small number of demonstration sites will provide valuable insights that

will eventually enable the agency to craft a careful

policy based on actual results. Congress may wish

to ensure that adequate finding is provided to

support those experiments. As the results become

available, Congress may wish to provide oversight

and conduct hearings to determine what further

action may be warranted.

Until recently, there was a lack of coordination

of federal efforts in research, policymaking, and

implementation of distance care. This has been remedied considerably by the creation of the telemedicine working group of the Administration’s

Information Infrastructure Task Force.

The costs of implementing telemedicine can be

a barrier to its diffusion, especially for small communities and facilities. To address this barrier,

Congress may wish to:

Create incentives for cooperative efforts

and consortia.

In many small communities, it makes economic sense for groups to share the costs of implementing, operating, and maintaining a

telecommunications network. For example,

schools, medical clinics, libraries, social services,

and others who would benefit from improved information services may need to join forces to get

started. The Department of Defense and the National Aeronautics and Space Administration

(NASA) have been leaders in research related to

telemedicine applications, and the military has

health facilities in a number of locations. In some

sites the military has cooperated with civilian

health care personnel to deliver services using

telecommunications. Where possible, the expertise that exists in the military and NASA should be

shared with the civilian sector. Agencies such as

the Department of Veterans Affairs could also be

involved in cooperative efforts with the civilian

sector.

Ensure that information about telemedicine is widely disseminated.

In many cases, those who might benefit most

from telemedicine applications know very little

about them. While information dissemination is

increasing in a variety of formats, there is a need

for a centralized, online database of telemedicine

information. Such coordination might include

creating an electronic clearinghouse that would

provide a range of information about telemedicine

projects, including funding opportunities, current

projects, and people to contact for assistance and

advice. Congress might wish to ensure that mechanisms exist, either in the public or private sectors,

to widely disseminate research results and other

information about telemedicine.

One of the goals of the IITF telemedicine working group is to investigate the feasibility of setting

up an online database of telemedicine activities,

and work is continuing to determine the best way

to achieve this. Such a clearinghouse could be established in a designated federal agency within

DHHS, such as the National Library of Medicine

or the Office of Rural Health Policy. Alternatively,

Congress could provide support for a private-sector group, such as the Telemedicine Information

Exchange network at the Telemedicine Research

Center, Oregon Health Sciences University. This

option would avoid duplication of effort and provide a single site where telemedicine information

could be maintained and obtained. However, it

would also require careful consideration concerning the content of the database and how information would be structured and formatted. Any

telemedicine clearinghouse would only be useful

if kept up to date, and support for qualified staff

would needed to be assured.

OTHER APPLICATIONS

The applications of information technology detailed in chapters 2 through 5 and summarized

above were selected because of their potential to

improve access to health care, improve the quality

of care, and reduce the costs of delivering care.

These were of particular interest to the study’s requesters. OTA was unable to undertake an indepth analysis of a number of other applications

of information technology that also have potential
24 | Bringing Health Care Online: The Role of Information Technologies

for improving health care. Two are mentioned

here—consumer health informatics and community networking.

❚ Consumer Health Informatics

Consumer health informatics has been defined as

“the study, development, and implementation of

computer and telecommunications applications

and interfaces designed to be used by health consumers.”23The basic principle is that of empowering people to play a greater role in their own health

care and to be active participants in decisions affecting their health.24 Information technology can

be used to provide more health-related information to consumers, “the largest untapped resource

for health care.”25 Taking measures to prevent illness and disease, by adjusting lifestyles or taking

safety precautions, for example, could have a positive impact on the health care delivery system and

allow people to lead healthier lives.

Shared decision support systems are designed

to inform patient/provider decisions regarding

prevention, diagnosis, management, and treatment, and ultimately to improve the quality of

care and reduce costs. Choices are made collaboratively by patients and their caregivers. An example is the interactive video disk system developed

at Dartmouth Medical School that allows men

with benign prostatic hyperplasia and early stage

prostatic cancer to share in decisions on their

course of treatment.26 Some regard these computer-based systems as transforming the culture of

the health care system to one in which patients,

physicians, and other providers play equal roles in

decisionmaking. 27

Information technology also could play an important role in reducing a consumer’s need for

health care services. Demand management can be

defined as the “the support of individuals so that

they can make rational health and medical decisions based on a consideration of the benefits and

risks of the options available.”28 Current examples include health risk appraisals, written and audiovisual media, telephone counseling services,

and community resources. Although a comprehensive demand management system does not yet

exist, information technologies can make interventions more available and effective, and provide a sophisticated, multipurpose information

system based on a new concept of the individual

health record. When developed, these comprehensive services will allow consumers to understand,

choose, and evaluate health services in new ways,

and could have a positive impact on health care

costs and quality.29

Information technology also fosters communication among people who can provide support

and encouragement to those dealing with chronic

illnesses or a medical crisis. There is a large and

growing community of people using computers to

provide help and support to one another to address

a variety of concerns. For example, as of early

23 Tom Ferguson (ed.), “Consumer Health Informatics: Bringing the Patient Into the Loop,” Proceedings of the First National Conference

on Consumer Health Informatics, July 1993, p. 2. The Administration’s Information Infrastructure Task Force, Consumer Information Subgroup, defines consumer health informatics as “any information that enables individuals to understand their health and make health-related

decisions for themselves or their families.”

24 John Wennberg, “Shared Decision Making and Multimedia,” Health and the New Media: Technologies Transforming Personal and Public Health, Linda M. Harris (ed.) (Hillsdale, NJ: Lawrence Erlbaum Associates, Inc., 1995).

25 Vergil Slee and Deborah Deatrick, “Reengineering Health Care Decision Making,” Health Commons Update, vol. 2, winter 1995, p. 6.

26 Wennberg, op. cit., footnote 24.

27 Deborah Deatrick, Executive Director, Health Commons Institute, personal communication, June 9, 1995. See also Slee and Deatrick, op.

cit., footnote 25, p. 1.

28 D.M. Vickery, “Demand Management, Self-Care, and the New Media,” Linda M. Harris (ed.), op. cit., footnote 24.

29 Ibid.
Chapter 1 Introduction, Summary, and Options | 25

May 1995, America Online reported it had 148

scheduled self-help groups.30 Some of these

groups address health-related concerns, such as

diabetes, stroke, AIDS, cancer, or disabilities.

Others support the caregivers of people suffering

from Alzheimer’s disease or other debilitating illnesses. Nonprofit groups, such as the American

Self-Help Clearinghouse, provide assistance and

information to those wishing to set up an electronic support group or find out about such groups.31

Information on a variety of online health resources

can be obtained from the National Health Information Center.32

The CHESS system is an example of one that

allows consumers to access information about

their illnesses and to support one another using

home terminals.33 Another is the Connect System, a computer and voice-mail system used to

monitor inner city drug-using pregnant women in

Cleveland, Ohio. At Case Western Reserve University, ComputerLink was a demonstration project that supported the caregivers of persons with

Alzheimer’s disease and AIDS by delivering information, communication, and decision support,

accessed through home terminals.34 (See ch. 5 for

more complete discussion of these systems.) Future systems geared to the needs of consumers are

likely to include interactive video to the home.

Participants in an OTA workshop in July 1994

had a number of suggestions regarding what actions are needed to foster greater electronic health

resources for consumers. These included:

1. support research and development;

2. support wide access to the NII as it develops;

3. insist on good needs assessment for consumer

applications;

4. incorporate medical informatics into the medical education curriculum;

5. support clinical trials of different ways of sharing health data;

6. reduce the cost of telephone links to electronic

bulletin boards;

7. subsidize premarket development of tools that

private corporations can use and resell;

8. facilitate the use of technology by managed

care organizations;

9. educate, support, and train users; and

10. provide grassroots technology “set-asides.”

The Administration’s Information Infrastructure Task Force has a subgroup of representatives

from federal agencies who are addressing consumer health information and the NII. This committee has coordinated the development of a draft

white paper outlining key policy issues for the

federal government to consider as the public increasingly relies on electronic means of information access and exchange.35 This paper was

released for public comment at a federally sponsored national conference on networked consum30 Todd Woodward, Self-Help Information Center, America Online, personal communication, May 8, 1995.

31 Barbara J. White and Edward J. Madara (eds.), The Self-Help Sourcebook: Finding and Forming Mutual Aid Self-Help Groups, 4th ed.

(Denville, NJ: St. Clares-Riverside Medical Center, 1992).

32 NHIC’s home page on the World Wide Web is located at <URL: http://hic-nt.health.org/ >. NHIC is a service of the Office of Disease

Prevention and Health Promotion, Public Health Service, U.S. Department of Health and Human Services, and the George Washington University Himmelfarb Medical Library.

33 F.M. McTavish et al., “CHESS: An Interactive Computer System for Women with Breast Cancer Piloted with an Under-Served Population,” n.d.

34 Patricia F. Brennan, “Differential Use of Computer Network Services,” American Medical Informatics Association, Proceedings,

Seventh Annual Symposium on Computer Applications in Medicine, Oct. 30-Nov. 3, 1993, Washington, DC, p. 27.

35 Kevin Patrick and Shannah Koss, “Consumer Information ‘White Paper,’” Consumer Health Information Subgroup, Health Information

and Application Working Group, Committee on Applications and Technology, Information Infrastructure Task Force, working draft, May 15,

1995.
26 | Bringing Health Care Online: The Role of Information Technologies

er health information in May 1995. It will serve as

the cornerstone for Administration policy in applications technology development and use.

Key policy issues for the federal government

identified in the paper include:

 the need to coordinate federal consumer health

information dissemination efforts both within

the government (federal, state, and local) and

with private providers;

 assurance of privacy and confidentiality;

 assurance of the availability of information

critical for public health;

 the need for research and evaluation of the impact of consumer health information;

 the role of standards in vocabularies and data

transmission;

 information validity and integrity;

 assurance of telecommunications infrastructure for adequate information delivery; and

 education and training.

❚ Community Networking

Human services, including health care, are often

delivered in a fragmented fashion, leading to duplication of effort on the part of providers and consumers. Telecommunications could be used to

coordinate and streamline these services through

community networking,36 enabling the providers

of a wide variety of social services to share information and communicate with one another. An

earlier OTA report discussed the role of the local

community infrastructure—schools, libraries, senior centers, and town halls—in delivering federal

services to citizens electronically, especially those

in rural areas, small towns, inner cities, and people

with special needs37 (see box 1-3). The difficulties

of building an infrastructure can be a barrier, however. One group of researchers commented:

Although there is widespread endorsement of

such proposed efforts as managed care and onestop shop service delivery, the more difficult

task in most communities is to build an infrastructure that supports such coordination with a

holistic approach to service and care.38

One example of a project using telecommunication and computer technologies to support

and coordinate health and human services at the

community level is the Community Services Network (CSN) in Washington, DC. This is a joint effort of the U.S. Public Health Service, Howard

University School of Social Work, Rice University and Baylor College of Medicine, Macro

International, Inc., United Seniors Health Cooperati

ve, and Bell Atlantic Corp. Several communities

across the country are currently exploring the development of CSNs. The Lawrence Livermore

Lab in California is helping Macro and other partners develop test-beds to move CSNs from pilot to

early operational status.39

36 For a discussion of the role of information technology in strengthening community action, see Nancy Milio, Engines of Empowerment

(Ann Arbor, MI: Health Administration Press, 1995).

37 U.S. Congress, Office of Technology Assessment, Making Government Work: Electronic Delivery of Federal Services, OTA-TCT-578

(Washington, DC: Government Printing Office, September 1993), ch. 5. See also U.S. Congress, Office of Technology Assessment, Telecommunications Technology and Native Americans: Opportunities and Challenges, OTA-ITC-621 (Washington, DC: U.S. Government Printing

Office, August 1995).

38 G.A. Gorry et al., “Health Care as Teamwork: The Internet Collaboratory,” in Health and the New Media, op. cit., footnote 24, p. 97.

39 Kevin Patrick, Department of Health and Human Services, personal communication, May 10, 1995.
Chapter 1 Introduction, Summary, and Options 27

OTA commissioned two grassroots computer networks to conduct computer conferences on the topic of

electronic service delivery. Big Sky Telegraph (BST), headquartered in Dillon, MT, and the National Public Telecomputing Network (NPTN), headquartered in Cleveland, OH, conducted the conferences during late summer

and fall of 1992. Lessons learned include:

1. The costs to users of grassroots computer networking can be minimized. Almost any personal computer

(PC) and modem wiII suffice, high-end, high-speed equipment is not necessary. Online telecommunication

charges can be reduced by copying messages to a PC and preparing responses with the telecommunications

line turned off, and by using fractional rates and bulk purchase discounts. Use of equipment that transmits

messages faster will reduce online charges further.

2 Any local community can have a community computer bulletin board. BST has, in effect, created six

“Little Skys” where people can dial in with a local call—further reducing online costs. BST IS a rural equivalent

of the NPTN’s network of “Freeness. ” BST is a rural FreeNet. All you need is a PC, modem, telephone line, and

inexpensive bulletin board software, And to further reduce costs, the “Little Sky” or “FreeNet” can dial up a

host computer once a night at off-peak rates to copy or add bulletin board items.

3. Community computer bulletin boards really extend a sense of community. BST and NPTN, Iike CompuServe and Minitel, found that users participate as much for sociability as for content. Users seek a comfort

level and degree of intimacy that is not always prevalent in the community-at-large. Computer conferencing

also greatly reduces any biases due to sex, physique, disabilities, speaking ability, etc. It is a leveling technology in this sense.

4. Community computer networks usually get only limited support from the established government and

business community. The BST and NPTN approach is low-cost and decentralized; the state and federal bureaucracies tend to favor higher cost, more centralized, or at least more controllable, approaches Also the

“not invented here” syndrome IS evident. Each organization has a tendency to invent its own solution or approach,

5. Grassroots computer network utilities like BST and NPTN can facilitate local access to national computer

networks that might not be otherwise technically feasible or affordable. If local residents find computer networks such as the Internet expensive or difficult to access directly, computer utilities can provide low-cost,

user-friendly connections.

6. Grassroots computer conferencing works for children. Children as young as the third grade can use

computer conferencing to learn keyboarding, e-mail, and the concept of communicating among a group electronically (even some first-graders can handle it).

7. Grassroots computer conferencing has significant potential for government service delivery For example: a) agricultural extension services, b) small business assistance, c) International trade—global trade networks offer tremendous potential for locally based global entrepreneurial networking, d) Indian reservation services, especially for the Indian schools and hospitals, e) vocational education for displaced homemakers, f)

job opportunities—potential for computerized catalogs of jobs and skill requirements, and g) public access to

the Iegislative process.

8. Training is essential to computer conferencing success. It is Important for first experiences to be positive

in order to develop self-confidence. Help lines work, rather than forcing users to struggle through manuals. As

confidence builds, users can do more themselves and handle more complex functions. Initially many people

are not ready for searching databases; but eventually users will want to and can do searches.

9. federal programs largely miss the potential of grassroots computing. The government does not have

good mechanisms to support small, local innovators who lack a major Institutional affiliation. Suggestions

mini-grants of up to $5,000 or so to local innovators; more flexibility in the National Science Foundation and

other federal grant programs to support individuals and small, grassroots organizations, inclusion of grassroots representatives on federal advisory and peer review panels; technology showcases and demonstrations

(e.g., fiber-to-the-school demonstrations in rural, economically disadvantaged areas).

SOURCE: Big Sky Telegraph, National Public Telecomputing Network, and Office of Technology Assessment, 1993 ‘-

— .

I

I

I

I
Information

Technologies for

Transforming

Health

Care

he central event of successful health care is the preservation of health or the healing of an infirmity through employment of medical expertise for the benefit of a patient.

This can be deeply satisfying for all parties, but it often

occurs within a complicated and frustrating health care delivery

system. Working from dimly remembered medical facts and perhaps a few consumer health information brochures or a thin

guidebook published by an insurance company, individuals must

decide which doctor to select, pay for their care, negotiate reimbursement, evaluate the care they receive, and choose healthy

lifestyles. But if patients and consumers have too little information, doctors and other health care practitioners generally have

too much. They must keep abreast of a burgeoning medical research literature, gather information from bulging but inadequate

paper record systems, diagnose and treat diseases, educate patients, and extend or limit patient access to specialists. Administrators and insurance companies must work within information

systems that are often poorly organized to answer complex questions as they compete for customers, comply with shifting regulatory policy, optimize use of resources, provide high-quality

health care, and meet investor demands for profitability. And the

federal government, in its role as a provider and purchaser of

health care, must find ways to minimize the cost of providing

health care.

Many of the frustrations encountered by participants in the

health care system can be traced to the inability of current information systems to provide adequate, accurate, timely, and appropriate information. Poor information flow has become an

impediment to efficient delivery of high-quality health care. | 29
30 | Bringing Health Care Online: The Role of Information Technologies

ISLANDS OF AUTOMATION

There is a long history of attempts to solve the

problems of inadequate health information systems by using computers. When the first generalpurpose laboratory computer was introduced to

the market, it was immediately used in a project

to compile computer-based medical histories.40

Today, many hospitals spend a large portion

of their budgets on computers and recordkeeping.

An entire academic field called medical informatics has developed around the study of administrative, clinical, demographic, research, and

educational information generated in the process

of delivering health care services. Many health

professionals believe that delivery and coordination of care might be greatly improved if all relevant information were collected in a standard

digital form and broadly connected in a health data

system. This would enable authorized persons to

rapidly access and modify data when necessary.

No such system currently exists.

Thirty years of academic, commercial, and

government research have produced successful

pilot programs and commercial implementations

of parts of a comprehensive digital health information system. Many hospitals have computerized their administrative or clinical records,

many insurance claims and orders for supplies are

submitted electronically, many research materials

are distributed over computer networks, and electronic distribution of consumer health information has begun. However, there is still no system

that comprehensively facilitates the flow of all

types of health information and symmetrically addresses the needs of clinicians, administrators,

policymakers, patients, and consumers. The full

potential of digital health information will only be

realized when it begins to flow beyond the confines of single departments, institutions, or communities.

The current situation is often characterized as a

series of islands of automation. This report provides a tour of that digital archipelago; it surveys

the history and terrain of the existing islands of automation and offers potential options for possible

federal roles in enlarging and connecting the islands. This chapter begins, as it were, with the

ocean: it provides an overview of the organization

and flow of information within the broad health

care system. It then describes information systems

within hospitals and clinics. By focusing on the

subset of clinical information that has been stored

conventionally as paper-based clinical patient records, the discussion illustrates some of the problems and challenges confronted in the effort to

digitize health information. The chapter also describes several key technologies that underlie efforts to build an interconnected health data

system. Subsequent chapters describe ways these

technologies are being used in administrative systems, clinical decision support and care evaluation systems, and systems for delivering health

care to a scattered and diverse population through

telemedicine and other techniques.

The story begins with a glimpse of the imagined mainland: the following scenario illustrates

some of the many ways that health care might be

different should information technology achieve

its full potential as a medical tool. The scenario is

fictional, but not utopian: it explores how the experiences of consumers, clinical teams, administrators, and policymakers might change in a world

where health information flows freely.41 It implicitly illustrates some of the problematic aspects of

40 W.V. Slack et al., “A Computer-Based Medical History System,” New England Journal of Medicine, vol. 274, 1966, pp. 194-198. Slack

used LINC, one of the first general purpose laboratory computers and an ancestor of the desktop computers now spreading throughout the

health care delivery system.

41 In the scenario, information “flows freely” in that structural and technological impediments to exchanging information have been minimized, but it only flows within prescribed channels. This qualification will need to be applied to any comprehensive health data system that

might develop. There must be adequate security and confidentiality mechanisms in place so that all participants are willing to trust the system

and put their information into it. In addition, the legal, regulatory, and technological standards that define the channels must be stable and rational enough for businesses and institutions to depend on them.
Chapter 2 Information Technologies for Transforming Health Care | 31

the digital revolution in health care, along with the

many possible opportunities and advantages.

Consider, then, a fictional scenario of health care

in a fully digital world.

❚ Simplified Administration

Emilia finished her reply to the clinic’s e-mail

message and launched her web browser. The

e-mail had been a reminder confirming her appointment later that day at the maternity clinic at

the medical school; with only a month remaining

until her due date, she was well acquainted with

the routine of arriving at the clinic, having the

nurse practitioner check the baby’s size and heartbeat, and returning home with a fresh stock of vitamins and increasingly real expectations for the

future. Emilia chose the medical school’s home

page from her browser’s list of recently visited

sites and typed her name and password into the

scheduling inquiry form. In a moment, the response to her query appeared: appointments in the

maternity clinic were running about 20 minutes

late. She had plenty of time for lunch before the

visit.

For the past few years, Emilia had received primary health care through the student health service at her college, but when she became pregnant

all that changed. She was referred to the maternity

clinic at a teaching hospital associated with the

university and had received all her prenatal visits

and screening there. From her first visit, it had

been apparent that things were done differently at

the hospital than at any doctor’s office or clinic she

had visited. Emilia and her husband John had arrived well before their scheduled appointment, expecting to have to complete a pile of paper forms.

Instead, they were directed to one of a set of kiosks

in the reception area where they sat down and began interacting with a computer program. The

computer asked Emilia to swipe the magneticstripe card from the student health service through

the reader next to the machine, and then the machine began asking them questions. Most of the

questions were the usual ones—“Do you have a

history of heart trouble?” for example—but at

least she didn’t have to fill out all those tedious addresses—her own, her next of kin, and the like.

The computer had already read them from the

magnetic card. It took only five minutes to complete the program’s questions because it didn’t ask

for the same information in many different ways

like paper forms often do. When she clicked on the

button indicating that she was an only child, the

program didn’t ask any further questions about the

health history of her siblings. The program had a

few sections for John to fill out about his own family history.

The kiosk then provided a curious section

about granting the hospital permission to use the

information generated during her care. Emilia had

seen similar language in small type at the bottom

of paper forms and had always initialed the boxes

indicating her agreement, but she had never paid

much attention to it. This program made the information permission seem almost as important as

the health history itself: it requested specific permission to use all her medical information within

the hospital, it asked for separate permission to release her record of care anonymously to state or

federal authorities for research purposes, it asked

for permission to automatically compare her profile with those sought for various clinical trials in

the hospital, and on and on. In the end, the program summarized all the permissions she had given and asked her once more to approve the whole

set. Emilia realized she didn’t fully understand

what sorts of clinical trials the questionnaire

might be referring to, and so she changed her approval of that item to a request for more information.

After completing the program, she returned to

the desk and the receptionist gave her a new plastic card. “It’s a smart card,” he said, “try not to

bend it.” Emilia asked why the program had been

so annoyingly thorough in asking for permission

to use her health information. “If we don’t annoy

you now, someone else might annoy you later,”

the receptionist explained. “We keep digital records instead of paper records in this hospital, so

we can’t control where our information goes just

by locking the drawer of a filing cabinet. Of

course, we use passwords, encryption, and other

security measures to control who can read and al-
32 | Bringing Health Care Online: The Role of Information Technologies

ter your records in the hospital, but some of your

health information goes elsewhere as well. We bill

your insurance company electronically so all you

ever have to worry about is the copayment, and we

abstract information from your records for reports

requested by our management and those required

by the government. The permission form you’ve

just completed provides another layer of security

that helps ensure that whenever your records are

used for purposes other than directly providing

care to you, you know about it and have approved

it. It’s a little like giving us a digital power of attorney—anyone who has your health information

and wants to release it to someone else for a different purpose has to check for your permission

against the file you’ve just created. That’s the rule,

even if everything directly identifying you has

been removed from the record. You’re not giving

us blanket permission to use your health data—

that’s why the form is broken into so many separate

questions covering different aspects of information sharing. And it’s fine to decline permission on

this form—that just means we’ll need to ask your

permission on a case-by-case basis later.”

Emilia thought for a moment. “So I own my

health records?” The receptionist smiled, “No,

and you certainly couldn’t reassemble all the information once it is released, but you can help determine where that information goes. I see that

you’ve asked for more information about enrollment in clinical trials. The computer has put a reminder on your nurse practitioner’s schedule to

discuss that with you. She’ll tell you about some

of our ongoing research and discuss how your care

might be affected by your decision to share or

withhold information from the system that

matches eligible patients with clinical trials.”

❚ Informed Patients and Consumers

Emilia and John had many more experiences with

the kiosk following that initial visit. Each time

they came to the clinic, they checked in by inserting the smart card and charging the copayment to

their credit card, then used their spare moments

before the nurse practitioner was available to learn

more about their baby. The computer referred to

information in Emilia’s electronic patient record

and then presented multimedia modules tied to the

gestational age of the baby. When ultrasound

scans were taken early in the pregnancy, they

could review them on the screen in full motion,

and Emilia was able to change the contrast and

color schemes so that even John could recognize

the baby’s face. They still got the little snapshot

that most parents take home, but they could also

e-mail their parents a minute or so of digitized video as well.

There were modules about the risks and benefits of alpha-fetal protein screening, genetic testing, pain medication during delivery, and the

many other decisions they had to make. When

John couldn’t go with her to the prenatal visits, he

would work through the same educational modules at home using a web browser over the Internet. Emilia liked being able to find the answers to

some of her questions without having to ask the

clinician directly—not only did she avoid having

to play telephone tag with the clinic or call in at

certain hours of the day, but she could get information on her own so that she was more confident in

asking questions face-to-face.

Emilia collected information from several different electronic information sources besides the

medical school. She borrowed a health information CD-ROM from a friend and found several

more disks and videos at the city library. She subscribed to a free Internet mailing list about pregnancy and childbirth experiences and participated

in a chat forum with other women on a commercial online service. And she made a point of regularly exchanging e-mail with some of the other

women in her birthing classes at the hospital. That

class was definitely not a place for high-tech multimedia programs, but for hand-holding and

education from a nurse who had seen many, many

births. Nonetheless, the scheduling for the class

was set up through the hospital computer system,

and the women kept in touch electronically with

each other and their teacher between classes.
Chapter 2 Information Technologies for Transforming Health Care | 33

❚ Paperless Medicine

When Emilia arrived at the clinic, she answered a

few questions that the kiosk had for her and then

went into a room where a nurse recorded her

weight and vital signs and measured her belly before the nurse practitioner arrived. The nurse inserted Emilia’s smart card into a computer in the

examination room and typed the weight and size

measurements into a form that appeared on the

screen; the blood pressure machine and thermometer were hooked directly into the computer system and their measurements appeared on the same

form automatically. Computers in the teaching

hospital certainly weren’t limited to multimedia

kiosks in the reception area. Every doctor, nurse,

receptionist, and treatment room had one, and all

the computers were interconnected by cables, radio, or infrared links. When the nurse practitioner

entered the room, she was invariably holding a

small computer in her hand and noting the new datapoint on the graph showing Emilia’s weight

throughout her pregnancy. A summary of Emilia’s

previous visits and her responses to the screening

questions today were also provided. The nurse

practitioner’s computer didn’t have a keyboard,

but that didn’t seem to matter because there was

little writing or typing involved. If the NP wanted

to order a laboratory test, for instance, she selected

the proper form from a menu on the screen and

most of the information would already be filled in

by the computer. She used a stylus to check off

boxes indicating what she wanted done and then

dispatched the order by tapping out her password

on a little keyboard displayed on the screen. During most of the encounter, the NP simply set the

computer aside and concentrated on the patient.

Today, she had a concerned look on her face.

“Emilia, I’m worried that your baby’s size

seems to be reaching a plateau rather than sharply

increasing in the usual way for the last few weeks

of pregnancy.” She showed her the screen of her

handheld computer, which had a plot of the sequence of Emilia’s measurements along with a

normative size development chart. “The dashed

lines represent the limits for a standard distribution of women. You’re still within those boundaries, and so your baby may well be developing

normally, but I’d like to order a few tests, beginning with another ultrasound. I can see that the ultrasound technician has an opening at 2:20, and

I’d like you to get the test done as soon as possible.”

Emilia’s heart fell. It would be her third ultrasound so far. The first one had been exhilarating,

and the second one less so. It had produced the expected pictures, but hadn’t really been mentioned

by her doctor after it was completed. It seemed

that the clinicians were willing to order tests very

readily, given that there wasn’t any paperwork involved and the results appeared very quickly on

their screens. How did they know that ordering so

many tests helped ensure healthier deliveries? It

certainly wasn’t cheap. At this point, though, she

wasn’t worried that the ultrasound was unnecessary but that it would be a harbinger of bad news.

As she refocused her thoughts, she could hear the

nurse practitioner saying, “You have an hour. Why

don’t you spend the time looking at our Delivery

and Birth CD-ROM just in case you don’t have

the opportunity to finish those classes?”

❚ Empowered Clinical Teams

In the staff conference room, Dr. Conway’s pager

vibrated and the digital assistant on the table in

front of her simultaneously awoke from its electronic slumber. The doctor felt a little sleepy herself, but at least she was getting continuing

medical education credits for these lunchtime

seminars utilizing the satellite link to Boston. She

glanced at the incoming e-mail, which indicated

that an obstetrics resident wanted her help with a

decision about a potential c-section. The doctor

left the seminar quietly and read the case précis

that the digital assistant displayed as she walked

down the hall.

Emilia’s ultrasound technician had used imaging software to measure pockets of amniotic fluid

around the baby and had recognized that the volume of the pockets was critically low for this stage

of pregnancy. One of the hospital’s decision support systems had come to the same conclusion by

comparing the numbers in the technician’s sum-
34 I Bringing Health Care Online: The Role of Information Technologies

mary to the predictions of the OB-GYN expert

system. After asking the technician to confirm its

finding, the computer issued an alert to the resident on call. The resident’s online work history indicated that he hadn’t had direct experience with

this type of case, so the system prepared a onepage summary of similar cases from the last year

and a set of hyperlinks to the abstracts of relevant

research literature. The resident skimmed the information as it appeared on his clipboard-shaped

computer, talked to Emilia, and came to a quick

decision to admit her to the hospital. With the

touch of several on-screen buttons, he dispatched

software agents that silently scheduled a room for

Emilia, requisitioned a suite of monitoring equipment, ordered IV bags and Pitocin from the pharmacy, altered nursing assignments, and summoned

Dr. Conway.

Emilia had entered the clinic that morning

thinking it would be a normal day, but now she

found herself in the labor and delivery room without so much as a suitcase . . . the baby needed to

come out, labor would be induced, and the only

question was whether a c-section could be

avoided. She longed for the sort of uncomplicated

birth described in her classes, but it was not to be.

As she was calling John on her bedside phone and

asking him to drive faster, a nurse wheeled in several monitors and an IV pump and quickly attached them to a bedside computer. The nurse

opened a panel on the IV pump and inserted a barcoded bottle; PITOCIN-FLOW OFF began glowing

on the computer screen. Now the monitors

hummed all around Emilia, measuring her pulse

and blood oxygenation and the baby “s as well, and

ready to measure the contractions that would

come. Emilia was attached to so many wires that

she felt her body itself was a part of the information superhighway. She felt disoriented, but at least

the nurse had sufficient time to sit with her for a

few minutes and explain what was happening.

Dr. Conway walked in with the resident and

introduced herself. “We’ve been watching the fetal monitor data as we discussed your case in the

next room—there’s no indication that the baby is

in distress, so we’re going to induce labor as soon

as your husband arrives and see how it goes.

Please try to relax-chances are you’ll be home

with your baby in 24 hours. Do you have any allergies to medications I should know about?” Emilia

almost replied that there wasn’t anything particularly relaxing about being sent home less than 24

hours after delivery, but she sighed and simply

said, “No, no allergies. ” Dr. Conway already knew

that—the pharmacy alert system had crosschecked Emilia’s history for potential problems

with the pain-management drugs that might be

used in the delivery and posted the results along

with the drug prices on her digital assistant—but

she always asked again, just to be sure. She chose

the medications she wanted from the displayed

formulary and dispatched a software agent that

would arrange for delivery of the drugs to Emilia

bedside and update the pharmacy’s inventory and

reordering system. She performed a quick physical exam and then sat at a console in the corner to

dictate her findings into Emilia’s patient record.

As Dr. Conway spoke into the microphone, the

computer recognized her words and inserted them

into forms on the screen in front of her much faster

than she could have typed them. She filled out the

care plan and entered nursing and laboratory orders with a few touches of a stylus on the screen of

her digital assistant. Finally, she used a password

to attach a digital signature and time stamp to the

orders and the findings and then turned in her

chair. “Emilia, when your husband arrives, you

should start discussing names for the baby. That

one decision our computers can ‘t help you make!”

THE LIFE CYCLE OF HEALTH

INFORMATION

Emilia’s story describes some of the ways that applications of information technologies could

change the delivery of health care. The scenario

focuses on the experiences of a patient in a specialized clinical setting titan urban hospital. However,

similar opportunities, difficulties, and changes

will arise as information technologies are incorporated into the jobs of health care workers and into

home health care, rural health care, medical

education, population-based public health services, and other types of health care delivery. The
Chapter 2 Information Technologies for Transforming Health Care | 35

first step in this process is the digitization of health

information and the creation of an infrastructure

that allows health information to flow seamlessly

among the various parts of the delivery system.

Although the experiences described in Emilia’s

story depend on the use of information from many

different sources and on communication between

networks administered by many different types of

institutions, they are sometimes said to be products of an electronic, digital, or computer-based

patient record. This report will use the term computer-based patient record in a more limited

sense: it is a compilation in digital form of all the

clinical and administrative information relating to

the care of a single individual. Computer-based

patient records serve as repositories for clinical information and as records of communications and

transactions; their analogs in traditional health information systems are paper-based patient records

or charts, usually kept in folders along with films

at each site of care. Although computer-based patient records may be localized in a single data file,

they might also be widely distributed in computers throughout an institution or among several

institutions. In either case, the perceived location

of the record is on a computer screen in front of the

person using it at any particular moment.

It is possible to design stand-alone computerbased patient record systems and some are in use,

but much of the advantage of computerizing

health information is lost if other systems and

processes within the provider institution are unable to interact with information in the record.

Maintaining a stand-alone patient record, for example, could require caregivers or clerical personnel to retype test results that were produced by a

computerized lab analyzer in order to get them

into the record, or to retype administrative information from the record for use in creating financial statements. To avoid these inefficiencies,

computer-based patient records are usually embedded in various other information systems.

These systems include not only computer hardware and software and networks, but also the

“people, data, rules, procedures, processing and

storage devices—and communication and support facilities” involved in managing the record

system and distributing data and information

throughout the provider organization.42 For hospital patients, computer-based patient records are

typically linked to clinical information systems

that track clinician-patient encounters, and they

may be linked to administrative, laboratory, nursing, and pharmacy information systems as well.

However, most health care encounters occur outside of hospitals. The large amount of health information generated in primary care and home

care settings could be captured in computerized

patient record systems embedded in information

systems appropriate for private and group practice

doctors and public health workers.

Ideally, within a single institution, the distinctions between these various information systems

should be transparent to users so they become

parts of a seamless enterprise information system.

In practice, however, the components for each

type of information system are usually procured

separately, and their integration can be plagued by

a lack of design coordination and technical standards. New departmental computer systems may

be incompatible with each other and with previously installed legacy systems. Although the

discussion in this chapter primarily encompasses

clinical information systems in hospitals, most of

the benefits described in the scenario will come

from the synergistic interaction between computer-based patient records and broader sources of information assembled from a variety of networked

information systems. The next section illustrates

how information flows within clinical information systems and discusses the content, utility,

strengths, and weaknesses of paper and computerbased patient records.

42 Richard S. Dick and Elaine B. Steen (eds.), The Computer-Based Patient Record: An Essential Technology for Health Care (Washington,

DC: National Academy Press, 1991), p. 12.
36 | Bringing Health Care Online: The Role of Information Technologies

❚ Clinical Information Systems

Figure 2-1 shows some of the ways that information flows between patient records and the various

information systems inside and surrounding a

large health care organization.43 The information

might be contained in a mixture of paper and computerized records and transferred via computer

networks, fax, modem, mail, or courier. The figure indicates general sources and destinations of

information, but is not intended to reflect the specific architectures or communication pathways in

a particular setting. For instance, the institution’s

data repositories are shown near the center of the

figure, but they may be implemented as a single

centralized record system or distributed among

various departments in the hospital. The data repositories include administrative and clinical patient records representing information about

individual patients. They also include financial

and other management-oriented databases that incorporate data gleaned from records of the entire

patient population. Information such as schedules, personnel records, internal communications,

and regulatory policies that support the operation

of the institution are also included. One of the key

advantages of shifting to computer-based patient

records is the opportunity to strengthen the link

between clinical records and management information systems so that resource use and quality

of care can be analyzed using clinical data.

Clinical patient records contain encounter

information, bedside data and nursing notes generated in the wards, laboratory reports, pharmaceutical receipts, images, and specialized reports

from various institutional departments. The administrative departments exchange information

with various external health care providers and

practitioners and with the patient. They also generate information about the patient’s demographics and movements within the hospital and

compile bills using information from the clinical

records. The bills and orders for new supplies are

passed to logistics departments, which generate

purchase orders for medical supplies and pharmaceuticals. They also send out bills to insurance

companies and request (through intermediaries)

reimbursement from the Health Care Financing

Administration (HCFA) and state agencies for

care provided through the Medicare and Medicaid

programs. Caregivers may use clinical research

literature, public knowledge bases, and other external information resources. Federal and state

governments indirectly shape the flow of health

care information by funding clinical research and

aspects of communication infrastructure development, and through the regulatory activities of the

Food and Drug Administration, HCFA, state licensing authorities, and other bodies.

One example of a comprehensive clinical information system is the Regenstrief Medical Record System developed by the Indiana University

Medical Center.44 This system is used for both

hospital and outpatient care in a network of three

hospitals and 30 clinics, several health maintenance organization (HMO) offices, and care sites

for the homeless and elderly. The system captures

data from clinicians through an order-entry system and through links to administrative, laboratory, and pharmacy information systems. In

addition, it captures nursing notes and some of the

data generated by bedside monitors and electrocardiogram carts. It automatically reviews each

patient chart for completeness and uses a set of

more than a thousand rules to generate notices

about allergies, potential drug-diagnosis interactions, treatment suggestions, preventive care, and

43 The figure gives a central role to the hospital as a reflection of this chapter’s emphasis on information systems in hospitals. Of course, most

individuals receive very little of their care at hospitals, and while hospitals generate an enormous amount of medical and administrative information, they are only one part of the overall health information complex. Chapters 1, 3, and 5 address this larger context and discuss primary

health care, integrated health maintenance organizations, consumer health information, and other generators and users of health information.

44 C.J. McDonald et al., “The Regenstrief Medical Record System—Experience with MD Order Entry and Community-Wide Extensions,”

Proceedings of the Eighteenth Annual Symposium on Computer Applications in Medical Care, vol. 18, 1994, p. 1059.
Chapter 2 information Technologies for Transforming Health Care 37

Government

product review

1

Manufacturers

pharmaceuticals

and

medical

equipment

Government H

Medicaid

Medicaid administration intermediaries

groups

physicians,

clinical private clinics

guidelines

Government \

 Governmen t

licensing

SOURCE: Office of Technology Assessment, 1995 Adapted in part from R Van de Velde, Hospital lnformation Systems:The Next Generation (Berlin:

Springer-Verlag, 1992), p 107
38 | Bringing Health Care Online: The Role of Information Technologies

compliance with institutional guidelines. Ensembles of patient records meeting specific criteria can be assembled by scanning a database

describing more than 800,000 patients and 80 million separate clinical observations. Administrators use this capability for quality-control

purposes and medical researchers use it to assemble cohorts of eligible patients for clinical

trials. The Regenstrief system is a hybrid of paperbased and computer-based information management: some information is captured and

disseminated electronically, but the system also

prints reports of rounds made by physicians and a

set of reminders, alerts, and customized encounter

forms on paper prior to each patient’s visit. Clerks

transcribe and code the handwritten notes on these

forms after the encounter.45

Some of the institutional capabilities described

in this section are also available for individual or

group medical practices through software that

adds the capability for clinical recordkeeping to

administrative practice management systems.

❚ Paper-Based Patient Records

Most of the clinical and administrative information that flows throughout the health care system

is still recorded on paper. Over 10 billion pages of

patient records are produced in the United States

each year,46 each of them a masterpiece of idiosyncratic functionality. In order to receive accreditation, hospitals must ensure that their records

meet certain minimum content standards established by the Joint Commission on Accreditation

of Healthcare Organizations, as well as any content requirements mandated by state regulations.47 In general, however, health care

organizations are free to determine how the information is arranged. Institutions design their

own filing and communications systems to meet

internally determined information needs, and individual departments often design forms to reflect

information generated in self-contained processes. To some extent, paper records are individualistic even to the level of single sentences

because much of the information is handwritten

and clinicians may phrase entries using their own

terms and conventions.

Box 2-1 lists some of the many types of information that usually appear in a hospital’s paper

records. Different types of providers might assemble records with different content; for example, ambulatory care records generally have fewer

categories of information than hospital records,

but they may span a much greater time period because they are historical records documenting

many encounters. Patient records also incorporate

administrative records such as letters, insurance

claims, and bills, although these may be stored

separately from clinical records.

Paper records within a single folder have traditionally been kept either in the chronological

order of collection or in source-oriented or problem-oriented formats. Source-oriented records

are organized with forms from nurses, physicians,

labs, and other sources in separate sections. Problem-oriented records organize the various notes

into a brief database of information identifying the

patient, a problem list of the aspects of the patient’s condition that require treatment, an initial

plan for treating the problems, and progress notes

detailing actions engendered by the problems and

plans.

This nonstandardization of patient records is

not necessarily a symptom of poor design;

instead, it is a reflection of the main task that patient records once served. They were a highly detailed, patient-centered documentation of the care

process and a record of everything that happened

45 C.J. McDonald and G.O. Barnett, “Medical Record Systems,” Medical Informatics: Computer Applications in Health Care, E.H. Shortliffe and L.E. Perrealt (eds.), G. Wiederhold and L.M. Fagan (assoc. eds.) (Reading, MA: Addison-Wesley, 1990).

46 U.S. Congress, General Accounting Office, Automated Medical Records: Leadership Needed To Expedite Standards Development

(Washington, DC: General Accounting Office, 1993).

47 Some examples of state legal requirements for medical records are discussed in ch. 3.
Chapter 2 information Technologies for Transforming Health Care 39

The admission/discharge record provides a synopsis of the overall patient record. It contains basic

identifying and financial information about the patient, along with certain clinical information such as the

admitting and final diagnoses, a summary of the procedures performed and medical consultations, and

a description of the disposition of the patient. This record is typically organized on a sheet attached to

the face of the other paper records, which contain two broad categories of information:

Administrative data:

■ Attestation statements certify that the diagnoses and procedures performed are accurately and completely documented to meet the requirements of Medicare and other payers.

■ Conditions of admission record the patient’s consent to be admitted and receive routine services,

diagnostic procedures, and medical treatment.

■ Consents for release of information allow the hospital to release health information to insurers or others.

■ Special consents authorize nonroutine diagnostic or therapeutic procedures.

Medical or clinical data:

■ The medical history includes descriptions of the chief complaint, present illness, past medical history,

psychosocial history, family history, review of physiological systems, and physical examination of the

patient.

■ Physicians orders specify tests, medications, and regimens of care.

■ Progress notes detail the course of the patient illness, response to treatment, and status at discharge.

■ Departmental reports record the contributions of the pathology, radiology, laboratory, physical therapy, respiratory therapy, and social service departments to the care of the patient.

■ Nursing data include notes with detailed observations of the patient and descriptions of the nursing

care regime, a sheet recording the patient’s vital signs and fluid intake and output, and a sheet documenting the time and dosage of each medication the patient receives.

● Operative reports include an anesthesia report, description of the surgical event, and a recovery room

record.

= Discharge summaries concisely recapitulate the patient’s treatment in the hospital and its results

Coronary care, intensive care, psychiatric, and other special care units typically contribute their own

special forms to patient records. Obstetrics and gynecology units usually have specific forms that in

include a patient’s antepartum records and medical history, her labor and delivery records, postpartum

records, and a newborn record describing the baby’s care.

SOURCE: Adapted from Jonathan P Tomes, Compliance Guide for Electronic Health Records (New York, NY Faulkner & Gray, 1994)

pp. 31-32

with respect to a patient during a particular epi- The problem is that the functionality required

sode of care. In ambulatory care settings, they

were also repositories of historical information

about an individual’s previous care. The records

mediated communications and conveyed instructions and responsibilities among members of the

medical team. In this context, designing a standard format for documenting patient-clinician encounters made about as much sense as trying to

enforce a standard format for phone conversations

or diary entries.

of patient records has grown far beyond the

bounds of recordkeeping and communication

within a limited team because of changes to both

the delivery system and clinical practice. Patient

records are now widely used for legal, administrative, and research purposes. They have become

sources of information for determining eligibility

for insurance payments and for documenting the

extent of injuries or the quality of care for use in

legal proceedings. They may be used to provide
40 | Bringing Health Care Online: The Role of Information Technologies

data for evaluating the quality and appropriateness of care for peer review, accreditation, or other

quality assurance programs and for reporting

communicable diseases and other required data to

civil authorities. With the advent of integrated

managed care organizations, clinical records have

become information sources for analyzing the resource requirements, outcomes, and profitability

of health care practices.

In response to these broader functions, patient

records now have at least two phases. In the active

phase, clinicians and administrators insert and

edit information. As legal documents, patient records are treated like other business records that

might be needed in a trial. Recorded entries must

be made by people with first-hand knowledge of

the events, acting in their ordinary capacity, and

the time and date of each entry must be shown.

When errors are found and corrected, the record

must show clearly both the original entry and the

correction, along with the name of the person

making the correction. In the passive, permanent

phase the patient record serves as an unalterable

legal record.48 Its contents are occasionally examined, usually by users far removed from the

clinical setting. At this point, information may be

abstracted from the record for research or management purposes, and all links identifying the information with a particular individual removed.

Even with this adaptation, paper records may

not be adequate for the information demands

of modern health care delivery systems. A number of weaknesses of paper records have been

identified:49

 Paper-based patient records document the

caregiving process inadequately. Medical recordkeeping is a hurried, ancillary activity in

the encounter room. Clinicians may not have

enough time to completely and accurately fill

out the forms comprising the paper records, and

the required health information is sometimes

unavailable or of questionable accuracy as the

notes are written. Physicians’ and nurses’ notes

may be illegible if handwritten, or inaccurate if

dictated and then transcribed. Detailed descriptions of the patient’s health problem and the

reasoning behind diagnoses and choices of services may be left out or abbreviated because

they are hard to summarize and tedious to record. The voluminous data from physiological

monitors are difficult to record accurately by

hand. Other components, such as laboratory

and radiological reports, may be missing because of filing or communication errors.

 Paper-based patient records hinder information flow. Once information has been recorded

within a set of bulky paper records, it may not

be readily accessible later. Efforts to compile a

more complete paper record are likely to exacerbate this problem. The data are bound to the

paper itself and individual pieces cannot be

sorted for relevance, making the record difficult to use when dealing with multiple problems or extended treatments. Collecting and

aggregating data from multiple records for purposes of quality monitoring or clinical research

involves an expensive and time-consuming

manual search. Paper records can be in only one

place at a time. Short of laboriously photocopying and then shipping them by courier, records

may frequently be unavailable to a caregiver

who needs them. When the record is unavailable, new data cannot be entered in a timely

manner; entries must often be made from

memory or copied from other forms or informal

notes. This can lead to the creation of “shadow

records” that are difficult to coordinate with the

primary record set and which may contain conflicting or anachronistic data. Finally, the data

48 J.P. Tomes, Compliance Guide to Electronic Health Records (New York, NY: Faulkner and Gray, 1994), pp. 9-11.

49 Dick and Steen, op. cit., footnote 3; and M.L. McHugh, “Nurses’ Needs for Computer-Based Patient Records,” in M.J. Ball and M.F.

Collen, Aspects of the Computer-Based Patient Record (New York, NY: Springer-Verlag, 1992), pp. 16-29.
Chapter 2 Information Technologies for Transforming Health Care | 41

are only as secure as the paper itself, and entire

records, or individual pages within a record,

can easily be misplaced, damaged, lost, or

stolen.

 Paper records impede the integration of health

care delivery, research, and administration.

The wide variety of formats, styles, and organizational systems for paper records frustrates

the coordination of care between different

providers, or even between departments or

practitioners in the same institution. The impenetrability of the record means that there are

few tools that can use information in the paper

records to generate reminders, decision aids,

and other supports for work.

❚ Computer-Based Patient Records

If all the information in paper-based records were

digitized and embedded within information systems that provide rapid, contextualized access to

the data and links to other information in the institution, some of the shortcomings of paper recordkeeping could be addressed:

 The health care delivery process could be fully

documented. Information could be gathered as

it is generated using a variety of conventional

and handheld computers equipped with keyboards, pen-based structured data entry, and

voice or handwriting recognition. Illegible or

inconsistent entries could be caught and corrected as they are entered. Physiological monitors could collect data and insert them

automatically into the record after checking for

errors, noise, and inappropriate values. Conflicting data from disparate sources could be

reconciled and cross-checked for accuracy.

Medical orders, their results, and all other internal transactions could be tracked automatically.

 Health information could be unfettered. It

could be stored as individually indexed items

of information that could be abstracted into reports and compared among patients. Records

could be accessed simultaneously by multiple

users and easily duplicated when necessary. Information anywhere in the record could be accessed with minimal delay. Data could be

liberated from any one delivery medium and

digital devices that access them could be designed with a wide variety of capabilities and

capacities.

 Caregiving, research, and administration

could be knit together. Data from digital records could be extracted and exchanged according to consensus standards. Their content

could be enriched through the development of

decision support tools. Patient records could be

shared within and across institutions, thus

avoiding delays.

Not all approaches to collecting health information meet these objectives equally well.

Most of the benefits of computerizing the patient

record are realized when information is delivered

to the caregiver or patient, but most of the expense

and problems of computerizing the patient record

are realized when the information is collected. In

general, converting raw data into electronic information that can be shared requires that caregivers spend extra time and lose some flexibility in

their recordkeeping—at least initially—and it requires institutional investments for training,

maintenance of standards, and redesigning work

processes. The costs and benefits of electronic patient records are proportional to the effort involved in collecting, organizing, and distilling

data into useful information.

For example, a page from a paper patient record

could be stored electronically in many different

ways. The information could be simply scanned

and stored as an image (much like a fax) that is a

picture of the paper form, but is not searchable or

editable. Document imaging systems are widely

available that use computers and optical disks to

store such images and make them available to clinicians on workstations with graphics terminals.

These systems reduce the amount of physical storage space required for patient records, and they allow the records to be shared by clinicians and

administrative offices without physically transporting the records. Preparing to implement an

image-based system can help institutions streamline their recordkeeping system by forcing them to

analyze the paper forms in use and eliminate re-
42 | Bringing Health Care Online: The Role of Information Technologies

dundant ones.50 Some systems allow clinicians to

use electronic signatures to approve document

images at the workstations, and others allow information from laboratory instruments or other

computerized processes to be captured as text

along with the images. While document imaging

systems can mitigate some of the problems of the

patient record, they are not really a step toward developing a true computer-based patient record or

provider information system. They have the distinct disadvantage of being primarily a collection

of images rather than a collection of separately addressable facts about each patient, and the information in those images cannot be easily

extracted or manipulated for reporting purposes or

for integration with decision support systems. Patient records from document imaging systems

cannot be easily shared with other departments or

institutions using different record systems.

Additional effort can be expended as the data

are collected and stored to make the health information in the records more useful. Document

images can be converted to textual form either by

applying secondary processing techniques such as

optical character recognition or by manually retyping the data using word-processing software.

Paper documents and document images can be

sidestepped entirely by entering the data directly

into computers through on-screen forms. Once information is stored as text rather than images of

text, it becomes much more mobile because it can

be exchanged electronically as files or e-mail with

other information systems. Free-text data is still

problematic, however, because it is unstructured—there is no set placement or format for the

information it contains—and because the terms

used in the text may have ambiguous or inconsistent definitions. These problems can be addressed

by using databases that store data as discrete elements that are separately addressable and editable—rather than as long, unstructured text

files—and by the adoption of various standards to

consistently define the structure and content of

electronic messages between information systems. Although the existence of various standards

may be transparent to the clinician, the use of such

standards is often facilitated through the use of

structured data entry, where the organization of

documentation and the choices of terminology are

predefined and standardized.

Implementation of an information system with

databases, structured data entry, and message

standardization requires more sweeping changes

in documentation practices than adoption of an

image-based system, but the resulting patient records are far more flexible and harness more of the

computer’s power as an analytical tool. Because

each fact about the patient is stored discretely and

can be retrieved separately, information can be organized and presented in different ways, depending on the needs of the user. The records can easily

incorporate information from laboratory and administrative systems and the information systems

of outside providers, and they can be supplemented by decision support systems. On the other

hand, collecting such information in usable form

from all the different sources can present a plethora of organizational and technical hurdles. Because of the costs involved, in terms of investment

in hardware and software, professional effort, and

changes in work process, organizations take these

hurdles a few at a time. Today, few, if any, provider

organizations have a completely electronic patient

record. Most providers who are working toward

developing computer-stored records find themselves somewhere along an evolutionary continuum, using a hybrid system encompassing both

computer and paper records.

KEY TECHNOLOGIES FOR THE

EMERGING HEALTH INFORMATION

INFRASTRUCTURE

Emilia’s scenario at the beginning of this chapter

is fictional; it portrays a suite of information tools

and resources harmoniously communicating with

50 “Case Study: The Toledo Hospital Turns to Document Imaging To Automate Emergency Center Medical Records,” Healthcare Telecom

Report, Sept. 26, 1994, vol. 2, No. 20, pp. 1, 5-7.
Chapter 2 Information Technologies for Transforming Health Care | 43

each other and integrated into health care delivery

in a way that is not available anywhere today.

However, while the synergy between the tools is

fictional, the tools themselves are readily available. Information technologies have been used for

many years in academic, governmental, and private research, in pilot projects, and in commercial

products, and consensus is emerging on which

ones will form the basis for an advanced health information infrastructure. This section introduces

several important communications and computer

technologies, including computerized data capture and distillation, high-capacity digital storage,

broadband telecommunications, and advanced

human-computer interface techniques.

There are several reasons why the technologies

and standards underlying applications must be understood for purposes of setting public policy.

First, technological changes are challenging the

relevance and enforceability of the existing body

of state and federal law. Several states virtually

preclude the development of computer-based patient records by specifying in pen and quill legislation the required storage media for patient

records.51 These laws were no doubt meant to ensure the singularity and permanence of patient records, but they were probably written without an

appreciation of the compactness, duplicability,

and durability of optical disks. While it is true that

optical disks have only become available relatively recently, their features have been described and

expected for at least 20 years. To avoid inflexible

and inappropriate laws, it is important to consider

technological trends well in advance of their implementation.52

Second, technologies have inherent affordances53—they make some activities very easy

and others more difficult, and they impose

constraints on the behavior of users. For example,

Canada has a telecommunications infrastructure

that ensures cheap, reliable data transfer using

modems, and France has an infrastructure that

supports the widespread use of smart cards, which

can hold several pages of data and be carried in a

wallet. One result of the different affordances of

these two technologies is that the experience of

procuring health care and transferring patient records in Canada is very different from that in

France. In Canada, smart cards are being used to

transfer data in small, special purpose situations,

but the bulk of the flow of health information occurs over integrated data networks.54 In France,

the extensive smart card infrastructure and the

ability of individuals to choose their own doctors,

health care establishments, and pharmacies have

given rise to over 70 different card systems. Basic

health information and the specific details related

to a single treatment or prescription are encoded

on a card and later accessed by the appropriate

health care provider, government services agency,

or pharmacy. The cards make patient records more

accurate and mobile than paper records, but they

do not to contain a person’s entire health history.55

Legislative action that encourages specific technological approaches, such as broadband communications, inevitably affords some conveniences,

some problems, and many striking changes in

how health care can be delivered. It is important

that such consequences be anticipated before legislation is crafted.

51 The laws, which usually specify paper or microfilm records, are explained more fully in chapter 3.

52 This caveat applies to legislation that might endorse any particular storage medium or other specific technology, including optical media.

For instance, the equipment to read optical disks is often obsolescent long before the disks themselves.

53 D.A. Norman, Things That Make Us Smart: Defending Human Attributes in the Age of the Machine (Reading, MA: Addison-Wesley,

1993), p. 106.

54 R. Alvarez, “Canadian Policies and Strategies for Health Cards,” unpublished paper presented at Cartes Santes conference, Marseilles,

France, September 1993.

55 Phoenix Planning and Evaluation, Ltd., “Potential Card Applications in the Health Care Industry,” unpublished contractor report prepared for the Office of Technology Assessment, U.S. Congress, Washington, DC, January 1994.
44 Bringing Health Care Online: The Role of Information Technologies

Finally, despite the evanescent nature of hightechnology products in an entrepreneurial society,

successful technologies and standards have enduring influence. Each new generation of information

technologies forms a legacy that future generations must support. At the cusp of what may be a

major expansion in the purchase of computers and

telecommunications equipment for health care

purposes, it is important that technological

choices embodied in legislative policy and government procurements be consistent with longrange congressional goals for public health,

medical research, and personal privacy. The

technologies described in the following sections

are shown in table 2-1.

❚ Capturing Data at the Point of Care

Clinical records document brief encounters between health care professionals and the patient

through descriptive text, diagnoses, treatment

protocols, and nurses’ notes typed or written by

hand on charts and forms. Measurements of physiological variables are a second major source of

clinical data. Nurses, respiratory therapists, and

other practitioners read these measurements from

medical monitors periodically and transfer them

to the patient record. Although clinicians and other end-users of patient records are most likely to

be held legally responsible for their quality, responsibility for entering the data is often either

delegated to a transcriptionist or delayed until the

end of the shift. Whenever the responsibility for

inserting these types of data into the record is delegated or postponed, the possibility of incorporating errors is increased.

Several new technologies may address this

problem by capturing clinical data as they are generated at the site of care. This generally improves

data quality because that quality is best verified by

those who rely on it most frequently.56 These data

Human-computer interaction

handheld computers

handwriting recognition

personal digital assistants

speech recognition

automated data collection

structured data entry

Storage, processing, and compression

computer-based patient records

magnetic stripe cards

smart cards

picture archiving and communications systems

medical imaging

optical storage

image compression

digital signal processors

object-oriented software design

Connectivity

clinical information systems

cabled, optical, and wireless networks

Internet and electronic mail

World Wide Web

Integrated Services Digital Network (ISDN)

frame relay

Asynchronous Transfer Mode (ATM)

client-server computing

messaging and coding standards

proprietary and consensus standards

Medical Information Bus

Security

passwords

fault tolerant computers

redundant disk (RAID) systems

authenticators

encryption

firewalls

Data distillation

decision support systems

pattern recognition

artificial neural networks

knowledge-based systems

relational databases

knowledge discovery

natural language processing

encoders and groupers

SOURCE: Office of Technology Assessment, 1995

56 S. Henderson et al., “Computerized Clinical Protocols in an Intensive Care Unit: How Well Are They Followed?” Proceedings of the

Fourteenth Annual Symposium on Computer Applications in Medical Care, vol. 14, 1990, pp. 284-288.
Chapter 2 Information Technologies for Transforming Health Care | 45

collection technologies include portable computers, digital assistants, speech and handwriting recognition, and the standardization of automated

data collection from medical monitors.

Portable computers may be either small versions of desktop computers or they may incorporate entirely new hardware, operating systems,

and data organization paradigms. Laptop computers are not widely used in hospital rooms because

there is rarely a flat spot on which to rest them.

Instead, tablet computers that can be operated

while being cradled in one arm are used. They usually contain small hard drives, backlit screens, and

batteries that last a few hours before recharging.

They may contain small PC cards (also known as

PCMCIA cards) that allow them to communicate

via wireless modem or with short-range radio or

infrared receivers attached to the computer network in the hospital.57 They resemble laptop computers in size and weight, but their keyboards are

either missing entirely or folded behind the display screen. The screen itself is a digitizer as well

as a display, which means that it can detect the

presence and position of a nearby stylus. The stylus is used like a mouse on a desktop computer to

pull down menus, activate icons, and press “buttons.” Numbers and letters can be entered with the

stylus via an image of a conventional keyboard,

but medical applications for tablet computers typically avoid ersatz typing as much as possible.

Instead, the user chooses from a branching set of

possible actions. For instance, to write a prescription, the doctor might use the stylus to pull down a

menu to initiate the process and then choose “antibiotic” from a short list of drug types that appears.

A list of antibiotics in the hospital’s formulary appears, and when one is chosen a list of appropriate

dosages appears, and soon. However, if this process is poorly designed, the clinician is trapped in a

single mode of communication-Prescription

writing-until entirely finished. It may be diffiThe Motorola Marco, a personal digital assistant with handwriting and gesture recognition and wireless networking capability Digital assistants and other handheld computers

allow clinical data to be collected at the time and place of

care.

cult to navigate through the series of lists and to

back up and correct errors.

Personal digital assistants (PDAs) area different type of portable computer. As shown in the

photo, they fit in the pocket of a medical lab coat.

They have smaller displays than laptop computers, and their batteries last much longer. PDAs

may have wireless communications capabilities,

and while they lack hard drives, they typically

employ high-performance computer processors.

The extra processing power allows them to address some of the shortcomings of mobile

computing without keyboards by using humancomputer interface designs not found on desktop

computers. One approach is to use a social inter57 PC cards are not limited to communications devices; they can contain more exotic equipment such as miniature hard drives, encryption

chips, or even atomic clocks.
46 | Bringing Health Care Online: The Role of Information Technologies

face such as that presented by devices employing

General Magic’s Magic Cap operating system.

Different capabilities of the computer are represented by different physical objects in a room portrayed on the display. To write prescriptions, the

clinician might tap on a picture of a notepad; she

could also tap on a medical reference book to look

up a drug’s description even as she works on the

prescription.

Other PDAs use handwriting recognition or

novel data storage strategies, such as those facilitated by Apple Computer’s Newton operating system. A wide variety of clinical applications have

been written for Newton PDAs, including charting and patient management software, medical

reference texts, applications for accessing drug information and writing prescriptions, and calculators for determining drug dosages, IV drip rates,

and other common medical computations. One

example is the Constellation Project at Brigham

and Women’s Hospital and Massachusetts General Hospital in Boston that equipped medical residents with PDAs containing the American

College of Physicians’ Medical Knowledge SelfAssessment Program, an ICU/CCU Drug Reference Book, the hospitals’ Medical Resident

Handbooks, a medical calculator, and several other medical reference texts.58

Handwriting recognition attempts to recognize

words and letters within handwritten script. Optical character recognition is a related technology

used with desktop computers and optical scanners

that attempts to recognize printed or neatly written

block letters on paper forms. Speech recognition

is yet another pattern-matching technology that

facilitates entry of textual notes into a computer

without using a keyboard. The technologies underlying handwriting recognition and speech recognition are briefly surveyed in box 2-2. Speech

recognition systems capable of recognizing specialized medical vocabularies have been available

for several years. They typically cost several thousand dollars per computer workstation. None of

the current implementations of speech recognition for clinical use is portable; they are usually

deployed to reduce the delay and potential for error involved in transcribing recorded notes, rather

than as data collection devices at the point of care.

Speech recognition systems are also useful in situations where notes need to be taken, but the clinician’s hands are not free.

Another approach to making data collection

immediate and accurate involves gathering all the

data generated by the suite of medical monitors

and therapeutic devices at the bedside without human intervention. Automated data collection

helps reduce the number of errors introduced and

propagated by end-of-shift recordkeeping59 and

reduces the 40 to 60 percent of nurses’ time that is

spent taking and organizing notes and charting patient care.60 It supports vigilant care by employing

computers to constantly monitor critical physiological variables and call attention to dangerous

conditions, and by allowing caregivers to check

on current patient status and developing trends

from afar. By providing accurate and timely depictions of patient status, automated data collection affords greater assurance that computerbased decision support tools will provide correct

information on which to base a clinical decision.61

58 S.E. Labkoff et al., “The Constellation Project: Access to Medical Reference Information Using Personal Digital Assistants,” Proceedings of the Eighteenth Annual Symposium on Computer Applications in Medical Care, vol. 18, 1994, p. 1024.

59 R.M. Gardner et al., “Real Time Data Acquisition: Experience with the Medical Information Bus (MIB),” Proceedings of the Fifteenth

Annual Symposium on Computer Applications in Medical Care, vol. 15, 1991, pp. 813-817.

60 B.W. Childs, “Bedside Terminals: One of the Answers to the Nursing Shortage,” Healthcare Informatics, vol. 7, No. 12, 1990, p. 37.

61 T.P. Clemmer and R.M. Gardner, “Medical Informatics in the Intensive Care Unit: State of the Art 1991,” International Journal of Clinical

Monitoring and Computing, vol. 8, No. 4, 1992, pp. 237-250.
BOX 2-2: Speech and Handwriting Recognition

Doctors may someday consider pocket information tools to be as indispensable as stethoscopes

and prescription pads. However, while they may be willing to carry some sort of small computer around,

it is unlikely that they will carry a computer keyboard as well. Speech recognition and handwriting

recognition are two technologies that seek to liberate computers from keyboards by transferring directly into the patient record any notes spoken into a tiny pocket computer or written on its face.

The diagram here shows a highly simplified illustration of the speech recognition process. The computer digitizes the electrical signal from the microphone and breaks it into separate utterances by identifying short pauses in

the speaker’s voice. The computer then uses

Fourier analysis to determine the frequencies

or pitches present in the utterance as a function of time. A lower resolution signature is derived from this spectrum by slicing it into frequency bands and time segments and averaging the spectrum within each cell. Finally, the

computer identifies the utterance by selecting

the best match for its signature from a library of

known speech patterns. Searching for a match

within a library containing all possible human

utterances would be hopelessly difficult; instead, searches are usually constrained. Natural language processing uses the syntax of previously recognized words to limit the range of

possible matches for the current utterance signature, and the words in the library typically are

further restricted to a certain domain of knowledge, such as radiology. Most of the calculations in current speech-recognition systems are

delegated by the computer processor to specialized chips called digital signal processors

(DSPs).

Discrete speech recognition systems require speakers to insert short pauses between

words. Continuous speech recognition systems

attempt the much more difficult task of recognizing normal speech, which has pauses for punctuation but no natural silences between words.

In this case, dividing the flow of speech into chunks is much more difficult and the utterances correspond more closely to phonemes than to words. Matching the utterance signature to a pattern in the

"defective heart valve"

"heart" waveform

"heart" spectrum

"heart" signature

"short" "heart" "smart"

Pattern Library

Separate


utterances

Calculate


spectrum

Calculate average


spectrum in cells

Recorded speech

Find best match


in library

"heart"

• • • •

Constrain


search

Previous


results

(continued)

Chapter 2 Information Technologies for Transforming Health Care | 47
48 Bringing Health Care Online: The Role of Information Technologies

library is more difficult as well because phonemes can be legitimately combined in many more ways

than words, and syntax constraints are difficult to apply until the phonemes have been assembled into

potential words. The pattern library itself can be built in two ways. Speaker-dependent recognition systems require the user to build a database of his or her own voice samples. Speaker-independent recognition systems use a preassembled library assembled from averages of the voices of many speakers. Adaptive systems customize a speaker-independent library to a user’s voice patterns over time.

Currently, discrete speaker-independent voice recognition systems are available for desktop computers, but continuous voice recognition is limited to very brief phrases. Continuous, speaker-independent speech recognition has been demonstrated in research laboratories on computers with 256 DSPs

operating in parallel.1 Most clinical applications employ adaptive or speaker-dependent technology

that typically must be trained for a few hours a day over a period of weeks by each clinician. Handwriting recognition is conceptually similar to speech recognition. The input variable is not the loudness of

the voice as a function of time, but the position of the pen’s tip as a function of time. Commercial handwriting recognition systems have been developed that focus on either block printing or cursive script.

Block printing, with well-formed, separated letters, is analogous to discrete speech; smoothly-connected cursive script is analogous to continuous speech. The recognition accuracy of all these technologies is somewhere between 80 percent and 95 percent, which is to say that the text contained in this

box would have at least 40 mistakes.

Many experts have questioned the wisdom of using technologies that require either extensive training or the power of hundreds of desktop computers to enter “the patient complains of nausea” in the

patient record with 95 percent accuracy. It is likely that successful implementations of these technologies will be a hybrid of recognition technologies with other human-computer interface approaches. One

example of this is the PEN-ivory system.2 “The computer displays an encounter form with groups of

descriptive terms on it. When a term is chosen, PEN-ivory guides the clinician through progressively

deeper levels of description by displaying additional terms appropriate for the original choice. For

instance, circling “cough” brings up a display with “severity,” followed by choices of “mild, moderate,

severe” and similar sets of choices for “onset, “ “frequency,” and other criteria. The system must recognize gestures such as circling of terms or crossing them out, but it need not directly recognize handwriting, The program compiles a paragraph of plain English text from content determined by the clinician’s

choices and transfers it to the patient record. Similar structured data entry approaches have been

employed in speech recognition systems, and they have an added benefit of helping to standardize

medical terminologies and descriptions in the patient record. The success of such an approach depends on the details of its design and the preferences of its users. Some hybrid recognition systems are

constraining and inflexible, while others are developing into fast, reliable transcription systems.

In any system that transforms ideas or words into permanent records, there is a tradeoff between

two different conveniences: users want perfectly accurate transcriptions of their ideas, but they also

want perfect flexibility to structure or amend the ideas as they choose. The competition for speech and

handwriting recognition systems is provided by pens, pencils, and paper, which have achieved both of

these goals admirably for many years.

SOURCE: Office of Technology Assessment, 1995

1 R.C. Johnson, “Speech Recognition Popping Up All Over,” Electronic Engineering Times, Feb. 6, 1995, P. 35.

2A.D. Poon and L.M. Fagan, “PEN-lvory: The Design and Evaluation of Pen-Based Computer System for Structured Data Entry,”

Proceedings of the Annual Symposium on Computer Applications in Medical Care, vol. 18, 1994, pp. 447-451.
Chapter 2 Information Technologies for Transforming Health Care | 49

Unfortunately, gathering data from medical monitors is not a straightforward task because different

devices use different communication protocols

and physical connections. Box 2-3 describes the

Medical Information Bus standard that is a proposed solution to this problem.

❚ Data Distillation Tools

Collecting clinical data as they are generated is

only the first aspect of the difficult problem of assembling digital patient records. As health care

professionals manually enter data in conventional

paper records, they perform several crucial but implicit tasks. They make judgments about the validity of the data, often mentally filtering a rapidly

changing display or perhaps reconciling readings

from one instrument with those of other instruments measuring the same quantity. They certify

data as relevant by entering them in the record and

reject aberrant observations, such as heart rate

measurements made on a patient having a fit of

coughing. They convert the data into a standard

format, with the physical layout of paper forms

serving as an interface that structures the information and highlights its important parts for doctors

and other clinicians. Professionals think about

what the data they are recording indicate about the

patient’s condition. Finally, they alert other caregivers if their observations suggest a critical

condition.

Data distillation is an informal label for the application of a set of diverse information technologies in the attempt to automate these secondary

functions traditionally performed as rapid, skilled

human judgments. One expert has observed:

The great mass of useful numbers we generate by computer has got to be tamed and controlled. We have learned how to make the

measurements. Now we must learn how to handle the resulting data and present them in understandable terms. Used right, automation can

integrate these data, simplify them, scan and

evaluate them. Automation is not a coldblooded monster-machine between us and the

patient. It is a tool to expand our medical power,

to let us get closer to the patient, and take better

care of him.62

Concerns about how to extract meaning from a

perceived flood of health data are not new. They

were mounting even in the early 1900s when

Harvey Cushing began arguing for the necessity

of regular monitoring of blood pressure.63 Data

distillation technologies can help refine problematic medical data and inform clinical decisionmaking. In administrative and research contexts,

they can also be used to discover patterns and correlations within massive compilations of health

information, an undertaking less tractable to

manual human effort.

Early computerized attempts to distill clinical

data sometimes tried to fully automate the diagnostic process. The programs asked the clinician a

set of questions about a patient and then used the

answers to navigate among a branching set of

mutually exclusive alternative diagnoses. They

then delivered the conclusion in oracular fashion;

unfortunately, the conclusions were sometimes

wrong, and few doctors suffer oracles gladly.

These logical decision-tree systems overlooked

not only the complexity, but the subtlety of medical decisionmaking.

More recent systems attempt to support clinicians’ thought processes, rather than supplant

them. Three types of data distillation systems in

common use are pattern recognition systems, neural networks, and knowledge-based expert systems. Pattern recognition is frequently used in

medical monitors to recognize emerging trends.

62 J.J. Osborne, “Computers in Critical Care Medicine: Promises and Pitfalls,” Critical Care Medicine, vol. 10, 1982, pp. 808-810.

63 H. Cushing, “On Routine Determination of Arterial Tension in Operating Room and Clinic,” Boston Medical Surgical Journal, vol. 148,

1903, p. 250, as cited in R.M. Gardner, “Medical Data: Their Acquisition, Storage, and Use,” Medical Informatics: Computer Applications in

Health Care, E.H. Shortliffe and L.E. Perrealt (eds.), G. Wiederhold and L.M. Fagan (assoc. eds.) (Reading, MA: Addison-Wesley, 1990), p.

369.
50 Bringing Health Care Online: The Role of Information Technologies

One of the challenges of assembling a fully digital patient record is finding ways to transfer into it the

wealth of physiological information generated at the bedside by sophisticated medical monitors, One

solution is to let the pulse oximeters, ventilators, IV pumps, and other devices do the job themselves. In

fact, most monitors could already do so if they could communicate with the hospital’s computers: many

bedside monitoring and therapeutic devices have, hidden (and forgotten) on their back panel, tiny

communications ports that can transmit in digital form the values displayed as numbers, lights, and bar

graphs on the front panel of the instrument, What is missing is agreement among manufacturers about

how that port should be designed and how it should exchange data with other machines. Such agreements are difficult because different types of medical devices generate data in widely varying amounts,

qualities, and formats, and the communications interface must be implemented inexpensively so that it

represents only a small portion of the overall cost of the least expensive instruments.

Vendors of clinical data management systems often design proprietary adapters and software modules to Iink their computers to individual medical devices. When new monitoring devices are acquired in

an intensive care unit, the interface software and hardware must usually be procured from the computer

vendor. While this may be an adequate solution for some settings, one director of clinical computing at

a major hospital has said, “What happens to us as users is that: 1 ) we pay a premium price for compatible devices that we are forced to buy from the primary manufacturer, 2) we do not get the monitoring or

measuring device at all, and 3) we are not able to Integrate the data from multiple devices conveniently." 1 While this grim assessment may not reflect everyone’s viewpoint, it is clear that the lack of industrywide Interface standards for medical devices has held back wide-scale connection of bedside devices

to the broader hospital information Infrastructure.

Consensus messaging standards such as HL7 (see box 2-8) and the IEEE P1073 Medical Information Bus (MIB) standard may be one solution to this problem. The MIB committee is a group of doctors,

vendors, medical engineers, and Information system specialists that is seeking to address the problems

Inherent in proprietary and custom-device networking approaches by establishing a common standard

for the hardware and software used to communicate between medical devices. The MIB standard is

conceptually similar to standards that have been developed for communication among electronic devices in airplanes, and it Incorporates many existing standards from other areas of communications and

computer design. The standard describes three types of “controllers” that comprise a medical device

network, Every medical monitoring device is associated with a device communications controller

(continued)

Electrocardiogram monitors, for instance, often cording to their shapes and a library assembled of

average the shape of a patient’s ECG trace for arrhythmia specific to the patient. Further traces

about 20 heartbeats in order to build a profile of a are then compared to the patient own customized

“normal trace.” Subsequent traces are then library of heart problems, and the urgency of an

compared to the normal trace; if they differ signif- alarm matched to the severity of the abnormaliicantly, they are classified as aberrations and an ty.64

alarm can be passed on to a caregiver. Moreover, Another type of pattern recognition can be imthe aberrant signals can themselves be sorted ac- plemented using arrays of interconnected simple

64 Gardner, “Patient-Monitoring Systems,” Medical Informatics: Computer Applications in Health Care, ibid., p. 382.
Chapter 2 information Technologies for Transforming Health Care 51

housed in an external adapter connected to an existing communications port or incorporated Internally,

perhaps on a single special-purpose integrated circuit. Every patient is associated with a bedside

communications controller located in a bedside computer. Caregivers can quickly connect multiple

medical devices to the bedside computer in a star topology and then disconnect or Interchange them

without turning off the power, Each device identifies itself unambiguously to the bedside controller and

automatically establishes communication when it is plugged in. The cables and modular connectors are

standardized so that medical devices can be redeployed rapidly much like telephones, modems, and

answering machines in the home.

A master communications controller connects the various bedside communications controllers with

each other and with the rest of the hospital information infrastructure through standard Ethernet or Token Ring networks. Two-way communications among these three controllers provide the means for automatic transfer of data from bedside devices into the patient record and allow device settings to be

adjusted remotely. They also facilitate full integration of bedside data with data from other sources in the

institution and enable cooperation between devices and systems. Additionally, future devices wiII Iikely

Incorporate lights on the front panel that indicate whether reliable communication has been established,

and textual messages such as the name of the medication in an IV pump.

Software applications running on device, bedside, and master communications controllers will communicate among themselves by sending messages whose syntax is specified by a new object-oriented

Medical Data Device Language (MDDL) defined by the IEEE PI 073 standard. The MDDL is one of

many consensus messaging standards discussed elsewhere in this report that are used to mediate information flows within health care institutions,

KEY: IEEE = Institute of Electrical and Electronics Engineers

SOURCES: M.M. Shabot, “Standardized Acquisition of Bedside Data: The IEEE P1073 Medical Information Bus, ” International Journal of Clinical Monitoring and Computing, vol. 6, No 4, 1989, pp. 197-204, R M Gardner et al , “Real Time Data Acquistion: Experience with the Medical Information Bus (MIB), ” Proceedings of the Fifteenth Annual Symposium on Computer Applications in Medical

Care, vol 15, 1991, pp. 813-817, and J. Wittenber and M.M. Shabot, “The Medical Device Data Language for the PI 073 Medical

Information Bus Standard, ” International Journal of Clinical Monitoring and Computing, vol 7, No 2, 1990, pp. 91-98.

1 R.M. Gardner, “Federal Medical Device Regulations What Are the Implications for Respiratory Care?” Respiratory Care, vol. 33,

NO 4, 1988, pp. 258-263

processors

65 called artificial neural networks.

Each processor makes a simple calculation based

on the values of a small number of input variables

that might be physiological measurements for a

patient. The output of the calculation for each

processor serves as the input for other processors

in the network. The network can be trained by using its overall output to adjust the strengths of the

connections between various processors. Ideally,

a neural network might be exposed to comprehensive sets of physiological data gathered from

many patients who died from sudden pulmonary

embolisms, and then trained through the feedback

process until its output is consistent for all the patients. If that feat could be accomplished, the network would then have “learned” which features in

the data set reliably indicate imminent pulmonary

embolisms, and it could then be used to monitor

other patients. One problem is that comprehensive, comparable data sets covering multiple pa65 The processors are usually simulated in software rather than being discrete electronic chips.
52 | Bringing Health Care Online: The Role of Information Technologies

tients are very rare. One of the benefits of digital

recordkeeping might be the compilation of data

sets that could be used to train artificial neural networks for clinical decision support.

Most of the decision support systems that issue

alerts and warnings based on clinical data are

knowledge-based systems, which attempt to interpret information about a patient using expertise

captured in a computerized database known as a

knowledge base. In a simple implementation, appropriate actions or diagnoses for a patient could

be identified by matching words used by doctors

in their written encounter records with terms

found in a library of disease descriptions or known

patient cases. More typically, expertise is captured

as a large set of heuristics (rules of thumb) rather

than as textual descriptions. Knowledge engineers

design these rule-based expert systems by interviewing medical experts and constructing rule

sets based on the experts’ practical experiences

and insights, institutional policies, and the medical research literature. A typical rule used with a

ventilator might read, “If a patient’s spontaneous

breathing rate changes by more than 10 percent

and the change is larger than five breaths per minute and the breathing rate is between 0.5 and 70

breaths per minute and the ventilator mode was

changed within the last minute, then bring the

change to the attending physician’s attention.”66

An inference engine coordinates the process of obtaining information from the patient record or clinician, finding applicable rules, and reconciling

the conclusions of multiple rules if the clinical

data match more than one. Expert systems work

well in narrow application areas such as determining appropriate antibiotic treatments. They are

less successful in supporting decisions in broadly

defined application areas because it is difficult to

define and maintain a complete, up-to-date set of

rules. One implementation of a rule-based expert

system in a hospital setting is the HELP system,

profiled in box 2-4.

Distillation tools are also important for health

administration and research after clinical and administrative data have been abstracted from individual records and stored in large institutional

databases. Relational databases organize data

into sets of two-dimensional tables and allow users to retrieve information from specific rows and

columns in the tables using brief requests in a

query language. While a relational database

might be used to store the clinical and administrative data for the patients in an HMO, the data really represent a complex multidimensional data set.

It might be very difficult, for instance, to assemble

with a query all the data necessary for a cost-ofcare analysis of a set of interventions using several

different measures of resource consumption over

time in different units of the HMO. Online analytical processing is a database query technique that

is optimized to support decisionmaking using information from complex, multidimensional data

sets.67 Querying techniques find sets of records

within a database that fit a desired pattern. Knowledge discovery techniques address the opposite

problem: they attempt to identify patterns useful

for describing a specified data set. For instance, a

typical medical research data set generated in a

multiclinic randomized trial designed to study

surgical interventions to control lipids contributing to atherosclerosis included 1,400 variables

measured on 838 patients for 7 to 14 years.68

Knowledge discovery techniques can be used to 

66 T.D. East, W.H. Young, and R.M. Gardner, “Digital Electronic Communication Between ICU Ventilators and Computers and Printers,”

Respiratory Care, vol. 37. No. 9, 1992, pp. 1113-1123.

67 A. Radding, “Blue Cross Climbs Mountain of Data with OLAP,” Infoworld, Jan. 30, 1995, p. 64.

68 H. Buchwals et al., “The Program on the Surgical Control of the Hyperlipidemias,” Surgery, vol. 92, No. 4, 1982, p. 654.
Chapter 2 information Technologies for Transforming Health Care | 53

Clinical information systems built around computer-based patient records have the potential to improve the quality of health care. They can help clinicians manage complicated medical situations and

make informed decisions Involving many variables and complex calculations. Such systems can help

Institutions evaluate and standardize the way clinicians deliver care. They also can facilitate the development and evolution of clinical policies and procedures based on the latest research results, on measured links between clinical outcomes and practices, and on considerations, such as local pathogen

trends, that may be unique to a particular institution. One example of a clinical information system that

achieves some of these benefits is the HELP (Health Evaluation through Logical Processing) system

HELP consists of several logical modules that support data collection and delivery at the point of care

and provide a rich system of reminders, alerts, and prompts based on clinical protocols for care of specific disease conditions.

The primary installation of HELP is at LDS Hospital in Salt Lake City, Utah, a private, 520-bed, tertiary-care hospital and teaching center associated with the University of Utah School of Medicine. The

HELP system was developed at LDS over a long period of time with direct Involvement of clinicians

(Including nurses and therapists as well as physicians), researchers, and administrators in the design of

the system. LDS Hospital is part of the nonprofit Intermountain Health Care, Inc., chain of hospitals and

outpatient clinics in Utah, Idaho, and Wyoming. The HELP system IS being installed at numerous locations within the Intermountain system and at several other hospitals around the nation. It IS distributed

commercially by 3M Health Information Systems of St. Paul, Minnesota.

The HELP system at LDS is installed on a centralized group of twelve fault-tolerant processors linked

through other computers to over 1,000 terminals at patient bedsides and other sites throughout the hospital. Nurses, physicians, respiratory therapists, and others enter data manually through keyboards as a

combination of multiple choice selections, number entry, and some free text entry. In the intensive care

unit, many of the medical devices, such as ventilators and pulse oximeters, are Iinked directly to the

HELP system. Patient information is stored in a central patient database connected to the medical records department, radiology and surgical units, and many of the laboratories and other departments.

The system processes an enormous amount of information, including over 18,000 data entry items per

day for respiratory care alone.

Each data entry is screened by a decisionmaking processor against a series of protocols stored in a

separate medical knowledge base. The protocols are derived from the published literature and from

consensus opinions of experts at LDS and at other institutions. They are also derived from analysis of

the clinical results for selected groups of LDS patients. The protocols may be simply algorithms for calculating derived quantities from measured variables in order to save time and reduce errors. They may

also be decision criteria that recognize and alert clinicians to potential drug allergies, drug-drug interactions, drug selection and dosing problems, organ dysfunction, or critical changes in laboratory or

physiologic parameters. Costs and charges for clinical care are routinely computed and displayed for

all chargeable items and for all nonphysician personnel time.

Managing a complex clinical situation such as ventilator support of respiration can involve consideration of hundreds of potential variables and sources of information. HELP protocols rationalize and systematize that process. They are developed by small working groups, first as flow diagrams on paper

and later as software code. Protocol calculations and recommendations are displayed on bedside terminals and incorporated into printed documentation including shift reports, daily rounds reports, weekly

reports, daily administrative and management reports, and final reports when patients are discharged.

Clinicians may deviate from the recommendations of the protocols, but typically they must justify their

(continued)
54 Bringing Health Care Online: The Role of Information Technologies

decisions with defensible reasons apart from personal style preferences. The quality and efficacy of the

protocols are continuously monitored through daily log reviews, on-call reports, and personal feedback

from clinicians to the working group.

One application of HELP protocols has been the empiric design of antibiotic therapies. Antibiotics

can be targeted to a patient’s specific pathogens once they have been identified through microbiological tests, but it is often impractical to wait for the results of laboratory cultures before beginning antibiotic therapy. Broad-spectrum antibiotics (which are more expensive than single-agent antibiotics) are

often prescribed in this situation, and HELP protocols have been developed that recommend one or

more antibiotics effective against the most probable pathogens at the lowest possible cost. They use

data from the computer-based patient record and infection-specific Information and identify the most

likely pathogens on the basis of those Identified in patients with similar characteristics during the previous five years and the most recent six months. The recommendations are tailored to the infection site

and to the patient’s allergies and renal problems. The data are updated every month to provide trend

analysis of pathogens and antibiotic resistance patterns within the hospital. Clinical trials have shown

that physicians using the protocols prescribe regimens that cost less, utilize fewer antibiotics, and cover a broader range of pathogens than those recommended by physicians in the absence of decision

support.

HELP protocols have also been used to contribute to the quality of clinical research through standardization of the care process one example involves randomized clinical trials at LDS comparing two

therapies for patients with adult respiratory distress syndrome (ARDS). Mechanical ventilators are used

to support the breathing of ARDS patients. Since their lungs are severely dysfunctional, high pressures

and volumes of air are sometimes required to maintain sufficient oxygenation levels, but the vigorous

ventilation can itself cause further lung injury. One alternative therapy revolves ventilation at lower frequencies and pressures and removal of C02 outside the body. Each ventilation technique is complicated and involves numerous adjustments of ventilator parameters throughout a month of care, comparison of the two therapies is extremely problematic unless the criteria for controlling the ventilators are

standardized for a suite of patients. HELP protocols were developed that assured equivalent intensity of

care for patients in trials of the two therapies. All the patients under protocol-guided care showed higher survival rates than expected from historical patterns, and the uniformity of care afforded by the protocols allowed direct comparison of the two ventilation therapies.

SOURCE: R.S. Evans et al., “lmproving Empiric Antibiotic Selection Using Computer Decision Support, ” Archives of Internal Medicine, voI. 154, 1994, pp. 878-884, A.H. Morris, “Protocol Management of Adult Respiratory Distress Syndrome, ” New Horizons, vol.

1, No. 4, 1993, pp. 593-602

find useful correlations or causal connections ❚ Storage and Compression Technologies

among the variables in such large databases; the Clinical monitoring and imaging devices spawn

correlations that are found can then serve as a copious amounts of data. For example, pulse oxiknowledge base for a rule-based expert system.69 meters report with every heartbeat the con69 J.M. Long et al., “Automating the Discovery of Causal Relationships in a Medical Records Database, " in Knowledge Discovery in Databases, G. Piatetsky-Shapiro and W.J. Frawley (eds.) (Menlo Park, CA: AAAI Press/The MIT Press, 1991 ), pp. 465-476.
Chapter 2 information Technologies for Transforming Health Care 55

Average number Average storage

Dynamic range of images requirement

— Modality Image size (pixels) (bits) per exam per exam (MBytes)

Computed tomography

.— —

512 X 512 12 30 –

15.0

Magnetic resonance imaging 256 X 256 12 50 6 5

Digital subtraction angiography 1,000x1,000 8 20 200

Digital fluorography 1,000x1,000 8 15 150

Ultrasound imaging 512 X512 6 36 9 0

Nuclear medicine 128 X 128 8 26 0 4

Computed radiography 2,000 x 2,000 10 4 32.0

Digitized film 4,000 x 4,000 12 4 128,0

SOURCE: Adapted from K.G. Baxter et al.,“Wide Area Networks for Teleradiology,” Journal of Digital Imaging, vol. 4, No. 1, 1991, pp. 51-59

centration of dissolved gases in the blood. Transferring this oxygenation data directly into the record would generate about 1.5 million bytes of

information per day per patient---equivalent to

about 400 pages of numbers—and the majority of

the data would never be accessed again.70 Institutions that develop systems for rapidly collecting

and distilling large quantities of health information will need to judiciously moderate their appetites for information and refine their skills for

determining which data can be safely discarded.

Nonetheless, the demand for permanent storage of

patient records is growing rapidly.

Some storage technologies make selected portions of patient records portable. Many institutions issue the ubiquitous magnetic stripe card to

their patients for identification purposes. These

can store about 250 text characters, enough to hold

a patient’s name, address, identification number,

date of birth, copayment information, and a brief

password. They are widely used in combination

with low-speed modem networks to verify patients’ eligibility for insurance benefits. Smart

cards are the same size as credit cards, but they

have embedded computer chips and enough static

memory to hold several pages of textual information. Laser optical cards have an even greater storage capacity, although once information is written

onto the cards it typically cannot be altered or supplemented. None of these card technologies can

replace computer-based patient records because

they are vulnerable to loss and fail to provide continuous access to an individual’s health data. They

may be widely employed, however, to carry emergency medical information and the demographic

information necessary to coordinate a patient access to services at multiple sites. Smart cards have

been used in several states to coordinate delivery

of multiple social programs, such as Medicaid and

the Women, Infants, and Children nutritional program (WIC), and to replace paper vouchers and

food stamps. 71 They are widely used in European

health care systems. An infrastructure of smart

card readers has not developed yet in the United

States, largely because the existence of a reliable

and relatively cheap telecommunications system

has made modem communications and magnetic

stripe cards a more attractive way to exchange

small amounts of data.72

The storage requirements for textual and numerical data in patient records are dwarfed by the

storage space requirements shown in table 2-2 for

70 East et al., op. cit., footnote 27.

71 Phoenix Planning and Evaluation, Ltd., op. cit., footnote 16.

72 Card technologies are discussed more fully in chapter 3, box 3-4.
BOX 2-5: Digital Image Compression

Image compression technologies play a crucial role in enabling the efficient storage and inexpensive

dissemination of medical images. The digital images shown in this box are representations of dental xrays (for illustrative purposes, they have been digitized with a far lower resolution than usual radiographic

images). The top image occupies approximately 96,000 bytes of storage space on a computer disk. The

second image occupies only 21,000 bytes of storage space; it has been compressed using a compression standard known as JPEG (Joint Photographic Experts Group). The two images are virtually indistinguishable, but subtracting one image from the other (and enhancing the contrast of the result) reveals

the information that was lost in the compression, as

shown in the bottom image. This difference image would

be a uniform white if the compression were lossless.

Instead, the image contains delicate grey patterns that

represent some of the subtle details present in the original image but missing from the compressed image.

The apparent similarity of the top two images is largely

an artifact of the printing technology used in this report:

the differences would be more noticeable had the films

been reproduced on a high-resolution image setter. Similarly, the appropriateness of compression in hospital settings depends on the display technology used to present

the image. To reproduce the enormous dynamic range

and spatial resolution of traditional photographic films,

radiological images used for interpretive diagnosis are

typically sampled 2,000 times per inch and displayed

on expensive high-resolution monitors. Compression

techniques that result in any loss of detail may be inappropriate for display of such images. Medical images

are used in many other less demanding contexts, however. For instance, the referring physician may wish to

discuss the image with the radiologist over the telephone

while viewing it on a desktop computer monitor that is incapable of displaying the subtleties of the image, even if

they were present in the file. JPEG or other compression

technologies are often used in situations like this to reduce

(continued)

56 | Chapter 2 Information Technologies for Transforming Health Care

medical images such as x-rays, magnetic resonance images, and computed tomography scans.

These new imaging technologies challenge the

ability of information systems to store and process data, but they enable the development of new

generations of highly localized surgical and radiation therapies that otherwise would not be possible. The computational resources necessary for

medical imaging will continue to grow with the

increasing use of high-resolution spatial imaging,

in which multiple images are assembled into a

Original Image


96kBytes

Compressed Image


21kBytes

Difference


(contrast enhanced)

three-dimensional model, and with the development of functional imaging, where processes such

as the rate of oxygen metabolism in a particular

body structure are studied by assembling multiple

copies of the same image over time.

Conventional films from x-ray and nuclear

medicine images are converted to electronic form

using laser digitizers, but many other imaging technologies produce digital images from the outset.

In some cases, images are compressed using technologies like those described in box 2-5 to re-
Chapter 2 information Technologies for Transforming Health Care 57

the size of an image file by a factor of 10 or more. Minimizing the size of image files is even more important when they are to be transmitted to a remote site over a telemedicine link or modem because compression can drastically reduce the cost and the elapsed time necessary to transmit the image

Compression technologies work by eliminating redundant information in images. Natural images 

contain coherent patterns: colors and tones usually change slowly across the width of an image. When

an image is relatively free of noise (like the “snow” on a television screen), the intensity of each tiny area

@xc/) in the image is often related to the intensity of its neighboring pixels. For instance, if the numbers

1 to 9 are used to represent the tones from black to white, then a series of pixels in the dental x-rays

above that cross the boundary of the tooth might be represented by the string of numbers:

11111111133399999999. A simplistic method for compressing the sequence of greys is run-length encoding, in which the string could be replaced by the much shorter string: 91 ’33 ’89, that is, “nine 1‘s,

followed by three 3’s, followed by eight 9’s.”

Practical schemes for image compression are much more sophisticated. The JPEG compression

used for the dental images divides the image into cells containing 64 pixels. Within each cell, the components of the picture that vary quickly across the cell are separated from those that vary slowly. The

high-frequency components are suppressed or discarded; they appear as the rapidly varying grey and

white pattern in the bottom image above. Remnants-of the 64-pixel cells are also visible in the bottom

dental image.

Compression technologies are used extensively to store and transmit digital medical images. They

have become very fast and inexpensive as a result of the intensive development efforts by computer

and communications companies seeking ways to efficiently transmit digitized images and video for

publishing and broadcasting.

SOURCE: Office of Technology Assessment, 1995.

duce transmission times and storage space re- machines. The imaging machines can share the

quirements. Medical images are typically stored

and manipulated on large hard drives, similar to

those in desktop computers, and then transferred

to digital tape, magneto-optical disks, recordable

CD-ROMs, or COLDS (Computer Output to Laser

Disks) for archival storage. The latter three

technologies use light beams to store and record

information on durable plastic or magnetic disks.

Although the disks themselves are likely to last for

many decades, it is not clear that the equipment

necessary to read the disks will be manufactured

throughout the life of the medical information.

Medical imaging is an ideal domain for integration of information technologies. The various

imaging machines are expensive and so highly

specialized that no single vendor can impose proprietary standards on vendors of different types of

same type of displays and data manipulation computers, however, and this has encouraged the development of broad data exchange standards.

Radiology and nuclear medicine are consultative

disciplines, but since the images need not be interpreted at the site where they are collected, consultations can be carried out at a distance or even

over telemedicine links. Radiologists usually examine images displayed with the highest possible

resolution, but primary care physicians who rely

on their interpretations may also wish to have access to lower resolution copies of images in order

to explain the interpretations to patients. Finally,

an economic incentive exists for developing fully

digital image storage: medical images are among

the most commonly misplaced or unavailable records. Some 40 percent of all x-ray films are unre-
58 | Bringing Health Care Online: The Role of Information Technologies

trievable, making it necessary to repeat imaging

procedures and extend hospital stays.73

Information systems that manipulate, store,

and share digital medical images are called PACS,

or picture archiving and communications systems.

PACS typically capture data directly from an

imager or a laser film digitizer, and then allow users to share and modify them using a computer, a

communications network, a large storage system,

and a high-resolution display. The communications between hardware components are governed

by a mature standard for PACS developed by a

committee of the American College of Radiology

and the National Electrical Manufacturers

Association.74 The DICOM (Digital Imaging and

Communications in Medicine) standard is one example of a communications standard. It defines

common formats for data generated by imaging

equipment and standard actions that can be performed on the images. It specifies how messages

about the data and the processing actions can be

exchanged among machines.

The DICOM standard also specifies approaches to compliance reporting and testing.

Vendors that sell machines purporting to adhere

to the DICOM standard must publish compliance

statements indicating which portions of the standard are implemented. Hospitals can then compare

compliance statements for all the equipment they

purchase and build a functional PACS system using equipment from a variety of vendors. This is

one example of how the development of industryspecific voluntary standards can help remove barriers to technology implementation.

The character of radiological practice is changing as PACS develop. PACS make it easier for primary doctors to consult radiologists, but they also

enable doctors to examine radiological images

firsthand and make their own interpretations.75

The development of PACS may eventually help

transform radiology into more of a laboratory service than an independent medical discipline in

hospitals.

❚ Display and Retrieval of Data

Most hospital information systems use the normal

graphical and textual interfaces found on desktop

computers, thus exposing their legacy as primarily administrative information systems. It is not

clear, however, that interfaces developed for administrative and business applications will be adequate for conveying the huge amount of clinical

information that will become available if patient

records are fully digitized. The stakes are high because floods of new data make it increasingly likely that people will overlook important parameters

and make faulty judgments.

Consider the difficulties in presenting all the

types of information in the patient record on a

single computer display. One candidate for such a

locus of information might be bedside patient

data management systems, which are dedicated

computers connected to various physiological

monitors for a patient in an intensive care unit.

Currently, they need to display physiological data

from up to 10 monitors, either as text or waveforms. If those data are to be entered automatically

into electronic records rather than summarized on

paper forms, the interface must provide ways for

users to attach vocal or textual annotations to the

data.76 If the bedside computer is to be linked to

the broader hospital information systems, the interface must then be able to cluster associated data

73 S.C. Horii et al., “A Comparison of Case Retrieval Times: Film Versus Picture Archiving and Communications Systems,” Journal of

Digital Imaging, vol. 5, No. 3, 1992, pp. 138-143.

74 American College of Radiology, National Electrical Manufacturers Association, “Digital Imaging and Communications in Medicine

(DICOM): Version 3.0,” Draft Standard, ACR-NEMA Committee, Working Group VI, Washington, DC, 1993.

75 H.L. Kundel, S.B. Seshadri, and R.L. Arenson, “Clinical Experience with PACS at the University of Pennsylvania,” Computers and Medical Imaging Graphics, vol. 15, No. 3, 1992, pp. 197-200.

76 E.H. Shortliffe and G.O. Barnett, “Medical Data: Their Acquisition, Storage, and Use,” Medical Informatics: Computer Applications in

Health Care, E.H. Shortliffe and L.E. Perrealt (eds.), G. Wiederhold and L.M. Fagan (assoc. eds.) (Reading, MA: Addison-Wesley, 1990).
Chapter 2 Information Technologies for Transforming Health Care | 59

from a broad variety of sources according to patient status: if a patient has an electrolyte imbalance, for instance, all the relevant laboratory

results, dietary information, and treatment orders

should be displayed alongside blood chemistry

data from a bedside analyzer. Because medical decisions are usually made with information from a

wide variety of sources, including laboratories

and radiology departments, the display must accommodate textual notes and display high-resolution images77 and video.

By now, the display is getting a bit cluttered,

but there is more. Clinical decision support might

be implemented at the bedside so clinicians can be

alerted to potentially dangerous situations, such as

drug-drug interactions and critical changes in laboratory and physiological parameters. If so, then

the screen must not only display the alerts, but

provide contextual information so they can be

evaluated; it will need to show an appropriate

amount of historical data along with the current

data. To enable clinicians to act on whatever decisions they make, the display must provide charting and order-entry forms. If administrative

functions are integrated as well, the display will

need to notify clinicians of the prices of the medications and lab tests they order, and display

e-mail, calendars, and scheduling information. It

must do all these jobs without the aid of the many

tools and customizations that help users cope with

desktop computers because bedside computers

need a standardized interface to accommodate

multiple users.78 And on top of all that, the interface should provide for easy editing and annotation of all the types of information mentioned thus

far, as well as robust security and methods for clinicians to disavow data that they do not trust or

deem irrelevant.

All of these objectives have to be accomplished

on video monitors smaller than a standard piece

of paper. In fact, the standard piece of paper remains the main competitor to video displays for

most of the information tasks listed above, and

many institutions that have implemented the most

comprehensive computer-based patient records

incorporate high-volume printing as their information distribution medium.79 Printed pages

can display up to 20 times more information in a

given area than standard computer monitors.80

Even computer displays with high-resolution

graphic monitors often sacrifice much of the available display area to a plethora of semi-permanent

“buttons” and other interface elements designed

to receive information from users rather than convey information to them.

It is not clear that the display techniques suitable for desktop computers or current-generation

patient data management systems are appropriate

for high-bandwidth display of clinical information. Interface designers have developed very effective techniques for conveying complicated

data to users (in aircraft cockpits, for example) and

for receiving complicated data from users (via

spreadsheets and word processors), and even for

letting users browse within complicated data sets

(through hypertext and graphical database frontends). The medical environment is a curious mix

of those three situations. Design approaches that

are sufficiently capable may not yet have

emerged. Many of the frustrations evinced in pilot

77 Current monitors used at the bedside have neither the spatial resolution nor the dynamic range to display diagnostic-quality radiological

images.

78 This consideration is less critical for long-term users who might design customized presentation configurations to be displayed according

to their preferences whenever they use a computer. Nonetheless, the basic functionality of the health information system and the accessibility

and interpretability of data it presents must not rely on such customizations because the systems are often used by a rapidly changing ensemble

of users with little time for training.

79 C.J. McDonald et al., “The Regenstrief Medical Record: 1991 A Campus-Wide System,” Proceedings of the Fifteenth Annual Symposium

on Computer Applications in Medical Care, vol. 15, 1991, pp. 925-928.

80 This is a conservative estimate. For a discussion of high-density information display, see E.R. Tufte, Envisioning Information (Cheshire,

CT: Graphics Press, 1990), pp. 37-51.
60 Bringing Health Care Online: The Role of Information Technologies

projects are due to inadequate solutions to humancomputer interface problems. In the absence of

new developments, the displays at the patient’s

bedside, the nursing station, and the physician’s

desktop are potentially “choke points” through

which most of the benefits of a fully computerized

patient record may fit only awkwardly. The advantages of the computer-based patient record

may be elusive, if only because they cannot be envisioned.

❚ Data Security

People reveal highly sensitive information to

health professionals. If clinicians or institutions

misuse or misrecord the confidential information,

it might be used to restrict or revoke a person’s

health insurance or revise judgments of their suitability for a job or a loan. When such mistakes are

made, it is often difficult for the individual to correct them or hold anyone accountable. Any new

health data recordkeeping system must ensure that

information is used appropriately or people will

avoid using it. In a 1993 Harris-Equifax poll, 27

percent of those responding indicated that their

personal health care information had already been

improperly disclosed and 71 percent indicated

that they felt that use of computers would need to

be restricted in order for privacy to be protected.81

Several issues are involved. First, health information needs to be confidential: it should be

used only for approved purposes and shared only

among authorized people typically associated

with the patient by a special relationship, such as

the physician-patient relationship. Second, an appropriate level of privacy for the information must

be established: some balance must be struck between an individual’s right to keep information

confidential and the benefits that can accrue to society if the information is shared more broadly. Finally, the records must have adequate security:

administrative and technical measures must protect them from unwarranted loss, modification, or

dissemination. Several technological approaches

to securing electronic patient records by restricting access are discussed in box 2-6. Maintaining

the privacy, confidentiality, and security of patient

records presents organizational and political

Appropriate use of health information can only be ensured if those trusted to use the information

merit that trust. However, there are technological approaches to ensuring that the data cannot be inadvertently lost, damaged, or erased, and that they are only available to a defined community of users.

If a computerized patient record system is to operate without a paper backup system, it must function reliably all of the time. To ensure data integrity, computer systems often store critical data on redundant arrays of independent disks (RAIDs). These arrays write data onto two or more hard disks simultaneously, In addition to providing a backup copy of the data, RAIDs also speed up the system, making

data accessible from the disk that can retrieve them the quickest. One of the disks is taken offline for a

few minutes once each day, and a copy of its contents can be transferred to a backup tape while the

other disk continues to function, after the backup is completed, the disks are desynchronized. The data

on the tapes are often transferred to magneto-optical or CD-ROM disks for longer term storage. Multiple copies may be made, with one copy remaining offsite. Redundancy is also used for the central

processing units and other hardware components of fault-tolerant computer systems so that faulty compo-

(continued)

81 Louis Harris and Associates, A.F. Westin, The Equifax Report on Consumers in the Information Age (Atlanta, GA: Equifax, 1990).
Chapter 2 information Technologies for Transforming Health Care 61

nents can often be identified and replaced without turning off the computers. Using these techniques,

patient record systems have been designed that are available for use 99.5 percent of the time.1

To restrict access to records to authorized personnel only, clinical personnel must enter their name

and a personal password before accessing computer files. This restriction only works if the password

cannot be overheard or easily guessed. Some systems either assign complex passwords or require that

they be periodically changed, but this raises the possibility that the passwords will be forgotten or misIaid because they are more difficult to remember. More robust techniques require that authorized users

possess some physical device in addition to a password. One such device is a handheld authenticator,

which encrypts a user’s password using a short string of text issued as a challenge by the host computer. The challenge text, and hence the expected response, can change with each attempted access to

the computer. Alternatively, security systems might require that a device such as a smart card be inserted in the computer while files are being accessed. Finally, biometric identifiers such as a retinal

scans or fingerprints can Identify authorized computer users, although these techniques are rarely

employed in health care institutions because they require expensive equipment.

Maintaining a usage log of all documents accessed and changed helps discourage improper use of

records by unauthorized (or even authorized) personnel, The log can be scanned manually or automatically to detect attempts to log onto the system or change files, and its presence discourages such attempts. The integrity of a document and responsibility for its contents might be additionally certified by

the use of digital signatures.

In principle, a hospital might choose to protect its patient records by using encryption techniques as

well, making the information uninterpretable. It could encrypt data using symmetric encryption, where

all users of the data would need to know a particular decoding password, or it might use asymmetric

encryption, where the documents for a particular user are encoded with a well-known public key and

decoded using a private key known only to the intended user. In practice, clinical documents and messages are intended for rapid access by multiple users; they are rarely encrypted because it slows down

the processing and because an adequate public key infrastructure has not been established.

Health care institutions often connect their computers to broader networks of computers so their

members can communicate via e-mail and have access to remote databases and internet resources.

Separate computer networks are sometimes maintained to isolate patient records from these communications needs. Alternatively, firewalls may be put in place that stand between computer networks internal and external to the health care institution; firewalls are systems of computers and switches that

restrict to approved locations the destination or source of data packets entering or leaving the hospital’s

network.

SOURCE: Office of Technology Assessment, 1995 Adapted in part from U S Congress, Office of Technology Assessment, Information Security and Privacy in Network Environment, OTA-TCT-606 (Washington, DC: U.S. Government Printing Office, September

1994)

40 Institute of Medicine, The Computer-Based Patient Record: An Essential Technology for Health Care (Washington, DC: National Academy Press, 1991), p 74
62 | Bringing Health Care Online: The Role of Information Technologies

challenges as well as technical challenges; these

issues have been discussed in detail in an earlier

OTA report.82

When institutional security standards governing the handling of paper-based patient records are

inadequate, the records can easily be lost or

viewed and copied without leaving any trace of

the action. Still, while the confidentiality of paperbased records is easily compromised by authorized people who misuse their access to patient

information, the sheer bulk of paper records helps

keep them private: information is not easily abstracted from paper records. The fluidity of computer-based patient records, however, makes

securing their confidentiality more problematic.

One of the benefits of computer-based records

is that information can be used for multiple purposes. The effectiveness of a certain AIDS treatment might be evaluated, for instance, by

comparing the outcomes of various treatments for

a panel of individuals enrolled in a controlled

study. Unfortunately, even if patients’ names are

removed from copies of the relevant information

extracted from their records, their identities can

often be determined by correlating the data with

information in other publicly available electronic

databases. One challenge is to develop identifiers for patients and providers that will allow

medical data to be exchanged among various information systems without compromising the patients’ privacy.

In addition to developing unique identifiers, a

set of privacy principles need to be established

that govern who can access health information and

how they may use it. Many private and public sector groups have developed strategies and policies

for protecting the privacy of health information.

For example, the Privacy Working Group of the

Information Policy Committee, Information Infrastructure Task Force has published a set of draft

principles for providing and using personal information in all contexts, including health care applications.83 Among other provisions, these

principles direct those who plan to collect personal information to assess the impact of those plans

on individual privacy and to limit the amount of

information collected to that necessary for their

immediate use. In addition, they should inform individuals why their information is being collected, how it will be protected, and how it will be

used, and they should take reasonable steps to prevent the disclosure or improper alteration of personal information. The principles also charge

individuals with the responsibility to understand

the consequences of releasing personal information and to discern how and why their information

is being collected. The working group’s principles

encourage both education about the uses of personal information and the establishment of rights

of redress for privacy abuse. Legislative action

may eventually be appropriate to guarantee the

privacy of health information as consensus develops on appropriate policies.

❚ High-Bandwidth Communications

Without telecommunications and networking

technologies, information is confined to the computer in which it is created. In addition to the traditional uses of telecommunications for phone

conversations and paging, there is an increasing

need for remote communications to transfer digital health information. Physicians might wish to

use computers at home to track the status of patients or receive notification of important lab results. Group practices might submit batches of

insurance claims to data-processing intermediaries electronically and remind patients of upcoming appointments using automated phone

systems. The term “house call” might reenter the

82 U.S. Congress, Office of Technology Assessment, Protecting Privacy in Computerized Medical Information, OTA-TCT-576 (Washington, DC: U.S. Government Printing Office, September 1993).

83 Office of Management and Budget, “National Information Infrastructure: Draft Principles for Providing and Using Personal Information

and Commentary,” Federal Register, vol. 60, No. 13, Jan. 20, 1994, pp. 4362-4370.
Chapter 2 information Technologies for Transforming Health

medical lexicon with the advent of in-home medical monitoring devices for elderly or chronically

ill patients, devices that can deliver basic physiological information to doctors via modem. Hospitals might link their information systems to

remote medical databases or support videoconferencing and telemedicine applications to broaden

their base of patients in the community. Integrated

health delivery institutions might link computers

at various sites into a single wide area network.

Community health information networks (CHINS)

might link various clinical institutions, components of the public health system, private medical

practices, payers, data repositories, and academic

institutions so that health information can be

shared on a regional basis. The telecommunications and networking technologies underlying

these new health information applications are surveyed in box 2-7.

Individuals are also beginning to use telecommunications and networking technologies to gain

access to medical information. One of the most

prominent applications of broadband communications is the delivery of educational

Care 63

materials

via the international network of computers known

as the Internet. Individuals can learn about health

issues and correspond with others who share common interests by joining electronic mailing lists

dedicated to discussions of specific medical

conditions. Many health care providers now provide educational materials for patients, consumers, and doctors through World Wide Web pages,

which are collections of pictures, text, sound, and

video along with links to related information on

other computers. The OncoLink Multimedia Cancer Resource web page at the University of Pennsylvania is shown in figure 2-2. From this page,

computer users can navigate to many other pages

that give them information about cancer terminology, ongoing clinical trials, how to prepare for a

hospital visit, and many other topics.84 There is no

incremental charge to access this or any of the

hundreds of other web sites offering medical and

health information on the Internet. However, a

home computer and modem are required, as well

as access to the network through an account purHow can computers in different parts of the country be connected to each other so they can share

health Information? One way to answer this question is to start with an understanding of how ordinary

telephone calls work. When a caller speaks into a phone mouthpiece, a microphone converts the

sounds into smoothly varying analog voltages, which then propagate along wires to the earpiece in the

distant phone where they are reconverted to sound. The wires from the two phones are connected by a

series of switches. If the two phones are within a hospital, the call will probably pass through just one

switch, within the private branch exchange (PBX) owned by the hospital. If the call’s destination is outside the hospital, the PBX wiII pass it on to an external switch owned by a local exchange carrier (LEC),

which is typically a regional Bell operating company. If the receiving phone is connected to the same

switch, the call goes through. Otherwise, it IS passed to other switches owned by the same LEC within a

LATA (Local Access Transport Area) region. The United States is divided into 137 LATAs of various

sizes; to go beyond the boundaries of a single LATA, the call must be passed to an interexchange carrier, such as AT&T, MCI, Sprint, WilTel, or others. At the far end, the call must again pass through the

series of switches owned by a different LEC until it arrives at its destination.

(continued)

84“OncoI.ink,’” University of Pennsylvania, April 1995. <URL:http://oncolink.upenn.edu>
64 Bringing Health Care Online: The Role of Information Technologies

LECs and interexchange carriers would have to maintain millions of sets of wires if all phone calls

were passed along as analog signals. Instead, the signal is usually digitized shortly after it leaves the

originating phone, often before it reaches the first switch. Many digitized signals can be easily mixed

together or multiplexed, carried on a single set of wires, and then separated at the destination. Moreover, the signals needn’t travel along wires: they can also be carried as pulses of light along fiberoptic

cables or as microwave signals between land stations or satellites. Digital communication links are

more robust than analog ones—they are more immune to noise and require less frequent reamplification

of the signals. If a hospital has a digital PBX or it wants to connect computers at different sites, its administrators might choose to bring a digital line right into the facility. The capacity or bandwidth of such

a connection is typically measured by the number of normal voice connections it can carry: a DS-0

connection (64 thousand bits per second) can carry a single voice connection; a DS-1 or T1 connection (1 .544 million bits per second) can carry 24 phone conversations; a DS-3 or T3 connection (45

million bits per second) can carry 672 voice conversations, and so on. Various fractional levels between

these capacities can be ordered as well. A typical x-ray image could be transferred over a DS-O connection in about eight minutes, over a DS-1 connection in about 20 seconds, over a DS-3 connection in

about 0.7 seconds, and over the high-capacity cross-continent “backbones” in a few milliseconds, The

bottleneck in telecommunications is the slowest connection.

A caller Initiates a connection by lifting the telephone handset from its cradle. The phone sends an

“off-the-hook” message to the nearest switch, which responds with a dial tone. The caller then presses

a sequence of touch-tone buttons, and the switch listens to the tones and figures out how to route the

call. This is called in-band switching because the caller can hear the dial tone, dialing, and pauses on

the same connection that will later carry the voice conversation. Some types of digital connections have

out-of-band switching, where separate connections carry the switching information. For instance, a basic rate integrated services digital network (ISDN) line contains two DS-0 channels for the messages

and an additional lower capacity channel for the switching signals. When the handset is lifted, the connection to the receiving party is established almost immediately, The familiar whistle and rasp of modems may become rare as basic rate ISDN lines become more common in homes and businesses,

Currently, ISDN modems can transfer digital data onto the wider telecommunications system about six

times as fast as a typical modem. ISDN services cost only a little more than normal phone lines on a

monthly basis, but they are less convenient to set up and require more expensive equipment. ISDN

lines with capacities up to DS-1 are also available, again with separate switching and data (or voice)

channels.

All the connections discussed so far link remote phones or computers through a series of switches.

Often a facility doesn’t need that switching capability, however. It may have a pair of computers or PBXs

at two sites that it wants to connect without allowing any other outside connections. In that case, it may

choose to have a dedicated or leased line installed between the two sites.

Normal telephone calls carrying voices typically occupy an entire channel for the duration of the

conversation-other users wanting to contact the recipient get a busy signal. Voice calls are usually

connection-oriented because momentary disconnections or imperfections in a conversation are annoying. However, it is not easy to annoy a computer; communications between computers are often intermittent or even connectionless, which means that no constant link between a particular set of originating and receiving computers is maintained. Digital data exchanges often consist of bursts of intense

activity surrounded by periods of silence. Packet-based communications exploit this pattern by inter-

(continued)
Chapter 2 information Technologies for Transforming Health Care 65

leaving the communications of whole sets of computers at once. Data streams are broken up into packets, and each packet contains a destination address indicating where it should go. Packet-based communications are commonly used within local area networks (LAN), which connect a limited number of

computers within an institution in a loop or branching structure. Digital signals on LANs may pass along

copper wires resembling phone wires or cable-TV cables, or through the air as radio or infrared signals

on wireless LAN connections. Often several LANs within an institution are connected into an enterprise

network by a high-speed backbone that sometimes utilizes fiberoptic cables.

Packet-based communications can be used for telecommunications as well as for computer networking, especially when data rather than voices are being conveyed. A long message might be broken up into a huge number of packets. Each packet wends its way through the telecommunications

network, guided by routers along the way. Computers prepare the packets according to networking protocols published by network vendors or by standards committees. Depending on the protocol, packets

can be guided along predefine routes, or they may take different routes to the destination and experience different delays along the way, but be reassembled by the receiving computer into the correct

order.

Different computer networks utilize different packet formats and protocols; the packets on different

networks might be different sizes or have different addressing schemes. It is inconvenient for a computer launching a packet to have to know what sort of packet is expected by the receiving computer,

which might be thousands of miles away. Sometimes this problem is solved by having all parties on the

network agree on a common standard such as the TCP/IP protocol (Transmission Control Protocol/lnternet Protocol) used for communication among computers in the worldwide Internet. Still, it is often necessary to transfer packets from one network to a different network with a different protocol. One way to

do this is to employ a sort of diplomatic pouch called frame relay: packets traveling on the high-capacity telecommunications network are wrapped in standard envelopes or frames and then unwrapped at

the receiving end into whatever packet format is required. The frames may have various lengths depending on the size of the packet inside. Frame relay communications work well for transferring data

files such as x-ray images, but they are less effective for transferring video streams because unpredictable delays experienced by different-sized frames can lead to pauses and jumps in the video playback. A different and faster approach is to reformat all packets into minimalist cells that are a kind of

least common denominator. That is the approach behind asynchronous transfer mode communications

(ATM). Because all ATM cells are exactly alike, the routing equipment that shuttles them around the

world can be designed to be extremely fast, and the transmission delays for a series of cells will be

relatively constant. Video streams can be reassembled from ATM cells with few noticeable delays

High-speed frame relay and ATM communications will be necessary for any large-scale networking

that involves sharing large amounts of health information.

SOURCE: Office of Technology Assessment, 1995, and “The Telecommunications Glossary, ” Wiltel Communications Corp. , April

1995. <URL:http://www.wiltel.com/glossary/glossary.html>

chased from an Internet service provider or a com- industry. Already, demand management systems

mercial online service. are in place within some integrated HMOs nurses

High-bandwidth communications may have a in centralized locations use telephones to give adprofound effect on the structure and process of vice for managing particular health problems to

health care services analogous to the changes that patients located throughout the HMO’s service

automated teller machines brought to the banking area. Consultative practices such as radiology and
Figure 2-2: Health Information on the Internet

66 | Chapter 2 Information Technologies for Transforming Health Care

dermatology are slowly beginning to use highbandwidth communications over dedicated

phone lines to practice telemedicine. As

switched high-bandwidth connections become

widely available, a dramatic change could occur in which the hub-and-spoke topology of

most telemedicine networks (with an academic

hospital at the hub of most consultations) may

dissolve into a more dynamic network, and a

competitive market for health advice may

emerge. Individuals may eventually be able to

get expert information about their health in

more convenient ways than from their doctors.

■ Distributed Computing and

Object-Oriented Software

Health care information systems, like most

other large computer applications, were designed for many years around the capabilities

of powerful mainframe computers. Users

gained access to information stored in the large

databases of a central computer using relatively

slow, text-based terminals. Although the central computer might be very fast, it had to perform many duties. Its performance in responding to a user's request for a patient's admission

records, for instance, might be slow if it were

occupied with another calculation-intensive

task, such as preparing a monthly payroll.

As the speed and capabilities of desktop

computers and networks have increased, the

centralized, hierarchical structure associated

with mainframe computers is being replaced in

many instances with distributed computing using a client-server architecture. The many tasks

performed by a monolithic central computer are

SOURCE: Oncolink, University of Pennsylvania, April 1995. URL: http://Oncolink.upenn.edu/
Chapter 2 Information Technologies for Transforming Health Care | 67

decoupled, and the workload dispersed among a

series of programs running on a set of smaller

computers, or servers. Each server handles a specific task, according to requests made by other

programs, or clients, on the network.

Typically, users interact with client programs

running on desktop computers with relatively sophisticated graphics capabilities. A client program for scheduling patient surgery, for instance,

might issue requests for information to servers

throughout the institution. A request might be for

a discrete piece of information, such as the patient’s admission date, which could be retrieved

from the admissions database. The request could

also be more complicated: it could spawn a sophisticated scheduling calculation on an administrative server that itself required information

evoked from other servers. The client program

melds the information from the various sources

and displays it to the user. The data and the computational resources of the information system are

distributed throughout the institution rather than

being localized in a centralized computer. The

failure of any one computer is unlikely to compromise the entire system. In addition, if the admissions server were heavily used, the department

might maintain a number of different servers, with

the load being passed to the server that is least burdened at a given moment. Thus, capacity can be

added incrementally to a client-server network.

Client-server computing replaces large, central

computers with interacting networks of servers,

each accomplishing specific tasks and communicating with standardized messages. A similar

trend known as object-oriented design is affecting

the internal structure of computer software. Increasingly, developers are decoupling large, multipurpose software applications into sets of

interacting objects. For instance, a common task

for a software designer might be to change the

type of information in a record—perhaps making

room for nine-digit zip codes instead of five-digit

zip codes. With traditional software design, this

type of change might require changing all of the

routines that ever manipulate zip codes, including

printing routines, file storage routines, sorting

routines, and so on. These routines could be scattered throughout the code, and finding and altering them is a difficult and time-consuming

project. Moreover, changing any of the routines

could have unintended consequences elsewhere in

the program for other data that use the same routines. Object-oriented design bundles all of these

routines along with the zip code itself into an encapsulated object. Thus, all the zip code routines

can be easily changed and tested, without affecting any of the rest of the software in the project.

Ideally, object-oriented design can lead to software code that is modular and reusable. Complicated software applications can be built rapidly

from standardized libraries of classes of objects.

This new software paradigm may pose significant

challenges for regulatory structures governing

distribution of medical software. Currently, medical software is regulated by the Food and Drug

Administration (FDA) under the same system

used for medical devices. Before marketing their

products, vendors must register their medical software with the FDA and obtain official approval of

its safety and effectiveness. Vendors must document their design process and demonstrate that

potential safety hazards associated with software

components have been identified and addressed.

Several categories of software are exempt from

this process, including general-purpose software

such as word processors, software designed for

use in teaching, nonclinical research, or private

practice, and knowledge-based systems that require human intervention before any impact on

human health could occur.85 This policy may be

adequate for medical software embedded in physical devices or distributed through conventional

channels, but it may prove cumbersome as more

research institutes become linked by the Internet.

85 Office of Device Evaluation, Center for Devices and Radiological Health, Food and Drug Administration, “Reviewer Guidance for Computer Controlled Medical Devices Undergoing 510(K) Review” (Washington, DC: 1991).
68 | Bringing Health Care Online: The Role of Information Technologies

Software developed for academic research purposes is commonly distributed at no charge to other researchers using a procedure known as ftp, or

file transfer protocol. In the absence of a clear

FDA policy regarding electronic distribution of

medical software, concerns that the FDA may

treat distributors of free software as medical vendors have delayed the ftp distribution of at least

one product intended for calculation of radiotherapy treatment doses.86

In addition, the policies deal inadequately with

software developed using object-oriented design

and perhaps assembled from components written

by a variety of sources and only assembled by the

final vendor. The exemption from regulation for

general-purpose software raises the possibility

that vendors could avoid FDA oversight of their

products by selling a general-purpose “shell” program that could then link together modules with

medical functionality that had been distributed via

ftp at no charge.

Finally, the distinction between source code

and object code for a computer program is becoming a key issue—source code is written in a computer language such as C++ or FORTRAN and

can be altered by any competent programmer,

whereas object code is a translation of the source

code into a form executable by a particular machine. To ensure uniformity of approved software,

the FDA has typically allowed vendors to distribute only the object code for their computer programs because it cannot be easily altered by the

end-user. A similar restriction on electronically

distributed software is problematic, however. Distribution of source code may be protected by the

first amendment, and such a restriction would

have a burdensome effect on academic research

and prevent cross-verification of the soundness of

code design by independent groups. The FDA is

currently reviewing and revising its policies on

regulation of medical software.

SHARING THE COMMON POOL OF DATA

❚ Standards

Standards are agreements on how to implement

technologies. They allow buyers to choose compatible medical equipment and software from a

variety of vendors, and thus encourage both innovation and price competition. Sometimes de

facto proprietary standards emerge when a single

vendor controls a large share of the market for a

particular item. Consensus standards are developed by committees with representatives from

many different stakeholders. The committees can

include representatives of vendors, the medical

community, the government, unions, and any other interested individuals who choose to participate

in the laborious process of writing and agreeing on

standards. Standards committees are accredited

by organizations such as the American Society for

Testing and Materials (ASTM), the American National Standards Institute (ANSI), or by other national or international organizations.87 They meet

over a period of years and develop drafts that

members of the committee vote on after extended

revisions and public review. Standards bodies occasionally have problems reaching decisions as

rapidly as new technologies are developed.

Understanding consensus standards is complicated in that the name of an individual standard is

usually an acronym that reflects the identity of the

standards committee, rather than the function of

the standard. Figure 2-3 shows the alphabet soup

of interrelated messaging standards for exchanging data among various parts of a hospital: standards written by ASTM Subcommittee E31.15

specify the format for messages traveling to and

86 “Council on Competitiveness Identifies Telemedicine Barriers in Report Summarizing Fall Conference,” Healthcare Telecom Report,

vol. 3, No. 1, Jan. 2, 1995; and Edward L. Chaney, Professor, North Carolina Clinical Cancer Center, University of North Carolina, personal

communication, May 1, 1995.

87 A complete description of the standards-setting process can be found in , U.S. Congress, Office of Technology Assessment, Global Standards: Building Blocks for the Future, OTA-TCT-512 (Washington, DC: U.S. Government Printing Office, March 1992).
102 | Bringing Health Care Online: The Role of Information Technologies

Note: Systems on the CHIN with their own repositories will require an intelligent gateway to match field names with data

SOURCE. M R. Gorsage and J.W. Hoben, “Technological Implications of CHINS, ” in R.T. Wakerly (ed.), Community

Health Information Networks: Creating the Health Care Data Highway (Chicago, IL: American Hospital Publishing, Inc ,

1994), pp. 115-140,

master or owner of specific data elements is diplomatic and political rather than technological.35

Through use of a common data model, the repository can be mapped onto the various systems of

record. Data for different entities can be tied together by using unique identifiers for patients,

payers, sites, providers, and other entities.

In time, a central repository containing both

clinical and administrative information could become too large to manage efficiently, especially if

it includes diagnostic images. An alternative approach to managing community-wide information is to maintain an intelligent central repository

that manages a federation of independent databases. All databases would share a common global model, and the central repository would contain

not copies of the transactions, but information on

where to find the information. This metatransaction (transactions about transactions) repository

would then contact the individual databases to

collect information needed by an authorized user,

and would have the knowledge needed for resolving any differences between the databases. This

concept is illustrated in figure 3-5.

■ Community Networks and Enterprise

Networks

There is uncertainty about the role of CHINs as

managed care organizations and integrated delivery systems (IDSS) begin to dominate health care

35 Ibid.
70 | Bringing Health Care Online: The Role of Information Technologies

from knowledge bases, ANSI X12 standards govern communication of financial data to insurers

and others outside the health care institution, the

NCPDP standard developed by the National

Council of Prescription Drug Pharmacies specifies the format for messages containing pharmaceutical information, and so on. Purchasers of

health care equipment and software can more easily build extensible systems by buying items that

store and exchange information according to one

or more of these consensus standards rather than

proprietary standards.

A model of communications published by the

International Standards Organization describes

seven different levels of computer communications, beginning with physical interconnections

and ending with the standards that specify how

messages are passed between software applications (the seventh level). One of the most widely

used messaging standards is the HL7 (Health Level Seven) standard for electronic interchange of

health data.

HL7 is explained in more detail in box 2-8.

Most of the standards in figure 2-3 are conceptually similar to HL7 and closely related to it. For

instance, standards written by ASTM Subcommittee E31.16 specify the format for messages

containing neurophysiological data. These messages use the same syntax, and most of the same

segments, as HL7 messages, but they include data

structures for continuous waveforms such as electroencephalogram traces.88 HL7 was originally a

standard for communicating laboratory data and

other clinical observation data between software

applications, but it now includes structures for

communicating clinical orders, billing information, and patient admission, discharge, transfer,

and registration information within single institutions.

This suite of standards has brought a modicum

of order to the varied approaches to sending messages within and among health care institutions.

Each standard defines the structure of messages

within a certain jurisdiction. But what happens

when a measurement generated by a laboratory

instrument and formatted according to the ASTM

E1394 standard needs to be passed to a bedside

monitor that normally formats information according to the P1073 standard? Individual standard-to-standard translation schemes could be

designed, but they would necessarily be in

constant flux as the various standards evolve. To

address these types of problems, ANSI created a

Health Informatics Standards Planning Panel

(HISPP) in 1993 to coordinate standards development efforts. A number of working groups have

formed under the aegis of HISPP, each made up of

representatives from organizations involved in

developing health messaging standards. One

working group, for instance, is developing a

framework for a common data model that will

serve as an evolving guide and resource for all the

various messaging standards. The framework will

incorporate the innovations of the various standards committees and harmonize their efforts over

the long term using an iterative process.89

The messaging standards in figure 2-3 define

how messages are communicated, but the content

of the messages is set by an entirely different set of

standards. Some of these were developed in industrial or scientific settings, such as the “metric system” or Systemé Internationale that defines units

of measurement. Others are specific to medical

contexts. Standards are necessary for coding and

88 Moreover, the chair of the group working on automated data within the HL7 committee has agreed to include these same message

constructs for transmitting wave forms in HL7 messages, and the same is true for other standards committees. Despite the diversity and multiplicity of committees and working groups, the emerging standards are generally complementary.

89 T.E. Rutt, “Work of the IEEE P1157 Medical Data Interchange Committee,” International Journal of Clinical Monitoring and Computing, vol. 6, 1989, pp. 45-57, and Trial-Use Standard for Health Care Data Interchange-Information Model Methods, Data Model Framework,

P1157.1 Draft 1 (Piscataway, NJ: IEEE Standards Department, 1994).
70 Bringing Health Care Online: The Role of Information Technologies

Standards for interchanging health data and assigning codes to medical concepts underlie all efforts to make patient records electronically accessible. This box presents one of the major messaging

standards (HL7—Health Level 7) and one of the major coding standards (ICD-9-CM—International

Classification of Diseases, 9th Revision, Clinical Modification). These are representative examples, but

HL7 is only one of the many messaging standards used to convey health data, and ICD-9-CM is one of

the two major coding systems used in the United States.

Messaging standards specify the syntax of an electronic message and coding standards specify its

semantics. A similar distinction exists for more familiar messages, such as postcards. The syntax of a

postcard corresponds to the arrangement of its elements: the addressee’s name appears in a standard

posit! on, the city in another, the message is placed in a box on the left half and the stamp in the upper

right, and so on. The arrangement IS set by international postal conventions. The meaning of the letters

appearing within a given element (its semantics) is determined by an entirely different set of conventions, namely the language employed by the correspondent. Similarly, HL7 and other messaging standards specify the order of the many discrete elements that make up a message and indicate which

elements are required and which are optional. ICD-9-CM and other coding systems assign meaning to

the characters in the message.

Electronic Messages

HL7 messages are streams of text that are relatively simple to interpret, As an example, the portion

of the message that carries the patient’s address might be represented as “...1432 Hosteler Street ‘Apt

232ˆChlcagoˆILˆ60603ˆUSA... ” In addition to demographic information identifying the patient, an HL7

message delivering the results of a laboratory test might include hundreds of other data elements containing numerical values for the measured parameters, the measurement units, and portions of the message that bore the initial request so that the request and response can be matched and reconciled. The

data elements contain internal indications of the coding standards to be used. For instance, one small

portion of the standard message defined by HL7 contains the patient’s diagnosis. This slot might be

filled with the characters “410.1ˆI9C. ” The software application receiving this message knows from the

position of the characters within the message that this is a diagnosis, and it simply has to assign meaning to the character by looking up diagnosis number 410,1 in the set of codes published by the

ICD-9-CM Committee. The table would indicate that the diagnosis is ‘(anterior myocardial infarction. ”

Alternatively, the same diagnosis could be conveyed in a different coding scheme employing an entireIy different code set, but still using the same HL7-defined structure. This allows the software application

sending a message to choose whatever coding scheme is most appropriate for the data it processes.

Libraries of disease and procedure descriptions can evolve without necessitating any changes in the

software governing how messages are sent.

(continued)

A model of communications published by the el Seven) standard for electronic interchange of

International Standards Organization describes health data.

seven different levels of computer communica- HL7 is explained in more detail in box 2-8.

tions, beginning with physical interconnections Most of the standards in figure 2-3 are conceptualand ending with the standards that specify how ly similar to HL7 and closely related to it. For

messages are passed between software applica- instance, standards written by ASTM Subcomtions (the seventh level). One of the most widely mittee E31. 16 specify the format for messages

used messaging standards is the HL7 (Health Lev- containing neurophysiological data. These mes-
Chapter 2 information Technologies for Transforming Health Care 71

Clinical Coding Systems

Codes are an attempt to standardize the description of clinical practice so that diagnoses or procedures relevant to different patients can be compared side-by-side. They are used for both research

purposes and reimbursement of claims. ICD-9-CM codes are widely used to describe inpatient treatments in hospitals, and CPT-4 codes (Physicians’ Current Procedural Terminology, 4th Edition) are

used by physicians and other health care professionals for billing purposes. The ICD-9-CM codes are

a combination of the ICD-9 diagnostic code set maintained by the World Health Organization for describing diseases and a set of codes for medical procedures maintained by the Health Care Financing

Administration (HCFA). HCFA requires that ICD-9-CM diagnostic codes be used for itemized Medicare

inpatient and ambulatory care claims, and it determines payment levels based on the grouping of treatments, according to the procedure codes, into Diagnosis Related Groups (DRGs).

Medical coders are employed in hospitals to assign codes to the procedures described in patient

records following guidelines published by the American Hospital Association. It is a very complex and

sophisticated task. Although there are some aspirations to automate the coding process by assigning

codes through computer analysis of clinical orders, it is Iikely that information technologies will be more

commonly used to assist medical coders rather than to replace them. Decision-support systems known

as encoders are commercially available starting from an initial suggested code, they prompt the coder

to investigate related codes and check to make sure that the group of codes ultimately assigned is

internally consistent. Groupers are software applications that deduce from the final set of assigned

codes a DRG, which is the basis for Medicare or other Insurance reimbursement Finally, many coders

use online libraries of coding reference manuals.

Current coding systems have been criticized as too Imprecise to describe some aspects of clinical

practice. Another common criticism is that the terminology used in various codes IS inconsistent Currently, Medicare reimbursements depend only on the primary DRG without regard for the significant extra expense involved in caring for a patient with a complicated secondary diagnosis. Future revisions of

ICD-9-CM may address these problems to some extent. The 10th revision will attempt to Incorporate

standard clinical definitions used throughout its specifications, and DRGs wiII be severity refined so that

reimbursements can more accurately reflect the cost of treating the patient. In recognition of the increasing importance of ambulatory care as managed care institutions seek to minimize the number of

hospital admissions, HCFA is also developing a new set of codes for use in outpatient care.

SOURCES: C.J. McDonald, D K Martin, and J.M. Overhage, “Standards for the Electronic Transfer of Clinical Data Progress and

Promises,” Topics in Health Records Management, vol. 11, No. 4, 1991, pp. 1-16, B. Siwicki,“Coding Changes on the Horizon Health

Data Management, vol 3, No. 1, 1994, pp. 42-43

— .

sages use the same syntax, and most of the same standard for communicating laboratory data and

segments, as HL7 messages, but they include data other clinical observation data between software

structures for continuous waveforms such as elec- applications, but it now includes structures for

troencephalogram traces.

88 HL7 was originally a communicating clinical orders, billing informa88 Moreover, the chair of the group working on automated data within the HL7 committee has agreed to include these same message

constructs for transmitting wave forms in HL7 messages, and the same is true for other standards committees. Despite the diversity and multiplicity of committees and working groups, the emerging standards are generally complementary.
Chapter 2 Information Technologies for Transforming Health Care | 73

der way to facilitate that expansion. One example

is the nonprofit Healthcare Open Systems and

Trials (HOST) consortium.90 HOST is establishing test sites for deployment of new information

technologies at medical institutions and an Open

Systems Laboratory where the compatibility of

various technologies can be demonstrated. The

HOST consortium has recently received a grant

through the Advanced Technology Program

(ATP) at the National Institute of Standards and

Technology, which is also funding several other

projects that develop or implement novel information technologies for use in the health care system.91

Integration of the various technologies and

standards into working systems is also one focus

of the High-Performance Computing and Communications (HPCC) program. This multiagency

federal effort was initiated by the President’s Office of Science and Technology Policy during the

Bush Administration and expanded by legislation

introduced by then-Senator Albert Gore. The National Science Foundation (NSF), National Aeronautics and Space Administration (NASA),

National Institutes of Health (NIH), and other

agencies participating in the HPCC program support the development of the underlying technologies essential for telemedicine and other health

care applications of the National Information Infrastructure, including the National Research and

Education Network (NREN), pilot implementations of advanced information technologies in

health care settings, and supercomputer centers.92

Recent HPCC grants through NLM have funded

research leading to implementation of computerbased patient records in the Indianapolis metropolitan area,93 creation of a statewide digital

network to support telemedicine and rural health

care providers in Iowa,94 development of advanced computer simulations of human anatomic

structure to support surgical planning and medical

education, and numerous other projects.

Population-based public health services may

also benefit from the development of standards

and technologies that will enable health information to flow freely. Advanced techniques for

knowledge discovery in databases may be applied

to help automate the identification of public health

threats, such as the recent Hantavirus outbreak

that was identified through a medical examiner

surveillance database maintained by the Centers

for Disease Control and Prevention (CDC). A

small number of grants supporting the development of public health applications have been

awarded by the National Telecommunications and

Information Administration, and other integrative

work is proceeding with support from CDC,

AHCPR, the U.S. Public Health Service, and other agencies.

POLICY ISSUES AND OPTIONS

The technologies for collecting, distilling, storing, securing, and communicating data are widely

used throughout American industry. They are

used in health care organizations as well, but their

application has been limited to scattered islands of

automation. Despite the incorporation of high

technology into almost every other aspect of clinical practice, information technologies have not

been fully embraced.

The health care delivery system has several

unique characteristics that discourage the spread

90 The HOST consortium has over 30 corporate and academic partners. It was co-developed in 1994 by the Microelectronics and Computer

Technology Corporation (MCC) and the Computer-based Patient Records Institute.

91 B. Deming, “Launching a High-Profile Automation Mission,” Health Data Management, vol. 3, No. 5, May 1995, pp. 15-19.

92 D.A.B. Lindberg and B.L. Humphreys, “The High-Performance Computing and Communications Program, the National Information

Infrastructure, and Health Care,” Journal of the American Medical Informatics Association, vol. 2, No. 3, 1995, pp. 156-159.

93 J.M. Overhage, W.M. Tierney, and C.J. McDonald, “Design and Implementation of the Indianapolis Network for Patient Care and Research,” Bulletin of the Medical Library Association, vol. 83, No. 1, 1995, pp. 48-56.

94 M. Kienzle et al., “Iowa’s National Laboratory for the Study of Rural Telemedicine: A Description of Work in Progress,” Bulletin of the

Medical Library Association, vol. 83, No. 1, 1995, pp. 37-41.
74 | Bringing Health Care Online: The Role of Information Technologies

of information technologies. Clinical practice is

extremely complex, and despite the efforts of

standards committees, no unified conceptual

model exists that is powerful enough to guide the

creation of computer databases that adequately

represent medicine as it is practiced. No consensus has emerged on what information should be

kept in electronic patient records, how detailed it

should be, or how it should be described and indexed.

It is not a lack of appropriate hardware that limits or impedes productive computing in health

care services. Rather, it is a failure to understand

the intricacies of health care delivery as related to

capture and use of medical data, and the ways in

which they must be manipulated. Hence, what is

put into software, and thus the software itself,

does not adequately reflect the real needs of health

care providers or the ways in which they conduct

their activities.95

Experience gained in solving problems in one

area of medical practice may not be applicable to

other areas. A clear example of this occurs with

decision support systems. Self-contained, rulebased systems are widely used in well-defined

areas such as infection diagnosis and in some

medical equipment, but attempts to extend the

scale of decision support to broader areas of medical expertise have been frustrated. This resembles

the general pattern of medical research: narrow

problems are solved on a local basis. The result is

an idiosyncratic vocabulary and nonuniform clinical practice. Perhaps medical informatics works

best at solving a large number of microproblems.

If so, efforts should turn toward smoothly integrating all the microsolutions.

In addition to the complexity of clinical knowledge, the structure of the health care industry

discourages implementation of information technologies. Providers of health care services are

often isolated in separate corporate entities from

the insurance companies that pay them for their

services. Providers and payers are further isolated

from the medical research community, government health care agencies, and public health

organizations. A network of private sector intermediaries has formed to facilitate the complicated

relationships between the various organizations.

None of these entities is likely to be willing to collect or organize data that saves money or effort for

some other organization, but delivers it no immediately useful benefit; systemic savings may be

irrelevant in a vertically fractured industry. In addition, many communities have only a few hospitals or major insurers. The cooperation necessary

to interconnect medical information within a horizontal layer of the health care system may be seen

as anticompetitive and subject to antitrust regulation, or it may be hindered by organizations that

regard their internal information systems as competitive advantages and accumulated patient records as corporate assets.

Information technologies tend to flatten organizations and may not mesh well with the rigidly

defined job roles and hierarchical structure of current clinical practice. As an example, a patient records system was installed at the University of

Virginia Medical Center that required clinicians to

enter medical orders on computers. This had an

unexpected effect on the education of fourth-year

medical students who are often allowed to place

orders for a patient’s care with the approval of a

resident physician. With paper records, this had

been a simple matter that saved time for the resident and gave satisfying responsibility to the students: the student drew up a list of potential

orders, consulted the resident, and had the list approved. With computerized order entry, the process was much more cumbersome. Each order was

issued separately and needed to be approved separately. This meant either calling a resident multiple times to approve individual orders or placing

95 T.L. Lincoln, D.J. Essin, and W.H. Ware, “The Electronic Medical Record: A Challenge for Computer Science To Develop Clinically and

Socially Relevant Computer Systems To Coordinate Information for Patient Care and Analysis,” The Information Society, vol. 9, 1995, pp.

157-158.
Chapter 2 Information Technologies for Transforming Health Care | 75

orders in suspension one by one and then finding

ways to reassemble them for a single consultation

with the resident.96

It might be argued that changes to the design of

the system, or implementation of a records system

more carefully tailored to support desired work

patterns, could alleviate this specific problem.

Nonetheless, the deeper issue is that completion

of every detail of order entry is a new and perhaps

unwelcome task for physicians. To some extent,

all information systems that deliver information

to a clinician at the point of care also require simultaneous collection of information by the clinician at the point of care. Job descriptions will

change as decisionmaking, authorizing actions,

and entering data become more tightly linked:

In contradistinction to the retail sector, which

can assign relatively inexperienced employees

to data-entry positions [and create competitive

advantages by capturing data at the point of

sale], the health care sector places the most

highly trained professional personnel with the

greatest opportunity cost in the data-entry

role.97

Changes in job roles will occur throughout the

health care system, should information technologies be widely adopted. These changes will be

accompanied by redistributions in health professionals’ time and by shifts in the responsibilities

and status associated with the various health disciplines.

Information technologies may have more subtle ramifications as well. The widespread adoption of integrated information systems will

challenge the legal system. Patients are the consumers of health services, and their traditional

protection against poor-quality care has been the

ability to file lawsuits against their providers. Information technologies are tools for providing

health care, but they are maintained and employed

by a variety of people who may be geographically

separated. Who is responsible if a treatment protocol recommended by a decision support system

turns out to be injurious? Is it the academician

who designed the protocol, the reviewers who approved its publication, the insurance company

that insisted it be implemented, the hospital board

that approved its use, the interface designer who

failed to provide contextual information that

could have contraindicated its use, or the primary

physician who employed the protocol, but may

have had no knowledge of its deficiencies? And if

no one can be held directly accountable, what alternative system of quality control must be designed to replace the current legal remedies?

Information technologies diffuse responsibility,

and changes in the hierarchical way that medical

care is practiced may be necessary before they are

fully embraced.

Finally, information technologies are expensive to implement and their benefits may be difficult to measure directly, even when all parties are

happy with the results. This may help delay their

deployment in an industry whose sophisticated

technological base is seen by some to be a driving

force in making health care more expensive.

❚ Opportunities and Challenges

Given these obstacles, installation and efficient

utilization of information technologies in health

care will continue to be incremental and difficult.

However, there are a number of reasons why Congress may wish to actively support this process.

First, implementation of information technologies could lead to reductions in federal health

care expenditures. The federal government is a

major purchaser of health care through Medicare

and Medicaid, and a major integrated provider and

payer through its health care programs for military

personnel, veterans, and Native Americans.

While individual private sector organizations par96 T.A. Massaro, “Introducing Physician Order Entry at a Major Academic Medical Center: II. Impact on Medical Education,” Academic

Medicine, vol. 68, No. 1, 1993, pp. 25-30.

97 T.A. Massaro, “Introducing Physician Order Entry at a Major Academic Medical Center: I. Impact on Organizational Culture and Behavior,” Academic Medicine, vol. 68, No. 1, 1993, pp. 20-25.
76 | Bringing Health Care Online: The Role of Information Technologies

ticipating in health care delivery may find it difficult to realize financial benefits from systemic

changes, the federal government is ideally situated to recoup whatever costs might be incurred

in encouraging adoption of information technologies at all levels of health care delivery by substantially reducing its own health care costs.

Researchers and others have suggested that multibillion-dollar annual savings might be possible

with increased use of information technologies in

health care. Chapter 3 discusses these projections

for administrative savings.

Information technologies may also foster competition in the health care industry. Chapter 4

discusses ways that advanced information technologies can be used to evaluate the effectiveness

of health care procedures and the efficiency of

health care organizations. Although these techniques for quality assessment are highly problematic, they may represent an unprecedented metric

by which organizations and practices can be

compared and contrasted, thereby enabling consumers and managers to make more informed

choices concerning their health care.

Implementation of information technologies

may help increase access to health care through

private sector activities. Chapter 5 discusses ways

that information technologies may allow health

care providers to extend their reach in the communities they serve through telemedicine or other

means for electronic delivery of services. In addition, new technologies may help decentralize

health care by increasing the flow of useful information to primary care doctors so that more

people can have access to state-of-the-art health

care without resorting to hospital or emergency

room care. This consideration is especially important in rural communities and inner-city communities where the viability of large health care

institutions is uncertain.

Finally, information technologies could lead to

systemic changes and opportunities that will enable the American health care system to better

serve its citizens through more convenient and

perhaps less expensive delivery of health services.

Some of the benefits and conveniences (as well as

some of the drawbacks) of health care enhanced

by information technology were envisioned in the

fictional scenario at the beginning of this chapter.

Many others will only become apparent once a

broad information infrastructure is in place. Every

new tool contains embedded ideas that go beyond

the function of the tool itself.98 When personal

computers were developed, there was little indication or intention that they would rapidly develop

into tools for individuals to publish and access information across the globe; the federal government played an important role in that development

through its support of the development of the Internet’s predecessors.

There are indications that similar dynamics

will emerge as the health information infrastructure continues to evolve. One example of this appears in the area of pharmaceuticals. The volume

of pharmacy claims is much greater than the number of claims for clinical procedures, and pharmacy claims are also much simpler to process than

other claims. Two crucial enabling standards exist: the National Council of Prescription Drug

Pharmacies (NCPDP) has developed a widely accepted standard for communication between community pharmacies and claims processors, and the

FDA has defined the National Drug Code that

specifies a unique code for each drug. As a result,

pharmacy claims were one of the earliest areas to

be computerized. Today, over 90 percent of community pharmacies are connected online to at least

one third-party pharmaceutical claims processor.99 This connectivity led to the expected administrative savings due to elimination of

paperwork and automation of eligibility verification and inventory replenishment, but it also had

the relatively unforeseen benefit of making avail98 N. Postman, Amusing Ourselves to Death: Public Discourse in the Age of Show Business (New York, NY: Viking Press, 1985), p. 30.

99 C.J. McDonald, “News on U.S. Health Informatics Standards” (letter), M.D. Computing, vol. 12, No. 3, 1995, pp. 180-186.
Chapter 2 information Technologies for Transforming Health Care | 77

to savings in pharmacy expenditures for many

providers using PBMs, although some studies

have shown that savings are sometimes offset by

increased use of other, more expensive services

such as hospital outpatient, inpatient, or emergency services.100 Information technologies have led

to significant changes in the distribution and purchasing of pharmaceuticals, such as the development of formularies, or lists of preferred drugs,

and the widespread use of generic drugs and drugs

discounted by manufacturers. The implementation of information systems has had a broad

impact even on pharmaceutical research and development because it has encouraged development of novel drugs and generic drugs, but made it

less attractive to develop new entries for drug

categories with numerous existing products.l01

Computerization of pharmacy transactions presents an opportunity for addressing more comprehensive health maintenance issues, such as patient

compliance with drug therapies, because physicians could be informed when their patients fail to

renew prescriptions or when they obtain additional drugs prescribed by other caregivers. Freely

flowing health information may have large implications for both the creativity and the competitiveness of the health care industry.

■ Policy Options

If Congress wishes to support and affect the diffusion of information technology in health care settings, it could consider a number of options.

Support standards-setting activities

Congress may wish to participate in or monitor

efforts to set standards for implementation of information technologies in the health care system.

Congress could:

■ support the development and adoption of consensus standards for electronic messaging and

clinical coding. This could be achieved by directing agencies to supply personnel to actively

participate in standards-setting meetings and to

develop aggressive timetables for government

implementations of consensus standards. Tax

credits could also be extended to encourage the

purchase of information systems that implement consensus standards.

■ support the development of coding systems and

nomenclatures necessary for communicating

the content of patient records. This could be

done by continuing to fund the development of

the Unified Medical Language System and related efforts at the National Library of Medicine.

■ ensure that technical standards for the content

of patient records and for minimum levels of

privacy and confidentiality meet privacy policy

goals. This mission could be delegated to: 1 ) a

special task force made up of technology, privacy, and health information experts; 2) a committee charged with an ongoing review of

health information privacy issues; ’02 or 3) an

existing committee, such as the Health Information and Applications Working Group of

the Information Infrastructure Task Force

(IITF).

Fund and coordinate research efforts to

overcome specific technological barriers.

Most of the technologies discussed in this

chapter have been developed through corporate or

academic research that was not connected directly

to health applications. As a result, some areas,

such as human-computer interface design for use

in medical contexts, are not well developed and

100 C.M. Kozma et al., PharmacoEconomics, VOl. 4, 1993, pp. 92-103, 187-202.

101 Judith L. Wagner, Senior Associate, Health Program, Office of Technology Assessment, testimony presented before the Committee on

Finance, U.S. Senate, hearing on Long-Term Care and Drug Benefits Under Health Care Reform, Apr. 19, 1994.

102 U.S. Congress, Office of Technology Assessment, op. cit., footnote 43, p. 2O.
78 | Bringing Health Care Online: The Role of Information Technologies

may pose difficult problems in the implementation of integrated systems. Congress could encourage research into these areas by creating

focused programs administered by the National

Science Foundation, the National Institutes of

Health, or other agencies providing traditional

peer-reviewed research grants. In addition, Congress could support research into large-scale implementation of information technologies in

health care settings through pilot programs and

testing centers.

Coordinate federal efforts to implement

health care information technologies.

This coordination could be achieved through

existing agencies and committees or through the

establishment of a special committee or commission. In particular, the relevant bodies might be

charged to:

■ establish procedures for expediting approval

and distribution of medical software. Faulty

software is as dangerous and worthy of regulation as poorly designed medical hardware, but

software has the unique feature that it can be developed incrementally and distributed electronically.

■ establish mechanisms (or support similar private sector efforts) for reviewing and disseminating clinical protocols. 103

■ advise Congress on specific needs of the clinical community with respect to legislation establishing regulations and policies pertinent to

information technologies. Current issues that

fall under this rubric are liability reform and

telecommunications deregulation legislation.

■ establish policies consistent with privacy

policy goals for implementation of uniform patient and provider identifiers for use in federal

agencies.

103 For further discussion, see chapter 4.
Networks

for

Health

Information

nformation technology can be used to automate many administrative processes in the health care system, including

transactions between those who provide health care services

and those who pay for them. The general term electronic

commerce is used in the chapter to describe the automation of

business transactions and the direct computer-to-computer exchange of information, business documents, and money.

This chapter examines electronic communications between

providers and payers (including interactions with electronic medical claims companies, value-added networks, clearinghouses,

and others that facilitate this communication). It also discusses

electronic commerce between health care providers and medical/

surgical manufacturers and distributors, as well as between pharmacies and both pharmaceutical distributors and claims payers.

The role of communication networks in facilitating the exchange

of health information among health care providers, payers, and

others on a community-wide or regional basis is examined. Figure 3-1 illustrates some of the directions in which information

needs to be exchanged, or transactions need to be effected, among

the various components of the health care delivery system.

Electronic communications can free administrative information from paper, allow it to be processed automatically (without

human intervention), and permit it to be readily reused for a number of related purposes. In many cases, it appears that electronic

commerce can provide some cost savings to health care system

participants and to the system as a whole. Realizing those savings

requires investment in equipment and training, as well as industrywide agreement on and compliance with standards for the format and content of messages. The chapter reviews some of the

research on costs and cost-effectiveness of various uses of elec- | 79
80 Bringing Health Care Online: The Role of Information Technologies

I I I

Medical/surgical

product

manufacturers

Medicare fiscal

intermediaries

and carriers

I

I

Medical/surgical

distributors

I

/

I HEALTH CARE I

I

Wholesale drug

distributors

Health Care

Financing

Administration

(Medicare)

I I

SOURCE: J. Moynihan and K Norman

I

L

Claims payers

■ Indemnity

■ Managed care

■ Self-insured

Medicaid

processors

I

Medicaid I L . I

Self-pay

“Health Care EDI: An Overview, ” EDI Forum, voI. 6, No 2, 1991, p 11

tronic commerce and regional networks in health

care. In addition, it outlines some of the overarching issues that affect the adoption of the technology by participants-industry fragmentation, the

slow development of standards, the fragmented

regulatory and policy environment, as well as concerns about privacy, confidentiality, and security

of health information in a networked environment.

ADMINISTRATIVE SIMPLIFICATION

Administrative simplification has come to mean

streamlining and standardizing the transactions

between health care providers and payers to reduce costs. The administrative costs of providing

health care have been estimated at between $108

billion and $135.1 billion per year in 1991,1 or between 12 and 15 percent of the health care bill. Es1 Lewin-VHI, “Reducing Administrative Costs in a Pluralistic Delivery System Through Automation,” prepared by A. Dobson and M.

Bergheiser for the Healthcare Financial Management Association, Apr. 30, 1993.
Chapter 3 Networks for Health Information | 81

timates of annual savings that could be realized

through increased use of information technology

to streamline administrative functions have

ranged from $5 billion to $36 billion,2 or enough

to reduce administrative costs between 0.5 and 3.6

percent.

Administrative simplification generally means

not only standardizing forms, procedures, and information requirements, but also moving to electronic technologies from paper-based transactions

and recordkeeping. This chapter will review some

of the technological, legal, and economic issues

involved in administrative simplification. It also

discusses more generally the concept of “electronic commerce,” the exchange of business information and money through computer networks, and

specific tools for electronic commerce such as

electronic data interchange (EDI). (See boxes 3-1

and 3-2.)

In the traditional “fee-for-service” health care

delivery system, the health care provider performs

services for the patient and then submits a bill to

the patient. If the patient is insured, either the provider or the patient will submit a claim to the payer

(insurer) to reimburse the patient or to pay the provider directly on the patient’s behalf. The information exchanged between care providers and payers

(insurers) can be very complex. The information

that a payer requires a health care provider to furnish in order to get a claim paid depends not only

on the payer’s policies, but on the laws of the

states in which the payer, provider, and patient are

located. In addition, because many patients are

covered by more than one insurance plan, there

may be secondary or tertiary payers involved in

paying a single bill. From the provider’s point of

view, getting that bill paid may be quite burdensome. The various payers may not only require

different information, in different forms, but may

also require the provider to furnish information

about the other payers in order to coordinate benefits for the patient.

Several studies of health care administrative

costs have suggested that the large number of different payer institutions (over 6,000) and the variety of formats in which they request claim

information are factors in making the cost of

health care administration much higher for the

United States than for other industrialized countries.3 A government-mandated change to a

single-payer system might reduce these costs, but

such an action appears unlikely. Administrative

simplification, through the introduction of electronic transactions and through standardization of

transactions and processes, may offer a way to

achieve more modest savings.

Many managed care companies now perform

the functions of both payer and provider. However, this does not necessarily reduce the number

of transactions or ensure that administrative simplification will be achieved simply by enrolling

most of the population in health maintenance organizations (HMOs) or other managed care systems.4 While some interorganizational transactions are eliminated, they are often replaced by

analogous exchanges of information within the

managed care company. In addition, managed

care organizations are “information hungry” and

are creating new management information exchanges between their “provider” and “payer”

components.

In some HMOs, where patients are served only

by providers employed by the HMO and where all

financial risks (the insurance functions) are assumed by the HMO itself, there is usually little

need to submit claims to payers, except for occasional referrals to outside specialists. However,

managed care is coming to have forms. Managed

2 Project HOPE Center for Health Affairs, Bethesda, MD, “Estimating the Cost-Effectiveness of Selected Information Technology Applications,” unpublished contractor report prepared for the Office of Technology Assessment, U.S. Congress, Washington, DC, March 1995.

3 U.S. Congress, Office of Technology Assessment, International Comparisons of Administrative Costs in Health Care, OTA-BP-H-135

(Washington, DC: U.S. Government Printing Office, spring 1994).

4 For more description of managed care, see box 1.1.
82 Bringing Health Care Online: The Role of Information Technologies

Electronic Data Interchange (EDI) IS defined as the application-to-application interchange of business data between organizations using a standard data format. 1 A computer application is a software

system that performs work Information IS routed through telecommunications networks, received by an

organization’s EDI system, and processed by its computer applications—all without human intervention.

Redundant data entry IS thus eliminated, which increases the accuracy of information and reduces administrative costs.

Organizations doing business with one another are called trading partners. Companies have used

EDI to reduce the costs of exchanging and processing documents for more than 25 years. In the last

several years, however, companies and consultants have placed EDI into a larger context called electronic commerce

Electronic commerce IS a management concept in which all information flows between and within

organizations through networked computer systems Work can be done in ways that differ from a paperbased system. In electronic commerce, for Instance, a process made up of discrete tasks may be performed as a series of parallel tasks. Only one person can work on a paper document at a time. When

the Information contained on that document is freed from the constraints of paper and ink and is available in electronic form, several people can access, use, and transform the information at the same

time.

EDI is not a concept like electronic commerce, it is a technology consisting of rules and standards

programmed into computers One could say that EDI is to electronic commerce as statistical process

control IS to total quality management, that is, EDI is one of the tools required to put the management

concept of electronic commerce into action.2

Standardization is the key to EDI. Computers cannot process the Information that moves between

organizations electronically unless it is encoded in a manner that the computers at both organizations

can recognize. In other words, both computers must be able to speak the same language. In Iinguistic

terms, they must follow standard usage. EDI provides a set of rules, grammar, and syntax that forms the

basis of standard usage in the electronic exchange of business data. EDI is both the means and the

language that computers use to “talk business.”3

SOURCE: C. Canright, “Electronic Commerce and Networking in Health Care, ” unpublished contractor report prepared for the Off Ice

of Technology Assessment, U S Congress, Washington, DC, Jan 31, 1995

1 C. Canright, “The Problem of Data Mapping, " EDI Executive, voI. 4, No. 6, June 1989, p 1

2 G. Gerson, Sr., “lnterview with Captain Bruce Bennett, USN, Executive Agent for Electronic Commerce, United States Department of Defense, ” EDI Forum, vol. 6, No 3, 1993, p 42

3 R.W. Notto, “EDI Standards: A Historical Perspective, " EDI Forum, vol. 1, No. 1, 1988, p. 120.

care organizations can have a variety of relation- Managed care organizations also exchange adships with providers (e.g., they may be employees, or they may accept patients under

exclusive or nonexclusive contracts). They may

also have a variety of relations with payers, assuming some financial risk internally, while still

submitting claims to other payers. Thus, these organizational arrangements still involve transactions between provider and insurer organizations.

ministrative or clinical information internally and

with their contract providers. In order to be profitable under flat-rate capitated contracts, managed

care organizations must reduce duplicative

services and manage each patient’s utilization of

services. This means that each clinician in the system who encounters a patient should ideally have

access to a fairly complete medical record in order
Chapter 3 Networks for Health Information 83

I

Value-added networks (VANS) are the means most companies use to exchange electronic data interchange (EDI) transactions. VANS are the electronic equivalent of a package delivery service Rather

than make a direct computer connection with trading partners, companies send their data to a VAN It

receives a bundle of EDI transactions—representing many types of business documents and bound for

many different trading partners—and routes the individual transactions to the appropriate trading partner’s electronic mailbox, When the trading partner connects with the network, the EDI transactions are

transmitted to its computer. VANS make EDI easier because they eliminate the scheduling problems

that arise when making direct computer connections. They can also be more secure than direct computer connections because trading partners are isolated from each other’s systems.

SOURCE: C. Canright, “Electronic Commerce and Networking in Health Care, ’ unpublished contractor report prepared for the Office

of Technology Assessment, U S Congress, Washington DC, Jan 31, 1995

to know what has been done by others. It also

means that management should know what resources are expended on that patient, even when

there is no need to actually generate a bill. Many

managed care organizations are finding the need

for “encounter reports” that contain much of the

same information that is currently included in insurance claim forms in a fee-for-service system.

While the encounter report could be considered an

internal communication within the managed care

company, in some cases delivering it will take

very much the same technology and pose many of

the same problems as the delivery of claim information between a provider and payer.

ADMINISTRATIVE ACTIVITIES IN HEALTH

CARE

Administrative activities related to health care occur at all levels of the health care system, including health care providers, payers, and local, state,

and federal government agencies. These activities

include:

■ Health care providers (individual and institutional): Calculating bills and billing payers;

transmitting records to outside providers or

payers; internal financial management; regulatory compliance; utilization review; quality asin

●

in

■

surance; and acquisition, distribution, and

storage of equipment and supplies.

Payers: Claims processing; coordinating benefits with other payers; claims payment; managing plan enrollment and eligibility; statistical

analyses and quality assurance; and regulatory

compliance.

Employers and other large purchasers of

health care services: Comparing and selecting

plans; and managing enrollment of employees

or members.

Consumers (patients): Submitting claims:

tracking eligible expenses; and paying copayments and uncovered bills.

Government agencies: All of the above activities in roles as providers, payers, and employers; data collection for vital statistics; health

care financing data; and regulatory oversight.

A fuller description of administrative activities

and costs is available in a previous Office of Technology Assessment report, International Comparisons of Administrative Costs in Health Care. -s

PROVIDER ADMINISTRATIVE ACTIVITIES

Many information exchanges that take place within a single provider’s organization (e.g., admiss ion-discharge-transfer messages or billing

5 Office of Technology Assessment, op. cit., footnote 3.
84 | Bringing Health Care Online: The Role of Information Technologies

information) are automated. Use of the Health

Level 7 (HL7) standard, discussed in chapter 2,

which is used for exchange of clinical information, is also growing for administrative and patient

management information. Most vendors of both

administrative and clinical information systems

are supporting the HL7 standard. Use of computers in administration and patient management is

not limited to hospitals or large clinics. Although

many doctors’ offices still rely on paper patient records and billing systems, a growing number are

computerizing at least some of their business and

administrative functions. Computerized practice

management systems (PMSs) automate functions

such as accounts receivable, insurance, billing,

and appointments; they also record the patient’s

diagnoses, procedures, medical history, and financial history. PMSs offer a wide range of functionality and very little standardization; some systems

were developed on an ad hoc basis by their users

and others were purchased from one of more than

400 vendors. Some PMSs also help physicians

deal with the complexities of managed care contracts, for example, by maintaining member lists,

posting capitation payments from plans, tracking

the number of visits or services provided for each

patient, and providing reports on the profitability

of the relationship with each plan.

Typically, providers only have information

about their own contribution to a patient’s care—

for example, hospitals maintain records of inpatient stays and doctors’ offices keep track of office

visits. But to manage patients’ use of resources effectively, managed care organizations want to

track patient care over several years and integrate

different services that were performed at various

locations. Integration of financial and clinical information is also important to managed care.6

Integrated Delivery Systems (IDSs) are emerging to meet the need of health care organizations to

deliver a full range of health care services to their

covered populations. An IDS, either through ownership, partnership, joint venture, strategic alliance, or contract, brings together hospitals,

ambulatory care facilities, affiliated physicians’

offices, nursing homes, home care services, laboratories, wellness programs, and so on. IDSs have

been springing up rapidly as managed care companies position themselves to compete; the result

is a conglomeration of provider organizations

with different levels and types of automation and

uses of information technology. Some IDSs are

making the investments needed to develop “enterprise-wide” information systems to allow exchange of clinical and administrative information

among their various components.

Health care providers perform a variety of administrative activities associated with each admission, visit, or episode of care. These activities

begin well before the face-to-face encounter with

the patient and last long after the patient has left

the institution or professional’s office. Preadmission and preregistration cover a variety of logistical, clinical, and financial activities, including

eligibility confirmations, certifications, and authorizations for care, which generally require

communication with the patient’s payer.

EXCHANGING INFORMATION BETWEEN

PROVIDERS AND PAYERS

During the course of treatment or admission, additional transactions flow between the provider and

payer or care manager, including reauthorizations,

recertifications, interim billing, and a variety of

review activities. Due to the limits on some health

care coverage, the provider might also have to

redo the eligibility function as well. Figure 3-2 illustrates some of the information flows between

payer and provider at various stages in the process.7

At some point during or after treatment, the

provider will issue a bill and/or a claim. Copies of

the bill might go to the patient, as well as to one or

6 D. S. Kolb and J. L. Horowitz, “Managing the Transition to Capitation,” Healthcare Financial Management, February 1995.

7 The following description of administrative information exchanges is based on information from D. Rode, immediate past co-chairman,

ASC X12 Insurance Subcommittee, Healthcare Task Group, personal communication, May 12, 1995.
Chapter 3 Networks for Health Information 185

Health care provider

Pre-admission,

registration, and

treatment period

Admission or registration

Inpatient treatment

------- -

Discharge

Billing period

--------- -

Followup

collection period

Payer or primary provider

communications

Eligibility verification request

<—Eligibility confirmation or denial-----------------------------------—

Primary provider,

benefits department, or

Coverage data request---------------------------------------> eligibility department

<----Coverage data reply

Precertification and/or authorization request->

<—precertification and/or authorization approval Utilization

Recertification request review

<-Recertification approval

Claim submission (interim bill and/or medical data)-->

<---Interim payment

Claim submission (final bill and/or medical data)--->

<—Claim status inquiry

I

Claims

processing

Claim status inquiry response

! J

transfer

SOURCE: Adapted from D Rode, “EDI Holds Potential for Cutting Receivables Processing Costs,” Healthcare Financial Management Association,

March 1990, p 15

more payers. When more than one payer is involved, the provider may send a bill to all parties

and work through a very complicated process to

coordinate billing (and payment). Even patients

who belong to managed care entities that capitate

payments or use other reimbursement methods

might need to have all or parts of their bill or claim

sent for management information purposes.

After the initial claim or billing, the provider

may have several followup steps, such as providing additional information to a payer inquiring

about the status of a claim previously sent to one

or more payers. Because more than one provider

may be billing for services rendered during the

same episode of care, both providers and payers

may have to coordinate and track their information. Many institutions and some individual providers are also required to send additional

information as attachments to the claim. Among

the required documents are discharge abstracts,

surgical reports, first reports of injury, and attestation reports. Late submission of these reports

might also delay the payment of the original

claim.

Finally, the provider receives a payment or rejection from the payer. This is a two-step process
86 I Bringing Healthcare Online: The Role of Information Technologies

Information systems allow many caregivers to share clinical

and administrative information.

because the provider must reconcile the payment

to the original claim, as well as to the posting process at its financial institution. The information received with the payment or rejection (usually

called remittance advice) can be as simple as a

check number or it may include pages of information responding to each line of the original claim.

If the patient has health care coverage from a secondary payer, the provider may then have to repeat

the process, submitting a secondary billing claim

to that payer, and including with the claim information about what was and was not paid by the

primary payer (some institutions bill the patient

who is then responsible for collecting from secondary payers). On average, most institutions do

not see payment on a claim for well over two

months. Individual and professional payments

often take longer.8

During the course of these provider-payer

transactions there can be many telephone contacts

and letters exchanged among the parties. In an inpatient environment, which is relatively stable,

the cost of carrying out these transactions is relatively low compared to the amount of the claim.

However, the opposite is true in an outpatient or

ambulatory-care setting. The provider’s costs for

processing each transaction, claim, or eligibility

verification is about the same as in an inpatient

setting, but the resulting revenue is much less. The

move of health care toward more outpatient care

will accentuate this problem.

The traditional model for health payments has

been that the provider charges the patient a fee for

the services provided. The patient (or the provider

on the patient’s behalf) files a claim with the patient’s insurer (payer) for payment of the covered

portion of this fee. There are several types of transactions in the fee-for-service environment where

electronic communications could be applied.

These transactions are: 1) claims submission, 2)

remittance advice, 3) claims inquiry, 4) enrollment, and 5) eligibility inquiry.

Claims submission is the process of preparing

and submitting documents to a payer on behalf of

a patient. Nearly all claims for hospital services

are submitted by the provider. Claims for services

in a physician’s office may be prepared by either

the patient or the provider; in preferred provider

networks, the physician usually files the claim. Information required to complete the claim form

may have entered the provider’s accounting system through either a direct interface with other information systems in the provider organization, or

through keyboard input by a data-entry clerk who

reads the various paper documents about the patient and enters the data into the patient-accounting system. This system, whether paper-based or

computer-based, must prepare a claim document

in a form that is acceptable to the payer.

Remittance advice is a document returned to

the provider by the payer along with payment after

the claim is processed. The remittance advice explains what the payment covers and how the claim

was adjudicated by the payer. The provider

compares the payment with the original claim to

determine whether the amounts match. If the

claim and payment do not match, the clerk checks

the remittance advice to determine where the differences lie. When the claim and the various payments match, either immediately or after a process

8 A review of quarterly analyses by Zimmerman & Associates, Hales Comer, WI, shows receivables always exceed 60 days. Ibid.
Chapter 3 Networks for Health Information | 87

of negotiating discrepancies, the claim is reconciled with its associated payments and closed. Remittance advice can be a paper document that

accompanies a check; an electronic document that

accompanies an electronic funds transfer; or an

electronic document that is separate from, but related to, an electronic funds transfer sent by other

means.

Claims inquiry is a process that providers use

either to determine when payment will be made or

to negotiate discrepancies in a claim that has been

partially paid. Often, inquiries are telephone conversations, but some vendors are beginning to offer online inquiries.

Enrollment is a process that involves the payer

and the patient’s employer (or sponsor of the

health care plan in which the patient enrolls). Enrollment transactions occur when people join a

health plan, change their family status, move,

change plans, and so on.

Eligibility inquiries are transactions between

providers and payers to determine what benefits

the patient is entitled to. Patients arriving at the

doctor’s office, hospital, pharmacy, or other provider location are asked what kind of coverage

they have and from whom. This information is

confirmed by an inquiry to the payer by mail, telephone call, or an electronic process. Having this

confirmation quickly is useful to the provider: it

means that correct copayment amounts can be collected right away, for example, or that certain services will not be offered to people who are not

entitled to them. EDI standards have been developed for the above transactions. (See box 3-3.)

In a managed care environment, some of these

transactions are different. For example, in an

HMO, where members are charged a fixed fee per

person (capitation) and are not billed for individual services, the traditional insurance claim is unnecessary. In some cases, however, HMOs are

using an encounter report to provide management

information about services provided, and these

could be considered surrogates for insurance

claims. Enrollment transactions and inquiries

about a member’s eligibility for services are as important in a managed care environment as in a feefor-service system; in some cases, they may be

internal transactions between parts of the same organization (perhaps at different locations) rather

than between different organizations.

❚ Status of Electronic Insurance

Transactions9

Health Care Financing Administration

As the largest payer of health care claims in the

country, the federal government for years has encouraged providers and insurers to do business

electronically, especially the submission of Medicare claims. The Medicare program (and the federal portion of the Medicaid program) is

administered by the Health Care Financing Administration (HCFA) which, beginning in the

1970s, established electronic links between hospitals and fiscal intermediaries—the insurance

companies that process Medicare claims under

contract with the government. Currently, 80 different insurance companies process some 730

million Medicare claims annually.10

Initially, the shift away from paper involved

hospitals submitting bills by either direct-data

entry (DDE) terminal, linked directly by leased

phone lines to the mainframe computer of the fiscal intermediary, or by computer tape. In either

case, clerical personnel would key in the necessary information. For computer tape transactions,

they would format the information on computer

tape, which was then sent to the fiscal intermediary. For the fiscal intermediary, the volume of information received on tape—and thus the reduced

costs of processing as compared with paper submissions—justified writing separate computer interfaces to translate the different tape formats as

required.

9 This section is based on C. Canright, “Electronic Commerce and Networking in Health Care,” unpublished contractor report prepared for

the Office of Technology Assessment, U.S. Congress, Washington, DC, January 1995.

10 “Implementing EDI on a Colossal Scale: An Interview with HCFA’s Carol Walton,” EDI Forum, vol. 6, No. 2, 1993, p. 47.
88 I Bringing Health Care Online: The Role of Information Technologies

The key to the concept of administrative simplification lies in data standa r

throughout this report. Indeed, the one thing that nearly everyone involved in health care automation

agrees on IS that uniform data standards are required to control health care administration costs.

Roughly speaking, data-processing standards have two components: content and transmission.

Data-content standards specify how meaning should be represented. Data-transmission (or messaging) standards specify how information encoded as strings of binary digits should be structured for

transmission over wires or through the air.

Data Transmission

EDI standards for business documents structure information in such a way that computers at different organizations can process it. Computers do not process documents like humans read documents.

Computers process data. To the computer, EDI is not a facsimile of a document that a computer stores;

it is a stream of data that actually causes a computer application to perform a specific action. 1

Data, however, are not quite enough. Data may be two-character codes that represent an idea or a

string of characters that represent, for instance, a Social Security number (SSN). Because all data are

represented as strings of 0s and 1s, computers need a means of distinguishing data denoting one idea

from data denoting another.

Computers distinguish one bit of data from another through positional relationships. If a health care

claim were written as a single line, then the computer would need to know what part of the Iine represented an SSN and what part represented a patient’s name. By cutting that Iine of characters up into

data elements, a computer can recognize one type of reformation from another. The first data element

might represent a patient’s name and address, while the second represents the line items on a claim.

EDI standards provide that type of structure. They provide a common way for computers to structure

the data that represent business documents.

The standards for moving the data that appear on common business documents between organizations are called the ASC Xl 2 standards for electronic data interchange, named after the American National Standards Institute’s Accredited Standards Committee Xl 2, which develops them. ASC Xl 2 standards define a syntax and provide a structure for moving data between organizations. In that way, EDI

standards are external data-transmission standards. The structure that represents a business document

is called a transaction set; transaction sets are the electronic equivalents of paper business documents .

Transaction sets, then, are composed of an ordered series of data segments. Data segments are

analogous to the groups of data that perform specific functions within a business document, such as

Iine items on a purchase order, terms of payment on an invoice, or the identification (name and address) sections that appear on any business document. Segments, in turn, are constructed of an ordered series of Iogically related data elements. Data elements specify such things as unit of measure,

price, quantity, and currency.

Data Content

The content of standards comes to the fore at the data-element level of the X12 standards. Much of

the content of a transaction set consists of codes used by a company or an industry to represent the

1E.J. Bass, “lntroduction to EDI,” unpublished paper presented to Accredited Standards Committee X12, St

Charles, IL, May 16, 1988

(continued)
Chapter 3 Networks for Health Information 189

specifics of its business. As much as possible, the Xl 2 committee seeks to standardize content across

industries. The segment and data elements used in transaction sets to represent a name and address,

for Instance, are the same for transportation concerns as for health care concerns.

Just because two organizations support the Xl 2 standards, however, does not mean that communication between them is seamless. On a technical level, both systems are compatible because they

are communicating using a common language. On a content level, however, compatibility is nowhere

near guaranteed, particularly in health care. The data content of ASC Xl 2 standards comes from industry- and company-specific codes. In health care, for instance, the ASC Xl 2 health care remittance advice standard uses Adjustment Reason Codes maintained by the Blue Cross and Blue Shield Association and Current Procedural Terminology (CPT) Codes maintained by the American Medical

Association. In fact, any organization can petition the ASC Xl 2 committee to include its codes into the

standard. As long as those codes meet the test of business necessity and perform functions that existing codes cannot perform, the codes are incorporated into the standard,

As a result, ASC Xl 2 standards accommodate a huge amount of data content and they can perform

the same business function in many different ways. Most Industries have Iimited this variability by publishing Implementation manuals specifying how a particular transaction set should be used to conduct

business with companies in that Industry.

The data content used in the ASC Xl 2 health care transaction sets IS still too broadly defined, Nearly

everyone revolved in EDI in the health care Industry agrees that widespread EDI implementation wiII

require greater uniformity in data content. As the WEDI committee puts it, “A significant barrier to the

Implementation of EDI IS the fact that implementation guides have not been developed that Incorporate

standard requirements and content across large segments of the health care industry It IS critical that

private payers and government programs, including Medicare and Medicaid, use a common set of formats to achieve the highest level of administrative cost savings and accelerate the implementation of

EDI.” 2

The health care industry needs a business model that specifies the data required in each transaction

and how they should be encoded and structured within the standards. Efficient standards require that

all participants in the industry agree on. 1 ) what data to collect, 2) when to collect it, and 3) how to

collect it.3

In the absence of industrywide implementation manuals, many in the industry are relying on implementation guidelines created by the Health Care Financing Administration (HCFA), the first payer to

Implement the health care claim payment and advice (ASC Xl 2.835) transaction set and the claim submission (ASC Xl 2.837) transaction set,

SOURCE: C. Canright, “Electronic Commerce and Networking In Health Care, ” unpublished contractor report prepared for the Off Ice

of Technology Assessment, Jan 31, 1995
90 | Bringing Health Care Online: The Role of Information Technologies

But as large chain-affiliated hospitals found

that they were dealing with many different formats, they asked HCFA to establish a standard

tape format, which it did in the late 1970s. The

standard tape format allowed hospitals and other

large institutions to introduce a degree of standardization into their claims submissions process.

However, they still faced different data requirements from different fiscal intermediaries in different states.

During the 1980s, with the growing use of personal computers, HCFA also began to encourage

physicians to do business electronically. In the

mid-1980s, HCFA aggressively put pressure on

providers to convert to electronic billing, and by

1985, HCFA received about two-thirds of Part A

hospital claims and one-third of Part B supplemental insurance claims electronically.11 Part A

claims are submitted by hospitals and other large

institutions for inpatient care. Part B claims are

submitted by physicians and clinics.

HCFA’s push for electronic claims processing

came to a standstill in the late 1980s. Congress, as

part of an attempt to balance the federal budget,

mandated an extended timeframe for paying all

Medicare claims. HCFA, however, had used expedited payment as an incentive for providers to submit bills electronically. Without the incentive of

faster payment, many providers saw no reason to

make the investments needed to submit claims

electronically.

HCFA started to promote electronic billing

again in 1991 as part of a short-term strategy to reduce administrative costs. Until then, HCFA had

concerned itself solely with automating claims. In

1991, however, the agency turned its attention to

automating the remittance advice document,

which accompanies a claim payment and explains

what the payment covers. Rather than develop its

own remittance format, HCFA adopted the EDI

format for health care remittance advices that had

just been approved by Accredited Standards Committee X12. HCFA became the first organization

to test the new EDI remittance advice format and

remains its largest user.

In 1992, HCFA established a uniform payment

policy and procedures for making electronic payments to medical providers for Medicare claims.

Providers who submit at least 90 percent of their

Medicare claims electronically can receive claims

payments electronically through the banking industry’s automated clearinghouse network and

their local banks, rather than through paper checks

mailed to their offices. HCFA again had a faster

payment incentive to encourage electronic claims

submissions. Since then, HCFA has adopted the

EDI-based claims form as its standard and mandated that all Medicare processors adopt it by July

1, 1996. The agency’s long-term goal is to have all

Medicare claims handled electronically by the

year 2000.

Private Insurers

Because many Medicare beneficiaries also carry

private insurance policies that cover deductibles

and copayment obligations under Medicare,

HCFA’s EDI projects also affect the administration of payments by private insurers. In many

states, the fiscal intermediary for the Medicare

program obtains its own private insurance claims

electronically through the same linkages used for

Medicare. With Medicare moving toward 100 percent electronic claim submission, “it seems likely

that private firms will be making use of the

technology as well.”12

Some large insurers accept and process nearly

80 percent of claims by computer.13 However,

there are many small insurers that are only beginning to accept electronic claims. Today, about 75

percent of hospital claims are submitted electroni11 M. Buffington, Director of Claims Processing, Health Care Financing Administration, personal communication, Sept. 7, 1994.

12 D. Fularczyk, Manager, Blue Cross and Blue Shield United of Wisconsin’s Proservices subsidiary, quoted in T. Higgins, “Setting Standard for Electronic Claims Could Lead to Paperless Providers,” The Business Journal-Milwaukee, February 1993, pp. S3-S5.

13 B. Politzer, “Claims of Excellence,” HMO Magazine, vol. 32, No. 6, November-December 1991, p. 39.
Chapter 3 Networks for Health Information | 91

cally, but the vast majority of these are Medicare

claims submitted to HCFA rather than to private

insurers. Physicians submit some 16 percent of

their claims electronically in total; however, they

submit 47 percent of their Medicare claims electronically.14

Electronic Medical Claims Services

One of the difficulties of connecting providers and

payers is the different data and networking formats that exist in the health care industry. Conventional wisdom, for instance, holds that electronic

claims are structured in some 400 different ways.

Electronic medical claims companies, including

value-added networks and clearinghouses, provide services that connect providers with many

payers using a single system.15

These services give providers a single point of

electronic contact to many payers. In addition to

routing information between a provider and its

payers, they edit and reformat claims data. This

frees providers from the burden of programming

their systems to handle the wide variety of electronic formats. For example, a physician’s office

wanting to send claims electronically generally

uses personal computer software that communicates with the service via telephone lines. Physicians using practice management systems can

often integrate this software with their systems.

This requires that the processing service cooperate

with the vendor of the practice management system (there are several hundred in the country) to

write the necessary interfaces. For physicians who

do not use practice management systems, the service provides software that allows clerical personnel to enter claims data directly into forms that

appear on a PC screen.

Provider-specific edits are needed on each

claim. Because health care claims are not universally standardized, different payers require data to

be presented differently in their claims. One payer

may also require data that another payer does not.

The software checks the claims that are keyed in or

received from a practice management system to

make sure they conform to the data requirements

of the designated payer.

If the claims meet all requirements, the PC software sends them to the electronic claims service.

The service performs further editing and then

transmits the claims to payers, in some cases

through direct network connections to the payer

and in others through a claims clearinghouse that

has such a connection.

Many electronic medical claims services can

perform some or all of the following transaction

types: electronic claims filing; claims-status inquiry and online claims correction; eligibility and

benefits inquiry; electronic remittance advice

data; automated electronic remittance posting,

along with supplemental and secondary billing;

and electronic funds transfer. The services available to a provider vary by payer and depend on

payer capabilities. Not all payers, for instance, can

provide remittance advice data electronically.

Most of the transactions processed by electronic medical claims services are currently not based

on EDI standards, particularly the nonclaims

transactions. However, use of standard EDI

claims may increase as HCFA mandates them.

Until then, however, many payers are not accepting standard EDI claims. Nonclaims transactions,

such as eligibility verification, are not based on

EDI standards because the standards are either

brand new or do not exist. Many of these services

intend to support EDI standards, but place more

emphasis on making transactions electronically,

whatever the format. They believe that it is better

to begin electronic processing now than to wait for

the often slow standards-development cycle.

The initial cost of getting a physician started

with an electronic claims service is between

$1,500 and $2,500, depending on the size of the

14 “Automated Medical Payments Statistical Overview,” Automated Medical Payments News, Feb. 8, 1993, p. 3.

15 B. Dodge, Vice President, HCS, Inc., personal communication, Aug. 26, 1994.
92 | Bringing Health Care Online: The Role of Information Technologies

practice. Staff training may be an additional expense. There is also a per-transaction fee, which

could be on the order of $0.35 to $0.85, depending

on the type of transaction. Claims fall toward the

upper end of the range because they are more complex documents and contain more data, while

transactions such as eligibility inquiries cost

less.16

In the early years of EDI development in other

industries, value-added networks (VANs) offered

similar translation services for companies that did

not want to develop or install their own EDI management systems. Over time, companies purchased their own EDI systems, rather than pay

translation fees to the VANs. A similar development is unlikely in health care. Only larger institutions are likely to have the financial and staff

resources to manage an EDI system. For smaller

medical practices, claims services and VANs may

continue to provide a way to transact business

electronically.

Financial Institutions

Completely automating the health care payment

process means involving the trading partners’ financial institutions. In the 1970s, the banking industry established its own formats for electronic

funds transfer (EFT) through the National Automated Clearing House Association (NACHA).

NACHA governs the automated clearinghouse

(ACH), a network of computer-based check-clearing and settlement facilities for the interchange of

electronic debits and credits among financial

institutions (note that bank clearinghouses are different entities from the insurance clearinghouses

mentioned above).

The banking industry designed its original EFT

formats to move money between financial institutions. In the 1980s, NACHA worked with corporations to set ACH formats for corporate-tocorporate payments. At that point, the NACHA

formats for EFT began to conflict with, and then

migrate toward, industry’s formats for EDI. The

hybrid of EFT, whose purpose is to move money

between financial institutions electronically, and

EDI, whose purpose is to move business data between corporations electronically, became known

as financial EDI (or EFT/EDI).

Since the development of financial EDI formats in the mid 1980s, the number of corporations

using the ACH to make payments has steadily risen, showing an average annual growth of between

25 and 30 percent per year for the past several

years. In terms of total payment volume, however,

financial EDI volume statistics are less impressive. Last year, the estimated 13 million payments

made through financial EDI represented only

about 0.1 percent of the total estimated volume of

11.7 billion payments.17

Financial EDI payments, in all industries, consist of two parts: the payment and the remittance

advice. One difficulty faced by the banking industry is that few banks are capable of processing all

of the information contained in financial EDI payments. ACH formats themselves are not compatible with the information-laden EDI formats. To

move native EDI data through the ACH requires

wrapping an EDI transaction in a NACHA envelope. The financial institution then unwraps and

processes the EDI payment transaction. The enveloping process puts some limitations on the

amount of data an EDI transaction can carry—a

potential problem given the amount of data in a

health care remittance advice document.

As a result, many companies are sending EDI

payment orders and remittance advices through

separate paths—the payment itself as a simple

EFT transfer through the ACH and the remittance

advice as an EDI transmission through a VAN. In

that case, companies receive the payment-deposit

information from their banks and reconcile it with

the remittance data received from the VAN.

However, some banks that specialize in financial EDI are moving into the health care market.

16 Ibid.

17 National Automated Clearing House Association figures reported in Canright, op. cit., footnote 9.
Chapter 3 Networks for Health Information | 93

BankAmerica, San Francisco, CA; Chase Manhattan, New York, NY; Huntington Bancshares,

Columbus, OH; PNC Bank Corp., Pittsburgh, PA;

and National City Corp., Cleveland, OH, are

among the national and regional banks that now

process medical bill payments electronically for

hospitals, clinics, and other health care providers

who are their banking customers. Some of them,

in addition to handling EFT payments, are also offering the services of a processing service.

❚ Standardized Forms

The federal government has played a major role in

standardizing electronic forms in the health care

industry. For instance, institutional providers are

encouraged to submit Medicare and Medicaid

claims using the UB-92 form, which was created

by the National Uniform Billing Committee

(NUBC). The difficulty is that each state adds its

own requirements to the UB-92 form, which

means that some payers and nearly all software

vendors have to support nearly 50 different versions of the UB-92.18 Moreover, the EDI standard

for transmitting claims, ASC X12.837 (health

care claim), can structure data contained in the

UB-92 in several different ways, all of which are

correct insofar as the standard is concerned.19 The

result is that the health care industry’s standards

are not yet standard enough for easy implementation of electronic commerce.

HCFA has developed implementation guides

for health care claim and remittance advice transactions. By July 1, 1996, all electronic claims will

be submitted to HCFA using the standard forms.20

The HCFA requirement is expected to stimulate

EDI use throughout the industry. To ensure that

the health care industry uses a single EDI version

of the UB-92, the Workgroup for Electronic Data

Interchange (WEDI) and the NUBC are developing EDI implementation guidelines based on the

HCFA guide, which is becoming the de facto industry standard.

LINKING HEALTH CARE PROVIDERS

WITH SUPPLIERS21

In contrast with health care payments, the use of

electronic commerce between large health care

providers and hospital suppliers has a longer history, dating back to the mid-1970s when the

American Hospital Supply Corp. (AHSC)

introduced the first electronic order-entry (EOE)

system called Analytic Systems Automated Purchasing (ASAP). ASAP initially allowed hospitals to place orders using a touch-tone telephone.

As ASAP evolved, hospital purchasing managers

could enter orders into terminals connected to

AHSC’s mainframe computer, which automatically reserved inventory and generated a packing

list. The system was so convenient that purchasing managers placed orders with AHSC at the expense of its competitors.22 Hospitals achieved

benefits by: 1) eliminating manual order writing;

2) reducing transcription errors that result when

orders are written manually or taken over the

phone; and 3) increasing the accuracy and timeliness of order, delivery, and cost information.

The proliferation of other EOE systems became

a problem to major hospitals, especially chains

and large purchasing groups. Those organizations

purchased supplies from several vendors, which

meant they had to use several different EOE systems. They faced the same problems that have led

to the development of EDI in other industries:

higher costs from having to support multiple pro18 D. Rode, “UB-92, HCFA 1500: The Genesis of EDI?” Health Care Financial Management, vol. 47, No. 1, January 1993, pp. 82-83.

19 D. Hodges, Integrating Computer-Based Technologies Into HMOs (Washington, DC: Group Health Association of America, Inc., 1993),

p. 41.

20 M. Buffington, op. cit., footnote 11.

21 This section is based on Canright, op. cit., footnote 9.

22 R. Forester, “A History of ASAP at Baxter Health Care: The Journey from Proprietary to X12 Standards,” EDI Forum, vol. 4, No. 1, 1991,

p. 96. (Baxter acquired the ASAP system when it merged with American Hospital Supply Corp. in 1984.)
94 | Bringing Health Care Online: The Role of Information Technologies

prietary systems,23 including additional space for

the terminals and additional training for purchasing personnel. Today, most hospital-supply companies are making a transition to EDI and offer

EDI-based alternatives to their proprietary electronic order-entry systems.

In addition to the companies that directly supply hospitals and other providers, the companies

that manufacture health care supplies and equipment are beginning to use EDI to connect with the

smaller companies that they rely on to distribute

their products to hospitals, physicians, and other

health care providers. For the manufacturers, EDI

connections result in cost savings because they no

longer need to key purchasing information into

their systems. By automating business with all

their distributors, the relatively small benefits that

come from automating each trading relationship

are multiplied over a large base. For distributors, it

is not clear whether the conversion to EDI results

in net savings or net costs.

When the process of purchasing and paying for

supplies is automated through EDI, it can be integrated with a larger automated materials management information system that can include

inventory control, automatic replenishment,

tracking of chargeable suppliers and equipment,

invoicing, and patient cost accounting. Greater

use of information systems for these purposes has

been shown to improve inventory control and reduce the costs of materials management in other

industries. Currently, only a few hospitals and

health care groups are using this technology to its

full potential.24

The movement to electronic systems in hospital materials management has not been pervasive

among hospitals. By 1990, hospitals used EDI to

place some 24 percent of orders to suppliers.25

Purchase orders and confirmations still represent

the bulk of EDI transactions in hospitals; hospitals

have been slow to use EDI for other purchasing

functions, such as electronic invoicing and payment.26 WEDI, for instance, estimated that some

6,000 of 6,138 acute care hospitals require EDI

upgrades.27

Overall, the health care supply portion of the

health care industry has made a good start in automating trading relationships. As suppliers offer

and providers adopt more sophisticated materialsmanagement strategies, EDI will become increasingly necessary as well as commonplace.

PHARMACEUTICAL INDUSTRY EDI

The drug distribution chain has been an early and

successful adopter of electronic commerce. As

early as 1972, a major drug wholesaler began a pilot project to transmit purchase orders directly to

the computers of major manufacturers. Industry

organizations, such as the National Wholesale

Druggists Association and the American Surgical

Trade Association, actively supported these activities and encouraged the development of industry-wide standards. Use of electronic ordering was

found to reduce order lead-times, which reduced

inventory requirements. Some industry analysts

believe that adopting electronic ordering is a major factor in alleviating and reversing economic

23 The terms “proprietary system” and “proprietary data format” refer to electronic business communications systems that work for a single

company—the one that provided the system or software. The terms “standard system” or “standard data format,” in contrast, refer to EDI systems that are designed to ease communications with any organization that supports EDI standards.

24 ECRI, “Computer Information Systems, Materials Management,” ECRI Special Reports, 202765 424-008 (Butler Meeting, PA: 1995),

p. 3.

25 Arthur Andersen & Co., Stockless Materials Management: How It Fits Into the Health Care Cost Puzzle (Alexandria, VA: HIDA Educational Foundation, 1990), p. 56.

26 J.J. Moynihan and K. Norman, “Health Care EDI: An Overview,” EDI Forum, vol. 6, No. 2, 1993, p. 11.

27 Workgroup for Electronic Data Interchange, Report (Hartford, CT, and Chicago, IL: October 1993), p. 9-34.
Chapter 3 Networks for Health Information | 95

hardships that drug wholesalers had been experiencing in the early 1980s.28 By 1986, 96 percent

of drug wholesalers were using EDI, as were 90

percent of pharmaceutical manufacturers—one of

the highest penetration rates of any industry at that

time.

Today, electronic commerce has also expanded

rapidly to independent drugstores and drug

chains. About 95 percent of drugstores are computerized. Many of them order from distributors

using either proprietary systems or EDI standards

and guidelines developed by the American Society of Automation in Pharmacy.

Because many prescription drugs are paid for

or reimbursed by insurance plans, electronic links

have also been established between pharmacies

and payers. A standard format for communication

between pharmacies and insurers is in widespread

use. Online eligibility systems have helped to

speed processing and payments by enabling pharmacies to check a patient’s benefits before filling

the prescription. After a physician or patient submits a prescription (either by phone or in writing),

the pharmacy enters the information from the patient’s prescription benefit card (issued by the insurer, health plan, or employer) and the

information from the prescription into an online

system using the National Counter Prescription

Drug Plan’s (NCPDP) standards for real-time

transactions. Through this system, the pharmacy

contacts a database where it can confirm the patient’s eligibility status, find out whether the payer

will pay for this drug, determine the copayment

amount, and ascertain whether the payer allows or

requires generic substitutions.

Pharmacy claims are much less complex than

other health care claims, and a much larger percentage of them are submitted electronically. In

1993, over half of the prescription claims reimbursed by insurance payers were submitted electronically and that percentage continues to

grow.29 NCPDP recently introduced a paperbased claim form based on the electronic format to

simplify reimbursement for patients whose payers

are not yet using electronic pharmacy claim submission.30

The existence of large databases of prescription-related information in a standard format is offering new tools to both the pharmaceutical and

insurance industries. Databases are being used to

analyze the patterns of drug purchase, to develop

formularies or lists of preferred drugs, to compare

costs of alternative drugs, and to compare the costeffectiveness of drugs to alternative treatments.

COMMUNITY AND REGIONAL

NETWORKING

❚ Community Health Information

Networks

A community health information network (CHIN)

can be either a proper or a generic name for a type

of information system that is still undergoing development and definition. Another term used is

community health management information system (CHMIS), which can also be both a common

or proper name. Both of these networks are envisioned as systems that allow the seamless exchange of clinical or administrative information

among health care providers, payers, and other authorized users. Currently, there are between 75

and 100 community networks in early stages of

startup or implementation that roughly correspond to the CHIN or CHMIS descriptions below.31 (This report will use the term CHIN as

generic and will use CHMIS only when distinguishing features of the CHMIS model).

28 P.K. Sokol, From EDI to Electronic Commerce (New York, NY: McGraw-Hill, Inc., 1995), pp. 212-219.

29 Ibid.

30 G. Muirhead, “Stake Your Rx Claim: NCPDP Issues Standard Paper Form for Reimbursement,” Drug Topics, Nov. 7, 1994, p. 106.

31 R. T. Wakerly, remarks at CHINs and CHMISs: Networks for Community Health Information and Management, meeting of the National

Health Policy Forum, Washington, DC, Oct. 25, 1994.
96 I Bringing Health Care Online: The Role of Information Technologies

Small clinics and individual health care providers are

beginning to use computer-based systems for practice

management, recordkeeping, and communication with

laboratories, hospitals, and insurers.

At their most basic, CHINs are electronic systems whereby claims filing, eligibility verification, and other transactions can be performed by a

provider (whether a single physician or a major

health care organization) and an insurance clearinghouse; or whereby a physician’s office can contact a hospital’s information system to obtain

clinical or administrative information on a patient.

However, CHIN developers envision them as expanding into systems that link all participants in

the health care system—providers, payers, banks,

pharmacies, public health agencies, employers,

and others. Moreover, a fully developed CHIN

might allow a physician to assemble a single patient’s information across different institutions

and databases to produce a complete medical record; or it could permit a researcher to aggregate

the data for many patients to compare performance of different plans and providers. In future,

CHINs might also be a means for sharing access to

medical knowledge, remote diagnostic applications, and expert advice based on outcome and effectiveness analyses.32

The difference between a CHIN and a CHMIS

is primarily one of initial priorities. All of these

systems start with some initial features and services and add others as they grow. CHINs, for the

most part, were developed to provide connectivity

and transport of data among the users. Some of

them are concentrating first on linking physicians

and clinics with hospitals and labs to access clinical data, and secondarily are providing claim filing and other insurance-related services. Some

CHINs have a long-term goal of building a community-wide data repository for outcomes research and for comparing the performance of

plans and providers, but they have not yet started

that phase of their development. Other CHINs

have no plans for building a centralized data repository, but envision that the standardization

they provide will eventually allow authorized users to transparently aggregate data across many

databases, thus accomplishing the same purpose.

CHMISs, on the other hand, have started with

the concept of building a data repository for use in

assessing the performance of health care providers

and plans. Collection and analysis of management

information is a priority. Although there is variation among the CHMISs started so far, most are

focusing on providing insurance transaction services (that is, connectivity and services linking

providers and payers) and on capturing data from

those transactions into the data repository. Services linking providers with providers to exchange clinical data are also planned in ‘many

cases.

Issues associated with CHINs include ownership and control, and network design and data

management.

■ Ownership and Control

There are several possible ownership models for

CHINs. One is a joint venture between a health

care provider and an information system vendor.

This is likely to be a for-profit organization, offering community-wide service, with the goal of providing easier communications among the various

32 D.L. Zimmerman, CHINs and CHMISs: Networks for Community Health Information and Management. Issue Brief No. 657 (Washington, DC: National Health Policy Forum, 1994).
Chapter 3 Networks for Health Information | 97

users. The vendor may first implement services

for the partner or lead sponsor and then attempt to

contract with other users based on demonstrations

of the usefulness of the service. An example of

this ownership model is the Wisconsin Health Information Network (WHIN), developed by Aurora Health Care Corp. and Ameritech Health

Connections (a subsidiary of Ameritech, the regional telephone provider). Initially, WHIN provided physicians with access to laboratory results,

patient census data, and other information in the

databases of the hospitals where they are affiliated. In addition, the network now offers an electronic claims service for filing claims and

performing some other insurance transactions.

Besides the Aurora-owned hospitals, 11 other

hospitals and their affiliated physicians are now

on the system. One difficulty with this ownership

model is that the system may be viewed with some

suspicion by competing hospitals who may worry

that the provider that owns the system is giving itself some advantage. Even in cases where a vendor is sole owner, late adopters may view the

system as “belonging” to the early adopters. There

are 45 to 50 communities with vendor-owned

CHINs.

An alternative model used by some CHINs is to

form an understanding among a broad group of

potential users before the system is built and

create an ownership structure that will be viewed

as more neutral by all participants. Although their

organization varies, systems under development

in Vermont, New York, Washington State, Chicago, Cincinnati, and other locations have attempted

to develop a broad coalition of community

groups—providers, payers, and employers—before the network is built. These groups then jointly

sponsor the creation of a not-for-profit organization to operate the system. This model also has

difficulties. Developing community consensus

about the goals and operation of the system can

take a great deal of time, so systems opting for this

model come to market much more slowly. Agreements between stakeholder groups may become

fragile when it becomes necessary for participants

to actually commit money to the major project. It

is not yet clear who should make the biggest investments in community networks because no one

knows who will accrue the most benefit from

them.

Other ownership patterns, including variations

and hybrids of the above, ownership by a consortium of vendors, or ownership by a state or local

government agency, are possible, and are being

tried in some locations.33

❚ Network Design and Data Management

CHINs vary widely in their approach to the function of the network, the content of the information

carried on it, and the standards to be used by or imposed on participants. One basic decision facing

all CHINs is whether or not the network will

maintain a central database of health information.

Although creating a central repository is a fundamental goal of some networks, others have actively rejected the idea and use the fact that each

participant maintains its own proprietary data as a

selling point.

Technology decisions related to designing a

CHIN are complex because their goal is to bring

together a diverse set of information suppliers and

users who are operating incompatible systems.

The network must establish “rules of the road” so

that participants can share information usefully.

This means standardizing formats for data content

and structure and creating interfaces so that different computers and different people can use them.

In the absence of clear national standards, different CHINs are developing their own ways of doing this.

Figure 3-3 outlines the high-level architecture

of a CHIN. The network must interact with a variety of different application systems in the participants’ information systems. For the most part,

network participants will not be willing or able to

33 Ibid.
98 I Bringing Health Care Online: The Role of Information Technologies

Admission, discharge,

and transfer

Laboratory

CHIN

Radiology gateway

Pharmacy

Other

Hospital

<-- ‘

--

Membership

--->

CHIN Claims system

gateway

Other

L

Payer

(Optional)

CHIN host system—

Switch functions Support functions

Help desk

Session management Reporting

I

I

Community

Database

Patient data

Payer data

Provider data

Employer data

Medical costs

I

CHIN user interface CHIN user/host interfaces CHIN host interfaces

Financial Medical journals

Physician’s office Clinic Medical information service

SOURCE: M R Gorsage and J W Hoben, “Technological Implications of CHINS, ” in R T Wakerly (ed.), Community Health Information Networks,

Creating the Health Care Data Highway (Chicago, IL American Hospital Publishing, Inc.,1994), pp.115-140
Chapter 3 Networks for HeaIth Information 199

change their own operations substantially in order

to participate, so the network must develop interfaces to diverse systems as well as gateways

(sometimes called application interface gateways

or translators) to convert messages from one standard to another (e.g., from a proprietary system to

HL7 or to a standard EDI format). The network

provides a number of value-added services to participants, including switching functions like routing (delivering data between trading partners),

security (maintaining passwords and access controls; encryption), session management (e.g.,

creating audit trails), and messaging (harmonizing disparate e-mail systems and providing access

to external databases or networks). Generally the

network also provides support functions for user

organizations, including a help desk and billing

and administrative information on system use.

User interface and point-of-service mechanisms, such as card readers and other devices, can

provide access to the network and initiate transactions. For example, scanning a patient’s identification card can initiate a verification of the

patient’s eligibility for benefits. For more information on cards as access and identification devices, see box 3-4.

User interfaces can be customized to allow each

user to see data in the form that is most convenient

for that user, as shown in figure 3-4. When a physician’s office contacts different hospitals for patient information, the user will see the information

in that office preferred format, despite the differences in hospital information systems. Similarly,

any data from the hospital that need to be downloaded into the physician’s practice management

system are formatted to be acceptable to that sysSmart cards, magnetic stripe cards, and other small portable devices may offer a low-cost way to

store and transfer electronic health information. Cards can be used as identification and authorization

tools or as actual storage media. Cards currently play a role in the health care system, predominantly as

a means of patient identification and association with a particular health plan.

Types of cards include:

■

in

■

●

Paper cards, usually with printed data and perhaps with a barcode or magnetic stripe; these are usually issued by health plans as a means of identification.

Magnetic stripe cards, such as those widely used in the financial industry (e.g., credit and automated

teller machine—ATM—cards). The magnetic stripe on the back can carry a limited amount of information—226 characters in the case of a typical three-track card. They are typically used with online systems for accessing a database.

Smart cards have an integrated circuit chip with a range of capabilities. They can support security

features such as encryption and differential access for different parts of the card. They can be used

to interact with online systems or to store varying amounts of data; the typical 24-kilobit card stores

one full page of text. A backup copy of stored data may be kept on a provider’s computer to protect

against loss.

Laser optical cards carry a wide stripe on the back that contains information that is “burned” into the

card with a laser. Once written, data cannot be modified, although new data can be added to some

types of laser optical cards. They can carry 2.5 megabytes of digital information (about 1,200 pages

of text). They typically do not have security features unless an integrated circuit chip is added to the

card for this purpose.

(continued)
100 I Bringing Health Care Online: The Role of Information Technologies

In the health care system, cards could be used to: streamline various administrative functions (e.g.,

claims processing); automate functions that tend to be repetitive in nature (e.g., filling out medical history forms); and improve the quality of care by reducing the likelihood of duplicative testing or possible

drug interactions. Potential applications of card technology include:

■ Patient Identification, enrollment verification, and eligibility verification

■ Emergency Information

■ Payments and claim processing

■ Prescriptions

■ Medical history

Magnetic stripe cards have wide use in health care in the United States, perhaps because of the

large installed base of cards and card readers already in use by the financial industry and the public’s

familiarity with these cards. A number of U.S. health plans use plastic magnetic stripe cards, and at

least 22 states use them to identify people eligible for Medicaid benefits. The patient presents the card

when entering the hospital, provider’s office, or other location. When the card is scanned, Information

that already exists about the patient can be linked with newly entered data in an automated fashion.

Eligibility for service, the amount of the copayment, and other payment reformation can also be obtained quickly so that accounts can be settled before the patient leaves. Although magnetic stripe

cards carry only a small amount of information, they are useful as access devices to Iink with the provider’s or payer’s online databases, and the U.S. telecommunications infrastructure is adequate to provide these linkages in almost any location.

A number of health plans in the United States are testing the use of smart cards. Currently, standards for the data format, encryption, and security features are only beginning to emerge. This means

that cards are only being used within closed systems. The Department of Defense is conducting a multimedia (magnetic stripe, bar code, integrated circuit chip, and photograph) identification card pilot

program, which wiII test the viability of deploying smart cards for multifunctional purposes with a primary focus on health care. Canada, Great Britain, and Japan are also looking into smart cards for health

care informatlon.

Smart cards are used more widely in Europe than in the United States, but even in Europe, their use

in health care is primarily for identification and for limited amounts of clinical and administrate information. In Germany, smart cards generally contain only administrative information. In France, cards typically contain some clinical information, but there is no attempt to store a complete medical record; rather, basic information is placed on the card and may be accessed by providers or pharmacies to reduce

errors or to speed data processing. The storage capacity of many cards currently in use is usually not

sufficient to maintain a complete medical history, although higher capacity cards are becoming available. Widespread use of portable electronic patient records in card form wiII depend on the availability

of standardized patient record systems in the computers of all providers who will interact with and update the cards. Such systems are not currently available in Europe or the United States.

Laser optical cards are still an emerging technology and are not widely used. In one pilot project, the

Texas Department of Human Resources has issued 2,500 cards containing demographic information

and Immunization records. Equipment to read the cards is available at only a few locations, but the

project is expected to expand. Experiments with laser optical health cards are also under way in Scotland.

SOURCE: Adapted from Phoenix Planning and Evaluation, Ltd , “Potential Card Applications in the Health Care Industry, ” unpublished contractor report prepared for the Off Ice of Technology Assessment, January 1994
Chapter 3 Networks for Health Information 101

Ourtown General Hospital

information system

Ourtown General Hospital

Admission/discharge/transfer (ADT)

Name ID

Option:

1. Review

2. Register

3. Reports

PC in hospital department

General Hospital ADT

PC in physician’s office

Note Common user systems sign-on allows for a custom screen (regardless of application) for users according to their profiles

SOURCE Adapted from M R Gorsage and J W Hoben, “Technological Implications of CHINS, ” in R.T. Wakerly (ed.), Community Health Information

Networks: Creating the Health Care Data Highway (Chicago, IL American Hospital Publishing, Inc., 1994), pp. 115-140

tern. The network system maintains a profile of

each user and the way that information must be

presented. Similarly, data for claims filing or other

transactions can be entered by the physician’s office in a single format, regardless of payer. The

network, through the application integration gateway function, can then take responsibility for

translating or reformatting the information to suit

the requirements of each payer. This approach

should reduce a participant’s training costs because employees only have to learn one set of

menus and navigational tools.

While the user’s view of data appears integrated through the use of common user interface

mechanisms, actually integrating data across multiple databases is another problem entirely.

CHINs that include a central data repository are

addressing this problem now. A repository is a

“central database populated by transactions from

several disparate departmental and organizational

systems.” 34 The repository contains copies o f

transaction data carried out by various trading

partners; it is not the original or sole source of information. Management of information from disparate sources can be a complex task:

To ensure data integrity, the [application integration gateway] should have data audit and

control mechanisms to synchronize replicated

data with its various storage locations. The task

of determining which transaction system is the

34 M.R. Gorsage and J.W. Hoben, “Technological Implications of CHINs," in R. T. Wakerly (cd.), Community Health Information Networks: Creating the Health Care Data Highway (Chicago, IL: American Hospital Publishing, Inc., 1994), pp. 115-140.
102 | Bringing Health Care Online: The Role of Information Technologies

Note: Systems on the CHIN with their own repositories will require an intelligent gateway to match field names with data

SOURCE. M R. Gorsage and J.W. Hoben, “Technological Implications of CHINS, ” in R.T. Wakerly (ed.), Community

Health Information Networks: Creating the Health Care Data Highway (Chicago, IL: American Hospital Publishing, Inc ,

1994), pp. 115-140,

master or owner of specific data elements is diplomatic and political rather than technological.35

Through use of a common data model, the repository can be mapped onto the various systems of

record. Data for different entities can be tied together by using unique identifiers for patients,

payers, sites, providers, and other entities.

In time, a central repository containing both

clinical and administrative information could become too large to manage efficiently, especially if

it includes diagnostic images. An alternative approach to managing community-wide information is to maintain an intelligent central repository

that manages a federation of independent databases. All databases would share a common global model, and the central repository would contain

not copies of the transactions, but information on

where to find the information. This metatransaction (transactions about transactions) repository

would then contact the individual databases to

collect information needed by an authorized user,

and would have the knowledge needed for resolving any differences between the databases. This

concept is illustrated in figure 3-5.

■ Community Networks and Enterprise

Networks

There is uncertainty about the role of CHINs as

managed care organizations and integrated delivery systems (IDSS) begin to dominate health care

35 Ibid.
Chapter 3 Networks for Health Information | 103

delivery. CHIN development takes time and, in

the meantime, some IDSs may build their own

proprietary enterprise-wide networks. IDSs will

carry out most of their data communication on their

own enterprise networks because many of their

administrative functions will be internal, and they

may not need to join a community-wide network.

There are two schools of thought on the possible interactions of CHINs and IDS networks.

One holds that IDSs have no need for CHINs, and

that CHINs are a short-term or limited phenomenon that will fade as markets become dominated

by two or three competing managed care organizations. Because the IDSs are competitors, they will

have no incentive to share information, and thus

connectivity between them will not be needed.

The other school of thought says that IDSs need

CHINs because even in a managed care environment there will still be out-of-plan referrals, providers with multiple affiliations, and mobility of

providers and patients among plans. In order to be

totally electronic in processing administrative information, IDSs will need access to a communitywide or regional network infrastructure. Further,

even though IDSs will want to keep private their

own data on outcomes, utilization, and costs, it is

likely that large purchasers of health care (and perhaps regulatory agencies) will insist on seeing at

least some of this information on a communitywide basis, and CHINs will offer a mechanism.36

There is even the view that some IDSs will eventually become CHINs, perhaps setting up subsidiaries to offer CHIN services to their competitors

and unaffiliated providers in their communities.37

❚ Networking and Public Health

The usefulness of community and regional networks increases if they are also able to interact

with public health agencies at the local, state, or

federal levels. The Department of Health and Human Services has been tasked by the Administration to act as the lead agency in coordinating

federal government activities related to health information systems.38 Among the long-term goals

to be pursued is the creation of a national forum for

collaboration on standards development for

health information. Health information networks,

automated payment systems, and other systems

are part of the national information infrastructure

(NII) where public- and private-sector activities

need to be coordinated.

The Public Health Practice Program Office at

the Centers for Disease Control (CDC) is developing an Information Network for Public Health Officials (INPHO) that provides state and local

public health officials with access to timely information on disease prevention and health

promotion, including: 1) local and national disease and injury rates and associated risk factors

and prevention measures; 2) preventive health

data, guidelines, regulations, training materials,

and emergency notices; and 3) reports of epidemiological investigations. The system will initially employ CDC’s personal computer software

(WONDER) as well as voice and fax technologies, but will eventually use Internet tools. It will

provide an electronic mail service for federal,

state, and local public health officials, starting

with local area networks and building toward

wide area networks. The INPHO system is being

pilot-tested in Georgia through a $5.2 million

grant from the Robert W. Woodruff Foundation to

Emory University in Atlanta, teamed with several

other academic and state government organizations in Georgia.

COSTS AND COST-EFFECTIVENESS

❚ System Costs

High system costs often pose a barrier for a business wanting to embrace EDI. Hardware, soft36 F. Bazzoli, “Will CHINs Be Able To Mesh with Enterprise Networks?” Health Data Management, March 1995, pp. 47-52.

37 R.T. Wakerly, “Models of CHIN Ownership,” in Wakerly, op cit., footnote 34, pp. 53-71.

38 A. Gore, Vice President, Washington, DC, memorandum to D. Shalala, Secretary of Health and Human Services, Washington, DC, Mar. 8,

1995.
104 | Bringing Health Care Online: The Role of Information Technologies

ware, installation, and staff training are all

expensive. If an organization opts to work through

an electronic claims company or a VAN, it must

pay per-transaction charges. If it creates a direct

line to its trading partners, it will incur costs for

network setup and telecommunications equipment. Staff will be required to manage the system,

adapt it to changing standards, and act as a liaison

with new trading partners.

One estimate puts the total average, per-company EDI investment at between $200,000 and

$700,000.39 The lower figure is for a supplier

company, while the higher is for a large company

seeking to connect all its suppliers. For the health

care industry, WEDI estimates implementation

costs at $7,500 to $15,000 for individual professionals and $25,000 to $500,000 for institutions.40 Costs include hardware, software,

consulting, and VAN charges. Most companies do

not perform a break-even analysis, according to

the EDI Group, a firm that studies EDI use generally. Those that do, however, report that they reach

the break-even point within two years.41

There are relatively weak near-term incentives

for some users in the health care industry to assume the high initial costs of EDI. Although there

are promises of administrative savings, these will

be spread out among most sectors of the industry.

Further, it is likely that savings will not be fully

realized until all transactions are electronic. A

business that has some trading partners using EDI

and some using paper has the expense of maintaining both systems. This is often the case in health

care at this time.

❚ National Estimates of Administrative

Cost Savings

A number of key studies focus on national estimates of potential savings from using information

technology for health care administrative functions. These include studies by WEDI, the Tiber

Group, Arthur D. Little, Inc. (ADL), HCFA, and

Lewin-VHI.42 The findings of these studies are

summarized in table 3-1. It is important to note

that comparisons across studies should be made

with caution: the definitions used for the various

administrative transactions vary widely, as do the

methodologies for estimating costs and savings.

Still, it is instructive to examine the findings from

these studies in clarifying possible savings from

information technologies in health care.

The studies on national administrative savings

project that information technology applications

could save in the range of $5 billion to $36 billion

per year in total health costs, which translates into

approximately 0.5 to 3.6 percent of total national

health spending. The Tiber Group study (which

was commissioned as part of the WEDI Report)

attempted to differentiate the savings per transaction for payers and for providers. It found that the

greatest savings for both would be in the areas of

claims inquiry and claims submission—which are

very information-intensive. With the exception of

the ADL report (which included some clinical as

well as administrative functions), the magnitude

of the projected annual savings was quite similar

across studies.

There is some reason to believe that these estimates may be overly optimistic. For example, ex39 D. M. Ferguson and D. J. Masson, “The State of EDI in the U.S. in 1993,” EDI Forum, vol. 6, No. 4, 1993, p. 10.

40 R.L. Schaich, “Health Care Reform Costs and Benefits,” EDI World, vol. 3, No. 12, December 1993, p. 51.

41 Ibid.

42 WEDI estimates and Tiber Group estimates are reported in WEDI, op. cit., footnote 27; Arthur D. Little, Inc., Telecommunications: Can It

Help Solve America’s Health Care Problems? No. 91810-98 (Cambridge, MA: July 1992); U.S. Department of Health and Human Services,

Health Care Financing Administration, White Paper on Financial Implications of Information Technology, 1991; Lewin-VHI, Reducing Administrative Costs in a Pluralistic Delivery System, report prepared for the Healthcare Financial Management Association, Apr. 30, 1993).
Study Application/function Claims Enrollment Payment & Eligibility Claims Total

submission remittance inquiry net savings

Workgroup for Electronic Data $45 to$13 1 billion $21 to $43 billion $1 1 to $1 3 billion $25 to $ 49 billion $28 to $ 40 billion $42 billion

lnterchange (WEDI) annually

Key assumptions

1

2

3

A comprehensive, standardized Electronic

Data Interchange capability is established

throughout the health care system according

to an aggressive Implementation schedule

over the next three years

Standard formats wiII be adhered to very

soon

Employer automation costs only reflect the

costs required to automate the transfer of

enrollment data for companies with over 50

employees

4

5

6

annually annually annually annually (over SIX years)

For enrollment, 171,722 employers with more than 50 7. Implementation schedule assumes costs are amortized

employees wiII save 0.5 to 1.0 FTE or $12,000 to over three years

$24,000 per year, minus annual transaction costs of $78 - 30% implementation occurs in year 1

($1.50 times 52 transactions) - 70% Implementation occurs in year 2

-100 % Implementation occurs in year 3

For eligibility, there wiII be an elimination of nearly 6,000

institutions to maintain enrollment or eligibility lists supplied by payers

For payment and remittance, on average, there are 15

claims per remittance advice.

Sources: Previous WEDI findings, Health Care Financial Administration reports, A.D. Little report, Lewin-VHl report, proprietary data, and Tiber Group study, which was part of WEDI report

Tiber Group study

Key assumptions

1. Startup costs and fixed costs used in the 3

study were assumed to be sufficient for

100% EDI.

2. Surveys were completed by only 14 physicians, nine hospitals, and SIX payers There- 4

fore, the data are assumed to be externally

valid in order to project national savings

$064,$110

(savings per transaction for insurer, then hospital) (over 5 years)

Broad definitions for the applications (or transactions)

were necessary due to definitional issues at many demonstration sites

Even though price competition in the computer industry

is quite high, costs were held constant for the study

Source: Surveys at each of three demonstration sites.

Arthur D. Little $6 billion

annually

$36 billion

Key assumptions annually

1. The $30 billion in savings not due to claims 3 Implementation costs are not included in the economic model

submission wiII come from electronic management and transportation of patient information, including the use of home health

terminals to reduce discussions with providers; reduction in emergency room visits; early intervention: and Improved creation, transport, storage, and retrieval of computerbased patient records

2 Legal issues regarding liability wiII have

been resolved

Sources: Data were gathered from available research and pilot studies when available, otherwise determined by panel of experts at Arthur D Little.

(continued)
Study Application/function Claims Enrollment Payment & Eligibility Claims Total

submission — — remittance — inquiry —net savings —

Health Care Financing Administration $58 billion $04 billion $24 billion $0.8 billion $0.1 billion $436 to $74 billion

Key assumptions annually

1 For claims subbmission, payers and provld- 4

ers wiII each save 50 cents per claim for an

estimated three billion paper claims

5

2. For eligibility, assumed 75 million transac- tions and savings of $140 per transaction.

3 For claims inquiry, assumed provider savings would be one-half as much as payer

savings estimated by WEDI

Source: WEDI report provided most of the information

annually annually

Administrative costs assumed to be growing at the rate

of total health care expenditures

Each visit, test, or procedure performed by a provider IS

counted as a separate “claim “

annually annually (over SIX years)

Lewin-VHl $1,9 to $4.5 billion $2.6 to $52 billion

Key assumptions annually net in 1993

1 The entire medical bill (all tests and procedures) is counted as one claim.

2. For claims submission, providers will

save $1 30 per claim and payers will

save 60 cents per claim

Sources: Cost estimates from Congressional Budget Office and General Accounting Office, industry sources, including The Medical Group Management Association; calculations by LewinVHI experts

o

SOURCE. Project HOPE Center for Health Affairs, Bethesda, MD, “Estimating the Cost-Effectiveness of Selected Information Technology Applications,” unpublished contractor report prepared for the Office of Technology Assessment, U.S. Congress, Washington, DC, May 9, 1995.
Chapter 3 Networks for Health Information | 107

perts interviewed by OTA note that the

assumption by both WEDI and the Tiber Group

that EDI will be rapidly implemented by a high

percentage of providers and payers is unrealistic.

However, the WEDI Report’s other assumptions

on savings from specific administrative transactions, which were based on industry surveys and

case studies, seem to be more reasonable.43 Potential savings noted in the ADL report also seem

generous for a number of reasons. The report did

not include the costs of implementing new systems, for example. The authors defended this

omission by pointing to the variability of pricing,

and the fact that the cost of implementation would

be widely shared with other industry applications.

Another problem was that some of the categories

of cost savings were vague and the data used to

support the claims were not always well justified.

Finally, the results include some clinical applications as well as administrative applications, so

comparisons with other national estimates are difficult to make.

The HCFA results, which relied heavily on the

WEDI methodology, may also be optimistic for

reasons noted above. In addition, the report was

not explicit about how some of the calculations

were made. The Lewin-VHI report was also vague

about some of the assumptions underlying their

calculations.

Despite limitations, however, it is interesting to

note that the studies taken together suggest that information technology applications in health care

administration will produce important, but not inordinate, savings to the health care system. In light

of some claims made about the potential reduction

in administrative costs that would arise from information technology, the actual savings projected appear rather modest. This general

prediction seemed to be shared by experts interviewed by OTA. They also emphasized that the

fact that existing studies do not show large savings

does not diminish the potential importance of

technology applications in increasing system efficiencies (which may be difficult to capture in an

evaluation) or in improving patient care.

❚ Savings from Reducing Errors and

Detecting Fraud

Creating a health care bill or claim is a very complex process, and there are many opportunities for

unintentional error or deliberate fraud. An important part of developing the bill is to describe the

procedures performed for the patient. This information must be transferred from the patient record to the administrative system and, ultimately,

into the bill or claim. Many payers, including

HCFA, use one of several diagnostic and procedural coding languages, such as ICD-9-CM, as the

basis of their payment formula. Many providers

try to capture coding information as close to the

source as possible, for example, by listing the

code along with the procedure name on paper

forms physicians use for ordering tests and procedures, or by having a computer-based system automatically record the code whenever a procedure

is ordered by name. When diagnoses and procedures are not captured in coded form (e.g., if they

are written in free-hand notes), then trained coders

must read through the record to find information

to be put in the bill.

The coding systems are far from perfect. Decisions about which code to use are not always clear

and can be the subject of negotiation between

payer and provider while a complex claim is adjudicated. Misreading, miskeying, and other mistakes can cause bills to have incorrect codes. In

addition, some providers deliberately engage in

fraudulent practices such as upcoding (describing

the procedure performed with the code for a more

complex one) and unbundling (billing for two or

more procedures when a single comprehensive

code exists that describes the procedure performed) in an attempt to get a higher level of compensation from the payer.

A number of software products have been developed to check claims for inconsistent, erro43 Project HOPE Center for Health Affairs, op. cit., footnote 2.
108 | Bringing Health Care Online: The Role of Information Technologies

neous, or suspicious coding. Some payers have

their own proprietary systems to check claims before paying.44 In addition, a number of commercial products are available for payers, providers,

or other firms that prepare claims on a provider’s

behalf. Detecting obvious errors in bills saves providers the trouble and expense of submitting

claims that will be rejected; such software is

sometimes available in practice management systems and other administrative software for providers.

A recent study by the General Accounting Office (GAO) tested several commercial fraud-detecting software packages on samples of Medicare

claims and found them very effective in detecting

errors and flagging possible fraud. GAO suggested that use of such software could have saved

HCFA about $603 million in 1993 and $640 million in 1994. These savings, amounting to about

1.8 percent of Medicare reimbursements for supplies and services, are in line with the savings reported by private insurers using the same

software. GAO also notes that Medicare beneficiaries would have saved money as well—$134

million in 1993 and $142 million in 1994.45

❚ Economic Justification of CHINs

No one has demonstrated whether of not CHINs

are cost-effective. Those that exist have only been

in operation for a few years and their data have not

been publicly analyzed. However, the large investments made by vendors suggest that their own

proprietary estimates show a profitable future for

CHINs. On the other hand, a number of vendors

have dropped out of this market already. In addition to the large investments involved, many of

them have perceived the possibility, or experienced the reality, of failing to develop community

consensus about the role of the CHIN and services

that need to be provided. Even if a project is initiated by a vendor rather than a coalition of community groups, it is necessary to have the interest and

commitment of a minimum number of potential

customers from the relevant user groups; otherwise the project is too risky.46

The investment required to build a community

network is large. Estimates for WHIN suggest that

the partners invested $4 million to $6 million in

hardware, software, sales, and operations teams

before recouping any costs. Costs for WHIN subscribers depend on their size and the level of service they desire. A hospital might make a

one-time investment of $50,000 to $125,000 (depending on its current level of automation, the

number of custom interfaces that must be built,

etc.). Ongoing costs are determined by an algorithm that includes the number of physicians on

staff, number of beds, and annual patient visits.

Other ongoing costs include a per-transaction cost

for insurance transactions. Physicians’ offices pay

a $450 installation and training fee, an ongoing

charge of $30 per physician per month, and a pertransaction charge for insurance services.47

Projected savings from participating in WHIN

could be $750,000 to $1.5 million per year for a

300-bed hospital. The actual savings might depend on how effectively the hospital was using information technology and EDI before joining the

community network. Before implementing the

WHIN, the Aurora Health Care Corp. operated a

proprietary network for communicating with physician offices. That system had required a $1 million initial investment and operating costs of

$250,000 to $350,000 per year. Aurora estimates

44 J. Newall and B. Colbert, “Using Automated Bundling, Unbundling, and Rebundling Processes Before Paying Claims,” in Health Information Networks, proceedings of a conference sponsored by the Health Care and Insurance Institute, Sept. 28-29, 1993, Philadelphia, PA.

45 U.S. Congress, General Accounting Office, Medicare Claims: Commercial Technology Could Save Billions Lost to Billing Abuse, GAO/

IMD-95-135 (Washington, DC: May 1995).

46 J. Sanders, remarks at CHINs and CHMISs: Networks for Community Health Information and Management, meeting of the National

Health Policy Forum, Washington, DC, Oct. 25, 1994.

47 M. Radaj, Vice President, Operations, Wisconsin Health Information Network, personal communication, July 8, 1994.
Chapter 3 Networks for Health Information | 109

that participation in WHIN will provide greater

functionality for half that cost per year. Annual

savings for physicians’ practices might be in the

$2,500 to $5,000 range.48 WHIN is currently

working with the University of Wisconsin to conduct a cost-effectiveness study.

Cost savings to participants could accrue from

a CHIN’s ability to: 1) link participants; 2) deliver

management information at the point of service;

and 3) standardize electronic transactions. Linking participants electronically can reduce the need

for telephone calls, travel, postage, and use of delivery services. For example, enabling physicians

to check test results, sign attestations, or view

images online presumably saves professional

time by eliminating some trips to the hospital. Reducing phone calls can be difficult to quantify as a

cost savings, but many office administrators have

cited it as an immediate and welcome benefit of

online systems.

Delivering management information at the

point of service can facilitate the process of registering patients, checking their eligibility, and giving them care. Having management information

available before treatment begins can reduce the

number of rejected claims and other costs of working without complete information. In addition,

user software at the provider’s location can check

the accuracy of entered data (e.g., in claim filing)

and put data into a format preferred by the payer—

all before it leaves the provider’s premises. This

could reduce personnel and staff training costs for

both providers and payers, and reduce the costs of

correcting rejected claims for both providers and

payers. Of course, services like these do not necessarily have to be delivered over a communitywide network. A large number of insurance

clearinghouses and other electronic medical

claims services offer these services directly to providers. The possible advantage of a CHIN is to

combine both clinical and insurance information

processing in a single system

Community networks offer providers of all

sizes the opportunity to move toward more uniform, standardized electronic communication

without having the immediate need to change

their existing systems. More information can be

captured automatically and used in additional

ways, which should reduce costs to participants.

Use of common interfaces and elimination or

standardization of some key entry tasks (such as

filing insurance claims) could also reduce personnel and training costs.

POLICY IMPLICATIONS OF ELECTRONIC

HEALTH INFORMATION

Among the issues affecting the health care industry’s adoption of information technology are: 1)

industry fragmentation; 2) complexity of information needs; 3) standards; 4) standard identifiers; 5) an inconsistent legislative and policy

environment; and 6) privacy, confidentiality, and

security concerns.

❚ Industry Fragmentation49

The industries that have implemented electronic

commerce most completely have been led by a

single industry group devoted to implementing

data standards. Examples include the Transportation Data Coordinating Committee that developed EDI standards for the transportation industry

in the mid-1970s or the banking industry’s National Automated Clearinghouse Association.

The health care industry has no single focus for

EDI activities. WEDI believes that implementation has been hampered as a result and will not

proceed quickly unless a central entity is formed

to coordinate implementation and education.50

An even more critical factor, however, is the

fragmented nature of the health care industry in

48 Ibid.

49 This section is based on Canright, op. cit., footnote 9.

50 Workgroup for Electronic Data Interchange, op. cit., footnote 27, p. 1-9.
110 | Bringing Health Care Online: The Role of Information Technologies

general. In most industries where EDI has been

successful (e.g., utilities, banking, transportation,

and auto manufacturing), a few large organizations—called hubs in the language of electronic

commerce—made EDI an explicit requirement

for continuing a business relationship. Thus, for

the smaller spoke companies, the decision was not

whether to adopt EDI, but how quickly. One

health care EDI consultant describes health care in

the United States as a $900 billion “cottage industry.”51 There are over 1.2 million health care providers, ranging from single practitioners to

1,000-bed hospitals and more than 3,000 private

payers. The effective number of different provider

organizations may decline somewhat with the current trend toward hospital mergers, the purchase

of clinics and medical practices by integrated delivery systems, and the continuing affiliation of

physicians into independent practice associations

and other arrangements. But the structure of the

health care industry is unlikely to approach the relative simplicity of banking or air transportation.

In health care, the industry hubs are providers, and

most providers are small organizations without

the time, finances, or staff resources to prepare implementation guidelines, set standards, and implement systems. They must rely on the guidance

of vendors that provide software, claims processing, and networking services.

HCFA has been the successful organization in

moving the health care industry toward EDI because of its financial reach. For many health care

organizations, it was HCFA’s development of the

Medicare Transaction System (MTS) and its incentives to submit Medicare claims electronically

that prompted initial interest in EDI. These incentives have included: 1) faster payment for clean

claims (14 days for electronic, 27 for paper); 2)

electronic funds transfer; and 3) free or at-cost

billing software. Private sector payers are unlikely

to offer many of these incentives to providers. For

example, payers have an incentive to delay payment as long as possible in order to maximize their

own use of the funds; they would be unlikely to offer providers quick payment as an incentive to begin an EDI relationship unless it could be clearly

demonstrated that EDI reduces their own costs

(not the provider’s costs or the costs of the system

as a whole) enough to offset this advantage. However, because many providers and payers are beginning to use EDI to deal with HCFA, the

infrastructure is being created that they can also

use to deal with one another.

❚ Complexity of Information Needs

In banking and financial services, most electronic

transactions are simple and highly standardized.

Consumers and businesses benefit from the ease

of using the automated teller machines and credit

card transactions made possible by that standardization. Health care payment requires a number of

different types of transactions, and often large

amounts of data have to be exchanged. In addition, the procedures, information needs, payment

arrangements, and authorization procedures for

each type of transaction can vary, depending on

the characteristics of the payer, patient, patient’s

employer, and sometimes the diagnosis or procedure involved.52 This complexity has slowed the

diffusion of electronic commerce into the health

care arena.

❚ Standards

The key to the functionality and growth of electronic medical payment lies in the establishment

of standards. As discussed in chapter 2, standardssetting and acceptance are moving slowly. Current

estimates put the number of proprietary claims

formats in use at 400—too many even for software

to translate between sender and receiver.

51 J. J. Moynihan, “More Payers Should Convert to EDI,” Healthcare Financial Management, vol. 48, No. 5, May 1994, p. 66.

52 Faulkner and Gray Health Information Center, Health Care and the Electronic Superhighway: A Provider Perspective on Electronic Data

Interchange and Automated Medical Payment (Washington, DC: Faulkner & Gray, 1992), p. 21.
Chapter 3 Networks for Health Information | 111

The standards-setting process is voluntary and

compliance with the standards will be voluntary

as well. Yet administrative savings may not actually be realized unless standards are more stringent and compliance with them is nearly

universal. As mentioned earlier, there are nearly

50 different implementations of the standard

UB-92 form, requiring providers and payers with

interstate business to use several versions of it. A

standard claim form will not truly be standard, for

example, as long as each payer can demand additional documentation to accompany it. While

payers usually request additional information in

an effort to reduce their own costs, the difficulty

and expense of maintaining different forms presumably raises costs for the industry as a whole.

❚ Standard Identifiers for Individuals,

Providers, and Payers

Interstate electronic commerce for health information would be facilitated by a system of

standard identifiers. Because each provider or

provider group (as well as payers and other users

of health information) maintains its own identification number scheme and assigns its own numbers, patient records are not uniquely identified

once they leave the institutions where they have

been created. This can create confusion in the

multi-institutional sharing of clinical or administrative information. Unique identification can be

accomplished by combining several different

identifiers—for example, a file number, plus

middle initial, plus address—but it is generally

agreed that a system of standard identifiers would

be more stable over time.

Some argue that the benefits of fully electronic

records are more easily obtained if each individual

could be uniquely identified. If each person had a

universal patient identifier it would be easier to

link the health information maintained at different

institutions, for example. In addition to identifying patients, health care providers and specific

sites of care also need to be identified. While there

are a number of recommendations for developing

numbering schemes de novo, some industry organizations recommend modifying or expanding existing identification number schemes in order to

get unique identifiers in place more quickly.53

Universal identifiers are common in some European countries where they are assigned to

people at birth. The United States has been slow to

adopt a universal numbering system and many

groups have actively opposed such a system based

on privacy concerns.

The Social Security Number (SSN), or another

number based on it, has been recommended for

use as the universal patient identifier. Because this

numbering system is already in place, some

groups argue that it would be the fastest and least

costly method of instituting a universal numbering system.54 The ubiquity and convenience of the

SSN make it a tempting candidate for a universal

health identifier.

However, privacy advocates have opposed the

use of the SSN as a health identifier precisely because it has had so many other uses. The SSN is

the key to a lot of nonhealth-related information

about a person—including financial, tax, credit,

educational, and other information on file with

government agencies and private firms. It is very

easy, with access to the SSN, to quickly develop

detailed dossiers on anyone. In addition, some individuals, primarily infants and noncitizens, do

not have SSNs. Some people have multiple SSNs.

The system has been in operation for 60 years, and

there is a long history of invalid and fraudulently

acquired numbers. Because the form of the SSN

dates from the precomputer era, it also lacks a

check digit (an extra digit added to a computerbased number that aids in error detection and

correction).

53 For example, see American Medical Informatics Association, “Position Paper on Standards for Medical Identifiers, Codes and Messages

Needed To Create an Efficient Computer-Stored Medical Record” (Bethesda, MD: Apr. 20, 1993).

54 Ibid., p. 2.
112 | Bringing Health Care Online: The Role of Information Technologies

It can be argued that many of the privacy-based

objections to the SSN—fraudulent numbers, linkages to other databases, and so on—will also apply to any new numbering scheme that could be

adopted. While there is merit in this argument,

there is also the possibility that a new numbering

system would be safer because, for example, it

would have legal protections from the outset to

prevent its use for other purposes.

Alternative schemes for developing unique

identifiers have been proposed. Some would include segments of the patient’s name, latitude and

longitude coordinates of the place of birth, date of

birth, and perhaps parts of the SSN. Some systems

also involve encrypting the number, or converting

it to an alphanumeric identifier, in order to either

protect privacy or to make the number shorter and

easier to remember.55

One system that is now being put into place to

identify providers is the National Provider Identifier (NPI), which will be implemented by HCFA

in 1996. In its present form, the NPI system is not

universal—it will apply only to Medicare participants. It will provide unique identification numbers for physicians, other providers, and the sites

where they provide care. In developing the NPI

system, HCFA worked with a number of federal,

state, and private-sector organizations. The NPI

will consist of a seven-character alphanumeric

identifier with a one-character check digit. NPI

numbers can be encrypted to protect privacy and

confidentiality.

By design, there will be no intelligence imbedded in the NPI number; that is, analysis of the

number itself will not yield useful information

about the provider it identifies. Rather, the number points to a location in a database called the National Provider File that will contain descriptive

data about the provider. Thus, numbers will not

have to be reissued when provider characteristics

(address, number of locations, or types of specialty) change. The numbering format has the potential to provide 10 million all-numeric identifiers

or up to 27 billion alphanumeric identifiers, making it sufficiently large to serve as a national system for identifying all providers, including

nonparticipants in Medicare. Should such a national system be desired, authorizing legislation

would be needed to allow HCFA to open the system.

HCFA is also in the process of developing a

registry and identifier system for payers. This system would identify and maintain information on

the payers who offer secondary coverage for

Medicare participants. The process of coordinating benefits is complex for Medicare as it is in the

private sector. A primary payer, such as Medicare,

is often not aware that a patient has secondary coverage, or may not have complete information on

the benefits for which the patient is eligible and

the rules for calculating reimbursement. Without

this information, the primary payer can sometimes pay inappropriately (that is, pay more than

the patient is entitled to). In addition, the process

of filing a claim with the secondary payer is complex; the provider or patient must often file a separate claim based on remittance information

provided by the primary payer. By incorporating a

registry of secondary payers and a complete set of

rules for coordination of benefits into its Medicare

Transaction System, HCFA hopes to be able to

more accurately calculate reimbursement based

on all the benefits available to a patient. At the

same time, it could automatically send a bill to the

secondary payer, simplifying the claim process

for patients and providers.

❚ Inconsistent Regulatory Environment

for Health Information

State government regulations concerning electronic health information and patient records, as

well as privacy, vary widely. This creates a difficult environment in which to implement standard55 For example, see P.C. Carpenter et al., “The Universal Patient Identifier: A Discussion and Proposal,” Patient Centered Computing: 17th

Annual Symposium on Computer Applications in Medical Care (New York, NY: McGraw Hill, Inc., 1993).
Chapter 3 Networks for Health Information | 113

ized processes. There are four areas in which state

legislation and regulation impact on electronic

health information. They include laws on: 1) storage media for medical records; 2) use of electronic

signatures; 3) privacy and confidentiality of

health information; and 4) patient access to health

records.

Storage Media for Medical Records

State governments generally have licensing authority over health care providers and require

them to maintain medical records. Nearly every

state regulates what media are permissible for

storing medical records. In many states, the language is reasonably “technology neutral” and the

use of catchall phrases such as “other useable

forms” or “other appropriate processes” has been

taken to mean that computerized record storage is

permitted. In some states, however, legislation

has served as a barrier to the development of automated patient records by specifying the permitted

media (e.g., microfilm or paper) and excluding

disks, tapes, and other computerized storage media. Other states require clinicians’ signatures in

ink on particular forms, implying a paper original

to which the signature can be affixed. Some states

specifically permit the use of computers for some

functions but forbid it for others, thus hindering

the development of a complete computer-based

record. There are other paradoxes and inconsistencies in legislation as well, with some states permitting electronic signatures for some purposes

but requiring retention of a paper or microfilmed

record.56

Only a few states specifically authorize computerized medical records. Indiana statutes, for

example, authorize the use of “computerized records that maintain confidentiality.” They specifically state that the recording of hospital medical

records by the data-processing system is “an original written record” and authorize the courts to

treat information retrieved from such systems as

originals for purposes of admissibility into evidence.57

Some of the states whose statutes posed barriers to electronic patient records are making progress toward changing the statutes. For example,

North Dakota is considering legislation that

would make the recording of a medical record on a

computerized system the equivalent of a

photographic process, thus making printouts and

other items retrieved from the system admissible

in court.

Recordkeeping rules for nonhospital providers—nursing homes and physicians’ offices, for

example—are often covered by different state

statutes or regulations and can be very different

from those that apply to hospitals in the same

state. Implementing a complete electronic patient

record in a multisite provider organization, that

might include hospitals and nursing homes, can be

complicated if these requirements differ widely.

The absence of state legislative or regulatory

support for electronic patient records does not

necessarily mean that providers in that state are

forgoing development of information systems or

electronic record systems. It does mean, however,

that the providers face certain legal risks if they do

not maintain the paper record system as well, and

they must bear the costs of operating both systems. Currently, most providers are not technologically capable of creating a “complete”

electronic record in any case. They maintain a

mixed paper and electronic system for practical,

as well as regulatory, reasons. The regulatory inconsistencies among states can create difficulties

for health care organizations that are attempting to

develop common patient record systems for sites

in more than one state.

Federal legislation governing business records

(which includes medical records) implies that

computerized records are permitted (once again

56 J. P. Tomes, Compliance Guide to Electronic Health Records” (New York, NY: Faulkner and Gray, 1994), pp. 14-19.

57 Burns Ind. Code Ann. sec. 34-3-15.5-2.
114 | Bringing Health Care Online: The Role of Information Technologies

using language about “other processes”).58 In addition, HCFA, which administers the Medicare

program, authorizes the use of computerized medical records if they are maintained in a form that

can be reproduced legally, and if the system meets

Medicare’s conditions for participation. These

conditions basically state that the system must

protect the security of the records and ensure that

only the authorized persons are able to sign them.

The Department of Health and Human Services,

in an effort to encourage the development of computerized patient records, had legislation

introduced in the 103d Congress to require providers to maintain outpatient data in electronic

form as a condition of participation in Medicare.59

Electronic Signatures

Signatures are necessary to attest to the completeness and authenticity of a medical record. Generally, each entry in a record is signed or

authenticated by the person responsible for that

entry. An electronic record can be signed electronically, and this is permitted in many states; once

again, however, electronic signatures are treated

differently from state to state. Some states are silent about the specific means or technology to be

used for the signature, or they say that industry

and professional standards should dictate the form

of the signature. This would seem to permit the

use of electronic signatures in those states because

the Joint Commission on Accreditation of Healthcare Organizations, American Hospital Association, and other industry groups have published

guidelines related to electronic signatures. Some

states (like Pennsylvania, Alaska, and California)

specifically authorize the use of an electronic signature activated by a computer key that is known

only to the authorized user.

HCFA accepts electronic signatures on admission data sheets, attestations, and other documents

used to reimburse providers treating Medicare patients. Providers must demonstrate that their computer systems meet HCFA guidelines.

Privacy and Confidentiality of Health

Information

Both federal and state legislation cover the privacy of patient records. Records held by the federal

government are protected under the Privacy

Act,60 which governs federal disclosure of confidential information. At the state level there is a variety of approaches to privacy protection, and a

number of states have privacy laws that cover

medical information. Other states have sections in

their Medical Practice Acts that prohibit physicians from revealing information obtained in confidence from a patient during treatment. The

American Medical Association has published

standards for hospitals to protect the privacy of patient information. Some courts have enforced

these standards under state contract law as implied

conditions of the contractual relationship between

physicians and patients.

Even among the states that have well-defined

laws on the privacy of medical records, few address the flow of information to secondary users,

such as insurance payers, researchers, and so

forth. Further, because states are so inconsistent

in how they deal with electronic information

generally, few of them confront issues directly related to protecting privacy in computerized patient

records. For a more detailed discussion, see the

previous OTA report, Protecting Privacy in Computerized Medical Information.61

58 28 U.S.C. 1732.

59 Tomes, op. cit., footnote 56, p. 14.

60 5 U.S.C. sec. 552a.

61 U.S. Congress, Office of Technology Assessment, Protecting Privacy in Computerized Medical Information, OTA-TCT-576 (Washington, DC: U.S. Government Printing Office, September 1993), pp. 41-45.
Chapter 3 Networks for Health Information | 115

Patient Access to Health Records

Because patients have a property right in their records, it seems reasonable that they should be able

to inspect or copy them. Access to medical records

held by the federal government (e.g., Department

of Veterans Affairs or other hospitals operated by

the federal government) is governed by the Privacy Act. The Privacy Act requires agencies to establish procedures under which individuals can

view or receive copies of their own records. It also

authorizes the establishment of special procedures

for handling information that might, in the judgment of the agency, have an adverse effect on the

individual. These procedures have generally involved designating a third party to examine the

records and releasing them to a physician designated by the patient.62

For private sector hospitals and other providers, state laws and regulations govern patient access to medical records. Thirty-seven states have

statutory provisions for allowing a patient to review and/or copy his or her medical records. In a

few additional states, the patient’s right to access

is not specifically stated, but can be inferred from

other language.63 In addition, some courts have

ruled that providers have a common-law duty to

allow a patient to access his or her records, absent

legislation.64 In 22 states, the patient may be

charged reasonable copying fees, and 19 require

that the patient apply for the records in writing.

Twelve states permit physicians to deny patient

access to a record if something in the record would

have an adverse affect on the patient; in most of

these cases, however, the record must be released

to an attorney, physician, or other representative

designated by the patient.65

A patient’s right of access to information

derived from the medical record, but housed in the

database of an insurer or other third party, is unclear in many states. Only 14 states have legislation giving patients access to insurance databases

and limiting redisclosure of medical information

held by nonproviders.66

❚ Privacy, Confidentiality, and Security of

Health Information

Privacy, confidentiality, and security of electronic

data are areas of great concern because of the sensitivity of health information. Privacy is essentially the right of an individual to limit access to

information regarding that individual. Confidentiality is a form of informational privacy characterized by a special relationship between people,

such as the relationship between doctor and patient. Security refers to technical and organizational procedures that protect electronic

information and data-processing systems from

unauthorized access, modification, destruction, or

misuse.67

The appropriate levels of privacy, confidentiality, and security, as well as the techniques for

achieving them, may vary depending on the institutional context and the use of the information.

Tradeoffs are often necessary. For example, within a single hospital, confidentiality might be best

served by allowing a patient’s record to be seen

62 U.S. Congress, Congressional Research Service, Access to Medical Records Under Federal Law, No. 93-708A (Washington, DC: Aug. 3,

1993), p. 16.

63 U.S. Congress, Congressional Research Service, Patient Access to Medical Records: A Statutory Survey of the United States, No.

92-896A (Washington, DC: Nov. 17, 1992), and Medical Records: State Laws and Regulations Regarding Ownership and Patient Access, No.

93-519A (Washington, DC: May 20, 1993).

64 R. S. Dick and E.B. Steen (eds.), The Computer-Based Patient Record: An Essential Technology for Health Care (Washington, DC: National Academy Press, 1991), p. 166.

65 U.S., Congressional Research Service, Patient Access, op. cit., footnote 63.

66 Dick and Steen, op. cit., footnote 64.

67 L. O. Gostin et al., “Privacy and Security of Personal Information in a New Health Care System,” The Journal of the American Medical

Association, vol. 270, No. 20, Nov. 24, 1993, p. 2487.
116 | Bringing Health Care Online: The Role of Information Technologies

only by the attending physician and the nurse assigned to that patient. However, such a policy

would affect the quality of patient care—it would

unduly inconvenience and slow the work of substitute nurses, consulting physicians, intensive

care personnel, or other caregivers who might

need the record on short notice. Thus, a balance

between confidentiality and convenience must be

found. Most hospitals allow fairly broad access to

patient records by authorized caregivers, and they

usually have security systems to keep track of

each access. In some cases, this feature is used regularly to keep caregivers aware that they are accountable for their use of the information system.

At one hospital, for example, users are regularly

notified on-screen that each instance of access to a

patient record is automatically recorded and that

patients have the right to see a list of those who

looked at their records.68

When information moves out of the single provider institution, priorities may change. The EDI

industry has focused most of its concern on the security of information. Companies engaged in

transmitting business information electronically—financial institutions in particular—have

adopted technical solutions to two problems. The

first is that information transmitted over phone

lines might be read by unauthorized persons. One

technique for addressing this is encryption. A second problem is that people sending or receiving

information may not, in fact, be who they say they

are. Authentication techniques—the use of passwords, keys, and other automated identifiers—are

used to verify the identity of the person sending or

receiving information.69

Thus far, the EDI industry has a good security

record, according to the Workgroup on Electronic

Data Interchange (WEDI), which says “there have

been no reported incidents of the confidentiality

of EDI messages being compromised.”70 Indeed,

the risk of data leakage to outside computer hackers can be minimized in an online system. Security measures such as encryption procedures,

password access, and audit logs help to discourage

data theft. With electronic information, system

administrators have more numerous and powerful

tools for monitoring and protecting information

than they do with paper-based records.71

Privacy and confidentiality—the main focus of

concern for the health care industry—are proving

more difficult to protect. As health care information increasingly moves over electronic networks,

it becomes accessible to more people at widely

scattered institutions with different policies and

procedures in place. The potential for abuse increases accordingly. Unauthorized uses of information by authorized users can be a major

problem that is difficult to stop by technological

means. Because of a plethora of conflicting state

laws regarding confidentiality, it is difficult to establish legally defensible policies on proper access to records; people handling records often

have no clear guidelines for acceptable release of

information. A 1993 OTA report on privacy and

confidentiality of health information notes:

The present system of protection for health

care information offers a patchwork of codes;

State laws of varying scope; and Federal laws

applicable to only limited kinds of information,

or information maintained specifically by the

68 C. Safran et al., “Protection of Confidentiality in the Computer-Based Patient Record,” M.D. Computing, vol. 12, No. 3, 1995.

69 For further information on network security issues and technologies, see U.S. Congress, Office of Technology Assessment, Information

Security and Privacy in Network Environments, OTA-TCT-606 (Washington, DC: U.S. Government Printing Office, September 1994) and Issue Update On Information Security and Privacy in Network Environments, OTA-BP-TCT-147 (Washington, DC: Government Printing Office,

June 1995).

70 Quoted in Benjamin Wright, “Health Care and Privacy Law in Electronic Commerce,” Health Care Financial Management, vol. 48, No.

1, January 1994.

71 Ibid.
Chapter 3 Networks for Health Information | 117

Federal Government. The present legal scheme

does not provide consistent, comprehensive

protection for privacy in health care information, whether it exists in a paper or computerized

environment.72

The situation has not changed appreciably since

this report was published.

Without uniform privacy and confidentiality

laws, it is extremely difficult to expedite the development of interstate health records transfer.

Accordingly, WEDI called on Congress to ensure

the uniform, confidential treatment of identifiable

information in electronic environments. As electronic interstate transfer of medical data increases,

policies concerning the access to medical information by secondary users of medical data, the

use of medical data for nontreatment purposes,

and the redress of privacy violations must be made

consistent in all state. Privacy legislation should

also address the requirements for informed consent of patients. Patients are often unaware of how

their medical information will be used, to whom it

may be released, and what rights they may have to

access or correct it once it is in the hands of a secondary user.

Whether information is stored in a computer or

on a piece of paper, the public fears the abuse of

medical information by both authorized and unauthorized parties. In a 1993 health privacy poll, 80

percent of all respondents believed that consumers had lost all control over the circulation and use

of health care information.73 These concerns can

lead (and have led) to physicians withholding information from patient records at the patient’s request in order to protect his or her privacy.74 To

create an inaccurate or incomplete patient record,

even with beneficial intent, could ultimately have

serious effects on the patient; in addition, such actions render records less useful for outcomes research and other statistical purposes.

Improved patient education about privacy

rights may decrease the lack of control patients

feel over the spread of medical information. Until

national, uniform privacy legislation is enacted,

WEDI suggests steps to protect privacy in its 1992

report.75 Providers should:

 ensure that the patient has authorized release of

health information to an insurer by signing the

release contained on the insurance form,

 ensure that they release information in strict

compliance with the written release,

 ensure that they have complied with any relevant laws governing disclosure to insurers,

 establish security policies for employees who

have access to and process patient health information, and

 establish security protocols for computer systems used to process claims.

The WEDI guidelines were not intended to replace the need for federal legislation or to absolve

system operators from responsibility to design

and maintain secure computing environments.

Although solutions to the networking problems

of privacy, confidentiality, and security remain

unclear, the questions they embody do not: What

potential benefits of increased access to health

care information will materialize, and will they

outweigh the reduction in individual privacy that

increased access to information inevitably brings?

These questions must receive considered answers.

“Opportunities for using electronic networks may

be lost if there is serious mistrust of their safety.”76

The concept of fair information practices set

forth in the federal Privacy Act is fundamental to a

number of existing privacy laws and proposed ini72 Office of Technology Assessment, op. cit., footnote 60, p. 13.

73 Gostin et al., op. cit., footnote 67.

74 Office of Technology Assessment, op. cit., footnote 60, p. 6.

75 Workgroup for Electronic Data Interchange, 1992 Report (Hartford, CT, and Chicago, IL: September 1992).

76 Gostin et al., op. cit., footnote 67.
118 | Bringing Health Care Online: The Role of Information Technologies

tiatives to protect medical information. Common

characteristics are:

1. Records pertain to medical information on individuals.

2. Individuals are given the right to access much

of the personal information kept on them.

3. Limits are placed on the disclosure of certain

personal information to third parties.

4. Health care personnel are required to request

information directly from the individual to

whom it pertains, whenever possible.

5. When a government entity requests personal

information from an individual, laws require

the individual to be notified of the authority for

the collection of data, whether the disclosure is

mandatory or voluntary.

6. The individual may contest the accuracy, completeness, and timeliness of his or her personal

information and request an amendment.

7. Health care personnel must decide whether to

amend the information within a fixed time,

usually 30 days after receiving a request.

8. The individual whose request for change is denied may file a statement of disagreement,

which must be included in the record and disclosed along with it thereafter.

9. The individual can seek review of a denied request.

Protecting Privacy in Computerized Medical

Records77 noted that basing new protection for

medical information solely on the Privacy Act and

on principles of fair information practices will fail

to consider the complexity of today’s information

environment, with its distributed processing,

sophisticated database management systems, computer networks, and widespread use of microcomputers.

It is apparent that protecting personal information in a computerized environment involves, at a minimum, access to records,

security of information flows, and new methods

of informing individuals where information is

stored, where it has been sent, and how it is being

used.78

POLICY CONSIDERATIONS FOR

CONGRESS

Attempts to improve administrative efficiency by

increased use of electronic commerce in health

care are an important component of a larger effort

to reduce costs, improve quality of care, and improve access. Compared with a paper-based system, electronic information systems do appear to

reduce costs for some users. The industry is moving in this direction. Standards development activities are under way.

However, getting started with electronic commerce is expensive. Some organizations have

weak financial incentives to make the necessary

investments to institute electronic payments,

while others are forging ahead without waiting for

standards to be set. Some experts interviewed by

OTA commented that the complexities of dealing

with paper records and paper-based transactions,

particularly as health care organizations grow

larger and enter new lines of business, are forcing

some organizations to implement electronic systems, even if they have no way to measure the actual cost-effectiveness of a particular system. The

computer network, like the telephone, is becoming a part of the way business is conducted; a firm

simply has to have one to compete in the market,

whether it makes economic sense or not.79

There may be some savings for the health care

system as a whole if electronic medical payments,

for example, are implemented on a near-universal

scale. However, at current rates of implementation, high levels of use of electronic payments or

compliance with standards may not be achieved

for some time. The health care industry in the

77 Office of Technology Assessment, op. cit., footnote 60.

78 Ibid., p. 79.

79 Project HOPE Center for Health Affairs, op. cit., footnote 2.
Chapter 3 Networks for Health Information | 119

United States is not organized as a “system” with a

central focus or consensus on how to deal with

systemwide problems. The different parts of the

system have diverse incentives, and efforts to control costs in one area may increase costs in another.

However, these shifted costs are so subtle and

spread over so many participants in a complex

system that they are hard to quantify. For example,

a major payer, in an effort to reduce its own costs,

may begin to request additional data and documentation (beyond what is on the standard forms)

when providers submit large claims. All providers

who deal with that payer then incur additional

costs to resubmit rejected claims, develop and

maintain different versions of the standard form,

or provide the additional data with all claims to

avoid the problem of deciding when to send it and

when not to. Situations like these make it difficult

for the industry to establish truly uniform procedures.

The trend toward managed care reduces this diversity of interest to some extent. The percentage

of people covered by traditional indemnity insurance in the fee-for-service sector can be expected

to decrease, thus reducing the number of transactions between providers and payers as well. Some

managed care organizations, like staff model

HMOs, will internalize these transactions, and

will presumably perform them efficiently out of

sheer corporate self-interest. But managed care is

taking many forms, including independent practice associations and other arrangements for

which transactions will remain external between a

network of different provider and payer organizations. For the near future, absent a far-reaching

government-imposed restructuring of the system,

many private insurers and health care providers

will continue to do business as independent firms

whose interests do not coincide.

There are three major areas in which government action might be considered: 1) providing

leadership in the adoption of standards for electronic medical payments and other transactions

and exchanges of health information; 2) establishing a system of unique identifiers for people,

providers, and payers; and 3) establishing a more

consistent regulatory environment for interstate

exchanges of health information.

❚ Standards

The federal government has already played a major role in establishing the current level of standardization. For example, in the area of electronic

medical payments, HCFA’s commitment to electronic claims-filing and its adoption of EDI standards have caused many providers and private

payers to use these technologies. Further steps by

HCFA—for example, offering truly expedited

payment to providers who file electronically

(instead of making delayed payment to those who

make paper claims, as is currently the case)

—could encourage more providers to make the

necessary investments needed to comply. HCFA’s

early adoption of EDI standards for other forms

and transactions could also inspire other payers to

make use of them. HCFA’s ongoing plans to establish a national payer file and to automate secondary payments should also serve as an example of

how to simplify the complex process of coordination of benefits. Thus, one option for federal action is to continue to influence the standardization

of health care information transactions through

the federal government’s role as a major insurer.

However, even HCFA’s leadership will not ensure universal compliance with standards among

all payers and providers, and it is likely that widespread compliance is needed in order to realize noticeable savings. As long as some set of

participants does not comply, many others will

have to maintain separate systems or multiple versions in order to do business with them. The information involved is very complex, and certain

classes of participants—payers, state governments, and others—will continue to create the

need for new types of data for their own purposes,

but not necessarily those of their trading partners

or the system as a whole. If they have either money

or licensing authority on their side, their trading

partners will have to comply with their demands

in addition to the standard.

Given that near-universal compliance seems to

be important, but is not being achieved as yet,
120 | Bringing Health Care Online: The Role of Information Technologies

Congress may want government to take a more active role in administrative simplification. Thus, a

more active approach would be for Congress to

consider requiring the adoption of industry-developed standards for core electronic transactions,

including maximum data sets, and setting timetables for their implementation.

This option suggests the adoption of standards

for a small set of core transactions within the near

future. It assumes that the transition from a feefor-service environment to a managed care environment is going to be a gradual one, and that for a

number of years it will be worthwhile to make the

basic fee-for-service transactions as efficient as

possible. This option is also limited in that its aim

is not to mandate sweeping requirements for implementing electronic transactions, but rather to

focus on a small set of transactions. Core transactions include: claims and billing, payment and remittance advice, eligibility inquiry, enrollment,

and coordination of benefits. Standard forms for

managed care transactions, such as the encounter

report, could also be considered in this group.

These are areas where the voluntary standards

process is well advanced. Requiring adoption of

standards for other transactions might be considered in the future.

The option includes a requirement for maximum data sets for each transaction. It will be necessary to obtain consensus from providers and

payers about what information is needed for the

transactions, and then ensure that participants

may not unilaterally increase information requirements that would lead to the proliferation of nonstandard forms.

A requirement for universal compliance with

an electronic transaction system would necessarily create problems for some providers and payers,

particularly small ones. Clearly not all providers

and payers will be able to handle electronic transactions or modify their proprietary systems to

meet standards within any given timeframe; however, they should be able to contract with community health information networks, clearinghouses,

electronic medical claims services, or other firms

who can provide these services for them.

Unfortunately, a government-imposed standards-setting process would require some central

focus of authority to set timetables and to ensure

compliance. Therefore, a necessary corollary to

the option discussed above would be to charge a

government agency with responsibility and authority to set standards and data definitions for

administrative transactions in consultation with

industry groups, and to manage changes to standards over time; or create an agency or commission for this purpose.

Establishing a central authority, whether within

an existing agency or in a new commission, is also

a cost—one that would be shifted from the health

care system as a whole to the government. However, it is unlikely that standards and timetables

will be adhered to unless someone is in charge.

Possible disadvantages of requiring standardization and creating an authority—for example,

locking into a standard too soon—do not appear to

be problems for electronic medical payments at

this time, at least for core transactions. Industry

groups have made progress with standards for the

basic core transactions and preliminary versions

are available for many. There is a need, however,

to ensure that the standards are implemented in the

same way so their use is uniform. Industry input,

from both payers and providers, is definitely needed for this. Clearly, if the agency or commission

attempted to develop standards de novo, many unnecessary costs could be incurred; therefore it

would have to work closely with industry groups

already in existence. A number of industry groups

have voiced support for greater government involvement, including actions to speed the standards-setting process.

❚ Standard Identifiers for Individuals,

Providers, and Payers

Consistent with the above options, another area

for nationwide action would be to establish a system of unique identifiers for patients, providers,

and payers.

Controversy continues about the particular system of identifiers to be used for individuals. In the
Chapter 3 Networks for Health Information | 121

past, OTA has cautioned against use of the SSN as

a national identification number of any kind,

largely on privacy grounds. OTA has suggested in

earlier work that a new numbering system, with

legal protections against misuse built in from the

beginning, would be more appropriate. Supporters of the SSN argue, with some merit, that the disadvantages cited for the SSN are bound to afflict

any numbering system eventually, even one that is

developed from scratch. With modifications, such

as a check digit or other additional digits, the SSN

may be the fastest and possibly the lowest-cost option for establishing a numbering system.

Identifier systems that meet the needs of both

private sector and government users would be

most useful. HCFA has made efforts to include a

variety of public and private stakeholders in the

development of its national provider identifier

(NPI). That system, which HCFA proposes to implement for Medicare providers in 1996, has the

potential to be expanded into a universal system.

Expanding the NPI to include non-Medicare providers would require congressional action to allow HCFA to open up the system and to establish

which agency should administer it. Similarly,

HCFA’s efforts toward developing a payer registry

and automating the secondary payment process

could serve as the basis for establishing a national,

automated coordination-of-benefits system for

private payers.

❚ Consistent Regulatory Environment

Some state governments, under the influence of

industry associations and other groups, are attempting to change state legislation that limits the

development of computer-based patient records.

However, the variety of state legislation that affects electronic health information is still bewildering and poses a barrier to the efficient

development of interstate electronic commerce in

health care. One option is to encourage the passage of uniform state legislation with regard to

privacy and confidentiality, allowable storage

media, and standards for health information. A

number of industry groups are already working

with legislatures to enact uniform legislation. In

addition, the Department of Health and Human

Services has recently been tasked by the Administration to take the lead in developing model state

privacy laws and model institutional privacy policies for health information. Such leadership by a

federal agency may be useful in speeding the

adoption of new information laws.

Privacy and confidentiality are particularly important areas in dealing with health information; if

there is little confidence that an electronic medical

information system will protect them, then providers and patients will be unwilling to use it. If

the process of revising legislation on a state-bystate basis is seen as too time-consuming, or not

sufficiently effective, then some additional federal intervention may be necessary either to support

uniform legislation or to provide federal legislation. In this case, Congress may wish to establish

federal legislation and regulation with regard to

privacy and confidentiality of medical information, as well as storage media for medical records

and electronic data standards for storage and

transmission of medical information. A corollary

to this option is to charge a government agency,

or create a committee or commission, to oversee

the protection of health care data; to provide ongoing review of privacy issues; to keep abreast of

developments in technology, security measures,

and information flow; and to advise Congress

about privacy matters in the area of health care

information.

The purpose of these options is to create a national environment where electronic commerce

and the development of computer-based patient

records is not discouraged by local differences in

regulation. This would establish a minimum floor

so that interstate commerce and information exchange can be maintained. There is still a need for

considerable research on the computer-based patient record and other kinds of health information.

Detailed standards about the computer-based patient record within a particular provider organization cannot be legislated or established by

regulation at this time, and, in fact, such regula-
122 | Bringing Health Care Online: The Role of Information Technologies

tion may never be desirable. However, minimum

standards for the storage and protection of health

information, and for its exchange among institutions, may now be in order.

Many violations of security, privacy, or confidentiality are caused by insiders—trusted individuals who exceed their authority or put information

they are authorized to have to an unauthorized

use.80 Establishing clear and uniform law to protect privacy and confidentiality, along with civil

and criminal penalties for violations, would encourage organizations that handle electronic

health care information to establish strong internal

policies and procedures, which will be as important as technological protections for information.

With regard to privacy and confidentiality, an earlier OTA report cited seven provisions to be considered in any federal legislation affecting health

information:

1. Define the subject matter of the legislation,

health care information, to encompass the full

range of medical information collected, stored,

and transmitted about individuals, not simply

the patient record.

2. Define the elements comprising invasion of

privacy of health care information and provide

criminal and civil sanctions for improper possession, brokering, disclosure, or sale of health

care information, with penalties sufficient to

deter perpetrators.

3. Establish requirements for informed consent.

4. Establish rules for educating patients about information practices; access to information;

amendment, correction, and deletion of information; and creation of databases.

5. Establish protocols for access to information

by secondary users, and determine their rights

and responsibilities in the information they access.

6. Structure the law to track the information flow,

incorporating the ability of computer security

systems to monitor and warn of leaks and improper access to information so the law can be

applied to the information at the point of abuse,

not to one “home” institution.

7. Establish a committee, commission, or panel to

oversee privacy in health care information.81

These principles will continue to be useful in

designing uniform state or federal regulation with

regard to health information security, privacy, and

confidentiality.

80 Office of Technology Assessment, op. cit., footnote 69.

81 Office of Technology Assessment, op. cit., footnote 60, p. 87
Using Information

Technology To Improve

the Quality of

Health Care

he quality of health care is ultimately judged by the impact

of specific health services on the patient’s health status.1

Improving quality involves identifying and using health

services that, when properly executed, produce the greatest improvement in health status. The most direct contribution

that information technology can make to improving the quality of

health care is to provide the clinician with better information

about the patient and health problem at hand, and alternative tests

and treatments for that problem, preferably at the point of care.

This would enable clinicians to choose more effective services

more quickly2 and help them avoid potentially tragic errors.3

This chapter discusses the potential for advanced information

technologies to improve the quality of health care—as indicated

1 Institute of Medicine, Medicare: A Strategy for Quality Assurance, K.N. Lohr (ed.)

(Washington, DC: National Academy Press, 1990), pp. 20-25.

2 K.L. Coltin and D.B. Aronow, “Quality Assurance and Quality Improvement in the

Information Age,” Putting Research to Work in Quality Improvement and Quality Assurance, M.L. Grady, J. Bernstein, and S. Robinson (eds.), Agency for Health Care Policy and

Research, Pub. No. 93-0034 (Rockville, MD: July 1993), pp. 51-54; S.D. Horn and D.S.P.

Hopkins, “Introduction,” Clinical Practice Improvement: A New Technology for Developing Cost-Effective Quality Health Care, S.D. Horn and D.S.P. Hopkins (eds.)(New

York, NY: Faulkner & Gray, 1994), pp. 1-5.

3 L.L. Leape, “Error in Medicine,” Journal of the American Medical Association, vol.

272, No. 23, Dec. 21, 1994, pp. 1851-1857; L.L. Leape et al., “Systems Analysis of Adverse Drug Events,”Journal of the American Medical Association, vol. 274, No.1, July 5,

1995, pp. 35-43; D.W. Bates et al., “Incidence of Adverse Drug Events and Potential Adverse Drug Events: Implications for Prevention,” Journal of the American Medical

Association, vol. 274, No.1, July 5, 1995, pp. 29-34.

| 123
124 | Bringing Health Care Online: The Role of Information Technologies

by the effectiveness of clinical decisionmaking4—and the potential role of the federal government in that process. The most relevant

technologies5 include:

 electronic patient records,

 structured data entry,

 advanced human-computer interface technologies,

 portable computers,

 automated capture of data from diagnostic and

monitoring equipment,

 relational databases with online query (keyword search and retrieval),

 knowledge-based computing, and

 computer networks.

This chapter first reviews the clinical decision

support approach to improving health care, and

the ways in which information technology could

enhance clinical decisionmaking. It then examines the performance assessment approach to

improving health care, which involves evaluating

specific health services, providers,6 and insurance

plans.7 Ways in which some of the problems confronting both approaches might be resolved by using information technology are explored. The

chapter concludes with a discussion of policy issues and options regarding potential governmental roles in those developments.

CLINICAL DECISION SUPPORT

Clinical decision support can be broadly and simply defined as the use of information to help a clinician diagnose and/or treat a patient’s health

problem. Two kinds of information are involved:

1) information about the patient; and 2) information about the kind of health problem afflicting the

patient and alternative tests and treatments for it.

Clinical decision support is by no means a new

phenomenon—such information traditionally has

been available from several sources. However,

those sources have limitations that often diminish

their reliability or their accessibility at the point of

care.

The time pressures of clinical practice do not

allow clinicians to study the patient’s entire health

history or review the latest clinical knowledge on

every nonroutine health problem they encounter.

Consequently, one major goal of clinical decision

support is to locate needed information and make

it available to the clinician in readily usable form

at the point of care as quickly as possible, and in a

manner that minimally interferes with the care

process. Moreover, the potentially severe consequences of incorrect clinical decisions for both the

patient and the clinician require that the information retrieved be as accurate as possible.

❚ Limitations of Traditional Information

Sources

Information About the Patient

The specific kinds of information about the patient that are useful in clinical decisionmaking fall

into two broad categories:

1. Health problems, both current (signs and

symptoms, physical findings, diagnostic test

results, functional status, etc.) and previous

(medical history, including previous services

for each health problem); and

4 This approach focuses on the effectiveness of the health services delivered by providers and insurance plans (see footnotes 6 and 7). The

role of the patient in clinical decisionmaking and self-care, and ways in which information technology can enhance that role, were discussed in

chapter 1.

5 See chapter 2 for details on these technologies.

6 Throughout this chapter, the term providers includes both individual clinicians and institutional providers such as hospitals. Clinicians

include physicians and other licensed practitioners, such as nurses. Physicians include allopathic medical doctors, osteopaths, chiropractors,

podiatrists, etc. In discussing clinicians who diagnose and treat health problems, this report includes nurse practitioners, physician assistants,

and other physician extenders who are licensed to prescribe medications.

7 The term health insurance plan here includes traditional indemnity plans and managed care organizations (health maintenance organizations, preferred provider organizations, etc.).
Chapter 4 Using Information Technology To Improve the Quality of Health Care | 125

2. Background, including demographic traits

(age, sex, ethnicity, and socioeconomic status),

risky behaviors (substance abuse and hazardous occupations, sports, hobbies, or sexual

practices), exposures (occupational and environmental hazards), allergies, and family history.

Information about the patient traditionally has

been drawn from the paper-based patient record

and direct clinical examination of the patient.

Briefly, the major difficulties with the paperbased patient record8 include:

 indecipherable content,

 lack of comprehensiveness,

 lack of completeness,

 inaccuracy,

 inaccessibility,

 lack of uniformity and standards,

 slow and cumbersome transmission,

 lack of security, and

 sheer physical volume.

These problems make it difficult to quickly locate accurate and readily usable information about

the patient at the point of care.

Problems with the clinical examination9 include:

 unsystematic methods in obtaining the

patient’s health history,

 unsystematic methods in observing the

patient’s signs and symptoms,

 faulty reasoning and inference in using the

collected information, and

 the amount of time required to obtain and

record all of this information.

These drawbacks jeopardize the completeness

and accuracy of new information about the patient’s current health problems.

Information About the Health Problem

The most efficient source of information about a

specific health problem is the clinician’s own

knowledge and experience with similar cases.

Such information can usually be retrieved almost

instantaneously from the clinician’s memory and

can be readily applied to a health problem in terms

that the clinician understands. Indeed, between 80

and 90 percent of clinical actions are based on

such information.10 However, it is impossible for

clinicians to remember all available information

about all of the health problems they are likely to

encounter, or all of the alternative tests and treatments for those problems. Even experts on a given

health problem are likely to have only selected information on that problem—information that may

be unsystematic, unrepresentative, and biased.

Most clinicians need to consult other sources of

clinical knowledge and experience, at least on occasion.

A clinician may seek the advice of other clinicians and researchers who have special knowledge or experience regarding the health problem

at hand. However, the patients usually seen by the

consultant may differ from the referring clinician’s patients in important ways. In addition, any

individual clinician’s patients may not be typical

of all patients with the health problem at hand, and

the consultant’s knowledge and experience could

also be highly selective. Finally, consultants sim8 Institute of Medicine, The Computer-Based Patient Record: An Essential Technology for Health Care, R.S. Dick and E.B. Steen (eds.)

(Washington, DC: National Academy Press, 1991), pp. 12-19; P.C. Tang, D. Fafchamps, and E.H. Shortliffe, “Traditional Medical Records as a

Source of Clinical Data in the Outpatient Setting,” Proceedings of the Eighteenth Annual Symposium on Computer Applications in Medical

Care, J.G. Ozbolt (ed.) (Philadelphia, PA: Hanley & Belfus, 1994), pp. 575-579; J.C. Wyatt, “Clinical Data Systems, Part 1: Data and Medical

Records,” Lancet, vol. 344, No. 8936, Dec. 3, 1994, pp. 1543-1547. For further discussion of problems with paper-based patient records, see

chapter 2.

9 See C. Selby et al., “Set Up and Run an Objective Structured Clinical Exam,” British Medical Journal, vol. 310, No. 6988, May 6, 1995, pp.

1187-1190.

10 B.C. James, “Advances in Computer-Based Patient Records for Health Services Research,” presentation at the 12th Annual Meeting of

the Association for Health Services Research, Chicago, IL, June 4-6, 1995.
126 | Bringing Health Care Online: The Role of Information Technologies

ply may not be available when needed in urgent

cases.

A related source of clinical guidance for practitioners is legal standards of care, which specify

the levels of care provided by the majority of physicians in particular clinical situations. These

standards are determined by the courts, largely on

the basis of testimony by expert witnesses during

malpractice lawsuits. The widely conflicting

opinions expressed by different experts in many

such contexts illustrate the extent to which legal

standards of care can be vague, inconsistent, and

incomplete.11 Extensive variation in practice patterns among clinicians within and across localities

has been thoroughly documented. This variation

reflects, in part, the lack of consensus regarding

the most effective ways to treat most health problems.12

To extend the individual knowledge and experience of individual clinicians, institutional providers or multifacility enterprises with large

numbers of patients sometimes conduct local

clinical research on those patients over time. Such

efforts can generate information that is useful in

those providers’ own clinical decisionmaking, as

well as for publication. (Providers with fewer patients often conduct such research as well, but the

number of cases may be too small to support statistically reliable comparison among treatment

groups.) However, local research may be useful

only in that setting if the institution’s patients or

practice patterns are atypical. In any case, extensive local research is not that common, even

among large institutions.

Information published in printed clinical literature (reference books, textbooks, research studies, and professional periodicals) is another

well-established source of information for clinical

decisionmaking. However, it can be difficult to locate such information quickly because of inadequate indexing and the problem of keeping paper

materials organized. In addition, a considerable

amount of time can elapse before new information

gets published; and once published, it quickly becomes outdated. Maintaining large amounts of

printed information in accurate, up-to-date, and

readily accessible form can be expensive.

As with clinician knowledge and experience,

clinical literature also may sometimes harbor

biases resulting from the use of unsystematic

methods in generating the information. Even peerreviewed research literature is hampered by publication bias stemming from the preference of

authors, journal editors, and reviewers for statistically significant results supporting specific hypotheses, particularly if those results are

perceived as being important.13 To be considered

worthy of publication, articles whose results fail

to support an hypothesis must strongly challenge

widely held theories and assumptions. On the other hand, published research findings are often

widely and uncritically accepted without careful

consideration of the soundness of the methodologies used.

Despite decades of clinical and epidemiological research, systematic evidence is still lacking regarding “what works” in diagnosing, treating, and

11 U.S. Congress, Office of Technology Assessment, Defensive Medicine and Medical Malpractice, OTA-H-602 (Washington, DC: U.S.

Government Printing Office, July 1994), pp. 30-31, 164.

12 H. Krakauer et al., “The Systematic Assessment of Variations in Medical Practices and Their Outcomes,” Public Health Reports, vol. 110,

No. 1, Jan.-Feb., 1995, pp. 2-12; U.S. Congress, Office of Technology Assessment, Identifying Health Technologies That Work: Searching for

Evidence, OTA-H-608 (Washington, DC: U.S. Government Printing Office, Sept. 1994), pp. 26-34.

13 K. Dickersin and Y.I. Min, “Publication Bias: The Problem That Won’t Go Away,” Doing More Harm Than Good: The Evaluation of

Health Care Interventions, K.S. Warren and F. Mosteller (eds.) (New York, NY: New York Academy of Sciences, 1993); P.J. Easterbrook et al.,

“Publication Bias in Clinical Research,” Lancet, vol. 337, No. 8746, Apr. 13, 1991, pp. 867-872.
Chapter 4 Using Information Technology To Improve the Quality of Health Care | 127

preventing most health problems—much less

which methods are most cost-effective.14 In addition, even the evidence that does exist is not always put to use in clinical practice. To rephrase an

earlier statement, only between 10 and 20 percent

of clinical actions are based on published scientific research.15

❚ Practice Guidelines and Protocols

Even when solid experiential or research-based

evidence is available, human beings are inherently

fallible processors of that information.16 They can

track no more than four variables simultaneously,

compared with the hundreds of variables that

characterize even a single health condition.17 It is

impossible for clinicians to remember all available information about all of the health problems

they are likely to encounter, or all of the alternative tests and treatments for those problems, or all

relevant characteristics and histories of all of their

patients. Moreover, recall is biased toward things

that are considered to be more important, that tend

to confirm one’s prejudices, and that are more recently experienced.18 Indeed, one researcher has

referred to clinical decision support as “uncertainty management.”19

In an effort to reduce this uncertainty, clinical

practice guidelines20 have been developed over

the past few decades by numerous medical specialty societies, insurance companies, utilization

review organizations, managed care organizations, and government agencies. Guidelines focus

on a given health problem or procedure, and are

usually developed through a group consensus

process among selected clinical experts on that

problem or procedure. The intent is to provide

broad parameters within which clinicians continue to exercise judgment, rather than to dictate exact steps to follow.21 Figure 4-1 reproduces an

algorithm that depicts a clinical practice guideline

for management of patients with heart failure, developed by the federal government’s Agency for

Health Care Policy and Research (AHCPR). Even

when practice guidelines are available, however,

evidence suggests that clinicians often forget to

follow them, or deviate from them without clear

cause, especially in high-stress situations.22 Research also shows that it is difficult to change clinician behavior simply by providing them with

information, even in the form of guidelines.23

Formal clinical protocols are more rigorous

models of the process of care for a given

14 U.S. Congress, Office of Technology Assessment, Identifying Health Technologies That Work, op. cit., footnote 12; P.J. Neumann and M.

Johannesson, “From Principle to Public Policy: Using Cost-Effectiveness Analysis,” Health Affairs, vol. 13, No. 3, summer 1994, pp. 206-214.

15 James, op. cit., footnote 10.

16 C.J. McDonald, “Protocol-Based Computer Reminders, The Quality of Care and the Non-Perfectability of Man,” New England Journal

of Medicine, vol. 295, No. 24, Dec. 9, 1976, pp. 1351-1355; Leape, op. cit., footnote 3.

17 A.H. Morris, “Protocol Management of Adult Respiratory Distress Syndrome,” New Horizons, vol. 1, No. 4, Nov. 1993, p. 594.

18 Ibid., p. 593.

19 E.H. Shortliffe, “Medical Informatics and Clinical Decision Making: The Science and the Pragmatics,” Medical Decision Making, vol.

11, No. 4, Oct.-Dec. Supplement, 1991, pp. S2-S4.

20 Clinical practice guidelines are sometimes called practice parameters or some variation of clinical paths or critical pathways—terminology adapted from critical path analysis in manufacturing and other industries.

21 U.S. Congress, Office of Technology Assessment, Identifying Health Technologies That Work, op. cit., footnote 12, ch. 7.

22 E. Coiera, “Medical Informatics,” British Medical Journal, vol. 310, No. 6991, May 27, 1995, p. 1383.

23 T.H. Lee. et al., “Failure of Information as an Intervention To Modify Clinical Management,” Annals of Internal Medicine, vol. 122, No. 6,

Mar. 15, 1995, p. 436; U.S. Congress, Office of Technology Assessment, Identifying Health Technologies That Work, op. cit., footnote 12, ch. 8.
128 Bringing Health Care Online: The Role of Information Technologies
Chapter 4 Using Information Technology To Improve the Quality of Health Care | 129

health problem. They are composed of highly specific steps and decision parameters regarding

diagnosis, treatment, or prevention of a problem.

The inputs and outputs of a given step can be either deterministic (involving a fixed value or action) or probabilistic (involving a range of

possible values or actions). Clinicians may still

exercise judgment and override any particular step

in a protocol, but having a clear sequence of specific steps to follow can help ensure that none will

be inadvertently forgotten or altered.24

Many clinicians view practice guidelines and

protocols skeptically as being “cookbook medicine,”25 concocted largely by clinically uninformed researchers and bureaucrats. Some are

also concerned that guidelines may be used

against clinicians in malpractice suits,26 although

evidence indicates that they are used by both

plaintiffs’ and defendants’ attorneys.27 Other clinicians criticize guidelines that are based more on

judgmental consensus than on scientific evidence.

These guidelines are seen as being vague and subjective, lacking in specificity and testability, and

based on incomplete and inaccurate information—drawbacks that make it difficult to derive

case-specific advice.28

For example, nurses at LDS Hospital in Salt

Lake City, Utah, found that the AHCPR guideline

for treating pressure ulcers was too vague to use in

clinical practice. Most importantly, the guideline

did not specify the treatment options for various

combinations of scores on six components of a

measure of risk for developing pressure ulcers. A

team of nurses, physicians, and researchers converted the guideline into a more formal clinical

protocol by developing exact specifications for

those treatment options through an iterative group

consensus process and monitoring of patient outcomes.29 This illustrates how local research can

be used to inform the development and refinement

of clinical practice guidelines and protocols. It

also emphasizes the need for careful testing and

screening of these kinds of clinical decision support.

❚ Potential Contributions of Information

Technology

The basic question in this area is whether advanced information technologies can 1) improve

the accuracy of the information needed in clinical

decisionmaking, 2) reduce the amount of time required to retrieve that information, and 3) make

that information accessible at the point of care.

This section highlights some of the potential contributions these technologies can make to clinical

decision support. A later section summarizes

some of the limited and mixed evidence bearing

on these questions.

Entering and Retrieving Patient Information

The key technology for improving patient information is the electronic patient record that

stores comprehensive information on the patient

24 Coiera, op. cit., footnote 22.

25 W.W. Parmley, “Clinical Practice Guidelines: Does the Cookbook Have Enough Recipes?” Journal of the American Medical Association, vol. 272, No. 17, Nov. 2, 1994, pp. 1374-1375.

26 F. Bazzoli, “Computerized Records Will Play a Key Role in the Implementation of Clinical Guidelines,” Health Data Management, February 1995, p. 32.

27 A.L. Hyams et al., “Practice Guidelines and Malpractice Litigation: A Two-Way Street,” Annals of Internal Medicine, vol. 122, No. 6,

Mar. 15, 1995, pp. 450-455.

28 C.J. McDonald and J.M. Overhage, “Guidelines You Can Follow and Can Trust: An Ideal and an Example,” Journal of the American

Medical Association, vol. 271, No. 11, Mar. 16, 1994, pp. 872-873.

29 S. D. Horn, C. Ashton, and D.M. Tracy, “Prevention and Treatment of Pressure Ulcers by Protocol,” Clinical Practice Improvement: A

New Technology for Developing Cost-Effective Quality Health Care, S.D. Horn and D.S.P. Hopkins (eds.)(New York, NY: Faulkner & Gray,

1994), pp. 253-262; “LDS Nurses Reduce Pressure Ulcer Incidence with Retooled Guidelines,” Report on Medical Guidelines & Outcomes

Research, Feb. 23, 1995, pp. 10-11.
130 | Bringing Health Care Online: The Role of Information Technologies

from a variety of sources (clinic, laboratory, pharmacy, etc.).30 Other technologies for handling patient information operate in conjunction with the

electronic patient record. Overall, these technologies could permit faster, easier, and more accurate

collection of information about the patient.

31

Clinical examination results can be entered by clinicians at or near the point of care, particularly

with the aid of portable computers. Structured

data entry, such as on-screen forms and menus and

prepared blocks of text, can encourage complete

data collection and reduce keying errors, particularly when pen-based computing is used rather

than keyboards. Automatic date- and time-stamping of entries facilitates documentation and tracking of patient care and outcomes over time.

Some patient data can be captured directly from

diagnostic and monitoring equipment, bypassing

human data entry altogether. Radiographic

images, full-motion videos, and sound recordings

can be digitized, stored, and transmitted electronically, often with resolution approaching that of

analog technologies. Patient background information and risk factors32 can be entered into

computers by patients themselves, again with the

aid of structured data entry and advanced humancomputer interface technologies. One example of

such a system is HealthQuiz33 (see appendix C).

Basic demographic traits can be obtained from

other computer databases (e.g., insurance eligibility files) through computer networks, again bypassing human data entry.

Using relational databases with online query,

information technologies can also permit faster,

easier, and better targeted search and retrieval of

previously collected information about the patient—even at the point of care. Portable computers and advanced human-computer interface

technologies can also be helpful here. Electronic

storage of digitized radiographic images, full-motion videos, and sound recordings can make them

easier to locate, although retrieving them can be

slow if the computers, telecommunications equipment, or transmission lines used have insufficient

capacity. Increasingly powerful and flexible

graphics software and higher resolution displays

can offer flexibility in the ways information is organized and displayed to suit the individual needs

of clinicians.

Retrieving Information About the Health

Problem

Computer and telecommunications networks, in

conjunction with online query, portable computers, and advanced human-computer interfaces,

can make information about various health problems more readily accessible from either local or

remote knowledge bases. Many research libraries

provide online access to their computerized catalogs (e.g., the Library of Congress’s SCORPIO)

and bibliographic databases (e.g., The National

Library of Medicine’s MEDLINE) that can be

queried online. Documents can be ordered electronically (even during an online literature search)

from one of the more than 4,000 member libraries

of the National Network of Libraries of Medicine.

Documents can be shipped in hard-copy form or

transmitted electronically via the Internet or fax.

Unfortunately, these databases do not cover all of

the clinical literature, and it can be difficult to

identify all studies of a certain kind, such as randomized controlled trials.34

30 Although the computer-based patient record is usually conceptualized as being a centralized repository, in reality different components of

the record may be stored in separate but seamlessly linked computer systems.

31 J.C. Wyatt, “Clinical Data Systems, Part 2: Components and Techniques,” Lancet, vol. 344, No. 8937, Dec. 10, 1994, pp. 1609-1614.

32 Risk factors are key health problems and background characteristics that can affect the patient’s outcome, independent of the specific

kinds of services received.

33 “ ‘HealthQuiz’ Makes Preventive Care Guidelines Easy To Apply,” Report on Medical Guidelines & Outcomes Research, Jan. 26, 1995,

pp. 5-6.

34 U.S. Congress, Office of Technology Assessment, Identifying Health Technologies That Work, op. cit., footnote 12, p. 81.
Chapter 4 Using Information Technology To Improve the Quality of Health Care | 131

The National Cancer Institute (NCI) maintains

a Physician Data Query (PDQ) system that provides online information via the Internet (CancerNet) and by fax (CancerFax) regarding various

cancers, ongoing clinical trials, and individuals

and organizations involved in cancer care. The

University of Pennsylvania also maintains a multimedia cancer information resource on the Internet called OncoLink. The Centers for Disease

Control and Prevention provide online access to

the full text of Morbidity and Mortality Weekly

Report, and has recently launched an online journal called Emerging Infectious Diseases. Several

biomedical journals are also available online.35

Some periodicals, and even complete books

and reports, are becoming available on CD-ROMs

that can be purchased or obtained through many

libraries. (In their current form, however, CDROMs cannot be updated, and must be replaced as

knowledge changes.) Both CD-ROMs and the Internet permit inclusion of graphics, videos, and

sound in textual documents. This helps offset the

complaint that it is not only less pleasant to read

documents on a video screen than on paper, but actually slower.36

Information technology is also making practice

guidelines more readily accessible. The National

Library of Medicine (NLM) offers online access

to practice guidelines developed by AHCPR, and

NCI’s PDQ system includes information on cancer treatment protocols. Private organizations

such as the American Medical Association are

also distributing their practice guidelines on CDROMs and computer diskettes.

In recent years, an international movement

among researchers and clinicians has developed

an approach to clinical problem-solving called evidence-based medicine.

37 It involves systematic

searching and critical appraisal of the research literature to identify findings that can be applied to a

clearly defined clinical problem. This approach

goes beyond the narrative review articles occasionally published in leading clinical journals. It

employs systematic review of the literature, in

which specific items of information are extracted

from each work and compared across works, using structured methods. The most sophisticated

form of systematic review is meta-analysis, or

quantitative synthesis of the statistical results of a

number of studies on a given topic.38 Special journals have been established to summarize and evaluate the vast literature on selected health

problems.39 The Cochrane Collaboration, an international network of researchers, distributes

results of systematic reviews of randomized controlled trials—or the most reliable evidence from

other sources—on selected health problems (beginning with pregnancy and childbirth) in uncopyrighted form via the Internet, as well as on

computer diskettes and CD-ROMs.40 However, it

is unclear how these results will get incorporated

systematically into clinical practice guidelines

and protocols.41

35 H.F. Judson, “Structural Transformations of the Sciences and the End of Peer Review,” Journal of the American Medical Association, vol.

272, No. 2, July 13, 1994, p. 93.

36 J.C. Wyatt, op. cit., footnote 31, p. 1613.

37 W. Rosenberg and A. Donald, “Evidence Based Medicine: An Approach to Clinical Problem-Solving,” British Medical Journal, vol. 310,

No. 6987, Apr. 29, 1995, pp. 1122-1126.

38 U.S. Congress, Office of Technology Assessment, Identifying Health Technologies That Work, op. cit., footnote 12, pp. 59-65.

39 F. Davidoff et al., “Evidence Based Medicine: A New Journal To Help Doctors Identify the Information They Need,” British Medical

Journal, vol. 310, No. 6987, Apr. 29, 1995, pp. 1085-1086.

40 Cochrane Collaboration, “The Cochrane Collaboration: Preparing, Maintaining, and Disseminating Systematic Reviews of the Effects of

Health Care,” Oxford, England, brochure, n.d.

41 J.C. Wyatt, “Clinical Data Systems, Part 3: Development and Evaluation,” Lancet, vol. 344, No. 8938, Dec. 17, 1994, p. 1687.
132 | Bringing Health Care Online: The Role of Information Technologies

The prospect of making information such as research results readily and inexpensively available

for online query through the Internet has spawned

visions of electronic (online) publishing.

42 Not

only are certain peer-reviewed journals already

available online, but in some disciplines, such as

physics, preprints containing preliminary results

are often distributed over the Internet prior to

printed publication.43 At first glance, this might

appear to reduce the problem of publication bias.

However, in addition to the fact that much of

that bias rests with authors themselves, there are

several other concerns about this prospect. Most

important is the absence of online screening

mechanisms to replace the process of scientific

peer review that seeks to ensure the quality of published research.44 Without such mechanisms for

screening documents for scientific rigor as well as

relevance to one’s interests,45 the increasing problem of information overload could worsen. Moreover, public access to unrefereed preprints of

medical research could lead some people to misuse medications.46 On the other hand, online access to the full text of commercially published

books and journal articles is likely to remain limited until electronic subscription and payment

mechanisms become established and issues regarding intellectual property rights and electronic

copying are resolved.47

Computer-Based Clinical Decision Support

Systems

Increasingly, the traditional sources of clinical decision support are being supplemented by clinical

information systems, mainly at large academic

medical centers. The most rudimentary of these

are library systems or simple data systems48 that

merely display information about the patient and/

or the health problem to the clinician without offering advice based on analysis of that

information. However, some clinical information

systems contain expert systems or knowledgebased systems that do offer advice to the clinician

regarding diagnosis, testing, or treatment.49 The

goal of either simple or knowledge-based decision

support systems is to provide more complete and

accurate information more quickly to the clinician—preferably at the point of care—thereby improving clinical decisionmaking in terms of

patient outcome measures. These benefits to the

clinician presumably outweigh the added burden

of more extensive data collection and entry. Clinical information systems may also contain other

applications besides decision support, such as on42 R.E. LaPorte et al., “The Death of Biomedical Journals,” British Medical Journal, vol. 310, No. 6991, 1387-1390, May 27, 1995, pp.

1085-1086; Judson, op. cit., footnote 35.

43 J.P. Kassirer and M. Angell, “The Internet and the Journal,” Journal of the American Medical Association, vol. 332, No. 25, June 22,

1995, p 1709.

44 Both Judson and LaPorte et al, op. cit., footnote 42, propose an online peer review system in which all readers of a document would

comment on it. LaPorte et al. go further in proposing that readers give each document ratings in various categories. These comments and summary ratings would subsequently be attached to the document for other readers to use in screening. One potential problem with this scenario is

that readers willing to take time to evaluate all documents that they read might well be a small, self-selected, hence unrepresentative group; and

there would be no way to ensure that they were qualified to evaluate the document. Kassirer and Angell discuss the perils of “majority rule”

compared to peer review. Op. cit., footnote 43.

45 LaPorte et al. suggest that software agents could be used to select only documents that meet certain user-specified content criteria. Op. cit.,

footnote 42.

46 Kassirer and Angell, op. cit., footnote 43.

47 U.S. Congress, Office of Technology Assessment, Information Security and Privacy in Network Environments, OTA-TCT-606 (Washington, DC: U.S. Government Printing Office, September 1994), pp. 96-110.

48 Wyatt, op. cit., footnote 41.

49 Wyatt refers to these as advisory systems. Ibid.
Chapter 4 Using Information Technology To Improve the Quality of Health Care | 133

line order entry, that allows the clinician to submit

orders for tests and treatments (including pharmaceuticals).

A knowledge-based system designed for clinical use, sometimes called a clinical decision support system (CDSS), usually involves three basic

components:50

1. Data on the patient being diagnosed or treated

are either entered into the system manually,

captured automatically from diagnostic or

monitoring equipment, or drawn from an electronic patient record.

2. A knowledge base contains rules and decision

algorithms that incorporate knowledge and

judgment about the health problem at hand and

alternative tests and treatments for it, mainly in

the form of “if-then” statements, such as “if the

patient’s potassium is less than 3.0 mEq/dl and

the patient is on digoxin, then warn the clinician to consider potassium supplementation.”51

3. An inference engine combines information

from both the patient data and the knowledge

base to perform specified tasks, outlined in appendix C.

Some CDSSs—usually those developed more recently—employ probabilistic and adaptive approaches, such as fuzzy logic, Bayesian networks,

or neural networks. Others—usually those developed earlier—employ rule-based systems, decision trees, and other deterministic methods,

although probabilistic decision nodes are sometimes employed.52

Many of the major applications of CDSSs were

implemented over the past 15 to 20 years in two

pioneer systems:

 the Health Evaluation through Logical Processing (HELP) system developed by Intermountain Health Care (IHC) and its flagship

institution, LDS Hospital and the University of

Utah in Salt Lake City;53 and

 the Regenstrief Medical Record System

(RMRS), developed by the Regenstrief Institute and Indiana University, initially at Wishard

Memorial Hospital in Indianapolis.54

Components of both of these systems are marketed commercially: HELP by the 3M Co., with

about five installations outside of Utah; and

RMRS by Shared Medical Systems, Inc. (SMS),

with about 10 installations outside of Indiana.

Several other CDSSs, or some of their particular

applications, are also commercially available.

However, most are implemented by clinical researchers in the form of highly specialized, localized, and experimental systems that vary widely

in their levels of development.

Computer-Based Clinical Protocols

The most advanced CDSSs integrate several of

the applications outlined in appendix C into formal clinical protocols. Again, some are based on

deterministic models, while others employ probabilistic and adaptive approaches. Converting a

clinical protocol into computer-based algorithms

forces the developer to use unambiguous terminology, examine the logic of all linkages

50 See D.P. Connelly and S.T. Bennett, “Expert Systems and the Clinical Laboratory Information System,” Clinics in Laboratory Medicine,

vol. 11, No. 1, March 1991, p. 136.

51 R.F. Gibson and B. Middleton, “Health Care Information Management Systems To Support CQI,” Clinical Practice Improvement: A New

Technology for Developing Cost-Effective Quality Health Care, S.D. Horn and D.S.P. Hopkins (eds.)(New York, NY: Faulkner & Gray, 1994),

p. 109.

52 R.A. Miller, “Medical Diagnositc Decision Support Systems—Past, Present, and Future,” Journal of the American Medical Informatics

Association, vol. 1, No. 1, Jan./Feb. 1994, pp. 11-16.

53 See chapter 2 and G.J. Kuperman, R.M. Gardner, and T.A. Pryor, HELP: A Dynamic Hospital Information System, Computers and Medicine Series (New York, NY: Springer-Verlag, 1991).

54 See C.J. McDonald et al., “The Regenstrief Medical Record System: 20 Years of Experience in Hospitals, Clinics, and Neighborhood

Health Centers,” M.D. Computing, vol. 9, No. 4, July/August 1992, pp. 206-217.
134 | Bringing Health Care Online: The Role of Information Technologies

among steps, and—in deterministic models—

specify exact parameters. It also facilitates refinement and updating of the protocol over time,

based on any of the traditional sources of clinical

decision support outlined earlier, plus feedback

from clinicians who use the protocol—particularly the reasons they document for overriding its

recommendations—and from local research on

patient outcomes.

Researchers at Intermountain Health Care55

have developed an approach to quality improvement, called clinical practice improvement, that

essentially combines computer-based protocols,

local research, and the principles of continuous

quality improvement (CQI).56 A protocol is developed for a selected health problem (e.g., acute respiratory distress syndrome) based on review of

relevant literature, clinician judgment, and retrospective analysis of data from the electronic patient record system. The protocol is refined

through discussion and consensus among clinicians, and serves to guide diagnosis and treatment

for the selected health problem. In addition, randomized controlled trials of various alternative

diagnostic and therapeutic procedures for that

problem are conducted, and the protocol is further

refined in light of the results of those trials.

Computer-based clinical protocols may also

prove valuable in a more indirect way. The full potential of CDSSs is constrained by the limitations

of electronic storage devices. Storing complete,

full-text information on all possible health problems and alternative tests and treatments for them

in a manner that permits rapid retrieval of that information at the point of care is prohibitively expensive. However, by distilling selected elements

of full-text information on a particular health

problem and its alternative tests and treatments

into explicit steps, criteria, and parameters, clinical protocols can greatly reduce storage requirements.

Other Potential Benefits of Information

Technology

Both clinical protocol development and local research can benefit from advanced information

technologies. Most patients receive care from

more than one provider, and within a given provider organization there are usually several separate information systems, often one for each

department (inpatient, laboratory, pharmacy,

etc.). Electronic patient record systems and computer networks within and across provider organizations can facilitate the tracking of all care and

outcomes of individual patients over time. These

systems make it easier and more efficient to link

the separate records for a given patient across all

departments and providers, particularly if a common, unique patient identifier is used in all records. The value of assembling patient data across

several departments is illustrated by local research

that used the HELP system at LDS Hospital to

identify specific causes of adverse drug events57

and hospital-acquired infections.58 Computer net55 S.D. Horn and D.S.P. Hopkins (eds.), Clinical Practice Improvement: A New Technology for Developing Cost-Effective Quality Health

Care (New York, NY: Faulkner & Gray, 1994).

56 CQI (also known as total quality management, or TQM) was originally developed in the field of manufacturing and was subsequently

adapted to health care. See W.E. Deming, Common Causes and Special Causes of Improvement: Stable System, Out of Crisis (Cambridge, MA:

MIT Center for Advanced Engineering Study, 1986); D.M. Berwick, “Continuous Improvement as an Ideal in Health Care,” New England Journal of Medicine, vol. 320, No. 1, Jan. 5, 1989, pp. 53-56; Institute of Medicine, Medicare: A Strategy for Quality Assurance, K.N. Lohr (ed.)

(Washington, DC: National Academy Press, 1990), pp. 58-64; S.B. Kritchevsky and B.P. Simmons, “Continuous Quality Improvement: Concepts and Applications for Physician Care,” Journal of the American Medical Association, vol. 266, No. 13, Oct. 2, 1991, pp. 1817-1823; Leape,

op. cit., footnote 3; Leape et al., op. cit., footnote 3.

57 R.S. Evans et al., “Preventing Adverse Drug Events in Hospitalized Patients,” The Annals of Pharmacotherapy, vol. 28, No. 4, April 1994,

pp. 523-527.

58 D.C. Classen et al., “Prophylactic Antibiotics Used To Prevent Surgical Wound Infections,” Horn and Hopkins, op. cit., footnote 55, pp.

217-221.
Chapter 4 Using Information Technology To Improve the Quality of Health Care | 135

works across provider organizations could also

permit wider and faster dissemination of clinical

protocols and the results of generalizable local research, particularly to remote sites.

An indirect but important way for advanced information technologies to enhance the quality of

health care could be improving the outcomes data

used in research on the effectiveness of specific

health services. Electronic patient records, structured data entry, advanced human-computer interfaces, portable computers, and automated data

capture from diagnostic and monitoring equipment could make the collection of patient data not

only faster and easier, but also more complete and

accurate. This could permit more valid and reliable measurement of patient risk factors, clinical

processes, and outcomes. Records or results for

patients with a given health problem but treated in

different ways could be pooled across providers,

creating very large databases for assessing the effectiveness of specific health services. This would

require using health problems, process and outcome measures, and analytical methodologies

that were as similar as possible across providers.

Research based on these improved data could enhance the medical knowledge on which clinical

decision support is based.

From the perspective of physicians, one direct

benefit of using advanced information technology

in medical practice recently became readily apparent: Two malpractice insurance companies began

offering reduced premiums to physicians who use

specific commercial electronic patient record systems.59 This development mainly reflects the improved patient information and documentation of

care that electronic patient records offer, compared with paper-based records.

❚ Continuing Problems in Clinical

Decision Support

Technology Development

As impressive as their applications are, the usefulness of clinical decision support systems can still

be hampered by incomplete, inaccurate, or inaccessible information—problems that advanced

information technologies could help overcome.

As discussed in chapter 2, however, the capabilities of many of the information technologies

employed in CDSSs remain limited and their

costs remain high, posing substantial barriers to

their widespread use. Several technological advances are needed for faster, easier, and more accurate collection, entry, and retrieval of patient

information, and more readily accessible information about the health problem. The needed advances include:

 advanced human-computer interface technologies, particularly voice recognition, for easier

and possibly hands-free input and retrieval of

information;

 more extensive use of structured data entry,

such as on-screen forms and menus and prepared blocks of text, to ensure complete data

collection and reduce keying errors;

 smaller, more portable computers that can link

into larger computer networks, either through

wireless technologies or docking stations;

 improved wireless technologies that minimize

such limitations as the restricted range and

placement of infrared technologies that use

line-of-sight transmission, or the electromagnetic interference generated by radio-wave

transmission;

59 “Malpractice Insurers Offer Discounts for Doctors Using Electronic Records,” Health Data Management, February 1995, p. 14.
136 | Bringing Health Care Online: The Role of Information Technologies

 more efficient methods of filtering and summarizing the enormous quantities of data captured

directly from diagnostic and monitoring equipment, such as focusing on abnormal data values

and trends;

 higher capacity and more flexible electronic

storage devices, such as updatable CD-ROMs;

 higher resolution computer displays;

 more powerful and flexible graphics software;

 improved technologies for capturing and storing digitized radiographic images, full-motion

videos, and sound recordings, and faster methods of retrieving such information;

 faster and more flexible methods of online

query using relational databases;

 higher capacity telecommunications equipment and transmission lines; and

 more complete coverage of the research literature by online bibliographic databases.

As one researcher put it:

[Clinicians] need a system that is easy to use:

computer terminals must be ubiquitous, system

response must be immediate (not seconds), necessary data should always be on-line, accessible,

and confidential, and very little training should

be required.60

In addition, system down time must be at an absolute minimum, and data should be retained for

as long as possible without diminishing system response times. Systems that meet all the needs of

clinicians may have to be developed in-house

rather than adapted from commercial products.61

Standards Development

The issues regarding standards development discussed in chapters 2 and 3 apply here as well.

However, some additional aspects of these topics

and issues that apply to clinical decision support

require further discussion.

Messaging standards

At first glance, it might appear that the development of messaging standards for electronic exchange of information among disparate computer

systems is less important in clinical decision support than in other health care applications of advanced information technologies, such as

electronic claims payment. Clinical decision support is inherently localized—that is, specific to individual providers—whereas electronic commerce

involves transactions among providers and between providers and other parties. Nevertheless,

most patients receive care from more than one

provider and from several departments within a

given organization. Thus, messaging standards

and common, unique patient and provider identifiers could facilitate patient record linkage

through computer networks. (At the same time,

standards for protecting patient and provider privacy would need to be developed and enforced—

see chapter 3.) Such standards could also

encourage wider and faster dissemination of clinical protocols and local research results, and could

enable providers with different types of computer

systems to access various central repositories of

medical knowledge.

Clinical information content

In theory, clinical decision support could also

benefit from further development of standards for

clinical information content—mainly common

medical nomenclatures and uniform coding systems for diagnoses, procedures, and test results—

to help ensure that all needed information is

present and accurate. Some analysts believe the

development of a universal clinical nomenclature

and coding system is critical to the effective use of

information technology to improve the quality of

health care.62 However, developing a truly univer60 Wyatt, op. cit., footnote 41, p. 1682.

61 Ibid., p. 1685.

62 M. Ackerman et al., “Standards for Medical Identifiers, Codes, and Messages Needed To Create an Efficient Computer-Stored Medical

Record,” Journal of the American Medical Informatics Association, vol. 1, No. 1, January./February 1994, pp. 1-7.
Chapter 4 Using Information Technology To Improve the Quality of Health Care | 137

sal system is a difficult task, given the wide variation in existing systems and the intensity of

institutional commitment to those systems. Indeed, some analysts question whether a truly universal system can ever be developed, contending

that “terminology evolves in a context of use” that

cannot be supplanted.63 Instead, “vocabularies

need to be constructed in a manner that preserves

the context of each discipline and ensures translation between disciplines.”64 An alternative to

compiling enumerative systems that attempt to

list all possible terms in advance is a compositional approach. Such systems use basic terms as

building blocks that can be combined in various

ways to form higher level terms tailored to particular applications and specialties.65

NLM has already made some progress in this

area through the ongoing development of its Unified Medical Language System (UMLS), which is

being tested at about 500 sites.66 (Institutions and

individuals receive the software free of charge in

exchange for testing it and commenting on it.) Despite its name, UMLS is not in itself a unified clinical language; rather, it is more a means of

translating among disparate clinical nomenclatures. Its major purpose is to facilitate the retrieval

and integration of biomedical information from

disparate machine-readable sources by mapping

and interpreting over 200,000 specific concepts

across different classification systems, coding

systems, and controlled vocabularies (in which

only one term denotes each concept). The central

component of the UMLS is a Metathesaurus that

essentially links synonyms from disparate vocabularies to a common term.

A separately developed Unified Nursing Language System (UNLS) is being incorporated into

the UMLS.67 A related NLM project is the Integrated Academic Information Management System, which provides grants to academic medical

centers for investigating communications and information processing technologies. These

technologies are designed to facilitate exchange

and interpretation of data among different computer systems, with the ultimate goal of developing integrated health care information systems.68

One such effort is the Arden Syntax, a language

for encoding and sharing medical knowledge

based largely on the HELP and RMRS systems

described earlier.69 The syntax is organized into

separate Medical Logic Modules (MLMs) that

contain sufficient logic to make a single medical

decision, running automatically in conjunction

with a program known as an event monitor. The

syntax offers the ability to query clinical databases, many of which have been found to be compatible with the syntax. Six institutions are

actively using the syntax, and three others are reviewing it. MLMs have been used to generate

alerts, interpretations, diagnoses, screening for

clinical research, quality assurance functions, and

administrative support. However, they have not

63 Coiera, op. cit., footnote 22, p. 1384.

64 P.F. Brennan, “On the Relevance of Discipline to Informatics,” Journal of the American Medical Informatics Association, vol. 1, No. 2,

Mar./Apr. 1994, p. 200.

65 Coiera, op. cit., footnote 22, p. 1385.

66 D.A. Lindberg, B.L. Humphreys, and A.T. McCray, “The Unified Medical Language System,” Methods of Information in Medicine, vol.

32, No. 4, August 1993, pp. 281-291; A.T. McCray, Chief, Cognitive Sciences Branch, National Library of Medicine, personal communication,

June 8, 1995.

67 K.A. McCormick et al., “Toward Standard Classification Schemes for Nursing Language: Recommendations of the American Nurses

Association Steering Committee on Databases To Support Clinical Nursing Practice,” Journal of the American Medical Informatics Association, vol. 1, No. 6, November/December 1994, pp. 421-427.

68 Coltin and Aronow, op. cit., footnote 2.

69 Columbia-Presbyterian Medical Center, Arden Syntax home page on the World Wide Web <URL:http://www.cpmc.columbia.edu/arden/>, 1995; T.A. Pryor and G. Hripcsak, “The Arden Syntax for Medical Logic Modules,” International Journal of Clinical Monitoring and

Computing, vol. 10, No. 4, November 1993, pp. 215-224.
138 | Bringing Health Care Online: The Role of Information Technologies

been fully validated for clinical use, and not all of

the ones developed are in active use. Nonetheless,

the Arden Syntax has been adopted as a standard

by the American Society for Testing and Materials

(ASTM document E 1460).

Effectiveness and Safety of Clinical Decision

Support Systems

Effectiveness

Evidence regarding the effectiveness of CDSSs in

improving clinical processes and patient outcomes is limited and mixed.70 One review of the development and evaluation of clinical data systems

focused on “simple data systems” that do not offer

clinical advice, but rather simply display information on the patient and/or the health problem.71 It

concluded that these systems improve some clinical processes (accuracy of predictions of patient

progress, number or types of diagnostic tests ordered, and completeness of data collection), but

that there is little evidence of improvement in patient outcomes. Regarding data accuracy, the reviewer noted:

If the system is not interactive, if data are collected largely for billing or administrative purposes, if coding staff are poorly instructed and

trained, and if clinicians are unaware of the system and do not monitor the data, inaccuracy will

be the rule. Reasons for data inaccuracy are

often organisational, not technical.72

Data completeness is improved when the system prompts the clinician or clerk for specific data

items. However, it is less clear whether payment

incentives improve data completeness, or whether

data are more complete when a clinician enters

them directly rather than using encounter forms. It

is also unclear whether using computers saves clinician time; but even if it doesn’t, it will likely improve the quality of data.73

A recent review of systematic studies of the impact of CDSSs on clinician behavior and patient

outcomes found generally positive effects on clinician behavior, although this effect varied according to the type of application performed by

the CDSS.74 Three of four studies of CDSSs for

determining the dose of toxic drugs reported

statistically significant improvements in achieving therapeutic levels. Four of six studies of preventive care reminder systems found significant

increases in the performance of specific immunizations or screening tests. Seven of nine studies

of the impact of CDSSs on active medical care

(e.g., adherence to a protocol for management of

hypertension) found significant positive effects.

On the other hand, only one of five studies of computer-aided diagnosis found a significant improvement in diagnostic accuracy. Moreover,

only three of ten studies of the impact of CDSSs

on patient outcomes found significant effects favoring the use of a CDSS.

More recent studies also demonstrate the

mixed potential of CDSSs. One study found that

computer-based alerts of rising creatinine levels in

hospitalized patients enabled clinicians to change

medications or dosages earlier, thereby decreas70 Wyatt, op. cit., footnote 41; M.E. Johnston et al., “Effects of Computer-based Clinical Decision Support Systems on Clinician Performance and Patient Outcome: A Critical Appraisal of Research,” Annals of Internal Medicine, vol. 120, No. 2, Jan. 15, 1994, pp. 135-142; D.M.

Rind et al., “Effect of Computer-Based Alerts on the Treatment and Outcomes of Hospitalized Patients,” Archives of Internal Medicine, vol. 154,

No. 13, July 11, 1994, pp. 1511-1517; E.S. Berner et al., “Performance of Four Computer-Based Diagnostic Systems,” New England Journal of

Medicine, vol. 330, No. 25, June 23, 1994, pp. 1792-1796; W.A. Knaus et al., “The SUPPORT Prognostic Model: Objective Estimates of Survival for Seriously Ill Hospitalized Adults,” Annals of Internal Medicine, vol. 122, No. 3, Feb. 1, 1995, pp. 191-203.

71 Wyatt, op. cit., footnote 41, p. 1686.

72 Ibid., p. 1684.

73 Wyatt, op. cit., footnote 41, pp. 1684-1686.

74 Johnston et al., op. cit., footnote 70.
Chapter 4 Using Information Technology To Improve the Quality of Health Care | 139

ing the risk of serious renal impairment by more

than half.75 The SUPPORT prognostic model (see

appendix C) predicted survival as well as did a

group of clinicians. However, incorporating the

clinicians’ subjective estimates as predictors in

the model improved both its predictive accuracy

and its ability to identify patients with high probabilities of survival or death.76

Using data describing 105 actual cases that differed in their degree of diagnostic difficulty,

another study evaluated the performance of four

general diagnostic CDSSs: Dxplain, Iliad, Meditel, and QMR (see appendix C). The performance

of these systems on several measures of diagnostic accuracy was compared to diagnoses determined by group consensus among 10 clinical

experts. No single system consistently scored better than the others on all performance measures. A

majority of the diagnoses that the systems listed

were correct (or closely related to the correct diagnosis), but the correct diagnosis usually did not

appear in the top five diagnoses listed by the systems. Moreover, far less than a majority of the

diagnoses they listed were considered relevant.

On average, they listed less than half of the diagnoses identified by the expert clinicians, but they

listed about two additional relevant diagnoses not

originally identified by the clinicians. These results emphasize the potential usefulness of

CDSSs in reminding clinicians of overlooked alternatives, but also the importance of clinician experience and judgment in interpreting and

filtering information.77

Safety

CDSSs, particularly computer-based clinical protocols, may reduce inappropriate practice variations and improve patient outcomes. Yet it is

possible that the most successful CDSSs could become viewed as rigid sets of rules for diagnosing

and/or treating particular health problems. Clinicians might then become overly dependent on

them, adhering to the recommended steps without

question or independent investigation, and allowing their own knowledge, skill, and judgment to

erode as a result.78 Alternatively, systems that

provide too many simultaneous streams of information could cause information overload,

prompting clinicians either to focus on certain

items and neglect other important tasks, or to shun

all such information .79

Any of these developments could adversely affect the quality of patient care and undermine the

interpersonal aspects of patient care (the “quality

of caring”).80 Indeed, there are indications that patients find clinicians less communicative when

using computers to enter patient data. Clinicians

themselves mainly fear that computers might

threaten patient and provider privacy, create legal

or ethical problems, increase government control

of health care, or rely on out-of-date knowledge.81

CDSSs are only as good as the medical knowledge on which they are based. Due to methodological errors in the research underlying a CDSS or to

substantive misinterpretation of research results, a

CDSS may contain incorrect parameters or decision criteria or may overlook crucial steps in the

75 Rind et al., op. cit., footnote 70.

76 Knaus et al., op. cit., footnote 70.

77 Berner et al., op. cit., footnote 70.

78 D. DeMoro, Director, Health Care Professions Council, Service Employees International Union Local 250, Oakland, CA, personal communication, Mar. 29, 1995.

79 D.M. Rind, R. Davis, and C. Safran, “Designing Studies of Computer-Based Alerts and Reminders,” M.D. Computing, vol. 12, No. 2,

Mar.-Apr. 1995, p. 125.

80 DeMoro, op. cit., footnote 78.

81 Wyatt, op. cit., footnote 41, p. 1684
140 | Bringing Health Care Online: The Role of Information Technologies

A patient in the Intensive Care Unit at IDS Hospital in Salt Lake City Utah, is monitored by computer-controlled devices that help

clinicians observe the patient's condition and alert them to unfavorable trends.

diagnosis or treatment of a given health problem.

It could thus mislead a clinician into making decisions that harm patients. One observer points out

that the vast amounts of information that computers can process at lightning speed can make it

virtually impossible for humans to verify that the

results are correct. He recommends that:

■ clinicians have substantial input into the design

and development of a clinical information system,

■ the limitations of the system be clearly spelled

out to the user, and

■ the system itself be designed to explain to the

user exactly what it is doing as it is being

used.82

Assessing Clinical Decision Support Systems

Some analysts have called for rigorous evaluation

of the effectiveness and safety of clinical information systems.83 However, there seems to be little

sentiment for mandatory testing and certification

of such systems by government authorities. Regardless, CDSSs should be used with caution, and

they should be carefully assessed regarding their

82 M.F. Smith, "Are Clinical Information Systems Safe? Clinicians Should Give More Attention to Possible Failures in Their Computer

Systems,” British Medical Journal, vol. 308, No. 6929, Mar. 5, 1994, p. 612.

83 Wyatt, op. cit., footnote 41; Rind, Davis, and Safran, op. cit., footnote 79; R. Wall, “Computer Rx: More Harm Than Good?” Journal of

Medical Systems, vol. 15, Nos. 5/6, December 1991, pp. 321-334; L.I.. Iezzoni, “ ‘Black Box’ Medical Information Systems: A Technology

Needing Assessment,’’ Journal of the American Medical Association, vol. 265, No. 22, June 12, 1991, pp. 3006-3007.
Chapter 4 Using Information Technology To Improve the Quality of Health Care | 141

effectiveness and safety—by their developers and

users, and perhaps by payers and accrediting bodies, if not by the government. As one researcher

put it:

Clinicians should try to judge the claims of

these newcomers in the same cautious way that

they would examine claims about a new drug.84

As pointed out in chapter 2, the U.S. Food and

Drug Administration (FDA) already regulates

medical software as medical devices. Current

policy85 exempts from regulation any software

that is either:

1. general in purpose (e.g., database management

systems or library systems for storing, retrieving, or disseminating health care information);

2. used in education or nonclinical research, or

only in the practice of the provider (practitioner

or institution) that developed it (i.e., without

being disseminated further); or

3. a knowledge-based decision support system

that is “intended to involve competent human

intervention before any impact on human

health occurs (e.g., where clinical judgment

and experience can be used to check and interpret a system’s output).”86

In its definition of research software, the FDA

intends to include software that is distributed free

of charge in source-code form so that it can be examined by other researchers.87 (Commercial software must be distributed as object code that is

designed to be read only by particular computers,

and is thus very difficult for humans to alter.)

In the case of “home-grown” software that is

not distributed beyond the originating institution,

and if the institution conducts research using federal government funds, then the use of such software on human subjects is regulated by the local

Institutional Review Board.88 There are apparently no restrictions on the development and use of

home-grown software in institutions that do not

conduct federally sponsored research, or among

practitioners in private practice. Yet these systems, too, could mislead clinicians into making

decisions that might harm patients. The issue is

whether the FDA should review and/or repeal any

of the exemptions listed above.

It can be argued that regulation of clinical decisionmaking is not within the FDA’s purview, and

that other public and private sector mechanisms,

such as the malpractice system and managed care,

can adequately perform that function. Further, the

effectiveness and safety of clinical information

systems could be assessed by private sector organizations, such as payers or professional societies.

On the other hand, those organizations may not be

capable of performing such assessments, or of

conducting research on the best methods of doing

so.

Assessment of CDSSs can include randomized

controlled trials in which the health outcomes of

patients treated with the aid of a CDSS are

84 Coiera, op. cit., footnote 22, p. 1381.

85 This policy is based on a draft statement published on Nov. 13, 1989 (see footnote 86) that has yet to be formally implemented. The FDA

has used this draft statement as a basis for determining the applicability of the medical device regulations to specific software products on a

case-by-case basis. The agency is in the process of developing formal regulations in this area. H. Rudolph, Acting Director, Office of Science

and Technology, Center for Devices and Radiological Health, U.S. Food and Drug Administration, personal communication, June 30, 1995.

86 U.S. Department of Health and Human Services, Food and Drug Administration, Center for Devices and Radiological Health, Office of

Device Evaluation, “Reviewer Guidance for Computer Controlled Medical Devices Undergoing 510(k) Review” (Rockville, MD: Aug. 29,

1991), pp. 37-40.

87 This new criterion for identifying research software was adopted partly in response to the case involving a radiotherapy dosing product

(see chapter 2, footnote 47). Rudolph, op. cit., footnote 85.

88 Ibid. Each provider institution that conducts research using federal government funds is required to establish an Institutional Review

Board, largely to ensure that required procedures regarding treatment of human subjects—mainly informed consent—are followed.
142 | Bringing Health Care Online: The Role of Information Technologies

compared with those treated by conventional

methods.89 However, numerous complications

can hamper such trials.90 In particular, implementing a CDSS may engender other changes in

practice patterns (e.g., teamwork, consultation,

training, and altered role relationships) that are

more directly responsible for any observed

changes in patient outcomes than is the CDSS itself.

Moreover, random assignment of patients or

clinical staff to comparison groups may not be feasible here.91 If only patients are randomized into

the comparison groups (with the CDSS being

used in one group and not in the other), then clinical staff may carry over CDSS-induced changes in

practice patterns from the treatment group to the

control group. Yet randomizing staff into the comparison groups can disrupt teamwork and alienate

one staff group or the other (e.g., new burdens for

the treatment-group staff or feelings of exclusion

for the control-group staff). Another approach is

to randomize entire staff teams or departments, although such clustering requires much larger samples to maintain precision of estimates. This

approach is similar to the method of the firms trial

in clinical research in which patients are randomly

assigned to similar (parallel) providers who use

different treatments, rather than to different

groups that receive different treatments from the

same provider.92

At a minimum, CDSSs appear to help prevent

clinicians from neglecting or altering basic steps

in specific processes of care. However, it will be a

long time before CDSSs cover every contingency

in those processes, even for highly specific health

problems. Despite the vagaries of clinician experience, memory, and judgment, these will continue

to be essential elements of clinical decisionmaking. As randomized controlled trials and other

forms of effectiveness research increase knowledge regarding which health services truly “work”

for a given health problem, marked deviations

from established standards of practice will become less justifiable. However, there will continue to be room for variation in the judgmental

application of those standards to individual patients in particular settings and locations. CDSSs

must continue to be viewed as aids to clinician experience and judgment, rather than as substitutes

for them; and clinicians must retain the ability to

override the recommendations of CDSSs. At the

same time, clinicians should also be required to

document the reasons for those decisions so that

the CDSSs can be improved over time.

PERFORMANCE ASSESSMENT

❚ Comparison to Clinical Decision

Support

A less direct approach to improving the quality of

health care is assessing the performance of providers and health insurance plans.93 This approach

seeks to:

 evaluate the performance of providers or plans

in delivering health services to patients,

 give providers or plans feedback on their performance to help them improve, and

 give performance information to payers, purchasers, and consumers to help them select providers and plans.

Performance measures can focus on several aspects of patient care. Two of the more important

ones are: 1) the use of specific services that are

considered to be appropriate for a given health

89 Johnston et al., op. cit., footnote 70; Smith, op. cit., footnote 82; Wall, op. cit., footnote 83; J. Wyatt and D. Spiegelhalter, “Evaluating

Medical Expert Systems: What To Test and How?” Medical Informatics, vol. 15, No. 3, July-Sept. 1990, pp. 205-217.

90 Wyatt, op. cit., footnote 41; Rind, Davis, and Safran, op. cit., footnote 79.

91 Ibid.

92 U.S. Congress, Office of Technology Assessment, Identifying Health Technologies That Work, op. cit., footnote 12, pp. 57-58.

93 This approach focuses mainly on providers. Even assessing the performance of insurance plans involves, in part, assessing the performance of the providers employed or contracted by those plans.
Chapter 4 Using Information Technology To Improve the Quality of Health Care | 143

problem, and 2) patient outcomes of those services, usually measured by adverse events such as

deaths, complications, and readmissions. In this

respect, the kinds of information needed to assess

providers or plans are similar to those needed for

clinical decision support: detailed information

about individual patients and their health problems, and the specific health services that individual providers (clinicians or institutions) use to

diagnose, treat, or prevent those problems. The

kinds of technologies required to generate and utilize that information are also similar.

Although, in theory, they should have no bearing on clinical decisionmaking, certain additional

factors (beyond those minimally needed for clinical decision support) may also influence clinicians’ choices of services and affect patient

outcomes.94 These include the patient’s socioeconomic status, social supports (marital status, living arrangements, etc.), and type of health

insurance (e.g., indemnity, prepaid, public, or

uninsured). These factors need to be considered in

assessing provider and plan performance, and perhaps in clinical decision support as well. In addition, the more subjective aspects of the care

process, such as patient satisfaction with the

health services they receive or with various features of insurance plans, are apparently of greater

interest in performance assessment than in clinical

decision support—at least at present.

In examining the link between processes and

outcomes, performance assessment usually focuses on adverse outcomes that result from services already rendered, thus helping to identify

processes that need correcting. In contrast, clinical decision support focuses on selecting services

in advance that are likely to maximize favorable

outcomes and minimize adverse ones. In both approaches, patient risk factors condition the relationship between processes and outcomes.

❚ Relationship to Other Recent Trends

The performance assessment approach to quality

improvement fits with recent trends toward managed care and increased competition among

providers and insurance plans.95 Traditional indemnity insurance and fee-for-service reimbursement are seen as creating incentives for providers

to overuse health services in order to maximize income. Thus, one goal of performance assessment

is to reduce “unnecessary” services, thereby restraining the escalation of health care costs.

On the other hand, managed care—particularly

prepayment for health services—is seen as creating incentives for providers to keep costs lower

than the prepayment amount. One way to do this is

to reduce the volume and intensity of services delivered to patients. If this leads to underuse of services that are “necessary” for the diagnosis,

treatment, or prevention of a given health problem, then patients’ health status could be adversely affected. Thus, another goal of performance

assessment is to monitor patient outcomes and

rates of use of services that are presumed to improve those outcomes.

The performance assessment approach assumes that giving providers feedback on their per94 J.S. Feinstein, “The Relationship Between Socioeconomic Status and Health: A Review of the Literature,” The Milbank Quarterly, vol.

71, No. 2, 1993, pp. 279-322; N.E. Adler et al., “Socioeconomic Inequalities in Health: No Easy Solution,” Journal of the American Medical

Association, vol. 269, No. 24, June 23/30, 1993, pp. 3140-3145; H.R. Burstin, S.R. Lipsitz, and T.A. Brennan, “Socioeconomic Status and Risk

for Substandard Medical Care,” Journal of the American Medical Association, vol. 268, No. 17, Nov. 4, 1992, pp. 2383-2387; J. Hadley, E.P.

Steinberg, and J. Feder, “Comparison of Uninsured and Privately Insured Hospital Patients: Condition on Admission, Resource Use, and Outcome,” Journal of the American Medical Association, vol. 265, No. 3, Jan. 16, 1991, pp. 374-379.

95 See R. Lavizzo-Mourey, “Measuring Quality in Health Care Reform,” Journal of Health Care for the Poor and Underserved, vol. 5, No.

3, 1994, pp. 202-211; J.E. Sisk and S.A. Glied, “Innovation Under Federal Health Care Reform,” Health Affairs, vol. 13, No. 3, summer 1994,

pp. 82-97; Health Care Quality Alliance, Quality Considerations: An Analysis of Federal Health Care Reform Plans (Washington, DC: Health

Care Quality Alliance, July 1994); C. Anderson, “Measuring What Works in Health Care,” Science, vol. 263, No. 25, Feb. 25, 1994, pp.

1080-1082.
144 | Bringing Health Care Online: The Role of Information Technologies

formance in terms of patient outcomes encourages

them to improve their processes of care by selecting the most effective services for a given health

problem. Identification and correction of problems in production processes is one major component of CQI in manufacturing, an approach that

was subsequently adapted to the health care industry. More recently, managed care organizations

and even pharmaceutical companies have sought

to adapt the CQI approach to the management of

specific chronic, costly health problems, such as

diabetes, asthma, and high blood pressure, across

all care settings. In part, this approach, known as

disease management, involves practice guidelines, outcomes measurement, and feedback to

providers and insurance plans.96 At the same time,

employers and health plans have sought to deal

with the rising cost of pharmaceuticals through

pharmacy benefit management, which employs

techniques of disease management as well as

pharmacy networks, negotiated discounts and rebates, lists of preferred drugs, and online utilization review.97

All of these related approaches rest on the following series of assumptions. The most effective

services also tend to be the most cost-effective

ones because, even if they cost more to provide,

their positive impact on patient health status leads

to reduced use and cost of services in the long run.

Thus, giving providers feedback on their performance both improves the quality and reduces the

cost of health care. In addition, distributing performance information to payers, purchasers, and

consumers helps them choose providers that

employ the most cost-effective services for a given health problem. Moreover, if sufficient numbers of payers, purchasers, and consumers use

only those providers that employ the most cost-effective services, then this forces all providers to

use those services and to reduce the prices of those

services. This increased competition among providers induces further improvements in the quality of health care and reductions in its cost.

❚ Performance Indicator Projects (Report

Cards)

In recent years, various groups have sought to develop summary sets of performance indicators

commonly called report cards.

98 Assessments using such indicators are designed to:

1. help consumers, payers, and self-insured purchasers compare and select among providers;

2. help consumers and purchasers select among

insurance plans; or

3. give performance information to accreditation

bodies for providers or insurance plans.

They can also be used to provide feedback to

providers for quality improvement purposes, and

to assist public policy makers in regulating plans

and formulating health policy.99 In addition, providers and insurance plans often tout performance

indicator projects or favorable results in their marketing efforts; others respond by trying to make

process changes that will improve their scores on

performance indicators.100 However, systematic

evidence regarding the impact of performance in96 K. Terry, “Disease Management: Continuous Health-Care Improvement,” Business and Health, April 1995, pp. 64-72; G. Anders, “Drug

Makers Help Manage Patient Care,” Wall Street Journal, May 17, 1995, p. B1.

97 L. Etheredge, Pharmacy Benefit Management: The Right Rx? Briefing Paper, Health Insurance Project, The George Washington University, April 1995.

98 For a critical appraisal of performance indicator projects, see A. Epstein, “Performance Reports on Quality—Prototypes, Problems, and

Prospects,” Journal of the American Medical Association, vol. 333, No. 1, July 6, 1995, pp. 57-61.

99 U.S. Congress, General Accounting Office, Health Care Reform: “Report Cards” Are Useful but Significant Issues Need To Be Addressed, GAO/HEHS-94-219 (Washington, DC: September 1994); J. Mangano, “Report Cards Come of Age,” 1995 Medical Quality Management Sourcebook, K.J. Migdail and M. Youngs (eds.) (New York, NY: Faulkner & Gray, 1994), pp. 1-21.

100 L. Oberman, “How Do Health Plans Perform?” American Medical News, Mar. 20, 1995, pp. 1, 30.
Chapter 4 Using Information Technology To Improve the Quality of Health Care | 145

dicator projects on provider or plan behavior is

lacking.

Perhaps the earliest and best-known performance indicator project was the effort by HCFA to

assess mortality rates among Medicare patients in

every hospital in the nation. Reports were released

annually to the public beginning in 1986, but were

suspended in 1993 due, in part, to criticism of

HCFA’s methodology,101 particularly regarding

risk adjustment.

102 As a supplement to its Peer

Review Organization program of quality assurance, HCFA is developing a new set of performance indicators for ambulatory care, known as

Developing and Evaluating Methods to Promote

Ambulatory Care Quality (DEMPAQ).103 Another government project is the U.S. Public Health

Service’s Year 2000 Health Objectives for the Nation, comprised of population-based measures of

health promotion and disease prevention, such as

infant mortality rates.104

In the private sector, the National Committee

for Quality Assurance (NCQA) developed the

Health Plan Employer Data and Information Set

(HEDIS) as part of its oversight of health insurance plans (largely managed care organizations).105 Box 4-1 summarizes the measures used

in HEDIS. Like many performance indicator projects, the HEDIS measures focus on processes of

care, that is, utilization of presumably appropriate

services among certain groups of plan members,

and the accessibility or availability of those services. Of the HEDIS “quality of care” measures,

only hospitalization for asthma and low birth

weight represent patient outcomes. Moreover,

none of the HEDIS measures is adjusted for member or patient risk factors. HCFA is in the process

of adapting the HEDIS model to its Medicare and

Medicaid programs.106

In 1994, NCQA conducted a one-year pilot

test of 28 of the HEDIS measures using data

from 21 health plans throughout the United States.

(The pilot study also included a survey of enrollee

satisfaction with health plan performance.) The

HEDIS pilot data from each participating plan

were audited for reliability and comparability by

an independent firm. Each audit involved a review

of the overall structure of the plan’s data collection

and processing procedures; a site visit to the plan

by an audit team; verification of the plan’s source

code and specifications; and validation of the

plan’s measures and data. The pilot study identified needs for additional quality measures in key

clinical areas (e.g., mental health), risk adjustment, field testing, improved standardization of

data collection procedures, investment in enhanced clinical information systems, refinement

101 U.S. Congress, General Accounting Office, op. cit., footnote 99; S.T. Fleming, L.L. Hicks, and R.C. Bailey, “Interpreting the Health Care

Financing Administration’s Mortality Statistics,” Medical Care, vol. 33, No. 2, February 1995, pp. 186-201.

102 Risk adjustment is statistical control of patient risk factors in the analysis of the utilization and outcomes of health services. The term also

refers to control of financial risk factors faced by insurance companies. See L.I. Iezzoni, “Risk Adjustment for Medical Outcome Studies,”

Medical Effectiveness Research Data Methods, M.L. Grady, and H.A. Schwartz (eds.), Agency for Health Care Policy and Research, AHCPR

Pub. No. 92-0056 (Rockville, MD: July 1992), pp. 83-97.

103 Delmarva Foundation for Medical Care, Inc., Developing and Evaluating Methods to Promote Ambulatory Care Quality, Final Report

(Washington, DC: August 1994), pp. 1-6.

104 U.S. Department of Health and Human Services, Public Health Service, Healthy People 2000: National Health Promotion and Disease

Prevention Objectives, DHHS Pub. No. (PHS) 91-50212 (Washington, DC: U.S. Government Printing Office, 1991).

105 National Committee for Quality Assurance, Health Employer Data and Information Set and Users’ Manual, Version 2.0 (Washington,

DC: 1993); National Committee for Quality Assurance, HEDIS 2.5: Updated Specifications for HEDIS 2.0 (Washington, DC: January 1995).

106 “HCFA, Outside Groups to Adapt HEDIS for Use in Medicare, Medicaid Programs,” BNA’s Health Care Policy Report, Mar. 27, 1995,

pp. 479-480.
146 Bringing Health Care Online: The Role of Information Technologies

QUALITY OF CARE

Childhood Immunization Rate: Proportion of children who had received specified Immunizations as of

their second birthday.

Cholesterol Screening: Proportion of adults aged 40 to 64 who received a cholesterol test during the

past five years.

Mammography Screening: Proportion of women aged 52 to 64 who received one or more mammograms during the past two years

Cervical Cancer Screening: Proportion of women aged 21 to 64 who received one or more Pap tests

for cervical cancer during the past three years

Low Birthweight: Proportion of all Iive births that were low birthweight (under 2,500 grams) or very low

birthweight (under 1,500 grams) during the past year.

Prenatal Care in First Trimester: Proportion of women with one or more Iive births during the past year

who had one or more prenatal care visits 26 to 44 weeks prior to delivery,

Asthma Inpatient Admission Rate: Proportion of members aged 2 to 19 (or 20 to 39) who had one or

more inpatient discharges with a principal diagnosis of asthma within the past year, also, of those members with such discharges, the proportion who had more than one such discharge.

Diabetic Retinal Exam: Proportion of members aged 31 to 64 with diabetes (i.e., who were dispensed

insulin or oral hypoglycemics) who received a retinal ophthalmoscopic examination during the past

year.

Ambulatory Follow-Up After Hospitalization for Major Affective Disorder: Proportion of members

aged 18 to 64 with an Inpatient discharge for major affective disorder during the past year who had one

or more ambulatory mental health encounters or day/night treatments within 30 days of discharge.

1 The listed measures are used in the set of performance measures for health insurance plans known as the Health Plan Employer

Data and Information Set (HEDIS), Version 25 HEDIS was developed by the National Committee for Quality Assurance (NCQA) as

part of its oversight of managed care plans The categories and titles of the measures are drawn from the NCQA manual, HED/S25

Updated Specifications for HEDIS 20 (Washington, DC January 1995) The descriptions of the measures are OTA summaries of the

detailed specifications presented in that manual. All measures are based on plan members who were continuously enrolled in the plan

during the specified time period. A plan IS a health insurance plan, a member IS a person who is enrolled in the plan

(continued)

of audit procedures, and more research on the crediting hospitals and other institutional

kinds of information consumers need. 107 providers. Implementation of the IMSystem beAnother performance indicator project is the gan in 1994, starting with voluntary participation

Indicator Measurement System (IMSystem) de- by hospitals that could generate the necessary

veloped by the Joint Commission on Accredita- data. 108 Box 4-2 summarizes the measures used in

tion of Healthcare Organizations, as part of its the IMSystem, which are about equally divided

“Agenda for Change” to adopt specific outcome- between process and outcome measures.

oriented measures to support the process of ac107 National Committee for Quality Assurance, Executive Summary for Report Card Pilot Project (Washington, DC: 1995), PP. 1-6.

108 Joint Commission on Accreditation of Healthcare Organizations, IMSystem General Information (Oakbrook Terrace, IL: 1994), PP. 3-6.
Chapter 4 Using Information Technology To Improve the Quality of Health Care 1147

OTHER MEASURES2

Access to Health Services: The proportion of adult members who had one or more provider visits during the past three years, the proportion of primary care physicians accepting additional members, and

average waiting time for a primary care provider appointment.

Member Satisfaction: The proportion of members who are satisfied with the plan, and the percentage

of members of who rate the plan as good, very good, or excellent

Membership: Total number of member years, and the proportion of members who disenroll from the

plan (including those who die), by type of plan health maintenance organization, preferred provider

organization, or point of service/other.

Utilization: Average length of inpatient stay, the number inpatient discharges per 1,000 member years

and the number of inpatient days per 1,000 member years.

Finance: Average revenue per member per month, the percentage change in average revenue, the

loss ratio (percentage of total premiums devoted to expenses), the number of years in business, net

income (revenue minus expenses), and net worth (assets minus Iiabilities).

Health Plan Management and Activities: The percentage of primary care physicians who are board

certified, the percentage of specialist physicians who are board certified, and the percentage of primary care physicians who left the plan

SOURCE: U S Congress, Office of Technology Assessment, 1995, based on National Committee for Quality Assurance, HEDIS 25

Updated Specifications for HEDIS 20 (Washington DC January 1995)

2

These are examples of measures Iisted under categories other than Quality of Care in the HEDIS 25 manual

The IMSystem also adjusts for patient risk factors (demographic traits, complicating health

problems, etc.) by developing an outcome prediction model for each performance measure. Each

model is based on risk factors that contribute significantly to the prediction of that performance

measure. Using a given model, each institution’s

actual sore on the performance measure is

compared to its predicted score. 109 Institutions

that score “worse” than predicted can then investigate the reasons behind those results. IMSystem

reports are available to consumers for $30 per hos -

pital. l10

109 Ibid., pp. 16-18.

Performance indicator projects are also being

conducted by several managed care organizations.

employer coalitions, and state governments, some

using the HEDIS model. Examples include:

United HealthCare Corp. (a national managed

care organization); the Massachusetts Healthcare

Purchaser Group (an employer coalition); and the

states of California, Florida, New York, and Pennsylvania. l11 Moreover, several legislative proposals for national health reform, including the

Clinton Administration’s 1994 plan, have contained mandates for the development of such indi -

110 “JCAHO Releases Data, Gets Blasted by AHA and AMA,” Business and Health, January 1995, p. 16.

111 U.S. Congress, General Accounting Office, op. cit., footnote 99; S. Vibbert et al. (eds. ), The Medical Outcomes & Guidelines Sourcebook

(New York, NY: Faulkner& Gray, 1994); K.J. Migdail and M. Youngs (eds.), 1995 Medical Quality Management Sourcebook (New York, NY.

Faulkner & Gray, 1994).
148 I Bringing Health Care Online: The Role of Information Technologies

Postprocedure Complications (five indicators): Proportion of patients undergoing procedures involving anesthesia administration and an inpatient stay who develop each of the following postprocedure

complications within two postprocedure days.

■ central nervous system complication,

■ peripheral neurological deficit,

■ acute myocardial infarction,

■ cardiac arrest, and

■ Intrahospital mortality.

C-Section: Proportion of deliveries done by Caesarean section.

VBAC: Proportion of patients with a history of previous Caesarean section who deliver by vaginal birth

after Caesarean section.

Low Birthweight: Proportion of Iive births with a blrthweight less than 2,500 grams

Birth Complications: Proportion of Iive-born Infants with a birthweight greater than 2,500 grams who

have one or more of the following complications

■ an Apgar score of less than 4 at 5 minutes,

■ admission to the neonatal intensive care unit within one day of delivery for longer than 24 hours,

■ clinically apparent seizure, or

■ significant birth trauma.

Low Birthweight Complication: Proportion of Iive-born infants with a birthweight greater than 1,000

grams and less than 2,500 grams who have an Apgar score of less than 4 at 5 minutes.

Delayed CABG Recovery: For patients undergoing isolated coronary artery bypass graft (CABG) procedures, the number of days from initial surgery to discharge.

Timely Thrombolytic Therapy: For patients admitted through the emergency department (ED) with a

principal discharge diagnosis of acute myocardial infarction (AMI) and receiving thrombolytic therapy,

the amount of time from ED arrival to administration of thrombolytic therapy.

CHF Diagnostic Accuracy: Proportion of patients with a principal discharge diagnosis of congestive

heart failure who have documented etiology indicating that diagnosis.

Delayed PTCA Recovery: For patients undergoing percutaneous transluminal coronary angioplasty

(PTCA), the number of days from procedure to discharge.

CABG Mortality: Proportion of patients undergoing an isolated coronary artery bypass graft who die in

the hospital.

PTCA Mortality: Proportion of patients undergoing PTCA who die in the hospital.

AMI Mortality: Proportion of patients with a principal discharge diagnosis of AMI who die in the hospital

Cancer Pathology Reporting: Proportion of patients undergoing resection for primary cancer of the

female breast, lung, or colon/rectum for whom a surgical pathology consultation report is present in the

medical record.

1 The measure listed are used in the set of performance indicators for hospitals and other institutuonal providers known as the

IMSystem (Indicator Measurement System) The IMSystem was developed by the Joint Commission on Accreditation of Healthcare

Organizations (JCAHO) for use in JCAHO’s procedures for accrediting such providers OTA adapted and abbreviated the titles and

descriptions of the measures from specifications presented in the JCAHO manual, IMSystern Genera/ Informafion (Chicago, IL Aug.

22, 1994), pp. 8-12

(continued,)
Chapter 4 Using Information Technology To Improve the Quality of Health Care 1149

Tumor Staging: Proportion of patients undergoing resection for primary cancer of the female breast,

lung, or colon/rectum who have stage of tumor designated by a managing physician.

Breast Cancer Testing: Proportion of female patients with Stage I or greater primary breast cancer

undergoing initial biopsy or resection who have estrogen receptor analysts results in the medical record

Lung Cancer Diagnosis/Staging: Proportion of patients with non-small cell primary lung cancer undergoing thoracotomy who have complete surgical resection of tumor.

Colon/Rectum Cancer Preoperative Evaluation: Proportion of patients undergoing resection for primary cancer of the colon/rectum whose preoperative evaluation by a managing physician included examination of the entire colon.

Trauma Monitoring: Proportion of trauma patients with systolic blood pressure, pulse rate, and respiratory rate documented on arrival in the ED and at least hourly for three hours or until ED disposition,

whichever IS earner

Head Trauma Monitoring: Proportion of trauma patients with selected intracranial injuries who have a

Glasgow coma scale score documented on arrival in the ED and at least hourly for three hours or until

ED disposition, whichever IS earner.

Airway Management for Comatose Trauma: Proportion of ED comatose trauma patients with selected

Intracranial Injuries who are discharged from the ED prior to endotracheal intubation or cricothyrotomy

Timely CT Scans: For patients undergoing computerized tomography (CT) scan of the head, the

amount of time from emergency department arrival to initial CT scan.

Timely Neurological Procedures: For patients undergoing selected neurosurgical procedures, the

amount of time from emergency department arrival to procedure.

Timely Orthopedic Procedures: For patients undergoing selected orthopedic procedures, the amount

of time from emergency department arrival to procedure.

Timely Abdominal Procedures: For trauma patients undergoing selected abdominal surgical procedures, the amount of time from emergency department arrival to procedure.

Preventable Death from Pneumothorax/Hemothorax: Proportion of patients who die in the hospital

with a diagnosis of pneumothorax or hemothorax who did not undergo a thoracostomy or thoracotomy.

Preventable Death among Trauma Patients: Proportion of trauma patients with a systolic blood pressure of less than 70 mm Hg within two hours of ED arrival who die in the hospital without undergoing a

Iaparotomy or thoracotomy.

SOURCE: U.S. Congress, Office of Technology Assessment, 1995, based on Joint Commission on Accreditation of Healthcare Organizations, IMSystem General Information (Chicago, IL Aug 22, 1994)

caters to be used in assessing all providers and magazine called Health Pages that reports on the

insurance plans. Private, for-profit companies services and prices of physicians, hospitals, and

have also entered the market for performance in- managed care plans in several cities for $3.95 per

formation, producing reports for sale to the gener- issue. 112

al public. A prominent example is a consumer
150 | Bringing Health Care Online: The Role of Information Technologies

In January 1995, a private, for-profit data analysis firm published a performance report on 10

hospitals in Orange County, California, using raw,

unadjusted Medicare billing data to measure

mortality rates for coronary artery bypass graft

surgery. The $10 purchase price of the report was

partially subsidized by an undisclosed subscription fee from the study’s top-ranking hospital,

which used the results in newspaper advertising.

While this case prompted some observers to call

for regulation of performance measurement methods and reporting—by the industry itself, if not by

the government—others expressed confidence

that “the market will eventually sort itself out.”113

❚ Information Technology and

Performance Assessment

Advanced information technologies could contribute to performance assessment in health care

in two main ways. One is improving the measures

and data on which those assessments are based.

The second is making the results of those assessments, and the measures and data on which they

are based, more readily accessible to payers, purchasers, consumers, and researchers.

By its very nature, performance assessment reviews past performance, and thus cannot feasibly

employ clinical trials and other forms of prospective analysis. Performance assessment thus employs retrospective analysis that involves either

primary data collection or secondary analysis of

available administrative data, or both (as with the

HEDIS and IMSystem measures). Primary data

are collected mainly through: 1) clinician reviews

of paper-based patient records, and 2) surveys of

patients and providers. Administrative data include hospital discharge abstracts, and health insurance claims or encounter records and

enrollment records. Each of these data sources has

certain limitations that advanced information

technologies might help overcome.

Given current information technologies and

analytic methods, tradeoffs exist between primary

and secondary data for assessing provider and

plan performance. A balance must be sought

among several considerations: 1) the clinical detail of the information that can be gathered, 2) the

number of patients that can be included, 3) the cost

per unit of information gathered, and 4) the

amount of time required to obtain and clean the

data. Larger numbers of patients enhance the precision of statistical estimates, and clinical detail is

essential in statistical control for confounding

variables—particularly patient risk factors—that

could affect the provider’s choice of services or

the patient’s outcome.

In general, administrative data can cover very

large numbers of patients at very low cost to the

analyst and can be obtained relatively quickly.

(The time and expense of collecting such data

have already been absorbed by administrative

processes.) However, they can cover only the

more objective measures of care processes (e.g.,

the proportion of diabetics receiving an annual retinal examination) and patient outcomes (e.g., the

proportion of births with low birth weight). Moreover, administrative data contain very little clinical detail to support process and outcome

measures.114

In contrast, primary data collection can cover

more subjective measures (e.g., appropriateness

of a procedure, patient satisfaction with the care

received, patient self-perception of health status

and quality of life, etc.) as well as several of the

more objective ones. Moreover, it can obtain rich

detail on those measures: clinical detail, in the

case of patient record review; and perceptual/attitudinal detail, in the case of surveys. However,

113 “Bypass Surgery Report Ignites Uproar Among Calif. Hospitals,” Report on Medical Guidelines & Outcomes Research, Jan. 26, 1995,

pp. 1, 2, and 12.

114 J.G. Jollis et al., “Discordance of Databases Designed for Claims Payment versus Clinical Information Systems: Implications for Outcomes Research,” Annals of Internal Medicine, vol. 119, No. 8, Oct. 15, 1993, pp. 844-850.
Chapter 4 Using Information Technology To Improve the Quality of Health Care | 151

such data are collected at much greater cost in both

time and money; so they are usually gathered on

far fewer patients, thereby reducing the precision

of statistical estimates. Ideally, all measures

would be obtained in complete clinical detail on

very large numbers of patients very quickly and at

very low cost. This is precisely the vision offered

by advanced information technologies.

A major limitation of readily available administrative data is the absence of measures of various

confounding factors that may affect a provider’s

choice of services or a patient’s outcome, and thus

distort the true effects of the processes of care being evaluated. The most important confounding

variables are patient risk factors (demographic

traits, complicating health problems, etc.). Failing

to adjust adequately for such factors could mislead payers, purchasers, and consumers regarding

provider or plan performance,115 as illustrated by

the recent case involving a private report card on

hospitals in Orange County, California.

Many of the most important patient risk factors

are best measured using detailed clinical data,

such as physical findings and diagnostic test results. Computerization of such clinical information should make it easier to obtain and use in

performance assessments. One approach would

be to require that more clinical information be included in administrative data. In recent years,

payers and government agencies have mandated

increased numbers of diagnosis and procedure

codes and other clinical data elements included in

claims and discharge abstracts. This has greatly

increased the information burden on providers;116

yet it still does not yield the kinds of clinical detail

required for valid performance assessment. Moreover, accuracy problems in diagnosis and procedure coding render those data suspect.117

The more promising approach to providing

needed clinical information is to computerize the

patient record. Rather than having clinically

trained personnel read, interpret, and code the information contained in paper-based patient records, most of the relevant information could be

precoded in the electronic patient record and

readily extracted for analysis. Alternatively, uncoded information (free text) contained in the

electronic patient record could be processed

through advanced methods of pattern recognition,

such as natural language processing (see chapter

2). The usefulness of these capabilities greatly depends on three other aspects of advanced information technologies: input, storage, and retrieval.

That is, to be useful for performance assessment

purposes, the information in the electronic patient

record must be accurately and easily entered (preferably at the point of care) and extracted (usually

at sites other than the point of care, e.g., an analyst’s office). Moreover, storage capacities must

be adequate to handle the huge quantities of information involved.

As stated earlier, computer networks could

make it easier to track the care and outcomes of individual patients by facilitating record linkage

across all providers and departments. Networks

could also make it easier to share patient data, performance measurement algorithms, and assessment results among providers, payers, purchasers,

and researchers to compare the performance of

providers or plans. Like assessing the effectiveness of specific health services, such comparisons

would require using health problems, process and

115 Epstein, op. cit., footnote 98, pp. 58, 60; S. Salem-Schatz et al., “The Case for Case-Mix Adjustment in Practice Profiling: When Good

Apples Look Bad,” Journal of the American Medical Association, vol. 272, No. 11, Sept. 21, 1994, pp. 871-874.

116 D.R. Longo et al., Inventory of External Data Demands Placed on Hospitals (Chicago, IL: The Hospital Research and Educational Trust

of the American Hospital Association, 1990).

117 See L.I. Iezzoni, Risk Adjustment for Measuring Health Care Outcomes (Ann Arbor, MI: Health Administration Press, 1994), pp.

142-167; R.A. Bright, J. Avorn, and D.E. Everitt, “Medicaid Data as a Resource for Epidemiologic Studies: Strengths and Limitations,” Journal

of Clinical Epidemiology, vol. 42, No. 10, 1989, pp. 941-943; J. Whittle, “Large Administrative Database Analysis,” Tools for Evaluating

Health Technologies: Five Background Papers, U.S. Congress, Office of Technology Assessment, OTA-BP-H-142 (Washington, DC: U.S.

Government Printing Office, February 1995), pp. 33-35.
152 | Bringing Health Care Online: The Role of Information Technologies

outcome measures, and analytical methodologies

that are as similar as possible across providers.

These efforts would also be facilitated by messaging standards for electronic exchange of information among different computer systems, and by

methods of translating among disparate clinical

nomenclatures and coding systems.

CONCLUSIONS

❚ Summary of Findings

Advanced information technologies—electronic

patient records, structured data entry, new humancomputer interface technologies, portable computers, automated data capture, relational

databases with online query, knowledge-based

computing, and computer networks—can potentially improve the quality of health care. They

could do so by enhancing clinical decision support

and by improving data for assessing the effectiveness of health services and the performance of

health care providers and insurance plans. Specifically, they could facilitate:

 faster and easier collection and entry of information about the patient’s health problem

and background, with portions of that information being:

—entered by clinicians at or near the point of

care;

—captured directly from diagnostic and monitoring equipment (including digitized radiographic images, full-motion videos, and

sound recordings); or

—entered by the patient prior to care;

 faster, easier, and better targeted search and retrieval (possibly at the point of care) of:

—previously collected information about the

patient; and

—information about the kind of health problem

afflicting the patient and alternative tests and

treatments for it, drawn from local or remote

knowledge bases;

 more flexible organization and display of this

information as appropriate for particular clinicians;

 development of computer-based clinical protocols and other forms of CDSSs that apply decision rules and other knowledge-based

approaches to information about the patient

and the health problem;

 more rigorous construction and analysis of

measures of service effectiveness and provider

and plan performance; and

 more rapid and widespread dissemination of

not only the results of these measures and local

clinical research using CDSSs, but also the patient data, measurement algorithms, and

CDSSs on which those results are based.

Currently, empirical evidence demonstrating

the ability of these technologies to achieve these

goals is limited, mixed, or incomplete. Moreover,

concerns have been raised about possible adverse

effects on the quality of health care arising from

these applications, including:

 incorrect parameters or criteria, or omitted or

altered steps, in clinical decision support systems that could lead to inappropriate care;

 excessive reliance on clinical decision support

systems, which could undermine the ability of

clinicians to exercise professional judgment in

nonroutine cases and reduce the interpersonal

aspects of patient care (“the quality of caring”);

and

 the temptation to use readily available administrative data for assessing the effectiveness of

specific health services or the performance of

providers or insurance plans. If the data are incomplete or inaccurate, the results could be

misleading.

❚ Policy Options

The private sector has been largely responsible for

the development and application of information

technologies in clinical decision support and performance assessment of health care providers and

insurance plans. The federal government’s role

has mainly involved:

 developing information systems and performance measures for its own health insurance

and health care delivery programs, most notably Medicare;
Chapter 4 Using Information Technology To Improve the Quality of Health Care | 153

 funding of intramural and extramural research

and demonstration projects; and

 participating in consensus standards-development processes along with private sector organizations.

All of these activities in both the private and public sectors are likely to continue, with some increasing and others decreasing. In an era of

budgetary and regulatory restraints, however,

major new government initiatives, such as funding for technology development or mandated regulation of clinical information systems, are

unlikely. It can be argued that this is appropriate—

in other words, that the federal government should

not interfere in private market decisions regarding

the selection of new technologies or their applications.

On the other hand, the federal government—

specifically HCFA—is responsible for ensuring

the quality of health care rendered to Medicare and

Medicaid beneficiaries.118 Recent efforts to move

more beneficiaries into managed care have underscored quality concerns, given the expectation

that capitation creates an incentive for underservice.119 Several policy issues regarding the potential impact of information technology on the

quality of care delivered to Medicare and Medicaid beneficiaries deserve the attention of federal

policymakers.

Effectiveness and Safety

The foremost issue is the extent to which clinical

information systems actually change clinical

practice patterns and patient outcomes, and

whether those changes are beneficial to providers

and patients. Empirical research on this issue remains limited, mixed, or incomplete, and more

solid evidence regarding these impacts needs to be

obtained. If these systems do indeed improve the

quality of care, then the next set of issues can be

addressed: What are the most efficient means of

developing and implementing such systems?

Much of the research supporting the development and evaluation of clinical information systems (including CDSSs) has been conducted by

academic institutions and other private sector organizations. Many of these projects have received

grant or contract funding from federal executive

branch agencies, mainly NLM and AHCPR (or its

predecessor, the National Center for Health Services Research, NCHSR). However, there has

been little coordination among these privately and

publicly funded projects in terms of their methods

of evaluating the effectiveness and safety of clinical information systems. The focus of these evaluations should be on the impacts of these systems

on clinical practice patterns and patient outcomes.

Where possible, these evaluations should be conducted prospectively, including randomized controlled trials.

Given its methodological shortcomings, assessing the performance of providers and insurance

plans and disseminating information regarding

that performance to various parties may prove to

be an ineffective approach to improving the quality of health care.120 At present, however, there is

great demand for performance information in both

the public and private sectors; and if such information is going to be produced and used, it should be

as valid and reliable as possible. Advanced information technologies—primarily electronic patient records—promise to improve performance

assessment by making more information on patients, providers, services, and outcomes more

readily available in a more detailed, accurate, and

usable form. Most importantly, such information

could improve methods of risk adjustment for performance indicators that are based on health care

processes and outcomes. Conversely, the development of reliable and valid performance assess118 The state governments share responsibility for the Medicaid program with the federal government.

119 Given a fixed payment per plan member, providers may be tempted to minimize the volume and/or intensity of services rendered for

each patient.

120 Epstein, op cit., footnote 98.
154 | Bringing Health Care Online: The Role of Information Technologies

ment indicators could improve the application of

information technology to health care by identifying the most important data elements to include in

electronic patient records.

Like clinical information systems, much of the

research and development work on performance

assessment and risk adjustment has been conducted by private sector organizations, often with

funding from federal agencies, mainly AHCPR

(or NCHSR) and HCFA. Working with private

sector organizations, HCFA has begun developing the DEMPAQ indicators for ambulatory care

among Medicare beneficiaries and adapting the

privately developed HEDIS system to the Medicaid managed care population. Nonetheless, there

has been little coordination among all of these privately and publicly funded projects on performance assessment and risk adjustment, or

between these projects and those evaluating the

effectiveness and safety of clinical information

systems. The basic issue is whether all of these

federal efforts should continue as they are, or

whether more or less funding and/or coordination

would be appropriate.

Maintain or increase funding for intramural research and extramural grants and contracts to

private sector organizations for research and demonstration projects designed to:

■

■

■

develop and test the reliability and validity of

various methods of measuring and assessing

(with risk adjustment) the performance of providers and health plans;

develop, implement, and evaluate specific systems of risk-adjusted performance indicators;

evaluate the effectiveness and safety of clinical

information systems, including CDSSs.

The FDA could employ the results of the evaluations of clinical information systems in formulating regulations for that class of medical software,

and HCFA could adapt the most promising performance assessment systems for use in its Medicare

and Medicaid programs—as it is now doing with

the Medicaid HEDIS indicators (which are not yet

risk-adjusted). This option would maintain the

current approach of funding research, development, and evaluation programs through several

government agencies, with little coordination

among them. It would thus preserve the autonomy

in program direction currently enjoyed by the various agencies and the consequent diversity in the

types of programs and their results. On the other

hand, HCFA would have to: 1) wait for the needed

performance assessment systems to be developed

and evaluated; and 2) use performance indicators

that still may not be truly appropriate for the

Medicare or Medicaid populations.

Maintain or increase funding for HCFA

to develop and evaluate performance assessment

methods and systems suitable for Medicare and Medicaid enrollees, using intramural research and extramural grants and contracts to private sector organizations

for research and demonstration projects as needed.

This is HCFA’s current approach in developing

the DEMPAQ indicators for ambulatory care

among Medicare beneficiaries. Given that HCFA

is also adapting privately developed indicators

(Medicaid HEDIS), options la and lb are not

mutually exclusive. However, option 1 a would be

more costly than option lb because, under option

1a, development and evaluation funding would be

spread over a broader array of performance assessment systems as well as clinical information systems. From another perspective, more effort could

be concentrated on the information needs of the

Medicare and Medicaid programs for a given

amount of funding. On the other hand, option lb

would sacrifice federal direction of evaluations of

clinical information systems that could be useful

to the FDA in formulating regulations.

Assign the task of coordinating the development and evaluation of performance assessment

methods and systems and clinical information systems

to a single agency

This option could be adopted regardless of

whether option la, option lb, or both were pursued. The designated agency—such as HCFA or

AHCPR—would ensure that all federally funded

projects employ rigorous and uniform methods to

enhance the soundness and comparability of their
Chapter 4 Using Information Technology To Improve the Quality of Health Care | 155

results. In addition, agency personnel would meet

with representatives of private sector corporations, foundations, and research organizations

that also fund or conduct such projects to discuss

the most promising approaches to research, development, and evaluation. This option would require only small additional costs for personnel,

travel, and meetings; yet it could greatly increase

the value and timeliness of project results. On the

other hand, it would diminish the autonomy in

program direction currently enjoyed by the various agencies and the consequent diversity in the

types of programs and their results.

Reduce funding for development and

evaluation of performance assessment methods and

systems and clinical information systems, and direct

HCFA to employ performance assessment methods

and systems developed and evaluated in the private

sector with minimal adaptation.

This option would capitalize on the diverse

array of performance assessment methods and

systems being developed in the private sector. It

would reduce government expenditures, depending on the amount of work needed to adapt privately developed performance assessment

systems to the Medicare or Medicaid populations—which in turn would depend on the initial

suitability of those systems’ indicators. However,

to an even greater extent than with option la,

HCFA would have to: 1) wait for the needed performance assessment systems to be developed and

evaluated in the private sector; and 2) use performance indicators that still may not be truly

appropriate for the Medicare or Medicaid populations.

Until more solid evidence is available regarding the effectiveness and safety of existing clinical

information systems and the reliability and validity of performance assessment systems, more drastic action—such as mandating the testing and

certification of all such systems—is probably not

justified. Legal questions regarding who should

be held liable in situations in which such systems

lead clinicians to make decisions that harm patients are probably best left to the courts to resolve.

Standards and Technology

Assuming that clinical information systems are

found to be effective and safe in terms of their impacts on practice patterns and patient outcomes,

the next set of issues focuses on the most efficient

means of developing and implementing those systems. Three options regarding government involvement in the development of standards and

technology that were presented in chapter 2 warrant additional emphasis here. One is continued

government participation (along with private sector organizations) in the voluntary, cooperative,

public- private process of developing consensus

standards for electronic messaging (exchange of

information among disparate computer systems).

The second is funding and coordinating research

to overcome specific technological barriers (e.g.,

limitations of electronic storage devices). These

actions would not only facilitate the development

and testing of clinical information systems and

performance assessment systems, but would also

enhance the clinical knowledge on which they are

based.

The third option concerns continuation of funding for NLM to develop the Unified Medical

Language System (UMLS). A major problem

confronting the UMLS project is that one of the

most widely used systems for classifying and coding health care services, called the Physicians’

Current Procedural Terminology, Fourth Edition

(CPT-4), is copyrighted by the American Medical

Association (AMA). Thus, the more recent versions of CPT-4 cannot be incorporated into

UMLS. 121 Many major payers currently employ

CPT-4 for “professional” billing by clinicians and

other noninstitutional providers and suppliers, but

also use the International Classification of Dis -

121 McCray, op. cit., footnote 66.
156 | Bringing Health Care Online: The Role of Information Technologies

eases, Ninth Edition, Clinical Modification (ICD9-CM), Volume 3 (Procedures), for billing by inpatient hospitals and other institutional providers.

For payment and other purposes, services rendered by a clinician in an inpatient setting must be

coded using both of these systems, creating additional costs for providers. For many services,

however, the codes in ICD-9-CM cannot be

equated (”crosswalked”) with those in CPT-4 because of substantial structural differences between

the two coding systems.122 Moreover, both

ICD-9-CM (Vol. 3) and CPT-4 have serious technical limitations, such as overlapping and duplicative codes and inconsistent and noncurrent use of

terminology. Most importantly, neither has adequate room for expansion, so both are running out

of codes as new services are created or different

uses of existing services are distinguished. In addition, neither system provides sufficient clinical

detail to support the creation of the kinds of databases required to accurately assess patient outcomes using advanced information technologies.123

Citing these and other problems, the National

Committee on Vital and Health Statistics

(NCVHS), an advisory body to the Secretary of

Health and Human Services, has recommended

the development of a single, unified classification

and coding system that covers all health care services rendered by all providers in all settings, and

that can be used for multiple purposes (reimbursement, research, etc.).124 The NCVHS maintained

that, although implementing such a system would

initially be costly (particularly in the conversion

of computer systems, databases, reimbursement

systems, and documentation), it would save

money in the long run through administrative simplification; more accurate coding and documentation; encouragement of automation and uniform

terminology, data collection, and data processing;

better monitoring and detection of errors, fraud,

and ineffective procedures; and reduced training

costs.125

Legislation that would have required the development of such a system was introduced in the

103d Congress (H.R. 1255), but was tabled in favor of incorporation into broader health care reform legislation that subsequently did not pass.126

A survey of users of ICD-9-CM (Vol. 3) and

CPT-4 found extensive dissatisfaction with them

and widespread support for the concept of a

single, unified system. Opposition to this concept

was expressed mainly by physicians and representatives of medical organizations.127 On the other

hand, concern has been expressed about the proprietary nature of CPT-4 and the AMA’s role in

maintaining a system that is widely used for public purposes.128

122 For example, in CPT-4 the code for total abdominal hysterectomy (58150) includes procedures performed with or without removal of

ovaries or fallopian tubes, whereas ICD-9-CM (Vol. 3) has separate codes for total abdominal hysterectomy (68.4) and removal of ovaries and/

or tubes (65.3 through 65.6). Thus, the CPT-4 code cannot be used to identify patients who had undergone only a total abdominal hysterectomy

(without removal of ovaries or fallopian tubes). See American Medical Association, Physicians’ Current Procedural Terminology, 1994 (Chicago, IL: September 1993), p. 355, and Practice Management Information Corp., International Classification of Diseases, 9th Revision, Clinical Modification, Fourth Edition, 1993 (Los Angeles, CA: 1993), pp. 935, 937.

123 Iezzoni, Risk Adjustment for Measuring Health Care Outcomes, op. cit., footnote 117, pp. 164-167; Whittle, op. cit., footnote 117; U.S.

Department of Health and Human Services, Public Health Service, National Committee on Vital and Health Statistics, The National Committee

on Vital and Health Statistics, 1993 (Washington, DC: May 1994), pp. 8-10, 54-75.

124 U.S. Department of Health and Human Services, Public Health Service, National Committee on Vital and Health Statistics, op. cit., footnote 123, pp. 54-55.

125 Ibid., pp. 59-62.

126 Ibid., p. 56.

127 Ibid., pp. 56-58.

128 Ibid., p. 60.
Chapter 4 Using Information Technology To lmprove the Quality of Health Care | 157

The NCVHS concluded that existing service

classification and coding systems “are structurally flawed and wastefully redundant,” and that neither ICD-9-CM (Vol. 3) nor CPT-4 “can be ‘fixed’

without a complete overhaul (that is, creating a

new classification).”] 29 Yet in 1994, even HCFA

reaffirmed its intention to continue this dual coding system policy in its Medicare and Medicaid

programs, despite the substantial barriers this

poses to efficient information processing and

analysis. l30 Although the agency intends to conduct a pilot study on the feasibility of modifying

or replacing ICD-9-CM (Vol. 3), and will remain

open to ideas regarding a unified system, HCFA

intends to continue its use of CPT-4 and its “cooperative relationship with the AMA.”l31

Provide additional funding for intramural and extramural research on the feasibility of developing a single classification and coding system that

could be applied to all health care services performed

by all providers in all settings.

Although this research could be conducted or

directed by a single agency (such as NLM, HCFA,

or AHCPR), extensive involvement by and cooperation with other agencies, private sector organizations (providers, payers, research associations, and particularly the AMA), and the World

Health Organization (WHO) would be essential.

If such a classification system were developed,

NLM could then incorporate it into UMLS. This

research would incur modest additional cost, and

would further delay development of a unified service classification and coding system.

Establish a new executive branch program to develop a unified service classification and

coding system.

This option would bypass research on the feasibility of developing such a system (option 2a).

Again, the program to develop a new system could

be conducted by one or more executive branch

agencies, with extensive input from other agencies, private sector organizations, and WHO. This

option would also incur larger additional costs

than option 2a; however, it could expedite development of the new system. On the other hand, it

would be more objectionable to parties that are

committed to the current dual coding system

policy.

Once a unified service classification

and coding system is developed, mandate that all federal agencies that manage health insurance and health

care delivery programs use that system in those programs.

In addition to HCFA, these agencies include the

Department of Defense, the Department of Veterans Affairs, and the Indian Health Service. Promoting efficient information processing and

analysis in these programs would seem warranted,

considering the government’s enormous investment in them. Given the magnitude of these programs in the health care marketplace, most private

payers would probably soon adopt the new unified

service classification and coding system, just as

they began using the ICD-9-CM system after

HCFA implemented it. On the other hand, such a

129 Ibid., p. 54.

130 U.S. Deparment Health and Human Services, Public Health Service, National Committee on Vital and Health Statistics, Subcommittee on Medical Classification Systems, Meeting Minutes, Washington, DC, Apr. 18, 1994, pp. 5-7, 9-10, For physician and supplier billing,

HCFA actually uses its own system, called the HCFA Common Procedure Coding System (HCPCS), that incorporates CPT-4 but also contains

additional codes.

131 Ibid., p. 5. In another manifestation of this relationship, HCFA and the AMA recently formed the National Uniform Claim committee,

“designed to give physicians more of a say in the creation and implementation of standards for electronic claims processing.” This move has

been harshly criticized by some participants in the existing voluntary, cooperative, public-private process of consensus standards development.

“Yet Another Group Prepares To Work on Claims Standards,” Health Data Management, May 1995, p. 14.
158 I Bringing Health Care Online: The Role of Information Technologies

mandatory approach would probably be the most

objectionable option to parties that are committed

to the current dual coding system policy.

Provide minimal funding for monitoring

and facilitating private sector development of a unified

service classification and coding system.

Rather than mandating and/or funding the development of a unified service classification and

coding system, Congress could continue to leave

the development of such a system to the private

sector. Minimal funding could be provided for existing agencies (e.g., NLM) and committees (e.g.,

NCVHS) to monitor private sector activities and

to facilitate those activities—for example, by

sponsoring meetings among interested parties.

This option would capitalize on the existing voluntary, cooperative, public-private process of developing consensus standards. It would also be the

least objectionable option to parties that are committed to the current dual coding system policy,

and it would only marginally increase government

expenditures. Its major drawback would be the

long period of time that would probably be required for the consensus standards-development

process to produce the needed system.
Telemedicine:

Remote Access to

Health Services

 and Information

elemedicine can be broadly defined as the use of information technology to deliver medical services and information from one location to another. Since the 1960s,

telecommunication has been used to exchange medical

information between sites in both rural and urban areas. One of

the earliest applications of telemedicine was at the University of

Nebraska where two-way, closed-circuit microwave television

was used for psychiatric consultations. Another was in Boston,

where a video link was established between a health clinic at Logan Airport and the Massachusetts General Hospital. The National Aeronautics and Space Administration (NASA) also was a

pioneer in the 1960s with its satellite support of a telemedicine

project, conducted by the National Library of Medicine (NLM),

that provided health services to the Appalachian and Rocky

Mountain regions and Alaska. In the 1970s, NASA also sponsored the STARPAHC (Space Technology Applied to Rural Papago Advanced Health Care) project, implemented with the

Indian Health Service and the Department of Health, Education

and Welfare on the Papago Indian Reservation in Arizona. 

Early expansion of telemedicine was affected, however, by the

cost and limitations of the technology. Recent technological advances—such as fiber optics, integrated services digital networks

(ISDN), and compressed video—have eliminated or minimized

many of these problems, fostering a resurgence of private- and

public-sector interest in the potential of telemedicine to lower

costs, improve quality, and increase access to health care, especially for those who live in remote or underserved areas. The

technology is not only better; it is also becoming cheaper.

While telemedicine has been practiced for more than 30 years,

its current iteration is still in the early stages of development. One | 159
160 | Bringing Health Care Online: The Role of Information Technologies

recent journal article remarked that: “Telemedicine is on its way (although it has not yet arrived).”1 Others believe that telemedicine has now

come into its own.

Having now come of age, telemedicine has

the potential of having a greater impact on the

future of medicine than any other modality . . . Telemedicine is, in the final analysis,

bringing reality to the vision of an enhanced accessibility of medical care and a global network

of health care.2

It may be a number of years before telemedicine is used widely enough and evaluated sufficiently in terms of its effectiveness and efficiency

for definitive statements to be made about its

overall value and recommended uses. Like all new

technologies, there will be impacts that cannot be

anticipated in advance. Rigorous evaluation studies are needed to determine telemedicine’s potential benefits, and such research is beginning to

take place.

With Congress, the Administration, the health

care industry, and consumers all searching for

ways to reduce the costs of delivering health care,

the potential of telemedicine has been receiving

careful scrutiny. A number of bills directly related

to telemedicine were introduced in the 103d Congress; so far in the 104th Congress, four bills have

been introduced that refer to telemedicine. The

Administration’s Information Infrastructure Task

Force is considering the role that information

technology can play in delivering health services

more efficiently and effectively as part of the

National Information Infrastructure (NII) initiative. A task force subgroup of representatives

from federal agencies is addressing the current

status and potential of telemedicine. Telemedicine

also has important international implications, and

organizations like the World Health Organization

and the European Commission are exploring its

potential as well.

TELEMEDICINE’S POTENTIAL EFFECTS

Parts of the United States that are sparsely populated continue to have difficulty attracting and retaining health professionals, as well as supporting

local hospitals and clinics. An earlier OTA report

outlined the ongoing problems of delivering adequate, high-quality health care to people who live

in rural areas.3 Since the report was released in

1990, the problems rural residents face in accessing health care have not changed substantially,

although there have been some selected improvements. Although access to physicians continues to

be limited and rural hospitals continue to close,

the financial picture for rural hospitals that remain

open has improved somewhat.4

One physician, discussing the potential benefits of telemedicine, described the problems facing rural health care this way:

What do you call a place the size of New York

State with almost no medical, surgical, or pediatric subspecialists? . . . Western Kansas. This

area has been medically underserved for generations. Subspecialty access has not been the only

difficulty. There are also serious problems with

the retention of primary care physicians, the

provision of nursing education and emergency

room coverage, and the financial health of rural

hospitals. The primary challenge has been geographic—and until recently there did not seem

1 E.A. Franken et al., “Telemedicine and Teleradiology: A Tale of Two Cultures,” Telemedicine Journal, vol. 1, No. 1, spring 1995, p. 7.

2 Michael E. DeBakey, “Telemedicine Has Now Come of Age,” Telemedicine Journal, vol. 1, No. 1, spring 1995, p. 4

3 U.S. Congress, Office of Technology Assessment, Health Care in Rural America, OTA-H-434 (Washington, DC: U.S. Government Printing Office, September 1990).

4 “Health Care in Rural America,” statement of the Office of Technology Assessment at a hearing of the Senate Committee on Agriculture,

Nutrition, and Forestry, June 9, 1994.
Chapter 5 Telemedicine: Remote Access to Health Services and Information | 161

to be any way adequately to confront the challenge.5

There are a number of reasons why isolated

areas have difficulty attracting and retaining

health care professionals. Medical practice is

often more demanding and less lucrative than in

larger centers. Providers may also feel isolated

from mentors, colleagues, and the information resources necessary to support them personally and

professionally. Equipment may be less up to date

and facilities less than adequate. Similar problems

often plague the delivery of health care to large inner-city populations. Telemedicine is a tool that

may help address the problem of provider distribution by improving communication capabilities and providing convenient access to up-to-date

information, consultations, and other forms of

support.6

The use of telecommunications to deliver

health services has the potential to reduce costs,

improve quality, and improve access to care in rural and other underserved areas of the country. Although the extent of this potential is largely

speculative at this time, researchers are beginning

to address telemedicine’s impacts. According to

one researcher:

. . . telemedicine may be unique in having the

potential for introducing low-cost, high-efficiency components that may, under certain

conditions, increase access to care while possibly limiting increases in cost by enhancing

health outcomes.7

If research results prove to be largely positive,

telemedicine is likely to become fairly routine

over the next 10 to 20 years.8

One thing is certain—no single technological

solution will work for all communities. Each location is unique, and systems designed to address

access problems must be tailored to meet the particular needs and culture of each community,

whether rural or urban. As noted in an earlier OTA

report, communities are endowed differently with

respect to their cultures, locations, landscapes,

and natural and human resources, as well as their

access to information technologies.9

❚ Costs of Delivering Health Care

Determining the costs of delivering medical services is a difficult task under any circumstances.

It is even more complicated when dealing with a

technical application like telemedicine where so

many aspects of its practice are still unknown.

Comparing the cost of telemedicine with the delivery of conventional medical services is one approach. However, it is important to keep in mind

that, in reality, the practice of telemedicine will assume its own characteristics and may ultimately

be quite different from previous models. Another

approach might be to compare telemedicine to

other ways of increasing access to specialist care

(i.e., visiting consultant clinics or satellite clinics).10 The cost of telemedicine needs to be considered in relation to how it contributes to

5 Ace Allen, “Telemedicine in Kansas: Introduction,” Kansas Medicine, vol. 93, No. 12, December 1992, p. 322.

6 See Daniel McCarthy, “The Virtual Health Economy: Telemedicine and the Supply of Primary Care Physicians in Rural America,” American Journal of Law & Medicine, vol. 21, No. 1, 1995.

7 R.L. Bashshur, “On the Definition and Evaluation of Telemedicine,” Telemedicine Journal, vol. 1, No. 1, spring 1995, p. 23.

8 Jim Grigsby et al., “Analysis of Expansion of Access to Care Through Use of Telemedicine, Report 4: Study Summary and Recommendations for Further Research,” Center for Health Policy Research, Denver, CO, December 1994, p. 3.2.

9 U.S. Congress, Office of Technology Assessment, Rural America at the Crossroads: Networking for the Future, OTA-TCT-471 (Washington, DC: U.S. Government Printing Office, April 1991), p. 7.

10 Michael G. Kienzle, Project Director, University of Iowa National Laboratory for the Study of Rural Telemedicine, Iowa City, IA, personal communication, May 10, 1995.
162 | Bringing Health Care Online: The Role of Information Technologies

improving the health of the population by preventing disease, treating illness, and ameliorating pain

and suffering, and how it compares with alternative systems.11

A recent report prepared for the Health Care Financing Administration (HCFA) that included an

extensive literature review of telemedicine research found no studies that provided an adequate

overview of its cost-effectiveness.12 Although it

is too soon to know whether the use of telecommunications to deliver health care services will actually lower costs, it would seem to have the

potential to do so for some participants. For example, telemedicine can eliminate time and wages

lost at work and traveling expenses incurred when

specialists and/or patients have to travel for consultations. In addition, keeping patients in their

own communities can increase local hospital revenues and decrease the cost to patients. The cost of

a bed in a community hospital is considerably less

than in a large medical center. Costs might also be

reduced by staffing hospitals and clinics with allied health professionals, such as nurse practitioners and physician assistants, who would deliver

services where there is no resident physician.

These providers could be assisted and monitored

remotely by physicians using a telecommunications link. In some cases, overall costs might also

be lowered using telemedicine if patients are

treated sooner when their illnesses are less severe.

However, if earlier diagnosis leads to an expensive course of treatment that would otherwise not

have been provided, costs could increase.

An earlier OTA report noted that one of the

greatest problems rural hospitals face is the outmigration of residents to urban areas for care.13

Many hospitals in small communities have been

forced to close because their bed census dropped

so low they became uneconomical to operate. The

economic impact on a small community when its

hospital closes is enormous. In addition to reducing access to care, such closures have a major impact on employment opportunities. The viability

of small hospitals might improve if telemedicine

allowed more patients to receive consultative services locally, rather than being referred to large

medical centers.

In addition to cost considerations, it is important not to lose sight of the value of telemedicine in

delivering services or ensuring health care jobs.

Communities suffer when people do not receive

needed care or become unemployed when a hospital closes because it is no longer economically viable. These societal costs are important, but

extremely difficult to measure. As one recent report stated:

. . . improved access and quality, benefits from

preventive care, and rural economic development are difficult to quantify and are likely to be

left out of the cost-effectiveness equation. When

this occurs, the cost-effectiveness analysis will

misrepresent telemedicine’s true benefits and

lead to sub-optimal decisions on whether and

how to invest in these systems.14

While telemedicine might reduce costs in certain cases, there is also the potential that costs may

increase, at least in the short term. A consultation

could represent an additional cost when used for a

patient who would not have been seen by a specialist at all without the availability of telemedi11 For a discussion of cost-benefit analysis and cost-effectiveness analysis, see R.L. Bashshur, “Telemedicine Effects: Cost, Quality and

Access,” Journal of Medical Systems, April 1995.

12 Jim Grigsby et al., “Analysis of Expansion of Access to Care Through Use of Telemedicine and Mobile Health Services, Report 1: Literature Review and Analytic Framework,” December 1993, p. 2.3. The lack of cost-effectiveness data on the use of information technology in

health care delivery is not unusual. An OTA contractor report reviewing such studies as they apply to administrative simplification found little in

the literature. “Estimating the Cost-Effectiveness of Selected Information Technology Applications,” Project HOPE, Center for Health Affairs,

unpublished contractor report prepared for the Office of Technology Assessment, March 1995.

13 U.S. Congress, Office of Technology Assessment, op. cit., footnote 3, p. 12.

14 Office of Rural Health Policy, Health Resources and Services Administration, Public Health Service, Department of Health and Human

Services, Reaching Rural, (Washington, DC: 1994), p. 11.
Chapter 5 Telemedicine: Remote Access to Health Services and Information | 163

cine. 15 However, the advantage of early diagnosis

and treatment using telemedicine may offset later,

more expensive episodes, thereby reducing the

overall costs of care. Concerns have also been

raised about the potential for overutilization or

- fraud if third-party reimbursement for telemedicine consultations becomes widespread, thus

driving up costs. There is also the possibility that

telemedicine might lower costs to patients, but increase costs for Medicare because more people are

provided access to health care.l6 What is not

known is whether real improvements in health status would offset the increase in demand for care,

should either occur.17

■ Access to Health Services

Access to health services is a function of demographic factors such as geography, education, economic status, and age. For patients to have access,

there must be health care providers and adequate

facilities and services to deliver care. In a June

1994 hearing, the Chair of the Congressional Rural Caucus testified:

. . . the primary discussion in rural areas about

health care reform is not focused on the structure

of alliances or the composition of the standard

benefits package, but is concerned about the financial stability of the local hospital or recruitment of a new town doctor. 1 8

Rural and remote areas face special problems

when it comes to delivering health care. For example, the rural population is disproportionately older and poorer. They have more chronic illnesses

For practitioners in rural or other underserved areas,

telemedicine can improve communication capabilities by

providing convenient access to consultants, up-to-date

information, and other forms of support

and more work-related accidents. A large percentage of general physicians are within five years of

retirement.l9

Geography is a critical factor because, traditionally, there has been a shortage of care in areas

where medical providers are less likely to want to

practice, such as rural and inner city locations.20 It

is difficult to recruit and retain health care providers because this type of practice tends to be less lucrative, fails to provide professional interaction

and support, and places high demands on practitioners. Although the number of physicians practicing in rural areas is increasing overall, rural

residents continue to be more than twice as likely

15 Jim Grigsby et al., “Analysis of Expansion of Access to Care Through Use of Telemedicine and Mobile Health Services, Report 2: Case

Studies and Current Status of Telemedicine;” May 1994, p. 3.2.

16 Grigsby er al., Report 4, op. cit., footnote 8, p. 7.6.

17 R.L. Bashshur, School of Public Health, University of Michigan, personal communication, May 15, 1995.

18 Congresswoman Jill Long, Chair, Congressional Rural Caucus, testimony before the Senate Committee on Agriculture, Nutrition and

Forestry, June 9, 1994.

19 Ibid.

20 Ibid.
164 | Bringing Health Care Online: The Role of Information Technologies

as the nation as a whole to face shortages of primary care physicians.21 To help attract and keep physicians, it seems clear that a community’s access

to health services may increasingly depend on

providing practitioners with electronic access to

information, continuing medical education, and

peer support. This may be particularly true for a

new generation of practitioners who are accustomed to using computers in their work.

The availability of telemedicine services may

help rural and other underserved communities

solve some of their problems in accessing health

care by making rural practice more attractive. Online access to information and expert advice may

help rural health care professionals overcome

their sense of isolation from other colleagues and

the lack of access to the up-to-date information

they need to practice effectively. Telemedicine

services also increase the access of rural physicians to medical specialists and vice versa, providing a two-way educational experience. Teachers in

academic medical centers learn about the problems physicians face in a rural practice, which will

help them better prepare medical students for the

realities of practice. Rural physicians gain in two

ways—from the educational experience of interacting with and learning from specialists, and by

having access to formal continuing medical

education courses.22 Some people caution, however, that improving telecommunication links

should not be viewed as a substitute for improved

physician availability in rural areas.23 Citizens

may take the view that they are receiving secondclass medical services if the role of telemedicine is

perceived as a substitute for a health care provider

in their community.

❚ Quality of Care

Experts who assess the quality of conventional

medical care use complicated measures of structure, process, and outcome.24 Structure refers to

staff, equipment, and organization; process refers

to measures of appropriateness, necessity, and

technical quality; and outcome refers to measures

of effectiveness, as well as the patient’s functional

status, health status, and satisfaction and quality

of life.

Because telemedicine is an electronic means to

deliver care, not a specific medical procedure, it

cannot be compared with conventional care in the

same way that individual procedures can be measured.25 Clinical effectiveness has not been demonstrated for all clinical functions using all types

of technology. However, a scale of clinical effectiveness can be constructed to differentiate those

services that have been assessed from those that

are still experimental. Grigsby et al. have suggested one way of demonstrating how the quality

of care delivered using telemedicine could be assessed, based on a number of applications. Their

report suggests four categories of current telemedicine applications:

1. Applications that are plainly effective.

2. Applications that are likely to be effective, but

the implications of implementing them are unclear. They would require further research to

understand their effects.

21 S.M. Korczyk, “Health Care Needs, Resources and Access in Rural America,” a report for the National Rural Electric Cooperative

Association (Washington, DC: National Rural Electric Cooperative Association’s Retirement, Safety and Insurance Department, spring 1994),

p. 14.

22 For a relevant discussion related to education, see U.S. Congress, Office of Technology Assessment, Teachers and Technology: Making

the Connection, OTA-EHR-616 (Washington, DC: U.S. Government Printing Office, April 1995).

23 Korczyk, op. cit., footnote 21, p. 19.

24 For a more complete discussion of quality assessment, see ch. 4, “Information Technologies and the Quality of Health Care.”

25 Grigsby et al., “Analysis of Expansion of Access to Care Through Use of Telemedicine and Mobile Health Services, Report 3: Telemedicine Policy: Quality Assurance, Utilization Reviews, and Coverage,” Center for Health Policy Research, Denver, CO, August 1994, p. 3.3.
Chapter 5 Telemedicine: Remote Access to Health Services and Information 1165

3.

4.

Applications for which the safety and effectiveness are currently unknown, or for which basic

research is required to specify requisite technical parameters.

Applications that are entirely experimental, or

which anticipate the integration of different existing advanced technologies.26

Whether and how telemedicine affects the quality of care delivered has not yet been proven.

However, it is possible to speculate that some aspects of the electronic medical encounter might

provide better care from the patient perspective.

Telemedicine could provide faster, more conve27 The ability to receive the ser- nient treatment.

vices of a specialist without having to leave one’s

community also provides better continuity of

care. Similarly, allowing a patient to remain in the

local hospital with family and friends for support

could improve the quality of the experience for the

patient and could, in fact, contribute to a faster recovery. These benefits would minimize the disruption of the patient’s life and reduce the amount

of working time lost. Followup care seems well

suited to telemedicine, and might be carried out

more effectively and efficiently by electronic

means, thereby avoiding the costs of time and

travel for an office visit.

For the health care provider, telemedicine can

offer tools to assist in providing high-quality services. Having timely, convenient access to the

most up-to-date information, continuing medical

education programs, decision support systems,

and consultations with specialists in large medical

centers should increase the provider’s options and

improve his or her ability to accurately diagnose

and effectively treat patients. The development of

clinical practice guidelines for telemedicine could

enable providers to deliver better care. However,

26 Ibid., p. 3.4.

whether or not telemedicine consultations improve the quality of care will only be known when

the research has been done to determine patient

outcomes.

TELEMEDICINE APPLICATIONS

Telemedicine is broadly defined as the use of information technology to deliver medical services

and information from one location to another.

However, there are differences of opinion regarding what the definition should include.28 Most

agree that it includes applications in areas such as

pathology and radiology, as well as consultations

CLOSE TO HOME JOHN McPHERSON

©1995 John McPherson/Dist by Universal Press Syndicate

8-10

“Mrs. Nortman just sent in this fax of a rash that

she’s got on her stomach.”

27 Norwegian researchers have found that—assessed by criteria for delivering health services in a timely fashion and as close to the patient

residence as possible-telemedicine maintains a higher level of quality than traditional medical services. U. Holand and S. Pedersen. “’Quality

Requirements for Telemedical Services,” Telemedicine, Telektronikk, vol. 89, No. 1, 1993, p. 52.

28 For a discussion of telemedicine definitions, see Bashshur, Op. Ch., footnote 7. pp. 20-22.
166 I Bringing Health Care Online: The Role of Information Technologies

■ Initial urgent evaluation of patients, triage decisions, and pretransfer arrangements.

■ Medical and surgical followup and medication checks.

■ Supervision and consultation for primary care encounters in sites where a physician is not available.

■ Routine consultations and second opinions based on history, physical exam findings, and available test data.

■ Transmission of diagnostic Images.

■ Extended diagnostic work-ups or short-term management of self-limited conditions.

■ Management of chronic diseases and conditions requiring a specialist not available locally.

■ Transmission of medical data.

■ Public health, preventive medicine, and patient education

SOURCE: Grigsby et al., “Analysis of Expansion of Access to Care Through Telemedicine, Report 4, Study Summary and Recommendations for Further Research, ” Center for Health Policy Research, Denver, CO, December 1994, p 43

in specialties such as neurology, dermatology, cardiology, and general medicine. While some consider certain forms of medical education within

the definition, others would exclude the use of

video to transmit purely didactic classroom lec -

tures where there is no direct interaction between

student and teacher. Whatever the definition, telemedicine implies a closer link between the telecommunications infrastructure and the health care

system that includes the entire range of teleservices. 79

Telemedicine can be used for a variety of purposes (see table 5-1 ).30 Some applications of telecommunications in the health field have been in

use longer than others. Teleradiology, for example, has about 30 years’ experience and a literature

dating from the early 1970s. Other applications

are newer, and as yet have produced few research

results. Current telemedicine projects vary with

respect to goals, organization, funding, and

technology. This diversity is shown in brief descriptions of some current telemedicine programs.

■ Teleconsultations

Medical College of Georgia Telemedicine

System

The Telemedicine System was initiated by the

Medical College of Georgia (MCG) in November

1991 when it connected with Dodge County Hospital in Eastman, Georgia, 130 miles away. The

system’s overall goal is to ensure that everyone in

the state has immediate access to quality health

care.

31 The director envisions a telemedicine network that would spread out from a medical center

complex to a number of satellite sites, such as rural hospitals, correctional facilities, and even military bases (see figure 5-1 ). Although the system is

currently used largely for cardiology and neurology consultations, it can be adapted for a variety of

specialties, such as dermatology, ophthalmology,

or gastroenterology through the use of a variety of

camera adapters. In addition to consultations, the

system can also be used to guide certain procedures, such as a endoscopy or laparoscopy. MCG’s

29 Birger J. Nymo, “Telemedicine,” Telektronikk, vol. 89, No. 1, 1993, p. 4.

30 A recent study prepared for HCFA reported findings on the current status of telemedicine in the United states. Grigsby et al., Report 3, op.

cit., footnote 25, pp. 3.1-3.5.

31 J.H. Sanders and F.J. Tedesco, “Telemedicine: Bringing Medical Care to Isolated Communities,” . . Journal of the Medical Association of

Georgia, May 1993, pp. 237-241.
Chapter 5 Telemedicine: Remote Access to Health Services and Information 1167

system is compatible with multiple types of communication systems—telephone, cable, microwave, and satellite. It is also portable and can be

loaded into a van and transported. This is particularly useful for locations that are too small to warrant a system of their own.

The system provides two-way interactive audio/

video communications. It has an open architecture

and individual components can be replaced and

upgraded. Hardware and software are off-theshelf technologies. The equipment includes a video conferencing console with a codec,32 personal

computer, VCR, electronic stethoscope with an

equalizer, a fax machine, CD-ROM, cameras, and

monitors. At the remote site, the doctor has a camera that can be attached to any scope (e.g., microscope or otoscope) to project images for the

consultant. The CD-ROM provides a medical

textbook database, the Scientific American Consult Program, that allows the consulting physician

to call up information on a particular diagnosis

and send it to the remote physician by fax or modem. The Telemedicine Center, with a grant from

the BellSouth Foundation, surveyed physicians

who have used the system. Seventy-eight percent

felt that their use of the system had been satisfactory to highly satisfactory.

The network has been paid for by the State of

Georgia as part of the Georgia statewide communications network. A dedicated T1 communications line is used.33 There are four channels and a

multiplexer. Four to 20 consultations take place

each week. A facilitator is available at both sites

during the consultation to manage paperwork and

videotapes, direct the camera, and operate the

equipment (or help the doctor do it). The setup

cost for each remote site is from $95,000 to

$115,000, and for the MCG hub site from $90,000

to $105,000. These costs include the system,

Rural hospital

Managed health care Military bases

International Medical center Correctional

health centers <----- --------> health care complex

Maritime vessels VTrauma network

Geriatric facilities

SOURCE Jay H Sanders, M D Medical College of Georgia (c) 1993

training, and system support (a teleradiology system costs extra).

The Telemedicine System is state supported:

personnel support is provided by the rural hospitals. The network is being extended statewide. and

consists of two tertiary care academic medical

centers (MCG and Emory) connected to nine secondary hubs that are comprehensive community

hospitals strategically located in a specific health

care region of the state. From each of the tertiary

and secondary hub sites, there will be three or four

spokes going out to primary health care facilities

consisting of rural hospitals, correctional facilities, public health facilities. and Area Health

Education Center sites. Present initiatives also include interfacing this system with all the distance

learning sites in the state so that real-time, interactive preventive and episodic health care can be

provided in the classrooms. Plans arc also in place

32 Codec is an abbreviation for coder/decoder. It is an electronic device that converts an analog electrical signal into a digital form for transmission purposes and decodes it at the receiving end.

33 A T1 line refers to a digital carrier capable of transmitting 1.544 megabits/second, suitable for high-volume voice, data, or compressed

video traffic.
168 | Bringing Health Care Online: The Role of Information Technologies

to interface military health care needs with the civilian hospital backbone. Based on the telecommunication infrastructure put into place to support

the telemedicine system, a patient at any site can

be examined by a physician at any other site. Distance is totally transparent and seamless. MCG

also has plans for a demonstration project that will

monitor certain patients in their homes, the socalled electronic house call, as well as for a desktop telemedicine system for the physicians’ offices.

Medicaid and Medicare are currently reimbursing the consultant and the referring physician at

Dodge County Hospital, and Medicaid pays the

rural hospital a facility fee. This reimbursement

was granted by the Medicare carrier (Aetna), and

applies only to the original sites in Georgia and

not to new ones. Blue Cross/Blue Shield reimburses only the consultant. MCG has estimated

that approximately 86 percent of patients who previously would have been transported to MCG now

are kept at the remote sites. The daily cost of a hospital bed in a rural area is placed at approximately

$800, compared with $1,300 at MCG, and the

costs of transportation, increased time away from

work, and delay in therapy represent additional

expenses.

Physicians in remote areas who use the MCG

system for consultations are given credit hours toward meeting their continuing medical education

(CME) requirements, which are necessary for license renewals. They do not have to interrupt their

practice to attend classroom lectures in a different

location. This educational activity becomes directly relevant to their day-to-day practice and

more meaningful than a lecture format.

Texas Telemedicine Project

With funding provided by foundations and vendors, the Texas Telemedicine Project began operations in April 1991. It was established as a

research project to study viability factors potentially operative in a national health care delivery

system. The project uses interactive two-way audio and video to connect sites in Austin with sites

in Giddings, a small town with fewer than 4,000

people.34 The sites in Austin are the Austin State

Hospital, the state headquarters of the Texas

Youth Commission, the Austin Diagnostic Clinic,

and the Texas Telemedicine project office. In Giddings, the Lee Memorial Hospital, a Texas Youth

Commission maximum-security unit, the Giddings Regional Dialysis Clinic, and the Community Mental Health Clinic are connected. Each site

has a unit with video, audio, and high-speed data

transfer channels; ports for a fax and laser printer;

and two 20-inch color monitors, two video cameras, two microphones, and a speaker. T1 telecommunication circuits are provided in part by

Southwestern Bell, GTE, and LDDS. Economies

of scale are produced by scheduled sharing of telecommunication lines.

At night, when emergency triage may be needed for auto accident victims, the system connects

the Giddings Hospital with the Austin Diagnostic

Clinic. In the morning, the Austin Diagnostic

Clinic is connected to the Giddings Dialysis Center to monitor patients coming off and going on

dialysis. Management rounds of each site are

made electronically by Telemedicine Interactive

Consultative Services each day. The Texas Telemedicine Project used a questionnaire for patients

and providers to document problems and satisfaction with the system. Results over the first two

years documented a 99.35 percent satisfaction

rate.

Kansas University Medical Center

Telemedicine in Kansas is a cooperative effort involving the Kansas City and Wichita campuses of

the Kansas University Medical Center (KUMC),

34 Description taken from J. Preston, F.W. Brown, and B. Hartley, “Using Telemedicine To Improve Health Care in Distance Areas,” Hospital and Community Psychiatry, vol. 43, No. 1, January 1992, pp. 29-30; also J. Preston, Director, Texas Telemedicine Project, personal communication, May 14, 1995.
Chapter 5 Telemedicine: Remote Access to Health Services and lnformation| 169

In 1991, before telemedicine was available, physicians from

The University of Kansas Medical Center in Kansas City

Kansas, traveled 270 miles to Hays, Kansas, to visit patients.

the state government, the Northwest Kansas Area

Health Education Center, and nine rural hospitals. 35 The system is designed to provide real-time

medical consultations involving a patient and

practitioner (physician, nurse practitioner, or physician assistant) at the distant end and a specialist

at the medical center. Full-motion, compressed

two-way video is used, and there are facilities for

interfacing imaging equipment, using an electronic stethoscope, for example. Continuing education courses (including courses that provide CME

credit for physicians) are offered over the same

equipment. The system is currently used 20 to 25

percent for clinical applications, 30 percent for

continuing education (nonphysicians), 20 percent

continuing medical education (physicians), and

20 to 25 percent for administrative functions.

Teleconsultations are mainly used to determine

the need for face-to-face treatment or for regular

followup after a face-to-face visit. In 1993, 180

consultations were conducted in 931 hours of total

operations (including continuing education and

administrative uses). In 1994, there were 189 consultations. KUMC estimates that, while telemedicine does not completely replace the need for

In 1995, an oncologist at The University of Kansas Medical

Center in Kansas City, Kansas, consults with a nurse

practitioner at the Hayes Medical Center via an interactive

videoconference without leaving the medical center.

transportation, it can eliminate a significant

amount of travel for patients and specialists.

Use of T1 telecommunications lines in the

State of Kansas network costs $35 per hour for onpeak use and $20 per hour for off-peak; but local

access is expensive, especially if the transmission

has to cross local access transport area (LATA)

boundaries. Hospitals in the telemedicine program are paying between $421 and $1,318 per

month for local access to the nearest point-ofpresence of the State network. Local access

charges for T1 lines are mileage-sensitive.

A telemedicine suite includes one or two

35-inch, 650-line digital monitors, one or two video cameras, graphics stand, slide converter

(35mm to video interface), VCRs, microphones,

and auscultation equipment (wireless stethoscope). The camera at the distant site can be controlled remotely by the physician at the central

site. Any medical imaging equipment that puts

out an NTSC (television) signal can be interfaced

directly, or a videotape made by that equipment

can be played. Radiographic images are transmitted via video camera (use of a digitizing scan35 Description based on site vitie, descriptive material provided; A. Allen, R. Cox, and C. Thomas, “Telemedicine in Kansas,’’ Kansas Medicine, December 1992, pp. 323-325; and A. Allen, Oncologist Telemedicine Project, University of Kansas, personal communication, July 6,

1995.
170 | Bringing Health Care Online: The Role of Information Technologies

ner is far more expensive). All inputs are sent to a

codec, which converts analog signals to digital

ones for transmission. When purchased, the cost

of a basic equipment suite was about $90,000, and

now has dropped closer to $50,000.

The State of Kansas permits educational, medical, county government, and other such organizations to connect to the KANS-A-N state-owned

digital telephone network. The network does not

yet extend to every county, and T1 lines are not yet

available for local access in all counties. The telemedicine application usually uses one-quarter of a

T1 line (384 kb). Compression to this bandwidth

gives some “ghosting” and “tiling” on fast motion, but is acceptable for viewing normal, medically significant motions such as a patient’s gait.

KUMC’s experience is that picture quality for

medical images such as ultrasound, computerized

axial tomography (CT) scans, magnetic resonance

imaging (MRI), or some x-rays is not perceptibly

impaired; however, quality is not good enough for

a mammogram. Picture quality on fast motion is

reportedly better using one-half T1 bandwidth.

The Mayo Clinic

The Mayo Clinic in Rochester, Minnesota, became a major developer of telemedicine in 1987

when it expanded to sites in Scottsdale, Arizona,

and Jacksonville, Florida. Today, Mayo uses telemedicine for clinical care, education, and administrative coordination to integrate the three sites.

Current projects include the use of satellite communications to deliver consultative care to the

Middle East and the use of compressed video and

land lines to deliver a wide range of services to affiliated entities within Iowa, Wisconsin, and Minnesota. Mayo Clinic also provides services for the

Amman Diagnostic Clinic in Jordan. During 12

weeks in 1994, Mayo joined with the Pine Ridge

Indian Reservation and NASA in an experiment to

provide professional education and clinical consulting services to professionals at Pine Ridge.

Based on questionnaires completed by all the participants, it was determined that the project was

both feasible and useful.36

Mayo is collaborating with NASA and the Advanced Research Projects Agency (ARPA) on a

project to use the Advanced Communications and

Technology Satellite (ACTS) to deliver services

to small communities in remote environments.37

In November 1993, Mayo sponsored a telemedicine symposium, and in April 1995 hosted the

Second International Conference on the Medical

Aspects of Telemedicine and Second Annual

Mayo Telemedicine Symposium.

East Carolina University School of Medicine

East Carolina University (ECU) performs telemedicine consultations to the largest prison in North

Carolina and two rural hospitals.38 Physicians see

and talk to the patients via the telemedicine link

and then diagnose and prescribe medications

when necessary. A digital stethoscope, a graphics

camera, and a miniature, handheld dermatology

camera are used to aid in patient examinations.

The working model developed for the prison system is now being expanded to six rural hospitals

and a large naval hospital (see figure 5-2). A

unique aspect of the ECU program is the hybrid

communications network and hardware that have

been integrated. With the addition of an asynchronous transfer mode (ATM) network, this will be

36 T.E. Kottke and M.A. Trapp, “The Pine Ridge Indian Reservation/Mayo Clinic/NASA Telemedicine Project: A Feasibility Study,” presented at the Second International Conference on the Medical Aspects of Telemedicine and Second Annual Mayo Telemedicine Symposium,

Rochester, MN, Apr. 6-9, 1995. See also U.S. Congress, Office of Technology Assessment, Telecommunications Technology and Native Americans: Opportunities and Challenges, OTA-ITC-621 (Washington, DC: U.S. Government Printing Office, August 1995).

37 E.G. Tangalos, Mayo Clinic/Mayo Foundation, Rochester, MN, “Hearing on Telemedicine: An Information Highway To Save Lives,”

held by the Subcommittee on Investigations and Oversight, Committee on Science, Space, and Technology, U.S. House of Representatives,

May 2, 1994, pp. 12-13.

38 Information from East Carolina University School of Medicine, “Telemedicine,” brochure, August 1995; and David Balch, Director,

Rural Eastern Carolina Health Network, personal communication, Aug. 15, 1995.
Chapter 5 Telemedicine: Remote Access to Health Services and Information 1171

Elizabeth

Ahoskie City

●

. Sites linked to ECU

◆ Major NCIH sites

Coastal

Community

SOURCE: East Carolina University, Greenville, NC, 1995

the only telemedicine program in the world operating integrated T1 line microwave and ATM

links. Current Federal support includes grants

from HCFA, the National Telecommunications

and Information Administration (NTIA), and the

Office of Rural Health Policy (ORHP).

ECU recently conducted a demonstration clinic

at a conference in California in which 84 people

were seen in three days via a live ATM link to

ECU. Conference participants were given the opportunity to have a consulting specialist at ECU

listen to their heart beat, examine their ears, look

at a skin lesion, or explore some other medical

problem of interest. Two-way video, audio, and

data were transmitted between the sites.

The Rural Eastern Carolina Health Network

(REACH-TV) (consisting of the ECU School of

Medicine, Pitt County Memorial Hospital, Eastern AHEC, and the Center for Health Sciences

Communication) focuses on telemedicine, teleconferencing/distance learning, and applied research interactive information environments.

RODEO NET Project

The mission of RODEO NET (Rural Options for

Development and Educational Opportunities Network) is “to pioneer advances in improving the delivery of human services by connecting people

using appropriate communication technolo-
172 | Bringing Health Care Online: The Role of Information Technologies

gies.”39 In 1991, the Eastern Oregon Human Services Consortium was awarded a three-year grant

of approximately $700,000 by the Rural Health

Outreach Grant Program of the Office of Rural

Health Policy (Health Resources and Services

Administration) for the purpose of demonstrating

an innovative model of mental health care in a rural area. RODEO NET uses three networks of Oregon ED-NET, which was created by the State of

Oregon in 1989. Network I provides live, interactive one-way video, two-way audio services to 45

“receive” sites in eastern Oregon. Network II provides two-way video, audio, and data services using digitally compressed video technology in 10

studios. COMPASS is a local “dial-up” computer

data network that provides a variety of information services. These include user-friendly access

to local, national, and international databases and

the Internet; government and academic libraries;

bulletin boards; electronic mail; and computerconferencing services.

RODEO NET currently uses all three networks

to train mental health providers in eastern Oregon.

For example, both professional and paraprofessional staff who work with children and adolescents who have severe emotional disturbances and

their families participate in a certificate program

to upgrade staff qualifications. Individual training

is also provided.

In addition to training, RODEO NET provides

crisis response using Network II to enable personnel to access the on-call psychiatrist at the Eastern

Oregon Psychiatric Center in Pendleton to help

deal with persons suffering extreme emotional or

behavioral turmoil. Such a response system often

saves the time and money required to transport an

individual and keeps that person in the community. RODEO NET provides ongoing clinics for

medication management and case consultations

on an ongoing or as needed basis, reducing the

number of admissions to acute care facilities. Interviews for preadmission, predischarge, and

transfers are now accomplished via Network II,

and precommitment and psychiatric review board

hearings are conducted using interactive TV. The

project also plans to work with consumer groups

to help them create their own computer networking conferences within the COMPASS system.

❚ Teleradiology and Telepathology

The use of telecommunications to transmit medical images is quite well developed and widespread.

A teleradiology system acquires radiographic

images at one location and transmits them to one

or more remote sites, where they are displayed on

an interactive display system and/or converted to

hard copy.40 Transmissions might include CAT

scans, MRIs, or x-ray images. CAT scans and

MRIs originate in digital form, but a film digitizer

must be used to convert conventional radiographs

from film to digital form. Teleradiology systems

often employ a wide area network.

Teleradiology systems transmit images from

one hospital to another, from an imaging center to

a hospital, or from an imaging center or hospital to

a radiologist’s office or home. Each requires different technologies and communication links and

each site has different requirements.41 For example, a radiologist who is on call may review an

image in his or her office or at home, but at a later

time will also review the original image before

making a final diagnosis. In this instance, a lower

image resolution, requiring less expensive equipment, may be acceptable. A higher quality image

is required if the radiologist is making a final interpretation without seeing the original image, as

39 Description taken from “RODEO NET Project Summary,” Oct. 25, 1993; and Cathy Britain, Program Manager, RODEO NET, personal

communication, June 1995.

40 For an in-depth description of teleradiology, see S. Batnitzky et al., “Teleradiology: An Assessment,” Radiology, vol. 177, 1990.

41 S.J. Dwyer, III, et al., “Wide Area Network Strategies for Teleradiology Systems,” RadioGraphics, vol. 12, No. 3, May 1993, p. 569.
Chapter 5 Telemedicine: Remote Access to Health Services and Information | 173

in the case of a request for a second opinion or a

hospital that contracts for its radiological interpretations.42

In its study for HCFA, the Center for Health

Policy Research found that, with some exceptions, radiology using telecommunications is feasible.43 For providers, training in the use of the

equipment appears to be a critical component, particularly learning to manipulate and interpret

images using a video image on a monitor. Preliminary research suggests, however, that in most

cases radiologists prefer conventional films and

view boxes to teleradiology because reading them

is less time-consuming and perhaps because they

are more familiar with them.44 The American College of Radiologists is currently evaluating equipment standards and practice parameters.

The field of medical imaging offers one of the

most fertile grounds for the application of advanced computer and communications technologies. All-digital systems, known as picture

archiving and communications systems (PACS),

now offer imaging of sufficient quality for primary diagnosis in radiology, although their high

costs are a barrier to diffusion. The University of

Virginia operates a PACS system that it plans to

hook into two remote sites, at distances of four and

10 miles, using a T1 telecommunications line.

Further expansion is planned based on the experience with the two sites.45

The use of telecommunications for telepathology is also well established. Because of the need

for high-quality imaging, the requirements of

pathology call for equipment that is more sophisticated than is required for other telemedicine applications.46 Early research findings suggest that

telemedicine allows frozen sections of tissue

specimens to be analyzed accurately.47 An example of a telepathology program is the ArizonaInternational Telemedicine Network (AITN), established at the University of Arizona in 1993. Its

goals are to provide consultation services, use

telepathology in quality assurance programs, participate in research on the development of telepathology systems, and examine the impact of

telepathology services on the practice of medicine, including patient outcomes. The network involves five locations in Arizona and one each in

Mexico and China.48

❚ Home-Based Health Services

In addition to using telecommunications to deliver health services from one medical facility to

another, there is also the potential to use it to deliver services to people in their homes.49 In some

ways, electronic “house calls” represent a move

back to a health care system that is more homecentered rather than hospital-centered.50 Using a

variety of technologies—including telephone,

computers, monitoring devices, and interactive

video—telemedicine could reduce or eliminate

patient travel, resulting in lower costs for the patient and perhaps making a hospital or clinic visit

unnecessary. This could be particularly helpful to

people whose mobility is limited or who may not

be well enough to travel. The elderly face particu42 Batnitzky, op. cit., footnote 40, p. 15.

43 Grigsby et al., Report 1, op. cit., footnote 12, p. 2.13.

44 Grigsby et al., Report 4, op. cit., 8, p. 2.3.

45 Healthcare Telecom Report, Sept. 12, 1994, pp. 5-6.

46 Grigsby et al., Report 1, op. cit., footnote 12, p. 2.6.

47 Grigsby et al., Report 4, op. cit., footnote 8, p. 2.3.

48 A.K. Bhattacharyya et al., “Case Triage Model for the Practice of Telepathology,” Telemedicine Journal, vol. 1, No. 1, spring 1995, pp.

9-17.

49 See also the section on consumer health informatics in ch. 1.

50 Mary Gardiner Jones, “Electronic House Calls: 21st Century Healthcare Services for Consumers,” Proceedings of the Mayo Telemedicine Symposium, Oct. 1-3, 1993, p. 39.
174 | Bringing Health Care Online: The Role of Information Technologies

lar challenges in meeting their need for services,

and advanced telecommunications—particularly

two-way video to the home—could ultimately

provide them a full range of services.51

Home-based telemedicine could be particularly effective for followup care and for monitoring

chronic illnesses, such as asthma or diabetes.

Monitoring allows preventive measures to be taken before problems get so severe that hospitalization becomes necessary. Telemetry devices at

home that connect to a computer—to provide

electrocardiograms or blood-pressure readings,

for example—could alert the patient’s physician

that treatment is necessary. Such a system could

provide a more cost-effective method of care by

reducing medical visits for conditions that are not

severe.

Several demonstrations are currently under

way related to home delivery of services. For example, in several months, Eastern Carolina University (ECU) will begin home trials for about six

patients (initially) for remote cardiac rehabilitation using telephone, cable TV, and telemetry

units. Using one-way video and two-way audio, a

physician will monitor a patient at home while the

patient rides a stationary bicycle. Patients will see

the physician on their cable TV and will be able to

converse with him or her.52 This will permit realtime monitoring of their vital signs by the medical

center. In addition, ECU and Economic Growth

Strategies, Inc., in conjunction with Smart House,

has created a health demonstration house. Health

House will use interactive communications to

provide monitoring, diagnosis, and information

products and services.

In collaboration with the Center for Total Access at Fort Gordon and the Georgia Tech Research Institute, the Medical College of Georgia

also is planning to place equipment in 25 homes to

monitor patients who have frequent hospitalizations or emergency room visits. A similar system

will be placed in a large nursing home, and into the

home of the nursing home’s medical director, to

avoid unnecessary admissions to the hospital. The

Harvard Community Health Plan in Burlington,

Massachusetts, operated a Triage and Education

System by placing computer terminals in 150

homes. Patients used the system to get customized

health information and guidance based on responses to a questionnaire they completed on the

screen. It enabled patients to manage common illnesses or injuries and monitor chronic health

conditions. The project was deemed a success, but

was discontinued because funds were unavailable

to finance it when the demonstration ended.53

The Comprehensive Health Enhancement Support System (CHESS) uses an interactive computer system to provide information, social support,

and problem-solving tools for people living with

AIDS and HIV infection. CHESS was developed

at the University of Wisconsin-Madison under a

grant from the W.K. Kellogg Foundation. The

system provides information, referrals to service

providers, patient support in making difficult decisions, and networking with experts and others

facing the same concerns. When computers were

placed in homes for three to six months, their use

was extremely heavy. Subjects who used CHESS

reported a significantly higher quality of life in

several dimensions, including social support and

cognitive functioning. Users also reported significant reductions in some types of health care

costs.54 CHESS has also been used in a study of

eight African-American women with breast cancer who lived in impoverished areas of inner-city

51 Mary Gardiner Jones, “Meeting the Home Health Care Needs of the Elderly in the 21st Century Through Telecommunications: Report

and Recommendations,” Consumer Interest Research Institute, Washington, DC, Mar. 10, 1995, p. 6.

52 Healthcare Telecom Report, vol. 2, No. 7, Mar. 28, 1994, p. 1.

53 Site visit, Harvard Community Health Plan, 1994. Most users liked the system, and HCHP noted a 15 percent increase in the use of selfcare to treat health problems, a 14 percent increase in appropriate level of care decisions, and a 5 percent reduction in health center visits.

54 D.H. Gustafson et al., “The Use and Impact of a Computer-Based Support System for People Living with AIDS and HIV Infection,” n.d.
Chapter 5 Telemedicine: Remote Access to Health Services and Information | 175

Chicago. It was very well received, extensively

used, and produced feelings of acceptance, motivation, understanding, and relief among participants.55

Delivering health services directly or providing

needed information does not always require the

user to have sophisticated equipment. The Connect System at Cleveland State University uses a

computer and voice mail system to monitor drugusing pregnant patients, patients in drug treatment, and mothers of newborns. This system is for

nonemergencies, and patients access it using a

touchtone telephone and a password. It is used to

communicate with caregivers, and the computer

calls the patient if there is a message waiting.

Those without a telephone can call in on a regular

basis to collect messages. There is also a Community Health Rap line that will find an expert to answer questions. Telephone Pals will connect

patients with others who share a common health

condition. Home Monitoring allows a clinician to

call a child’s parent at regular intervals to ask a series of questions. Answers are sent directly to the

clinician, who will contact the parents if there is a

need for action. Appointment and medication reminders are also sent. Research showed that sending reminders for immunizations resulted in 82

percent of patients in the experimental group

keeping their appointments, compared with 69

percent for the control group. The resulting immunization rates were 68 percent for the experimental group, compared with 45.5 percent for the

control group. This is in a community in which

only 4 percent graduated high school and 40 percent owned their own telephone (12 percent were

both homeless and phoneless).56

❚ Other Sites

Telemedicine offers safety, security, and cost advantages in delivering services to correctional facilities. For example, since 1992, the East

Carolina University (ECU) School of Medicine

has provided consulting services to the Central

Prison in Raleigh, North Carolina, a top-security

prison.57 The prison doctor is able to consult via

telecommunications with specialists at ECU, thus

avoiding the need to transport inmates or bring in

specialists. Consultants were reluctant to visit the

prison, and the cost of transporting an inmate to

the hospital ranged from $700 to $5,000, depending on the amount of security required.

In Texas, the University of Texas Medical

Branch at Galveston has seen 40 to 62 patients a

week from the prison population in Phase 1 of a

program that began in October 1994. Their goal is

100 patients per week by the end of 1995.58 Patients are usually presented by physician assistants. The Texas prison system is looking at

telemedicine as a way to reduce referrals to the

state’s tertiary care centers, such as the one at Galveston, which are overburdened with inmate referrals. The Medical College of Georgia also is

connected to correctional facilities, and inmates

who previously needed to be transported for

health care can now be treated at the prison using

telemedicine.59

It seems clear that the delivery of health services using telecommunications is possible in any

55 F.M. McTavish et al., “CHESS: An Interactive Computer System for Women with Breast Cancer Piloted with an Under-served Population,” n.d.

56 F. Alemi, Health Administration Program, Cleveland State University, Cleveland, Ohio, personal communication, May 11, 1995.

57 East Carolina University School of Medicine and the Center for Health Sciences Communication, World Wide Web site home page:

<URL: http://www.telemed.med.ecu.edu/>.

58 R.M. Brecht, “Implementation of Telemedicine Into the Texas Prison System,” presented at the Second International Conference on the

Medical Aspects of Telemedicine and Second Mayo Telemedicine Symposium, Rochester, MN, Apr. 7, 1995.

59 J. Sanders, testimony, hearing of the House Committee on Science, Space, and Technology, Subcommittee on Investigations and Oversight, May 2, 1994.
176 | Bringing Health Care Online: The Role of Information Technologies

number of settings, including school clinics and

nursing homes. In addition to rural areas, experiments are taking place in urban areas as well. An

example is at Stanford University in California,

where a pilot project is under way to connect an urban clinic serving the poor, a large multispecialty

group practice, and a nursing home.60 Telemedicine’s potential to respond in emergency situations, such as natural disasters or military

deployments, has already been demonstrated.61

Decisions concerning potential applications

clearly will be based on the usual criteria of how

they affect health care costs, access, and quality.

❚ Telemedicine Projects in Other

Countries

A number of other countries, particularly those

with remote or isolated areas, currently use telecommunications to deliver health services. The

characteristics of these programs tend to reflect

both the health care and telecommunications policies of the individual country.

For example, in Norway, the health sector has

been chosen by the government as one of the main

areas for the national plan for information technology.62 Remote areas and severe winter weather

conditions make the delivery of health care difficult. The University Hospital of Tromso, with the

support of Norwegian Telecom Research, has

been using telemedicine since 1988 for remote

diagnosis in Northern Norway for radiology;

pathology; dermatology; cardiology; ear, nose

and throat; and psychiatry. The system is also used

extensively for distance education for physicians

and nurses, as well as training in use of the

technology. This is a coordinated research and development project with an interdisciplinary research group based in Tromso. Cooperation with

institutions and personnel in the regional health

service is encouraged. Local research institutions

participate and local industry is involved in developing the technology.63 The telemedicine network is expected eventually to expand to Oslo and

additional remote areas of Norway. Plans are also

under way to link up with the Mayo Clinic and

Johns Hopkins University Hospital in Baltimore,

Maryland, for consultations.64

In Canada, the oldest and best-known use of

telemedicine is at the Memorial University of

Newfoundland where its Telemedicine Centre has

operated since 1975. The Centre operates a dedicated audio network with 54 sites in health centers

and the remainder in community colleges, high

schools, university campuses, and government

buildings. It provides both health programs (continuing health education, medical data transfer,

community health education programs, and

health professional meetings) and a wide range of

distance education programs and administrative

meetings for government and others.65 Another

telemedicine program in Western Canada links

Drumheller Regional Health Complex with the

University of Calgary and adjoining Foothills

Hospital. This program was developed in partnership with Alberta Government Telephones and

Calgary-based Hughes Aircraft, which is providing the hardware and software.66

South Australia established a Telemedicine

Project in June 1991 to examine the potential role

of telemedicine in health services delivery. It is a

60 Bob Holmes, “Medicine Cruises the Infobahn,” Stanford Medicine, spring 1995, pp. 20-23.

61 J.B. Crowther and R. Poropatich, “Telemedicine in the U.S. Army: Case Reports from Somalia and Croatia,” Telemedicine Journal, vol. 1,

No. 1, spring 1995, pp. 73-80.

62 B.J. Nymo and B. Engum, “Telemedicine To Improve the Quality, Availability and Effectiveness of the Health Service in Rural Regions,”

paper presented at “Seminar on the Regional Impact of Advanced Telecommunication Services,” Kiruna, June 19-21, 1990, p. 1.

63 Ibid., p. 4.

64 Healthcare Telecom Report, July 18, 1994, p. 8.

65 Memorial University of Newfoundland, Telemedicine Centre, Information Sheet, 1993.

66 Calgary Herald, “Long-Distance Healing,” June 27, 1993, p. A1.
Chapter 5 Telemedicine: Remote Access to Health Services and Information | 177

collaborative effort of the Economic Development Authority of South Australia, the South

Australian Health Commission, MFP Australia,

and Telecom Australia.67 The project was established between the Royal Adelaide Hospital,

South Australia’s largest teaching hospital with

more than 800 beds and a full range of specialist

services, and South Australia’s largest country

hospital in Whyalla, situated 400 kilometres

northwest of Adelaide. The Whyalla Hospital has

150 beds, services a town of 27,000 people, and

has a limited range of specialist services. From

September 1992 to June 1993, a total of 190 telemedicine sessions were held, divided between

education, clinical, administration, and demonstration and training sessions. A study of the project reported that clinical use was most successful

for psychiatry, dermatology, and geriatric assessment. Postgraduate medical education and administrative education were also very successful. The

project proved less successful for physiotherapy,

occupational therapy, speech pathology, and dentistry. The study also concluded that telemedicine

services will be most successful where they complement and enhance existing health services.

TELEMEDICINE ISSUES

Like all applications of new technologies, there

are barriers to widespread diffusion of telemedicine.68 Some of the problems are related to the

technology, but most can be attributed to other

factors.

❚ Reimbursement for Services

A critical issue for telemedicine is whether and

how it will be reimbursed by Medicare/Medicaid

and other third-party payers. In rural areas, up to

40 percent of physicians’ patient base consists of

Medicare/Medicaid patients.69 As one congressman testified at a 1994 hearing on rural health

care:

Telemedicine is particularly important to rural health delivery systems. . . However, without the assurance of payment for telemedicine

services, the full potential of telemedical

technology will never be realized. . . This administrative roadblock prevents the development and expansion of these systems in rural

America.70

HCFA, the federal agency responsible for

Medicare/Medicaid reimbursement of services,

has been under pressure to reimburse for services

delivered using telemedicine, and is considering

what its policy should be. Traditionally, physicians have not been reimbursed for consultations

using telecommunications (i.e., the telephone).

Current rules for reimbursement require face-toface contact (defined as in the same room) between physician and patient. Services that do not

involve direct interaction with the patient, such as

teleradiology, telepathology, or EKG testing, are

also reimbursed;71 however, consultations in

which there is interaction between patient and

consultant using videoconferencing are not.72

Aetna, the Medicare carrier in Georgia, currently

covers telemedicine consults at the Dodge County

Hospital, part of the Medical College of Georgia’s

telemedicine system. This policy does not apply

to new sites in Georgia.

To assist HCFA in its decisionmaking, the

agency commissioned a study of the primary factors to consider in any reimbursement policy. The

researchers outlined three principal consider67 “South Australian Pilot Telemedicine Project,” Project Team Evaluation Report, November 1993, p. 2.

68 For a discussion of barriers to implementation, see J.H. Sanders and R.L. Bashshur, “Challenges to the Implementation of Telemedicine,”

Telemedicine Journal, vol. 1, No. 2, summer 1995.

69 BNA’s Health Care Policy Report, vol. 2, Feb. 28, 1994, p. 418.

70 Pat Roberts, (R-KS), hearing before the Committee on Ways and Means, Subcommittee on Health, House of Representatives, U.S. Congress, Feb. 7, 1994.

71 Office of Rural Health Policy, op. cit., footnote 14, p. 6.

72 Ibid.
178 | Bringing Health Care Online: The Role of Information Technologies

ations: 1) the adequacy of the technology, 2) medical effectiveness, and 3) the appropriateness of the

applications.73 The report concluded that it would

be reasonable to proceed with reimbursement for

some telemedicine services—those that are widely accepted as effective; those that are probably effective, but with unknown effects on the health

care system (with some restrictions placed on reimbursement); and applications that require basic

research (evaluated for reimbursement on a caseby-case basis).74 Coverage might also be restricted to certain geographic areas, institutions,

or applications. In addition to this recently completed project, HCFA is currently supporting several demonstration projects that will help in its

decision process. The agency also has funded a

telemedicine evaluation project, to be conducted

by researchers at the University of Michigan, and

a data collection project at the Telemedicine Research Center in Portland, Oregon.

At a May 1994 hearing on “Telemedicine: An

Information Highway To Save Lives,” a HCFA

official testified:

Because of our limited experience with delivery of telemedical services in the real world,

we would like to proceed with caution. However, I can say with confidence, that through the

use of pilot projects undertaken by both the Government and private industry, we will be able to

learn the best approach to provide effective and

efficient health care services for our beneficiaries. HCFA envisions accessible health care being provided through the use of telemedicine

and other emerging technologies but it must be

based on solid data so that the quality of health

care provided is not compromised.75

It is unlikely that HCFA will move ahead without a clearer understanding of all the issues. Research currently under way should address some

of the questions that the agency would want answered before proposing a uniform reimbursement policy for telemedicine. In the meantime,

some experiments could be tried that would further the decisionmaking process, particularly with

respect to costs. HCFA is currently seeking a

Medicare waiver from the Office of Management

and Budget that would allow the agency to provide reimbursement for physician services rendered via telemedicine for pilot projects in Iowa,

Georgia, West Virginia, and North Carolina.

HCFA will continue to be concerned about telemedicine’s safety and effectiveness, quality of

care, practice standards, and the impact on physician distribution. However, the agency will also

be concerned about any increase in Medicare

spending that could result from reimbursement for

telemedicine services. At a time when reductions

in the growth of Medicare are being proposed,

there will be reluctance to initiate policies that

could increase costs by increasing access to services.

❚ Lack of Research/Experience

Another barrier to telemedicine is the lack of research demonstrating its safety and efficacy, clinical utility, and cost-effectiveness. This is a

problem for potential users, payers, and policymakers. No one knows for certain which medical

conditions are best suited to the use of telemedicine. For example, believing that the “hands-on”

experience is critical for initial patient examinations, some providers feel that telemedicine works

better for followup care than for an initial visit.

Clearly, some procedures are better suited to the

use of interactive video than others in terms of the

patient’s comfort level. Research on patient satisfaction with telemedicine is limited, but results indicate that in general they like it.

Early experiments in telemedicine were terminated before they produced answers concerning

its cost, impact on access, and effects on quality of

73 Grigsby et al., Report 1, op. cit., footnote 12, p. i.

74 Grigsby et al., Report 4, op. cit., footnote 8, p. 5.1

75 Helen L. Smits, Deputy Administrator, Health Care Financing Administration, statement at a hearing at the National Institutes of Health

before the Committee on Science, Space and Technology, U.S. House of Representatives, May 2, 1994, p. 13.
Chapter 5 Telemedicine: Remote Access to Health Services and Information | 179

care.76 Those projects did not end because they

failed to achieve their objectives. Instead, the reasons included: 1) lack of familiarity and limited

experience with the systems, 2) lack of institutional commitments to sustain them when outside

funding ran out, 3) lack of incentives for physicians to use the systems, 4) limitations of the

technology, and 5) poor system planning and design.77

In its request for proposals for an exploratory

evaluation of telemedicine, the Office of Rural

Health Policy listed four primary objectives:

1. to determine the current status of telemedicine

in rural health with respect to the number and

types of systems in operation, levels of technology employed, types of specialty services provided, utilization of services, costs, and patient

and provider acceptance;

2. to explore the effects of telemedicine on access

to care, practitioner isolation, and the development of health care networks;

3. to explore the organizational factors (at facility,

network, community, and state levels) that aid

or impede the successful development and implementation of telemedicine systems; and

4. to develop, test, and refine data collection

instruments that may be used in subsequent

evaluation efforts.78

The results of this exploratory evaluation and

other research under way should lay the groundwork for future research projects designed to

answer the many questions concerning the effectiveness of telemedicine. Evaluation tools will

clarify what telemedicine technologies are most

appropriate and which health care services are best

suited to remote consultation.79 The National Library of Medicine, with some support also from

HCFA and the Department of Veterans Affairs, is

currently sponsoring a study by the Institute of

Medicine that will try to establish clear evaluation

criteria by which the appropriateness, effectiveness, acceptability, and other aspects of telemedicine might be rigorously measured and assessed.

(See also appendix D.)

Several organizations have formed to promote

and coordinate telemedicine research activities

and share research strategies. Examples are the

National Consortium for Telemedicine Evaluation (see box 5-1) and the Clinical Telemedicine

Cooperative Group (see box 5-2). The American

Telemedicine Association also promotes research

as part of a comprehensive agenda for telemedicine.

❚ Telecommunications Infrastructure

The technology exists to provide a wide variety of

telemedicine services over regular telephone

lines. For example, the teledermatology program

at the Oregon Health Sciences University (supported by NLM’s High Performance Computing

and Communications initiative) uses still images

over standard phone lines to transmit skin images.

In many rural areas, however, the telecommunications infrastructure does not provide a medical facility with sufficient bandwidth to carry the

necessary signals for interactive video telecon76 Bashshur, op. cit., footnote 11.

77 Ibid., p. 6.

78 Office of Rural Health Policy, Health Resources and Services Administration, Public Health Service, Department of Health & Human

Services, Request for Proposal No. HRSA 240-OA-22(4) for “Exploratory Evaluation of the Rural Application of Telemedicine,” 1995, p. 9.

79 D.A. Perednia, “Evaluating the Use of Telemedicine for Mental Health Applications,” June 1994, pp. 8-9.
180 I Bringing Health Care Online: The Role of Information Technologies

The National Consortium for Telemedicine Evaluation (NCTE) was organized in 1993 at the University

of Michigan, School of Public Health, Department of Health Management and Policy for the purpose of

conducting multistate, multisite evaluation of telemedicine systems The evaluation IS focused on accessibility, cost, and quality, The consortium serves two specific objectives: 1) to assist in the evaluation

of individual telemedicine programs/projects as prototype systems of care involving specific configurations of technology (high end, low end), manpower (MD and non-MD providers), organization (organized and unorganized, Integrated networks), and clinical applications (specific diagnostic services, full

service, full-time service) To date, participants in the Consortium include NASA, Medical College of

Georgia, University of West Virginia, MD-TM University of Kentucky, Louisiana Health Care Authority,

and Mid-Nebraska Telemedicine System, The Consortium is developing detailed methodologies for

telemedicine evaluation, including sample design and data collection protocols

SOURCE: National Consortium for Telemedicine Evaluation, Department of Health Management and Policy School of Pubic Health,

University of Michigan, Ann Arbor, Ml

sultations. 80 The cost of the telecommunications

links required for telemedicine represents a major

barrier to its broader use. Often new lines must be

laid and new tariffs developed. If a single facility

has to absorb the full costs of the transmission services. the costs may be prohibitive. In addition to

laying a new line for broadband service, it may

also be necessary for the communications carrier

to install a digital switch to ensure that the quality

of the compressed video signals is acceptable.

Boundaries were established after the breakup

of AT&T that made telephone calls placed outside

the local access transport area much cheaper than

those placed within the same service area.81 The

high cost of connectivity between local and longdistance carriers is a difficult hurdle for telemedicine systems to overcome. 82 To lower transmission costs, some have suggested that an essential service rate be set for local governments, hospitals, and educational facilities that would

provide a basic level of service at guaranteed

prices that are not based on distance.83 In some

cases, cooperative efforts among telemedicine

providers, state agencies, and telephone companies have resulted in negotiated rates that are more

affordable for the providers .84 Implementing telemedicine projects generally is easier in states like

Pennsylvania, North Carolina. Georgia, Kansas,

and Iowa where statewide networks already exist.

As the number of statewide networks increases,

80 For an in-depth discussion of the rural communication infrastructure, see U.S. Congress, Office of Technology Assessment, op. cit., footnote 9. For further discussion of the communication infrastructure, see U.S. Congress, Office of Technology Assessment. Critical Connections.”

Communication for the Future, OTA-CIT-407 (Washington, DC: U.S. Government Printing Office, January 1990). For a description of broadband network technology, see U.S. Congress, Office of Technology Assessment, Advanced Network Technology, OTA-BP-TCT-101 (Washington. DC: U.S. Government Printing Office, June 1993), ch. 3. For an in-depth discussion of the role wireless technologies will play in the emerging Nil, see U.S. Congress, Office of Technology Assessment, Wireless Technologies and the National Information Infrastructure, OTAITC-622 (Washington, DC: U.S. Government Printing Office, July 1995).

81 Office of Rural Health Policy, op. cit., footnote 14, pp. 4-5. The report cited the example of the Texas MedNet Project, whose 1992 monthly transmission costs were $27 per mile within the same local telephone service area, and $5 per mile between service areas.

82E.G. Tangalos, ‘“Telemedicine Outcomes: What We Know and What We Don’t,” paper presented at the Rural Telemedicine Workshop.

Office of Rural Health Policy, Washington, DC, Nov. 3-5, 1993, p. 4.

83 Office of Rural Health Policy, op. cit., footnote 14, P. 17.

84 Dena S. Puskin and Jay H. Sanders, “Telemedicine Infrastructure Development, ’’. Journal of Medical Systems, vol. 19, No. 2, 1995, p. 2.
Chapter 5 Telemedicine: Remote Access to Health Services and Information 1181

The Clinical Telemedicine Cooperative Group (CTCG) IS a not-for-profit, independent medical research corporation with offices in Portland, Oregon, and Kansas City, Kansas CTCG members share

common telemedicine research protocols, data collection instruments, and testing methodologies, By

coordinating research efforts, members are able to perform statistically valid telemedicine research

faster, and at a lower cost, than would otherwise be possible, Expertise in computer systems, research

design, imaging, statistical analysis, engineering, and specific medical expertise IS available to CTCG

members through TRC staff and affiliates The CTCG network IS based on successful community-based

research cooperatives---models that demonstrate the advantages and validity of large-scale, multicentered trials in clinical research. Pilot funding for the CTCG was provided by the Health Care Financing Administration.

SOURCES: D.A. Perednia, “Telemedicine System Evaluation and a Collaborative Model for Multi-centered Research, Journal of Medical Systems, vol. 19, No 3, 1995, and J Kadel, Member Information Coordinator, CTCG, Oregon Health Sciences University, Portland, OR personal communication, July 11, 1994

more and more uses will be found for telemedicine are interoperable, technology standards will be esin both rural and urban areas.

In rural areas, hospitals, schools, government,

and other community groups can aggregate demand and share a network to help spread the system costs. This can only be accomplished, however,

when residents are involved in planning and developing a system and have a sense of ownership

in it. In an earlier study, OTA suggested that Rural

Area Networks would allow rural communities to

customize networks to their own needs, while

achieving economies of scale and scope85 (see figure 5-3). By sharing in the creation of such a network, rural communities would be able to enjoy

some of the benefits of their urban counterparts. A

system of “bandwidth on demand”, in which users

pay only for the time they use on the system,

would greatly reduce the costs of telemedicine and

obviate the need for a dedicated communications

line. Such service could be provided using an advanced switching technology such as asynchronous transfer mode, which can support many

different kinds of services. To ensure that systems

sential for communication providers. 86 Many of

these issues are currently being addressed in the

context of the Administration’s NII initiative, particularly by members of the Information Infrastructure Task Force (IITF).

Delivering health care to the home is increasingly important for people who need convalescent

or chronic care. A public network that can provide

two-way video, high speed data transfer, and

graphics is required before a wide range of health

services can be delivered directly to the home.

Some telephone companies are beginning to respond to this recognized need by devising strategies to implement such advanced services, and

home services are figuring prominently in NII discussions.

❚ Legal/Regulatory

Remote diagnosis and treatment across state lines

could bring differing laws and regulations into

conflict. Telemedicine raises a number of legal issues related to privacy/confidentiality, licensing

85U.S. Congress, Office of Technology Assessment, op. cit.. footnote 9, p. 59.

86 For discussions of technology standards, see chs. 1 and 2. See also U.S. Congress, Office of Technology Assessment, Global Standards:

Building Blocks for the Future, TCT-512 (Washington, DC: U.S. Government Printing Office, March 1992).

d
182 | Bringing Health Care Online: The Role of Information Technologies

SOURCE: U.S. Congress, Office of Technology Assessment,

Rural America at the Crossroads: Networking for the Future,

OTA-TCT-471 (Washington, DC: U.S. Government Printing

Office, April 1991), p. 83.
Chapter 5 Telemedicine: Remote Access to Health Services and Information | 183

and credentialing, and liability that could represent significant barriers to its broader diffusion.

Privacy and Confidentiality

Privacy in health care information has been protected in two ways: 1) in the historical ethical obligations of the health care provider to maintain

the confidentiality of medical information, and 2)

in a legal right to privacy, both generally and specifically, in health information. Confidentiality

involves control over who has access to information. Other terms frequently used in privacy

protection discussions are integrity and security.

Integrity assures that information and programs

are changed only in a specified and authorized

manner, that computer resources operate correctly, and that the data in them are not subject to unauthorized changes. A system meeting standards

for access allows authorized users access to information resources on an ongoing basis.87 Security refers to the framework within which an

organization establishes needed levels of information security to achieve, among other things, the

confidentiality goals.88

The use of telecommunications to deliver medical care may pose additional risks to the privacy

of patients and their records. For example, the creation of a videotape of a consultation might pose a

new privacy threat for the patient unless appropriate safeguards to control access to it are built into

the process. The issue of who has access to this information will need to be considered and resolved

in advance. Depending on the nature of the examination, the patient may also have privacy concerns in terms of who is actually present in each

location during the consultation. Nonmedical personnel, such as a technician or facilitator, may be

needed to assist in the consultation.

If a videotaped consultation becomes part of

the patient’s medical record, it would be treated

like other videotaped information on the patient

(e.g., an angiographic procedure, for example). In

these cases, the usual privacy laws would apply.

State laws governing the transmission and retrieval of patient medical records vary, and officials are

concerned about user verification and access, authentication, security, and data integrity.

A previous OTA study found that the present

system of protecting health care information offers a patchwork of codes; state laws of varying

scope; and federal laws applicable to only limited

kinds of information, or information maintained

specifically by the federal government.89 The

present legal scheme does not provide consistent,

comprehensive protection for privacy in health

care information, whether it exists in a paper or

computerized environment. Clearly the privacy

implications for telemedicine will continue to receive careful scrutiny. Vice President Gore has recently asked the Department of Health and Human

Services (DHHS) to develop model institu- tional

privacy policies and model state laws for health

information in the context of the NII.90 This activity is to be coordinated with the activities of the

IITF in the privacy area.

Physician Licensing

Physicians must be licensed by the states in which

they practice. Telecommunication facilitates consultations without respect to state borders and

could conceivably require consultants to be licensed in a number of states. This would be impractical and is likely to constrain the broader

diffusion of telemedicine programs. In July 1994,

the State of Kansas passed legislation requiring

87 C.P. Pfleeger, Security in Computing (Englewood Cliffs, NJ: Prentice Hall, Inc. 1989), pp. 5-6.

88Ibid., p. 90.

89 U.S. Congress, Office of Technology Assessment, Protecting Privacy in Computerized Medical Information, OTA-TCT-576 (Washington, DC: U.S. Government Printing Office, September 1993), pp. 12-13.

90 Vice President Al Gore, memorandum to Donna Shalala, Secretary of Health and Human Services, Mar. 8, 1995.
184 | Bringing Health Care Online: The Role of Information Technologies

that out-of-state physicians who provide consultations using telemedicine be licensed in Kansas.

The licensing problem for telemedicine could

be addressed by the implementation of national licensing standards or the classification of physicians practicing telemedicine as consulting

physicians, thereby circumventing state rules. For

a start, such a national license could be provided to

physicians who provide consultations to underserved populations. A precedent exists for physicians serving in the military, the Department of

Veterans Affairs, the Indian Health Service, and

the Public Health Service.91 Another way to address the problem of licensing is to place the overall responsibility for the patient’s care in the hands

of the referring physician and view a consultant in

a different state as making recommendations only.

A novel approach unique to telemedicine would

be to consider that the patient is being “transported” electronically to the consultant, thus obviating the need for the specialist to be licensed in

the patient’s home state.92

The issue of credentialing arises with telemedicine in terms of the use of consultants. In the Medical College of Georgia program, the Joint

Commission on Accreditation of Hospitals (JCAHO) has determined that hospital credentials are

not a problem for the consulting physician as long

as all physician orders are written by the referring

physician. The Federation of Boards of State

Medical Examiners has established a task force to

deal with the problem of providing interstate telehealth care, while preserving state licensure, credentialing, and monitoring of health care

professionals.93

Liability

The liability implications of telemedicine are unclear. At least two aspects of telemedicine could

pose liability problems. One is the fact that, in a

remote consultation, the specialist does not perform a hands-on examination, which could be regarded as delivering less than adequate care. The

second aspect is that the use of compressed video,

in which repetitious information is eliminated as

the data are converted from analog to digital and

back, may raise the issue of diagnosing with less

than complete information.94 On the other hand,

telemedicine may, in fact, decrease the threat of

malpractice suits by providing better recordkeeping and databases, and the fact that taping the consultations will automatically provide proof of the

encounter. Tapes could also help to prove the innocence of providers who are falsely accused.

Consulting physicians could reduce their liability by adhering to practice guidelines for various telemedicine applications. Such guidelines

would need to be established by national health

professional associations.95 Another way of limiting liability would be to protect physicians and

medical centers that provide telemedicine consultations to the underserved under the doctrine of

sovereign immunity, which might take the form of

a cap on economic damages or some other holdharmless protection.96 Liability considerations

for telemedicine must, of course, be viewed in the

context of ensuring the patient adequate recourse

in cases of actual negligence.

91 Sanders and Bashshur, op. cit., footnote 68.

92 Ibid.

93 J. Preston, M.D., President, American Telemedicine Association, personal communication, May 14, 1995.

94 Office of Rural Health Policy, op. cit., footnote 14, pp. 8-9.

95 Ibid., p. 9.

96 Ibid.
Chapter 5 Telemedicine: Remote Access to Health Services and Information | 185

❚ Development Costs/Financing

The costs of developing a telemedicine project can

be high. These costs include telecommunication

charges, equipment costs, technical support, training, and administrative support. Many small communities operating on their own will be unable to

afford these costs. Telemedicine lends itself to

cost-sharing as a way of financing projects as well

as assembling the expertise necessary to make it

successful. For example, the Medical College of

Georgia project is a partnership that includes private industry, the state government, the Governor’s office, academia, and, most importantly, the

primary health care facilities. There are many other examples of groups working together to share

the expense of building a system. Within communities, systems that are too costly for health applications alone can be shared with educational,

local government, social, and community services

to make the investment feasible.

One suggestion for small rural health care facilities is to lease a system for three to five years.

The revenue generated by the anticipated increase

in bed census and ambulatory care activity could

be used to offset the leasing costs. Some facilities

may still need government support in the form of a

loan for start-up purposes before they could assume the costs of leasing a system.97

❚ Technological and Implementation

Issues

In implementing a telemedicine project, it is important to first define its objectives, and then select the appropriate technology to meet those

needs.98 The focus should be on how telemedicine

can contribute to better clinical decisionmaking

and patient care. Depending on what the project is

designed to achieve, the technology might range

from a touchtone telephone to a sophisticated

multimedia system. This points to the need for

careful planning in advance and a clear understanding of the project goals. Experience suggests

the need for a flexible, open system that can easily

be adapted to advances in technology. The complexity and sophistication of the technology selected will depend on what it is required to do.

Transmission speed, image resolution, storage capacity, mobility, and ease of use are important

considerations.

Those who will be using the system must be

involved in its design from the beginning. Once

implemented, onsite technical assistance is necessary to ensure that any technological problems can

be immediately addressed and rectified. It is important that the system be conveniently located so

providers can access it easily. Adequate training

must be provided, and the presence of a facilitator

will ensure that consultations run smoothly. As

desktop multimedia telemedicine platforms become available to place in the health care provider’s office, issues of cost, location, convenience,

and the operational and maintenance difficulties

of telemedicine will diminish significantly.

One of the barriers to telemedicine is the lack

of technical standards. To achieve an integrated

network of providers, the ability to interconnect

using uniform standards will be essential. (Technical standards are discussed in detail in chapter

2.)

Earlier telemedicine demonstration projects

often did not survive when funding ended. Some

also ceased to function when individuals who had

spearheaded the projects left. Some recent federal

grants made for telemedicine demonstration projects are building in safeguards to ensure that projects have the ability to continue beyond the pilot

stage. Some researchers suggest that relying on

any government funding can be a potential impediment to implementation. Administrators will

need to be convinced that telemedicine consultations will provide the possibility of generating

97 J.H. Sanders, “Telemedicine: Challenges to Implementation,” paper presented at the Rural Telemedicine Workshop sponsored by the

Office of Rural Health Policy, Nov. 3-5, 1993, p. 9.

98 D.S. Puskin, “Telecommunications in Rural America: Opportunities and Challenges for the Health Care System,” Annals of the New York

Academy of Sciences, vol. 670, Dec. 17, 1992, pp. 71-72.
186 | Bringing Health Care Online: The Role of Information Technologies

revenue to cover their costs. Assuming reimbursement is available for services delivered using telemedicine, a telemedicine system should only be

initiated if the economics can support its operation.99

❚ Human Infrastructure

While issues related to technology are important

and often get most of the attention, it is also apparent that organizational, management, and human

factors also play a critical role in implementing a

telemedicine system. As one telemedicine user

points out:

In the final analysis, it will be the human

component at each end of the system—not the

technology—that will determine whether it is

successful or not.100

A family physician who worked in a hospital

that had installed a little-used teleradiology system commented that “the personnel part of the

equation is far more complex and difficult than the

technology part of the equation.”101 For example,

the nature of the relationship between the referring

and consulting physicians may be a key factor in

whether or not a system is fully used. Existing referral relationships between providers may need

to be altered when telemedicine is introduced,

which could cause some dislocations and affect its

use.102

How well the system is organized, managed,

and maintained, as well as whether or not it is conveniently located, will help to determine its rate of

use. Several telemedicine programs have reported

that scheduling can be a major problem. Because

time is an important factor to busy professionals,

they are likely to be more responsive to using telemedicine if scheduling is efficient and convenient.

This problem may be resolved when the telemedicine technology eventually reaches the physician’s desktop.

Resistance to change is often a problem when

new technologies are introduced. Health care professionals are no exception, and many will not be

interested in or willing to participate in telemedicine. Some will feel threatened by the introduction of technology into their practice. However, as

one telemedicine pioneer put it:

Telemedicine does not replace the physician

or relegate him to a less important role. Telemedicine depends upon him and his special abilities, and it offers him a new way to practice

medicine. Through an interactive telemedicine

system, the fundamental doctor-patient relationship not only can be preserved, but potentially augmented, enhanced and more critically

focused.103

Nevertheless, telemedicine will change the

way providers practice. Some practitioners will

miss the hands-on aspects of examining a patient

that has been such an integral part of their medical

training and experience.104 Some may also have

concerns about the quality of the image or the ability to make an accurate diagnosis based on the

available equipment.105

99 J.H. Sanders, Professor of Medicine, Medical College of Georgia, personal communication, May 1995.

100 Office of Rural Health Policy, op. cit., footnote 14, p. 13.

101 Tom Dean, quoted in “Is Telemedicine the Answer to Rural Health’s Problems?” Rural Health News, vol. 1, No. 2, spring 1994, p. 9.

102 P. Whitten and T. Franken, “A Survey of Rural Primary Care Practitioners’ Attitudes and Perceptions of Telemedicine,” abstract book,

Second International Conference on the Medical Aspects of Telemedicine and Second Annual Mayo Telemedicine Symposium, April 1995,

p. 6.

103 K.T. Bird, “Telemedicine: Concept and Practice,” in R.L. Bashshur, P.A. Armstrong, and Z.I. Youssef (eds.), Telemedicine: Explorations

in the Use of Telecommunications in Health Care (Springfield, IL: Charles C. Thomas, 1975), p. 90.

104 Researchers at the Georgia Institute of Technology are working on a project to design a glove that could be worn by the consultant that

would mimic the hands-on experience.

105 Grigsby et al., Report 4, op. cit., footnote 8, p. 7.2.
Chapter 5 Telemedicine: Remote Access to Health Services and Information 1187

The American Telemedicine Association (ATA) was incorporated in 1993 to promote professional,

ethical, and equitable Improvement in health care delivery through telecommunications technology and

to enhance broad-based community telecommunications applications. The Association will: 1) promote

telemedical research and education; 2) assist in the development of telemedical policy and standards,

3) provide education to public and professional organizations; 4) interact with worldwide communication systems, 5) serve as a clearinghouse for telemedical information and services; and 6) support local

health care system initiatives in telemedicine, especially in medically underserved areas, In November

1994, the Board of Directors adopted a set of telemedicine policy priorities focused on practice guideIines, privacy, Iiability, reimbursement, medical Iicensure, national disasters, technology development,

the national telecommunications Infrastructure, research and demonstrations, and interactive distance

Iearning.

ATA affords a structured forum for clinicians, technologists, research bodies, and public policy institutions. It has provided leadership in consumer advocacy for reimbursement, provided an emergency

response structure that Incorporated guidance from those at the site in a recent national disaster, stimulated educational and political action with organized medicine, Initiated research and teaching recommendations for medical schools by national medical leaders, and provided testimony before Congress,

SOURCES: American Telemedicine Association information sheet, n d , American Telemedicine Association Policy Priorties, November 1994 and Jane Preston President, American Telemedicine Association, personal communication, May 14, 1995

TELEMEDICINE POLICY OPTIONS

There is ongoing activity and interest in telemedicine at the federal level in both the executive

and legislative branches. A community of people

interested in telemedicine—including representatives from federal agencies, Congress, telemedicine users, researchers, and vendors—meet in a

variety of forums. Hearings have been held, seminars have been conducted, and demonstrations of

telemedicine have been provided. At the same

time, the number of organizations, conferences,

newsletters, and journals related to telemedicine

is rapidly proliferating, and online information

and discussion groups have helped to inform

people about its potential (see appendix E).

Responsibility for telemedicine policy is

shared among federal, state, and local lawmakers,

and many of the decisions affecting the diffusion

of telemedicine are influenced largely by the private sector. Groups such as the American Telemedicine Association have provided leadership in

consumer advocacy for reimbursement, stimulated educational and political action with organized medicine, initiated research and teaching

recommendations for medical schools, and testified before Congress (see box 5-3). Federal efforts

to reform both health care and telecommunications, each traveling its separate path, will have an

impact on telemedicine’s progress. As noted by

one telecommunications expert:

. . . Telemedicine barely rated a blip on the radar

screen when Congress debated new telecommunications legislation last year. This omission is

all the more remarkable in [that] . . . the other

major legislative initiative in the 103d Congress

was improving Americans’ access to health care

while simultaneously controlling health care

costs . . . Congress dealt with communications

in one hearing room and health care in another

[and] failed to connect the two together. 106

106 Newton W. Minow, Director, The Annenberg Washington Program, “Telecommunications, Medicine and the Public Interest,” speech

given at the Second International Conference on the Medical Aspects of Telemedicine and Second Annual Mayo Telemedicine Symposium,

Rochester, MN, Apr. 8, 1995.
188 | Bringing Health Care Online: The Role of Information Technologies

Aspects of telecommunications reform related

to universal service, health care, and tariffs are

relevant to telemedicine. Health care reform initiatives center on reducing costs and improving

access and quality. These goals reflect the trends

toward managed care, new competitive strategies

on the part of health care providers, and the move

toward outpatient care and away from large inpatient facilities.

Federal telecommunications policymakers involved in reform initiatives have an important role

to play in ensuring that proposed legislation supports the delivery of health care using telecommunications. The Snowe-Rockefeller amendment to

the Telecommunications Competition and Deregulation Act of 1995, S. 652, supports access to the

NII for schools, libraries, and rural health care

providers. Section 253 of the Act on Universal

Service calls for actions that will benefit consumers in rural and high-cost telecommunication

areas. In Congress, both the House/Senate Ad Hoc

Committee on Telemedicine and Health Care Informatics and the Congressional Rural Caucus

continue to explore the potential of telemedicine

to meet the needs of their constituents. A telemedicine conference held at Airlie House in Virginia,

in August 1994, was requested by the Ad Hoc

Committee, and a report was recently released that

sets out a policy agenda for telemedicine over the

next several years.107

Telemedicine is considered an integral part of

the Administration’s NII planning efforts. A key

player is the Information Infrastructure Task

Force, a forum where both telecommunications

and health care needs converge. Telemedicine is

being addressed by a task force subgroup, and

considerable progress has already been made

toward formulating telemedicine strategies. The

National Telecommunications and Information

Administration is helping to fund telemedicine

demonstration projects through its Telecommunications and Information Infrastructure Assistance Program. The National Information Infrastructure Testbed, a nonprofit consortium, has

provided telemedicine demonstrations as part of

its goal of advancing the NII (see box 5-4). Along

with NII activities, federal agencies such as the

Office of Rural Health Policy, the Rural Utilities

Service, the National Library of Medicine, the Department of Defense, the Department of Veterans

Affairs, the Agency for Health Care Policy and

Research, and the Health Care Financing Administration support telemedicine in various ways

(see appendix D).

Telemedicine is likely to proceed with or without federal support. However, federal government

support will be required to guarantee that telemedicine benefits those who need it most—people

living in rural locations, inner city areas, and Native American communities that the private sector

is likely to bypass for more lucrative areas. In a

time of fiscal constraints, any federal funding provided will need to be carefully monitored to ensure it is being used wisely. If Congress wishes to

encourage the diffusion of telemedicine, it can

have the most impact in the areas of research funding and reimbursement for telemedicine services.

The two are closely connected, in that formulating

a reimbursement policy is dependent on obtaining

satisfactory answers to many of the questions

raised about telemedicine.

❚ Federal Funding for Telemedicine

Research

One option for Congress is to continue to provide

funding for telemedicine demonstration and evaluation projects. Telemedicine research currently

under way is critical to answering many of the

questions about its efficacy and effectiveness.

Proposed funding cutbacks could adversely affect

these efforts, many of which are just getting

started. Requiring matching funds or other con107 Bashshur et al. (eds.), Working Conference on Telemedicine Policy for the NII, sponsored by the Health Information and Application

Working Group of the IITF Committee on Applications and Technology and the Senate/House Ad Hoc Steering Committee on Telemedicine

and Health Care Informatics, coordinated by the Center for Public Service Communications (Washington, DC: May 1995).
Chapter 5 Telemedicine: Remote Access to Health Services and Information 1189

The National Information Infrastructure Testbed (NIIT) is a nonprofit consortium of over 50 members

formed by industry with participation by academic institutions and government agencies to accelerate

the development of a National Information Infrastructure (Nil) Members participate in a series of application-focused demonstration projects designed to assess the technological, operational, and policy

issues associated with creating an NII. NIIT’s Healthcare Working Group consists of organizations such

as AT&T, Hewlett-Packard, Hughes Aircraft Co , Jet Propulsion Laboratory, Lawrence Livermore National Laboratory, Network Systems Corp., Pacific Bell, Polaroid Corp., Sandia National Laboratories,

SunOptics Communications, University of Southern California (USC) Medical Center, the USC-Advanced Biotechnical Consortium, and WilTel. In September 1994, the NIIT presented a nationwide demonstration via satellite to congressional and Administration staff in Washington, DC The demonstration

was based on a simulated medical emergency using teleconsultation, 3-D Imaging, and real-time collaboration in the diagnosis and treatment of a patient.1

SOURCE: Background materials provided by the National Information Infrastructure Testbed, Sept. 20, 1994

1 Background materials provided by the National Information Infrastructure Testbed, Sept. 20, 1994

tributions from those applying for federal grants a fertile area for federal support, perhaps in coopis one way of leveraging investments in telemedicine projects. This mechanism necessitates a major investment and commitment on the part of the

grantees, which helps ensure that projects will

continue after federal funding ceases. Innovative

approaches to funding should be considered wherever possible to get the most out of scarce financial resources.

Until recently, there was little or no coordination of telemedicine activities among federal

agencies. Mechanisms are now in place through

the telemedicine working group of the Administration’s Information Infrastructure Task Force to

monitor and coordinate federal support of telemedicine, which is essential in the current climate of

budget cutbacks and fiscal constraint. Representatives of federal agencies have been meeting regularly for over a year in an effort to share

information and begin to coordinate telemedicine

funding activities.

Current federal funding for telemedicine is

heavily weighted toward rural communities. Because telemedicine could provide a partial solution to the severe problems faced by some

inner-c it y health care providers, this also would be

eration with private sector organizations. Funding

for telemedicine demonstrations in other areas,

such as public health or geriatrics, could also provide valuable information to Congress and the

Administration about its potential value in improving health care delivery.

❚ Fostering Cooperative Strategies

To reduce the cost barriers of implementing telemedicine, Congress could provide incentives to

encourage cooperative efforts and consortia. In

many small communities, it makes economic

sense for groups to share the costs of implementing, operating, and maintaining a telecommunications network. For example, schools, medical

clinics, libraries, social service agencies, and others who would benefit from improved information

services may need to join forces to share the costs

of a system. Federal funding could be designed to

encourage and reward such cooperative efforts.

The U.S. military and NASA have been leaders

in research related to telemedicine applications.

The military has devised ways to use telecommunications to deliver health care to remote areas,

whether for battlefield or peacekeeping opera-
190 I Bringing Health Care Online: The Role of Information Technologies

The Telemedine Information Exchange (TIE) was launched in February 1995 by the Telemedicine

Research Center (TRC) at the Oregon Health Sciences University in Portland, Oregon Begun with demonstration funding from the Health Care Financing Administration and several private corporations, TIE

provides a comprehensive telemedicine clearinghouse that is easy to use, easily accessible, comprehensive, and continuously maintained TIE uses available health care Information resources, and currently benefits those directly or indirectly affected by telemedicine, including health care providers, individuals, community and economic development leaders, and rural-based corporations The databases

include complete bibliographic Information, listing of active telemedicine programs, Iegislative and

funding information, upcoming meetings, and relevant product and services. Updated weekly, TIE is

available to users online, 24 hours-per-day, through use of computer modems, toll-free 800 number services in the continental United States (1 -800 -555 -5 TIE), and the Internet System via World Wide Web

Client Access <URL http//tie.telemed.org/ >

SOURCE: D. A. Perednia, Oregon Health Sciences University, personal communication, May 9, 1995

(ions. In some cases, the military is cooperating

with civilian health care personnel to deliver telemedicine services. For example, Eisenhower

Medical Center is working with the Medical College of Georgia to develop the “electronic housecall.” In addition, the Army’s health care system

in Georgia will utilize the civilian telemedicine infrastructure. Walter Reed Army Medical Center

works with North and South Carolina in collaborative telemedicine projects. In a pilot project, the

Naval Hospital at Camp Lejeune will link East

Carolina University using asynchronous transfer

mode technology, focusing on emergency care

and teleradiology.108 The military and the Department of Veterans Affairs have health facilities

throughout the country, and could be encouraged

to cooperate with local civilian groups in setting

up a telemedicine system. Wherever possible,

cooperative efforts could be fostered to spread the

federal expertise as broadly as possible and take

advantage of economies of scale and scope.

■ Disseminating Research Results

In many cases, the people who might benefit most

from telemedicine applications know very little

about them. The recent increase in seminars and

meetings on the subject, especialy those that offer

continuing medical education credits and research

presentations, is beginning to fill some of the

knowledge gap. Online databases are also helpful

in spreading information about telemedicine.

However, as government-supported research results become available, it is important that agencies disseminate these as widely as possible to

providers in rural and other underserved areas.

The electronic clearinghouse concept would be a

useful vehicle to educate potential users, although

in many cases those with the greatest need to know

may not have the means to access electronic databases.

Congress might wish to ensure that mechanisms exist to widely disseminate research results

and other information about telemedicine. This

could be done by a federal agency within DHHS,

such as the National Library of Medicine or the

Office of Rural Health Policy.

One of the original goals of the IITF’s telemedicine working group was to prepare an online database of federal telemedicine projects. When this is

complete, and if it is kept current, it should pro108 From East Carolina University School of Medicine World Wide Web home page <URL:http://www.telemed.med.EDU/>.
Chapter 5 Telemedicine: Remote Access to Health Services and Information | 191

vide information that will track federal spending

on telemedicine. An electronic clearinghouse of

information concerning telemedicine would greatly facilitate the sharing of all types of information

related to telemedicine. A viable alternative to a

federal clearinghouse would provide support for a

private-sector group, such as the Telemedicine Information Exchange (TIE) network operated by

the Telemedicine Research Center at the Oregon

Health Sciences University (see box 5-5). This option would avoid duplication of effort, although a

database of federal activities might still be desirable. The major problem with any online database

is keeping it up to date. Sufficient staff and financial support would be required to do this, whether

in the public or private sectors.

❚ Reimbursing for Telemedicine Services

Because the data that would support a uniform reimbursement policy for telemedicine consultations are not yet available, HCFA is moving

slowly and deliberately in accumulating the necessary information on which to base a sound decision. This seems a prudent strategy. Experimenting with reimbursement in certain demonstration sites will provide valuable insights that

will eventually enable the agency to craft a careful

policy based on actual results. Congress may wish

to ensure that adequate funding is provided to

support those experiments. As the results of these

experiments become available, Congress may

wish to provide oversight and conduct hearings to

determine if further action is required.
Appendix A:

Workshop

Participants

Federal Activities Workshop – May 17, 1994

Linda Brink

Walter Reed Army Medical

Center

Max Buffington

Health Care Financing

Administration

Robert Esterhay

International Cancer

Information Center

J. Michael Fitzmaurice

Agency for Health Care Policy

and Research

James Garvie

Indian Health Service

Susan Katz

National Institute of Standards

& Technology

Robert Kolodner

Department of Veterans

Affairs

Thomas Lewis

National Institutes of Health

Daniel Masys

National Library of Medicine

Carole Mintzer

Office of Rural Health Policy

John Silva

Advanced Research Projects

Agency

Paul Tibbits

Office of the Assistant

Secretary of Defense

Joan Turek–Brezina

Office of the Assistant

Secretary for Planning and

Evaluation

Norman Weissman

Agency for Health Care Policy

and Research

Anne Francoeur Wilson

Health Care Financing

Administration

| 193
194 | Bringing Health Care Online: The Role of Information Technologies

Consumer Workshop – July 26, 1994

Fred Wood (Chair)

Office of Technology

Assessment

Farrokh Alemi

Cleveland State University

Gail Casper

Case Western Reserve

University

Lowell F. Christy

East Carolina University

School of Medicine

Tom Ferguson

Self–Care Productions

Linda Golodner

National Consumers League

David H. Gustafson

University of Wisconsin,

Madison

James C. Hunt

University of Tennessee

Karen Storek Lange

New Parents Network

Edward J. Madara

American Self-Help

Clearinghouse

Michael D. McDonald

The C. Everett Koop Institute

Robert Olson

Institute for Alternative

Futures

Warner V. Slack

Harvard Medical School

Cost and Cost-Effectiveness Workshop – March 9, 1995

Mark Gordon

Thomas Edison State College

Ruby Grewal

Columbia University

Shyam Heda

INOVA Health System

Tim Hill

The Office of Management

and Budget

Harold Lehmann

John Hopkins University

Peter Newmann

Project Hope Center for

Health Affairs

Clark Paramore

Project Hope Center for

Health Affairs

Stephen Parente

Project Hope Center for

Health Affairs
Appendix B

Reviewers

and

Contributors

Diane Adams

Agency for Health Care Policy

and Research

Laura Adams

Medical College of Georgia

Ace Allen

Kansas University Medical

Center

G. Octo Barnett

Massachusetts General

Hospital

Rashid L. Bashshur

University of Michigan

Joseph R. Binder

Rural Utilities Service

Catherine Britain

RODEO NET

Naomi Broering

Georgetown University

Alfred S. Buck

Joint Commission on

Accreditation of Healthcare

Organizations

Eric Christenson

CAIRN Healthcare, Inc.

Robert B. Cohen

Economic Consultant

Richard Correll

Center for Health Care

Information Management

Stephen E. Cross

Carnegie Mellon University

D. Sophocles Dadakis

Consultant

Deborah Deatrick

Health Commons Institute

Don DeMoro

Service Employees Union

International

Steve Downs

National Telecommunications

and Information

Administration

Elizabeth A. Draper

APACHE Medical Systems,

Inc.

Joseph P. Eaglin

Macro International Inc.

Thomas D. East

LDS Hospital

Daniel Essin

University of Southern

California Medical Center

Lawrence Fagan

Stanford University

Lawrence Frisch

Humboldt State University

Mark E. Frisse

Washington University

Gary J. Gagnon

APACHE Medical Systems,

Inc.

Francis Ganong

Kurzweil Applied Intelligence

Reed M. Gardner

LDS Hospital

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196 | Bringing Health Care Online: The Role of Information Technologies

Rob Geen

MACRO International, Inc.

John Glaser

Brigham & Women’s Hospital

Jim Grigsby

University of Colorado

W. Ed Hammond

Duke University

Linda M. Harris

The George Washington

University

Debby Hindus

Interval Research Corp.

Debra Hopkinson

Aetna Life & Casualty

Max House

Memorial University of

Newfoundland

Ron Huber

Crawford County Hospital

Betsy L. Humphreys

National Library of Medicine

Lisa I. Iezzoni

Beth–Israel Hospital

Mary G. Jones

Alliance for Public

Technology

Michael G. Kienzle

University of Iowa

William A. Knaus

APACHE Medical Systems,

Inc.

Andrew B. Lefton

National Health Information

Center

Gerald C. Macks

National Institutes of Health

William S. Mahler

Kansas University Medical

Center

Kathleen Mathai

Quantitative Medicine

Kathleen McCormick

Agency for Health Care Policy

and Research

Kathy Milholland

American Nurses Association

Christopher P. Moberg

Georgetown University

Hospital

Alan H. Morris

LDS Hospital

John Norris

Consultant

Keven Patrick

U.S. Public Health Service

Douglas Perednia

Oregon Health Sciences

University

Dena Puskin

Office of Rural Health Policy

Ron Ribitzky

University of Massachusetts

Medical Center

Richard Rockefeller

Health Commons Institute

Dan Rode

Healthcare Financial

Management Association

Jay H. Sanders

Medical College of Georgia

Chris Schmandt

MIT Media Lab

Ben Schneiderman

University of Maryland

Harvey Schwartz

Agency for Health Care Policy

and Research

Cary Sennett

National Committee for

Quality Assurance

Kim Silva

Systems Plus

Thomas Stair

Georgetown University

Hospital

Eric G. Tangalos

Mayo Clinic

Michael Tibbott

Apple Computer

Robbi Watnik

Healthcare Financial

Management Association

OTA REVIEWERS

Elaine Power

David Jensen

Judy Wagner

David Wye
Appendix C

Applications of

Clinical Decision

Support

Systems1

linical Decision Support Systems (CDSSs)—at least

those whose effectiveness has been evaluated—perform

one or more of the following functions: diagnosis, drug

dose determination, preventive care reminders, and active

(diagnostic or therapeutic) care advice.1 These applications and

some recent examples —including ones whose effectiveness has

not been evaluated—are discussed in the following sections.

With most of these systems, clinicians do not interact directly

with the computer; rather, staff personnel input the needed data on

the patient and provide the clinician with computer-printed reports.2

COMPUTER-AIDED DIAGNOSIS

These systems are designed to assist the clinician in determining

the patient’s exact diagnosis or the condition underlying his/her

presenting health problem. The systems take as input the patient’s

signs and symptoms, physical findings, test results, and background information, and then report one or more possible diagnoses that match that combination of characteristics. The patient

data must ordinarily be manually key-entered in a particular format required by the system. Rather than attempting to cover all

diagnoses, most systems focus on specific health problems.

1 Johnston et al., op. cit., footnote 1. Connelly and Bennett propose a similar scheme

for classifying the functions of knowledge-based systems that have clinical laboratory applications: classify (e.g., diagnosis), predict (e.g., adverse events), plan (i.e., recommend

specific actions), monitor (including alerts, reminders, and process control/scheduling),

facilitate (make a human task easier), and convey (present data, conclusions, etc.). D.P.

Connelly and S.T. Bennett, “Expert Systems and the Clinical Laboratory Information System,” Clinics in Laboratory Medicine, vol. 11, No. 1, March 1991, pp. 136-138.

2 Johnston et al., op. cit., footnote 1, p. 137.

| 197
198 | Bringing Health Care Online: The Role of Information Technologies

However, several systems, including Dxplain,3

Iliad,4 Meditel,5 and QMR,6 are designed to address the entire field of internal medicine. They

employ either deterministic or probabilistic/

adaptive algorithms to produce a list of possible

diagnoses, ranked in order of likelihood.7

DRUG DOSE DETERMINATION

These systems are designed to assist the clinician

in determining the proper dosage of a specific

drug for a particular kind of patient.8 Some evidence suggests that clinicians have a particularly

difficult time calculating drug dosages.9 Again,

data on the patient is usually entered manually in

a format required by the system. (The patient’s

diagnosis is usually assumed by the system, based

on the drug being used.) The algorithms in the

knowledge base then ascertain the proper dosage

of the drug in question, either as an exact quantity

or as a permissible range. One example of such a

system generates estimates for dosing of aminophylline for acute asthma cases presenting in the

emergency room.10 Commercial programs have

also been developed for dosing of selected drugs

based on patient-specific characteristics and measured drug concentrations.11

PREVENTIVE CARE REMINDERS

These systems are designed to remind the clinician to administer a particular preventive service

when the patient reaches a certain stage in the

process of care for a given health problem (e.g.,

retinal examination for diabetics), or simply a certain stage of life (e.g., immunization). Unlike

computer-aided diagnosis and drug-dose determination, which are usually designed to provide

a single report in response to a specific set of data

on a given patient, a preventive care reminder system requires repeated input of data on the patient

over time. This includes not only the patient’s

diagnoses and other clinical characteristics, but

also the treatments and tests administered and

when they were administered. To the extent that

the set of rules for generating reminders represents

a model of the disease process for which a preventive service is to be administered, they constitute

a type of formal clinical protocol.

The protocol specifies exactly what preventive

treatments should be performed at each stage in

the process of care for the health problem at hand,

based either on the amount of time that has elapsed

since the previous stage (e.g., a previous treatment

or test) or on data values measuring the patient’s

3 Massachusetts General Hospital, Boston, MA.

4 Applied Informatics, Salt Lake City, UT.

5 Meditel, Devon, PA.

6 CAMDAT, Pittsburgh, PA.

7 E.S. Berner et al., “Performance of Four Computer-Based Diagnostic Systems,” New England Journal of Medicine, vol. 330, No. 25, June

23, 1994, pp. 1792-1796; R.A. Miller, “Medical Diagnostic Decision Support Systems—Past, Present, and Future,” Journal of the American

Medical Informatics Association, vol. 1, No. 1, January/February 1994, pp. 8-27.

8 R.W. Jelliffe et al., “Adaptive Control of Drug Dosage Regimens: Basic Foundations, Relevant Issues, and Clinical Examples,” International Journal of Biomedical Computing, vol. 36, No. 1-2, June 1994, pp. 1-23.

9 S. Rolfe and N.J.N. Harper, “Ability of Hospital Doctors To Calculate Drug Doses,” British Medical Journal, vol. 310, No. 6988, May 6,

1995, pp. 1173-1174.

10 E.R. Gonzales et al., “Computer-Assisted Optimization of Aminophylline Therapy in the Emergency Department,” American Journal of

Emergency Medicine, vol. 7, No. 4, July 1989, pp. 395-401.

11 Dasta et al., op. cit., footnote 1.
Appendix C Applications of Clinical Decision Support Systems | 199

condition at that point in time. The Regenstrief

Medical Record System at Indiana University12

was apparently the first CDSS to develop a comprehensive set of preventive care reminders, for

example, to administer influenza vaccinations.13

More specialized examples include two systems

that provide reminders to perform blood pressure

measurement and cervical cancer screening, respectively.14 The HealthQuiz program elicits

background information and risk factors from patients, then compares their answers to detailed

preventive care guidelines, flags problems, and

recommends appropriate interventions.15

ACTIVE-CARE ADVICE

These systems are designed to assist the clinician

in performing diagnostic or therapeutic procedures (including pharmaceutical treatments)

when the patient reaches certain stages in the process of care for a given health problem, again often

modeled in a formal clinical protocol. An activecare advisory system requires repeated input of

data on the patient’s health problems, tests, and

treatments over time. The protocol specifies exactly what diagnostic and therapeutic procedures

should be performed at each stage in the process

of care for the health problem at hand. This type

of computer-based clinical advice can take six basic forms:

1. Treatment recommendations (including pharmaceuticals) appropriate for the health problem

at hand, for example, the MYCIN program that

provides diagnostic and treatment advice for

patients with meningitis,16 and the antibiotic

consultant component of the Health Evaluation

through Logical Processing (HELP) system at

LDS Hospital in Salt Lake City, Utah, that recommends appropriate antibiotics in light of the

patient’s characteristics and specific infection,

drawn from an electronic medical record.17

2. Reminders to the clinician to perform specific

diagnostic or therapeutic procedures at certain

stages in the process of caring for the health

problem at hand, such as adult respiratory distress syndrome in the HELP system.18

3. Alerts to the clinician regarding potential adverse events, for example, worsening of the patient’s condition, based on feedback of

abnormal test results.19

4. Feedback (including alerts) regarding orders

that the clinician entered for the patient, including:

 possibly inappropriate treatments, given the

patient’s complicating health problems and/or

12 C.J. McDonald et al., “The Regenstrief Medical Record System: 20 Years of Experience in Hospitals, Clinics, and Neighborhood Health

Centers,” M.D. Computing, vol. 9, No. 4, July/August 1992, pp. 206-217.

13 C.J. McDonald, S.L. Hui, and W.M. Tierney, “Effects of Computer Reminders for Influenza Vaccinations on Morbidity During Influenza

Epidemics.” MD Computing, vol. 9, No. 5, September-October 1992, pp. 304-312.

14 I. McDowell, C. Newell, and W. Rosser, “A Randomized Trial of Computerized Reminders for Blood Pressure Screening in Primary

Care,” Medical Care, vol. 27, No. 3, March 1989, pp. 297-305; I. McDowell, C. Newell, and W. Rosser, “Computerized Reminders To Encourage Cervical Screening in Family Practice,” Journal of Family Practice, vol. 28, No. 4, April 1989, pp. 420-424.

15 “’HealthQuiz’ Makes Preventive Care Guidelines Easy To Apply,” Report on Medical Guidelines & Outcomes Research, Jan. 26, 1995,

pp. 5-6.

16 E.H. Shortliffe, “Computer Programs To Support Clinical Decision Making,” Journal of the American Medical Association, vol. 258, No.

1, July 3, 1987, pp. 61-66.

17 R.S. Evans, D.C. Classen, and S.L. Pestotnik, “Improving Empiric Antibiotic Selection Using Computer Decision Support,” Archives of

Internal Medicine, vol. 154, No. 8, Apr. 25, 1994, pp. 878-884.

18 A.H. Morris, “Protocol Management of Adult Respiratory Distress Syndrome,” New Horizons, vol. 1, No. 4, November 1993, pp.

593-602.

19 K.E. Tate, R.M. Gardner, and L.K. Weaver, “A Computerized Laboratory Alerting System,” M.D. Computing, vol. 7, No. 5, SeptemberOctober 1990, pp. 296-301; D.M. Rind et al., “Effect of Computer-Based Alerts on the Treatment and Outcomes of Hospitalized Patients,”

Archives of Internal Medicine, vol. 154, No. 13, July 11, 1994, pp. 1511-1517.
200 | Bringing Health Care Online: The Role of Information Technologies

background characteristics (even if the treatment would otherwise be appropriate for the

health problem at hand), for example, alerts regarding drug allergies in the order-entry system

at Brigham and Women’s Hospital in Boston;20

 possibly inappropriate treatments regardless of

the patient’s health problems or characteristics,

for example, commercial programs to detect

drug-drug and drug-nutrient interactions;21

 likely conflict or redundancy between a chosen

test and others already ordered for the patient;22

 likely results of a test ordered for the patient; if

the probability of an abnormal result is low, the

clinician can reconsider whether the test is really worth performing;23

 results of previous tests on the patient that are

like the one being ordered, so the clinician may

reconsider whether the test really needs to be

repeated;24

 the cost of a test or treatment ordered for the patient, so the clinician can reconsider whether it

is really worth performing;25 and

 tests or treatments that would be less costly

than the one ordered, but equally effective in

treating the health problem at hand.26

5. Prompts to the clinician for decisions regarding

testing or treatment options, or for entry of information on the patient’s health problems or

background, as in the drug order-entry system

at Brigham and Women’s Hospital.27

6. Prognoses of intensive care unit patients based

on such predictors as severity of illness (using

vital signs and other physical measures) and

physiological reserve (age and complicating

health problems) in the Acute Physiology and

Comprehensive Health Evaluation (APACHE)

system.28 APACHE is also used as a method of

measuring severity of illness and risk-adjusting

outcome measures.29 An expanded prognostic

model known as SUPPORT (Study to Understand Prognoses and Preferences for Outcomes

and Risks of Treatments) is designed to predict

survival to 180 days (rather than to discharge)

and includes patients who are not severely ill.30

20 R. F. Gibson and B. Middleton, “Health Care Information Management Systems To Support CQI,” Clinical Practice Improvement: A New

Technology for Developing Cost-Effective Quality Health Care, S.D. Horn and D.S.P. Hopkins (eds.) (New York, NY: Faulkner & Gray, 1994),

pp. 116-117.

21 T.I. Poirer and R. Giudici, “Evaluation of Drug Interaction Microcomputer Software: Comparative Study,” Hospital Pharmacy, vol. 26,

No. 1, January 1991, pp. 30-37; T.I. Poirer and R. Giudici, “Evaluation of Drug-Food/Nutrient Interactions Microcomputer Software Programs,” Hospital Pharmacy, vol. 26, No. 6, June 1991, pp. 533-540.

22 Connelly and Bennett, op. cit., footnote 2.

23 W.M. Tierney et al., “Computer Predictions of Abnormal Test Results: Effects on Outpatient Testing,” Journal of the American Medical

Association, vol. 259, No. 8, Feb. 26, 1988, pp. 1194-1198.

24 W.M. Tierney et al., “Computerized Display of Past Test Results: Effect on Outpatient Testing,” Annals of Internal Medicine, vol. 107, No.

4, October 1987, pp. 569-574.

25 W.M. Tierney, M.E. Miller, and C.J. McDonald, “The Effect on Test Ordering of Informing Physicians of the Charges for Outpatient Diagnostic Tests,” New England Journal of Medicine, vol. 322, No. 21, May 24, 1990, pp. 1499-1504.

26 W.M. Tierney et al., “Physician Inpatient Order Writing on Microcomputer Workstations: Effects on Resource Utilization,” Journal of the

American Medical Association, vol. 269, No. 3, Jan. 20, 1993, pp. 379-383.

27 Gibson and Middleton, op. cit., footnote 21.

28 W.A. Knaus, D.P. Wagner, and J. Lynn, “Short-Term Mortality Predictions for Critically Ill Adults: Science and Ethics, Science, vol. 254,

No. 5030, Oct. 18, 1991, pp. 389-394; J.E. Zimmerman, W.A. Knaus, and M. Seneff, “Outcome Prediction in Intensive Care,” Intensive Care

Rounds, No. 10125 (Abingdon, England: The Medicine Group (Education), Ltd., January 1993).

29 L.I. Iezzoni, “Risk Adjustment for Medical Outcome Studies,” Medical Effectiveness Research Data Methods, M.L. Grady and H.A.

Schwartz (eds.), Agency for Health Care Policy and Research, AHCPR Pub. No. 92-0056 (Rockville, MD: July 1992), pp. 83-97.

30 W.A. Knaus et al., “The SUPPORT Prognostic Model: Objective Estimates of Survival for Seriously Ill Hospitalized Adults,” Annals of

Internal Medicine, vol. 122, No. 3, Feb. 1, 1995, pp. 191-203.
Appendix D

Executive

Branch

Telemedicine

Activities

n September 1993, the Clinton Administration published its

Agenda for Action report, outlining its vision of the National Information Infrastructure (NII) and specific actions the

government would take.1 By Executive Order 12864, the

President appointed the Information Infrastructure Task Force

(IITF), under the direction of the Secretary of Commerce. The

IITF is comprised of high-level representatives of the federal

agencies that play a role in developing and applying information

and telecommunications technologies, including independent

agencies and commissions such as the Federal Communications

Commission. The President also appointed the Advisory Council

on the NII, which broadly represents the key constituencies affected by the NII (business, labor, academia, public interest

groups, and state and local governments).2

The IITF’s Committee on Applications and Technology coordinates efforts to develop, demonstrate, and promote applications

of the NII and develops and recommends technology strategy and

policy to accelerate its implementation. One of the subgroups of

the Health Information and Applications Working Group is responsible for telemedicine. The purpose of the telemedicine subgroup is to promote the efficient, effective use of telemedicine in

the delivery of health care services through the coordination of

federal resources and policies. In August 1994, the IITF Health In1Information Infrastructure Task Force, “The National Information Infrastructure:

Agenda for Action,” National Telecommunications and Information Administration,

Washington, DC, Sept. 15, 1993.

2NII Principles and Actions: A Checklist of the Clinton Administration’s Progress,

September 1993-94, September 1994, p. 3.

| 201
202 | Bringing Health Care Online: The Role of Information Technologies

formation and Applications Working Group convened a meeting of experts to devise a policy strategy for telemedicine. In April 1995, a report of the

conference’s conclusions and recommendations

was released.3

In March 1995, Vice President Al Gore requested the Department of Health and Human Services (DHHS) to lead an interagency effort to

address and resolve major policy issues involved

in the NII and the health sector.4 This effort is to

be coordinated with the ongoing work of the Information Infrastructure Task Force. With respect

to telemedicine, DHHS was asked to prepare a report on current telemedicine projects, the range of

potential telemedicine applications, and public

and private actions to promote telemedicine and to

remove existing barriers to its use.

The federal government has funded a number

of pilot projects in telemedicine over the past 30

years. There is currently a good deal of interest in

and funding for both demonstration projects and

evaluation projects, although proposed budget

cutbacks could have a significant negative effect

on funding for telemedicine projects . A sample of

executive branch telemedicine activities is provided below.

DEPARTMENT OF HEALTH AND HUMAN

SERVICES

The Office of Rural Health Policy (ORHP), in the

Health Resources and Services Administration,

has been involved in telemedicine for more than

5 years, mainly providing grant funding for demonstration projects. These have included Texas

Tech University (in cooperation with the Health

Care Financing Administration and the Assistant

Secretary for Planning and Evaluation), West Virginia University’s Robert C. Byrd Health

Sciences Center in Morgantown, and RODEO

NET in Oregon (described in chapter 5). ORHP

sponsored a workshop in November 1993 to explore major telemedicine policy issues and the

role of telemedicine systems in rural health care

network development. Conference deliberations

resulted in the publication of the report, Reaching

Rural.

5

In November 1994, ORHP awarded three-year

grants totaling $4.5 million to support 11 telemedicine projects in 10 states. These were awarded

under the Rural Telemedicine Grant Program, and

will demonstrate the use of telemedicine as part of

rural health network development and provide a

baseline of information for conducting a systematic evaluation of telemedicine systems serving

rural areas. Cost participation was required on the

part of grantees. In addition, continuation funding

of $800,000 was granted to the Robert C. Byrd

Health Sciences Center telemedicine pilot project

in West Virginia. In the fall of 1994, ORHP also

awarded a grant for an 18-month evaluation of

telemedicine projects.

The Health Care Financing Administration

(HCFA) is a key player in telemedicine in terms of

developing policies for Medicare and Medicaid

reimbursement of telemedicine services. The

agency has supported several research projects in

telemedicine, most notably at Texas Tech University (with the Assistant Secretary for Planning and

Evaluation and ORHP) and Iowa Methodist Hospital in Des Moines. HCFA also supported the

University of Colorado’s Center for Health Policy

Research in a study to develop a framework for

3Report of the Working Conference on Telemedicine Policy for the NII, sponsored by the Health Information and Application Working

Group of the IITF Committee on Applications and Technology and the Senate/House Ad Hoc Steering Committee on Telemedicine and

Health Care Informatics, April 1995.

4Vice President Al Gore, memorandum to Donna Shalala, Secretary of Health and Human Services, Washington, DC, Mar. 8, 1995.

5Reaching Rural, Office of Rural Health Policy, Health Resources and Services Administration, Public Health Service, Department of

Health and Human Services, 1994.
Appendix D Executive Branch Telemedicine Activities | 203

evaluating various types of telemedicine.6 In the

summer of 1994, new grants were awarded as part

of a congressionally supported research and demonstration program. HCFA provided startup funding for the Clinical Telemedicine Cooperative

Group, an ad hoc alliance to share common telemedicine research protocols and testing methodologies; it also provided some startup funding for

the Telemedicine Information Exchange(TIE), a

database established at the Telemedicine Research Center, Oregon Health Sciences University. HCFA is also providing some of the support for

the Institute of Medicine’s study of evaluation criteria for telemedicine.

The National Library of Medicine (NLM),

through the High Performance Computing and

Communications Program (HPCC), funds applications research in a number of areas, including

telemedicine. For example, the National Laboratory for the Study of Rural Telemedicine at the

University of Iowa has recently received a threeyear grant of $7.3 million to test the use of Iowa’s

fiberoptic network to link medical facilities and libraries at the University to hospitals, clinics, and

perhaps doctors’ offices, throughout the state.

Oregon Health Sciences University, University of

Pittsburgh, and West Virginia University also received funding for telemedicine projects from the

HPCC Health Care Awards. NLM is the principal

funder of an Institute of Medicine study under way

on criteria for evaluation of telemedicine projects.

NLM has also compiled a telemedicine bibliography containing more than 1,600 citations that is

also available on the Internet.7

The Agency for Health Care Policy and Research (AHCPR) helped to support the development of telemetry (transmitting electrocardiograms

and vital signs), and telemedicine (including the

early NASA STARPAHC project on the Papago

Indian Reservation in Arizona). It has also provided support for meetings on telemedicine.

DEPARTMENT OF AGRICULTURE

The Rural Utilities Service (RUS) (formerly the

Rural Electrification Administration) sponsors

the Distance Learning and Medical Link Grant

Program, which demonstrates the ability of rural

communities to utilize existing or proposed telecommunications systems to achieve sustainable,

cost-effective distance learning or medical-link

networks. Implemented in fiscal year 1993, a total

of $20 million in funding has been committed to

a total of 61 projects. Approximately 20 of these

are primarily medical links and a majority have

some health-related aspects. For fiscal year 1995,

a total of $7.5 million is available to fund $75 million in applications from about 250 applicants.8

For Medical Link Projects, RUS funds equipment

used in physician consultation, teleradiology, and

educating rural health care providers. Some of the

equipment includes teleradiology workstations,

x-ray scanners, and digital microscopes, as well as

distance-learning equipment such as encoding

and decoding devices, specialized cameras and

video monitors, video switchers, microphone

mixers, computers, and local area networking

equipment.

DEPARTMENT OF COMMERCE

In October 1994, the National Telecommunications and Information Administration (NTIA),

through its Telecommunications and Information

6The Center for Health Policy Research, Denver, CO, produced four reports for HCFA. Jim Grigsby et al., Analysis of Expansion of

Access to Care Through Use of Telemedicine and Mobile Health Services: 1) Literature Review and Analytic Framework, December 1993;

2) Telemedicine Policy: Quality Assurance, Utilization Review, and Coverage, August 1994; 3) Study Summary and Recommendations for

Further Research, December 1994; and 4) Telemedicine Policy: Coverage and Payment, February 1995.

7”Telemedicine: Past, Present, and Future, January 1966 through March 1995,” Current Bibliographies in Medicine, CBM No. 95-4,

National Library of Medicine, U.S. Department of Health and Human Services, Public Health Service, National Institutes of Health, Bethesda, MD. Internet access through FTP to nlmpubs.nlm.nih.gov and login as anonymous.

8J.R. Binder, Director, Rural Development Assistance Staff, Rural Utilities Service, personal communication, May 10, 1995.
204 | Bringing Health Care Online: The Role of Information Technologies

Infrastructure Assistance Program (TIIAP),

awarded more than $24 million for fiscal year

1994 to support the development of the NII. A total of 14 of 92 grants were for planning and demonstration projects that are designed to develop,

demonstrate, and promote applications of information technology that will educate, restrain

health care costs, improve quality, and increase

access to health care with the potential for widescale deployment and interconnection over NII

networks. Grantees were required to provide

matching funds.

DEPARTMENT OF DEFENSE (DOD)

The Medical Research and Materiel Command,

Fort Detrick, is conducting several telemedicine

and teleradiology projects in cooperation with

other branches of the military and various universities. The Walter Reed Army Medical Center

(WRAMC) has successfully employed telemedicine in Somalia, Croatia, Macedonia, and Haiti.

WRAMC is also working with several southern

states to develop peacetime clinic and hospital

consultation procedures. The Center has also taken the lead with the Uniformed Services University of the Health Sciences in establishing a military

telemedicine initiative to provide retrospective

and prospective evaluations of the various projects.

The Medical Diagnostic Imaging Support

(MDIS) system, developed by DOD based on the

commercial Picture Archiving and Communication System (PACs), is employed in several teleradiology networks that use satellites as well as land

lines to connect military treatment facilities with

each other and with ambulatory clinics and university medical centers throughout the world.

These projects include the Hilltop Plan (based on

four central sites in the United States and Korea),

the AKAMAI project (linking Tripler Army Medical Center in Hawaii with several sites around the

Pacific Rim), and Project Daybreak (linking several remote sites in Korea with Tripler as well as

the central site in Seoul). Future plans envision integration of MDIS with other health care information systems, including computer-assisted

diagnosis programs, multimedia devices, and reference databases.

Other branches of the military are also using a

variety of telemedicine systems to better meet

their needs to deliver health care to their members

in a variety of settings. The Tri-Service Telemedicine Testbed Project, established in September

1994, provides a plan for guiding the Testbed

Project and integrating telemedicine technologies

into the Military Health Services System. This action also implemented the National Digital Telemedicine Testbed initiative of the DOD National

Performance Review. In July 1995, the Army

Medical and Materiel Development Command

and the ISIS Center, Georgetown University Medical Center, co-sponsored a meeting to develop approaches for DOD technology assessment and

evaluation of telemedicine.9

NATIONAL AERONAUTICS AND SPACE

ADMINISTRATION (NASA)

NASA has had a long-term involvement in telemedicine activities. The agency is interested in

telemedicine for medical care in space for future

long-duration space platforms and to minimize

risk to astronauts. NASA was involved in the early STARPAHC Program, as well as the Spacebridge to Armenia, which provided consultations

via satellite to a disaster area in 1988. NASA was

recently involved in a joint effort with Russia, the

Spacebridge to Moscow, to link several U.S. medical centers with a hospital in Moscow. The

agency also participated with the Mayo Clinic in

a telemedicine feasibility study with the Pine

Ridge Indian Reservation in 1994. In September

1994, NASA joined with the Uniformed Services

University of the Health Sciences in sponsoring

the Second International Conference on Teleme9The Chestertown Roundtable, “Developing Approaches for DOD Technology Assessment and Evaluation of Telemedicine,” Chestertown, MD, July 30-August 1, 1995.
Appendix D Executive Branch Telemedicine Activities | 205

dicine: Remote Health Care and Disaster Response.10

DEPARTMENT OF VETERANS AFFAIRS

(VA)

The VA is testing the use of its electronic mail systems for teleconsultation. This system handles

text, images, voice, scanned documents, electrocardiogram signals, and patients’ reports. Using

the VA’s wide area network, this capability will allow consultations between physicians at different

VA locations. The Birmingham (AL) VAMC

plans to purchase videoconferencing equipment

for all VA medical centers in Alabama. This

equipment will be placed in the treatment areas of

the hospitals. Physicians will be able to consult

with specialists prior to transporting patients for

specialty care, including discussing x-rays and

other pertinent medical data. The patient will also

be able to participate in these discussions, if feasible and medically advisable. It is believed that this

will greatly reduce the number of patients needing

to be transported for care, and will also serve as an

education tool for physicians. Also, the Tuscaloosa VAMC has transmitted radiology images to

the Birmingham VAMC for reading by the radiologist in residence. The VA is also a supporter of

the Institute of Medicine study of evaluation criteria for telemedicine.

10The conference proceedings are published in three special issues of the Journal of Medical Systems, vol. 19, No. 1, February 1995;

vol. 19, No. 2, April 1995; and vol. 19, No. 3, June 1995.
Appendix E

Electronic

Health

Information

Sources

n enormous amount of health information is now available in electronic form. Until recently, most of these resources were accessible through dial-up bulletin board

systems or, if the files resided on a computer connected to

the Internet, through a number of different means of transferring

copies of the files from the source computer to a remote user’s

computer. Recently, however, a new graphical interface to the Internet, known as the World Wide Web (WWW), has made it possible to rapidly retrieve, arrange, and display on web pages the

contents of files—rather than just their names—and for users to

transfer from resource to resource along a virtually endless web of

hyperlinks with the click of a mouse button.

This appendix briefly surveys some of the audio, visual, textual, and hypertextual health information available on the WWW.

The Uniform Resource Locator (URL) that accompanies each

electronic resource identifies its location and filename and the appropriate method for accessing the files. The URLs are used by

web browser software, such as Netscape Navigator,1 Mosaic,2 or

Lynx,3 to locate and retrieve the files. This list of web sites represents only a sample of the wide variety of free health information

that is available on the WWW.

1 Netscape Communications Corp., <URL: http://home.netscape.com/ >. URLs

listed in this appendix are accurate as of the date of publication but will change over time.

The indices mentioned in the last section of the appendix should be consulted for updated

access information.

2 National Center for Supercomputer Applications, <URL: http://www.ncsa.uiuc.edu >.

3 W3 Consortium, <URL: http://www.w3.org/hypertext/WWW/Lynx/Status.html >.

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CONSUMER AND PATIENT INFORMATION

University health clinics are a rich source of information for consumers and patients. Sites such

as Healthwise4 at Columbia University, the

HEALTHLINE Server5 at the University of Montana, and the HealthInfo Gopher6 at Rice University offer multimedia educational materials,

advice columns, mailing lists, and other resources

addressing preventive medicine, nutrition, AIDS,

sports medicine, drug and alcohol abuse, women’s

health, sexuality, and other general health information topics. Abstracts and summaries of articles about health issues from newspapers and the

popular press are collected at sites such as Biomedicine and Health in the News7 and Health and

Medicine in the News.8 The Iowa Health Book at

The Virtual Hospital9 has patient information,

such as a guide for helping a child cope with visiting a family member hospitalized in an intensive

care unit. The TALARIA Hypermedia Clinical

Practice Guidelines for Cancer Pain10 and the

PharmInfoNet DrugDB11 (a descriptive database

of pharmaceuticals and their effects, organized according to generic and trade names) are two other

examples of resources available throughout the

web that may help consumers understand complex medical care. In addition, the web indices

summarized at the end of this appendix contain

subscription information for a huge variety of email mailing lists and Usenet discussion groups

concerning specific diseases and health conditions.

RESOURCES FOR HEALTH

PROFESSIONALS

Numerous web pages contain information and hyperlinks designed for specific health professionals. Nightingale,

12 NP Web,13 Physician’s Guide

to the Internet,14 and the Interactive Medical Student Lounge15 are sites designed respectively for

nurses, nurse practitioners, physicians, and medical students. Sites such as the Emergency Medicine and Primary Care Home Page16 provide

resources and discussion forums for specialized

health disciplines, and reference sites such as the

CHORUS Collaborative Hypertext of Radiology17 contain quick reference materials. Cumulative indices of research literature from over 20

different subject areas in biomedicine are maintained at Current Bibliographies in Medicine.

18 A

variety of sites are devoted to medical education.

Some, such as the University of California at San

4 Columbia University Health Service, Health Education and Wellness Program, <URL: http://www.cc.columbia.edu/cu/healthwise/ >.

5 University of Montana Student Health Services, <URL: http://healthline.umt.edu:700/ >.

6 Rice University Student Health Service, <URL: gopher://riceinfo.rice.edu/11/Safety/HealthInfo >.

7 University of Connecticut Health Center, Lyman Maynard Stowe Library, <URL: gopher://inform.uchc.edu/11gopher_root%3a%5b_data04._data0401%5d >.

8 University of Minnesota, <URL: gopher://lenti.med.umn.edu:71/11/news/citations >.

9 University of Iowa College of Medicine, Department of Radiology, Electric Differential Multimedia Laboratory, <URL: http://indy.radiology.uiowa.edu/VirtualHospital.html >

10 University of Washington, Department of Statistics, <URL: http://www.stat.washington.edu/TALARIA/TALARIA.html >.

11 Pharmaceutical Information Associates, Ltd., <URL: http://pharminfo.com/drugdb/db_mnu.html >.

12 University of Tennessee at Knoxville, College of Nursing, <URL: http://nightingale.con.utk.edu:70/0/homepage.html >.

13 University of New Hampshire, Department of Nursing, <URL: http://unhinfo.unh.edu/unh/acad/health/nursing/index.html >.

14 NetRep Explorist, <URL: http://www.netrep.com/global/biz/pgi/pgi.html >.

15 University of Kansas, <URL: http://falcon.cc.ukans.edu:80/~nsween/ >.

16 Emergency Medicine Bulletin Board System, <URL: http://www.njnet.com/~embbs/ >.

17 Medical College of Wisconsin, <URL: http://chorus.rad.mcw.edu/chorus.html >.

18 National Library of Medicine, <URL: ftp://nlmpubs.nlm.nih.gov/bibs/cbm/ >.
Appendix E Electronic Health Information Sources | 209

Francisco Primary Care Teaching Module19 and

The Interactive Patient,20 are designed for medical students and residents, and others—including

the University of Washington Radiology Webserver,21 the Interesting Case Conference,22 and MedEd23—offer practice in diagnosis or continuing

medical education courses. MedSearch America24

is an electronic bank of job listings for health professionals.

MEDICAL IMAGES

As web browsers capable of displaying photographic images and video clips have been developed, the World Wide Web has become an ideal

medium for distributing medical images for

instructional and historical purposes. The Visible

Human Project25 documents human anatomy in a

series of magnetic resonance, photographic, and

computerized tomography images of cross-sections of a human body at one millimeter intervals;

the Visible Embryo Project26 is a related compilation of images illustrating human developmental

embryology. The GE Three Dimensional Medical

Reconstruction27 page includes animated “flythroughs” of heart arteries, the lungs, and the

brain, and a simulation of a baby delivery. A compendium of brain images is found at the Whole

Brain Atlas.

28 The Medical Illustrator’s Home

Page29 serves as a contact point for medical illustrators, publishers, authors, and medical schools.

Nearly 60,000 historical images from the archives

of the National Library of Medicine are found in

OnLine Images from the History of Medicine.

30

An index of other medical imaging resources is

found at Medical Imaging on the Web.31

TELEMEDICINE AND RURAL MEDICINE

Information about distance medicine, telemedicine, and rural medicine can be found at the Telemedicine Information Exchange,32 Telemedicine

Resources,33 REACH-TV,34 and RuralNet.

35

HEALTH POLICY AND GOVERNMENT

Many government agencies maintain WWW sites

with information for both health care professionals and health care consumers. The web site at the

19 Stanford University and the University of California at San Francisco, Divisions of General Internal Medicine, <URL: http://wwwmed.Stanford.EDU/MedCenter/MedSchool/DGIM/Teaching/Modules-index.html >.

20 Marshall University School of Medicine, <URL: http://medicus.marshall.edu/medicus.htm >.

21 University of Washington, Department of Radiology, <URL: http://www.rad.washington.edu/ >.

22 Massachusetts General Hospital, Department of Emergency Medicine, <URL: http://emergency.mgh.harvard.edu/wicc.htm >.

23 Loyola University (Chicago) Medical Education Network, <URL: http://www.meddean.luc.edu/lumen/MedEd/Medpage.html >.

24 MedSearch America, <URL: gopher://gopher.medsearch.com:9001/1 >.

25 National Library of Medicine, <URL: http://www.nlm.nih.gov/extramural_research.dir/visible_human.html >.

26 National Museum of Health and Medicine, Human Developmental Anatomy Center <URL: http://bubba.afip.mil/ >.

27 General Electric Corporate Research and Development, <URL: http://www.ge.com/crd/ivl/three_dim_medical.html >.

28 Harvard Medical School, <URL: http://www.med.harvard.edu/AANLIB/home.html >.

29 Mednexus, <URL: http://www.mednexus.com/med_illustrator/index.html >.

30 National Library of Medicine, <URL: http://www.nlm.nih.gov/hmd.dir/oli.dir/ >.

31 Center for Advanced Studies, Research, and Development in Sardinia, <URL: http://www.crs4.it/~france/MEDICAL/institutions.html >.

32 Telemedicine Research Center, <URL: http://tie.telemed.org/ >.

33 University of Washington, Image Computing Systems Laboratory, <URL: http://icsl.ee.washington.edu/~cabralje/tmresources.html >.

34 East Carolina University School of Medicine, Center for Health Sciences Communication, <URL: http://www.telemed.med.ecu.edu/

telemenu.htm >.

35 Marshall University School of Medicine, <URL: http://ruralnet.mu.wvnet.edu/ >.
210 | Bringing Health Care Online: The Role of Information Technologies

Health Care Financing Administration36 contains

information about Medicare and Medicaid, and

the web site at the Department of Health and Human Services37 guides consumers to a wide variety of health information available through

agencies such as the Food and Drug Administration38 and the National Institute on Aging.39 The

Health Services/Technology Assessment Text40

includes the full text of clinical practice guidelines, quick-reference guides for clinicians, and

consumer brochures developed with the support

of the Agency for Health Care Policy and Research. The Centers for Disease Control and Prevention41 and the Public Health Service42

maintain WWW sites with information about

communicable diseases, epidemics, and population-based health care. Many institutions, such as

the World Health Organization,43 maintain web

sites with information on international health issues. A useful index to governmental health information resources is found at the National

Health Information Center.44

STANDARDS

Two useful web resources dedicated to the various

technical standards discussed throughout this report are the MSDS Healthcare Standards Home

Page45 and the Gateway to Standards Organizations.46

PROFESSIONAL ORGANIZATIONS AND

JOURNALS

Many professional societies including the American Medical Informatics Association,47 the

American Psychological Society,48 and the International Society of Nephrology49 maintain

web pages with membership information and

news about society activities and publications.

Peer-reviewed academic journals are beginning to

appear online, including The Digital Journal of

Ophthalmology50 and The Journal of Medical

Imaging,

51 as well as government publications

such as the Morbidity and Mortality Weekly Report.52

36 Health Care Financing Administration, <URL: http://www.ssa.gov/hcfa/hcfahp2.html >.

37 Department of Health and Human Services, <URL: http://www.os.dhhs.gov/ >.

38 U.S. Food and Drug Administration, <URL: http://www.fda.gov/fdahomepage.html >.

39 National Institute on Aging, <URL: gopher://gopher.os.dhhs.gov/1/dhhs/aoa/aoa/agepages >.

40 National Library of Medicine, <URL: http://text.nlm.nih.gov/ >.

41 Centers for Disease Control and Prevention, <URL: http://www.cdc.gov/ >.

42 Public Health Service, <URL: http://phs.os.dhhs.gov/phs/phs.html >.

43 World Health Organization, <URL: http://www.who.ch/programmes/WHOProgrammes.html >.

44 National Health Information Center, <URL: http://nhic-nt.health.org/ >.

45 Duke University Medical Center Information Systems, <URL: http://www.mcis.duke.edu:80/standards/ >.

46 United Technologies National Standards System Network, <URL: http://hsdwww.res.utc.com/std/gateway/orgindex.html >.

47 American Medical Informatics Association, <URL: http://amia2.amia.org/ >.

48 American Psychological Society, <URL: http://psych.hanover.edu/APS/ >

49 International Society of Nephrology—Renal Pathology Society, <URL: http://synapse.uah.ualberta.ca/synapse/000p0035.htm >.

50 Massachusetts Eye and Ear Infirmary, Department of Ophthalmology, <URL: http://www.meei.harvard.edu/meei/DJOhome.html >.

51 Johns Hopkins University, School of Medicine, Department of Radiology and the William H. Welch Medical Library,

<URL: http://jmi.gdb.org/JMI/ejourn.html >.

52 Centers for Disease Control and Prevention, <URL: http://www.crawford.com/cdc/mmwr/mmwr.html >.
Appendix E Electronic Health Information Sources | 211

INDICES

The World Wide Web resources listed above are

only a small fraction of the existing sites, and new

sites are being developed at a very rapid pace. Several sites maintain current catalogs of health information resources on the Internet. The index

sites include Medical Matrix,

53 IHPNet,54 Hospital Web,

55 The Whole Internet Catalog: Health

and Medicine,

56 MedWeb,57 and the Yahoo! Medicine List.

58

53 Internet Working Group of the American Medical Informatics Association, <URL: http://kuhttp.cc.ukans.edu/cwis/units/medcntr/Lee/

HOMEPAGE.HTML >.

54 International Network for Interfaith Health Practices, <URL: http://www.interaccess.com/ihpnet/health.html >.

55 Massachusetts General Hospital, Department of Neurology, <URL: http://dem0nmac.mgh.harvard.edu/hospitalweb.html >.

56 Global Network Navigator, <URL: http://nearnet.gnn.com/gnn/wic/med.toc.html >.

57 Emory University Health Sciences Center Library, <URL: http://www.cc.emory.edu/WHSCL/medweb.html#toc2 >.

58 Yahoo! Corp., <URL: http://www.yahoo.com/Health/ >.
Appendix F

Boxes,

Figures, and

Tables

Boxes

Chapter 1

1-1: Effects on the Health Care Workforce

1-2: Managed Care

1-3: Grassroots Computer Networking: Lessons Learned

Chapter 2

2-1: The Content of Patient Records

2-2: Speech and Handwriting Recognition

2-3: Automated Data Collection and the Medical Information Bus

2-4: The HELP System

2-5: Digital Image Compression

2-6: Security Technologies

2-7: A Voice and Data Communications Primer

2-8: HL7 and ICD-9-CM

Chapter 3

3-1: EDI and Electronic Commerce

3-2: What is a Value-Added Network?

3-3: EDI Standards

3-4: Card Technology and Health Records

Chapter 4

4-1: Health Plan Performance Measures Used in the Health Plan and Employer Data and Information Set (HEDIS)

4-2: Provider Performance Measures Used in the Indicator Measurement System (IMSystem)

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Chapter 5

5-1: National Consortium for Telemedicine Evaluation

5-2: Clinical Telemedicine Cooperative Group Organized by the Telemedicine Research Center,

Oregon Health Sciences University

5-3: American Telemedicine Association

5-4: National Information Infrastructure Testbed

5-5: Telemedicine Information Exchange

Figures

Chapter 1

1-1: Information Technology Applications Currently Being Adopted

Chapter 2

2-1: Health Information Pathways to Hospital Information Systems

2-2: Health Information on the Internet

2-3: Messaging Standards for Clinical Institutions

Chapter 3

3-1: Health Care Industry Trading Relationships

3-2: Payment-Related Transactions

3-3: High-Level Architecture of a Community Health Information Network

3-4: Common User Interface

3-5: Federated Database Approach for a Community Health Information Network

Chapter 4

4-1: Algorithm Depicting a Clinical Practice Guideline for Evaluation and Care of Patients with

Heart Failure

Chapter 5

5-1: A Telemedicine Health Care Network

5-2: East Carolina University Telemedicine Network

5-3: Rural Area Networks

Tables

Chapter 2

2-1: Key Information Technologies for Health Care

2-2: Storage Requirements for Imaging Techniques

Chapter 3

3.1: Estimates of Cost Savings for Payers, Providers, and Employers Through the Use of Information Technology

Chapter 5

5-1: Summary of Telemedicine Application Categories
Appendix G

Abbreviations

and

Glossary

ACTS

Advanced Communications and Technology Satellite

Administrative data

Data used in the administration of public programs or agencies or private businesses. In health,

examples of administrative data are hospital discharge abstracts and health insurance claims and

enrollment records.

Administrative simplification

Efforts to reduce the cost and complexity of health

care through increased standardization and automation of health care providers’ and insurers’

administrative activities.

Admission/discharge record (or discharge

abstract)

A synopsis of a patient record containing basic

identifying and financial information about a patient, along with clinical information, including

the admitting and final diagnosis and a summary

of procedures performed.

Affordances

Behaviors and actions that are allowed or enabled

by a specific technology.

AHCPR

Agency for Health Care Policy and Research

AITN

Arizona-International Telemedicine Network

AMA

American Medical Association

AMI

Acute myocardial infarction

ANSI

American National Standards Institute

Arden Syntax

A computer language for encoding and sharing

medical knowledge in discrete modules.

ARPA

Advanced Research Projects Agency, DOD

Artificial neural network

A linked network of simple software-based processors, analogous to a biological neural network,

that can be trained as an ensemble to respond consistently to a set of numerical input stimuli.

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ASC (Accredited Standards Committee)

A committee chartered by ANSI to work on standards in a particular area of commerce. For example, ASC X12 is the committee working on standards for the insurance industry, including health.

ASTM

American Society for Testing and Materials

Asymmetric encryption

An encryption scheme in which information intended for an individual is encoded with his/her

well-known, public encryption key, but may only

be decoded with his/her private key (generated

from a guarded password).

ATM (asynchronous transfer mode)

A fast networking protocol based on small, uniform packets. ATM communications are suitable

for continuous transfer of large amounts of data,

including video streams.

ATP (Advanced Technology Program)

A Commerce Department program that funds

cooperative development and validation of enabling technologies, including computer and information technologies.

Authenticator

A device that provides an internally stored or calculated response to verify a user’s identity when

logging onto a computer. Only authorized users

are likely to both know a unique piece of information (the password) and be in possession of a

unique piece of equipment (the authenticator).

Automated data collection

Direct transfer of physiological data from monitoring instruments to a bedside display system or a

computer-based patient record.

Backbone

A high-capacity communications channel that

carries data accumulated from smaller branches of

a computer or telecommunications network.

Bandwidth

The amount of information an electronic connection can carry per unit of time, usually expressed

in bits per second.

Biometric identifier

A retinal pattern, fingerprint, or other anatomical

feature that can be used by a computer program

(along with appropriate interface equipment) to

positively identify a user.

C-section

Caesarean section

CABG

Coronary artery bypass graft

Capitation

A method of paying for health care based on a set

fee per member (of the health care plan) per unit of

time.

CAT scan

Computerized axial tomography scan

CBA (cost-benefit analysis)

A comparison of the net costs of an intervention

with the net savings.

CD-ROM

Compact disk, read-only memory

CDSS

Clinical decision support system

CEA (cost-effectiveness analysis)

A structured, comparative evaluation of two or

more health care interventions.

CHESS (Comprehensive Health Enhancement

Support System)

An interactive computer system developed at the

University of Wisconsin that provides information, social support, and problem-solving tools for

people living with AIDS and HIV infection.
Appendix G Abbreviations and Glossary | 217

CHF

Congestive heart failure

CHI (consumer health informatics)

The study, development, and implementation of

computer and telecommunications applications

and interfaces designed to be used by health consumers.

CHIN (community health information network)

Electronic systems that facilitate communitywide exchange of clinical and administrative information among providers, payers, banks, pharmacies, public health agencies, employers, and

other participants in the health care system.

CHMIS (community health management

information system)

An electronic system similar to a CHIN that has an

explicit emphasis on building a data repository for

use in assessing the performance of health care

providers and insurance plans.

Clinical decision support

The use of information to help a clinician diagnose and/or treat a patient’s health problem, including information about the patient and information about the kind of health problem

afflicting the patient and alternative tests and

treatments for it.

Clinical information system

Hospital-based information system designed to

collect and organize data related to the care given

to a patient, rather than administrative data.

Clinical practice guideline

An outline of broad parameters for the diagnosis,

treatment, prevention, or rehabilitation of a particular health problem.

Clinical protocol

A rigorous, detailed model of the process of care

for a particular health problem.

CME

Continuing medical education

Cochrane Collaboration

An international network of researchers that distributes results of systematic reviews of randomized controlled trials—or the most reliable evidence form other sources—on selected health

problems.

Codec

1) In telemedicine, an abbreviation for coder/decoder, an electronic device that converts an analog

electrical signal into a digital form for transmission purposes and decodes it the receiving end. 2)

In computer-based video technology, an abbreviation for compressor/decompressor, the software

that reduces the size of digitized video frames.

Coding standard

A system for assigning alphanumeric codes to

specific words, concepts, or actions for the purpose of standardizing messages between computers or organizations.

COMPASS

A local dial-up computer data network in Oregon

that provides a variety of information services.

Computer-based patient record

A compilation in digital form of all the clinical

and administrative information related to the care

of a single individual.

Confounding variable

A factor other than the health service in question

that may influence the outcome of that service.

Consensus standard

A non-proprietary technological standard developed through an open, participative process under

the aegis of a standards development organization.

Coordination of benefits

The determination of primary payer, that is, the

payer whose coverage is applied first. A secondary payer reimburses, subject to the terms of its

contract, that portion of a claim unpaid by the primary payer.
218 | Bringing Health Care Online: The Role of Information Technologies

CPR

Computer-based patient record

CPT-4 (Current Procedural Terminology, Fourth

Edition)

A classification and coding system for health services maintained by the AMA that is used in billing by clinicians and other noninstitutional providers.

CQI (Continuous Quality Improvement)

A method of analyzing and improving processes

for manufacturing products or delivering services

to meet customer needs and expectations.

CSN (Community Services Network)

A project in Washington, DC, that uses communication and computer technologies to support

and coordinate health and human services at the

community level.

Data distillation

An informal label for the process of deriving

meaning from raw data.

Data repository

The component of an information system that accepts, files, and stores data from a variety of

sources.

DDE

Direct data entry

Decision support

See Clinical decision support.

Demand management

A method of controlling health care costs by controlling access to health care services.

DEMPAQ (Developing and Evaluating Methods

to Promote Ambulatory Care Quality)

A set of performance indicators for ambulatory

care providers that is being developed by HCFA

for its Medicare program.

DHHS

Department of Health and Human Services

DICOM (Digital Imaging and Communications in

Medicine)

A standard for communications among medical

imaging devices.

Discharge abstract

See Admission/discharge record.

Disease management

A method of managing the care of a specific health

problem (usually a chronic and costly disease)

that employs the principles of continuous quality

improvement, including the use of clinical practice guidelines, outcomes measurement, and feedback to providers and insurance plans.

DOD

Department of Defense

DRG (Diagnosis Related Group)

A class of health problems derived from sets of

diagnosis and procedure codes and used by HCFA

to determine reimbursement for treatments.

DS-0, DS-1, DS-3

Digital telecommunications channels capable of

transmitting 64 kilobits, 1.544 megabits, and 45

megabits per second, respectively. The higher capacity connections are suitable for high-volume

voice, data, or compressed video traffic.

DSP (digital signal processor)

A special-purpose computer processor customized to make rapid calculations associated with

audio or video data streams.

ECU

East Carolina University

ED-NET

A statewide network created by the State of Oregon in 1989 that offers a full range of services for

those who have a need to communicate.

EDI (electronic data interchange)

The application-to-application interchange of

business data between organizations using a standard data format.
Appendix G Abbreviations and Glossary | 219

Electronic mailing lists

Free, subscription-based, electronic mail communications on the Internet or commercial online services focused on defined topics.

Encoder

Decision support systems used to facilitate accurate assignment of codes for clinical procedures.

Fault-tolerant computer systems

Reliable computer systems incorporating redundant processors, disk drives, and power supplies

to ensure almost full-time operation of a critical

information network.

FDA

Food and Drug Administration

Firewall

Computer hardware and software that block unauthorized communications between an institution’s

computer network and external networks.

Firms trial

A form of randomized controlled trial in which patients are randomly assigned to similar (“parallel”) providers who use different health services,

rather than to different groups that receive different services from the same provider.

Frame relay

A fast networking protocol in which data are packaged in variable-length frames for shuttling between computer networks.

Functional imaging

Medical imaging modalities that portray the function (such as oxygen uptake) as well as the

morphology of anatomical features.

Grouper

Software used to deduce DRGs from sets of diagnosis and procedure codes, or to analyze the

grouping decisions of medical coders for consistency and thoroughness.

Handwriting recognition

Conversion of script or block lettering to computer-based text.

HCFA

Health Care Financing Administration

HEDIS (Health Plan and Employer Data Set)

A set of performance indicators for managed care

plans, developed by NCQA.

HELP (Health Evaluation through Logical

Processing)

A clinical information system at LDS Hospital in

Salt Lake City, Utah.

HISPP (Healthcare Informatics Standards

Planning Panel)

A body created by ANSI to coordinate standards

development efforts among the various standards

bodies in health care.

HL7 (Health Level 7)

An application-level interface specification for

transmitting health-related data transactions, generally used within a single institution.

HMO

Health maintenance organization

HOST

Healthcare Open Systems and Trials consortium

HPCC (High Performance Computing and

Communications)

An advanced technology program involving several agencies of the federal government, including

NLM and NIST.

Human capital approach

A valuation technique used in cost-benefit analysis that assigns a monetary value to a human life

based on an estimate of the individual’s projected

future earnings.

ICD-9-CM (International Classification of

Diseases, Ninth Revision, Clinical Modification)

A classification and coding system for health

problems and services, maintained by NCHS and

HCFA, and used for billing by inpatient hospitals

and other institutional providers.
220 | Bringing Health Care Online: The Role of Information Technologies

IDS (integrated delivery system)

An organized system of health care providers

spanning a range of health care services.

IEEE

Institute of Electrical and Electronics Engineers

IHC (Intermountain Health Care)

A provider organization based in Utah.

IITF

Information Infrastructure Task Force

IMSystem (Indicator Measurement System)

A set of performance indicators for inpatient hospitals and other institutional providers maintained

by JCAHO.

Inference engine

A computer routine that coordinates the activities

of a knowledge- or rule-based decision support

system.

IPA (independent practice association)

An organization that contracts with a managed

care plan to deliver health services at a single capitation rate.

ISDN (integrated services digital network)

A digital telephony protocol.

JCAHO

Joint Commission on Accreditation of Healthcare

Organizations

JPEG (Joint Photographic Experts Group)

A standard for compression of static images.

Knowledge-based system

A decision support system based on automated,

systematized application of sets of rules or heuristics for analysis of raw data.

KUMC

Kansas University Medical Center

LAN (local area network)

Communications lines linking a localized group

of computers, printers, and servers.

Laser optical card

A plastic device the size of a credit card that can

hold large amounts of digital data. Typically, the

data cannot be altered once they are written to the

card.

LATA (Local Access Transport Area)

A geographic region used to define telephone

areas.

LOINC (Laboratory Observation Identifier

Names and Codes)

A set of universal names and codes for identifying

laboratory test results in order to facilitate the exchange and pooling of clinical laboratory results.

Magnetic stripe card

A plastic card with a magnetic strip on the back

that can store about 250 characters, mainly for

identification and verification of eligibility for insurance benefits.

Managed care (or managed health care)

A vaguely defined term referring to various systems of health care delivery that attempt to manage the cost, quality, and accessibility of health

care.

Managed care organization

An organization, such as an HMO or PPO, that

uses one or more techniques of managed care.

MCG

Medical College of Georgia

Messaging standard

A standard governing the structure of electronic

messages between computers.

Meta-analysis

Quantitative synthesis of the statistical results of

numerous studies on a given topic.

MIB (Medical Information Bus)

A hardware and software standard (IEEE P1073)

that enables standardized connections between

medical monitoring devices and clinical information systems.
Appendix G Abbreviations and Glossary | 221

MLM (Medical Logic Module)

A component of the Arden Syntax.

MPEG (Motion Picture Experts Group)

A video compression standard.

MRI

Magnetic resonance imaging

Multiplexing

Combination of many low-capacity communications channels into one high-capacity communications channel by interleaving the various

channels in discrete time or frequency slices.

NASA

National Aeronautics and Space Administration

NCHS

National Center for Health Statistics

NCHSR

National Center for Health Services Research

NCI

National Cancer Institute

NCQA

National Committee for Quality Assurance

NCVHS

National Committee on Vital and Health Statistics

NII

National Information Infrastructure

NIST

National Institute for Standards and Technology

NLM

National Library of Medicine

NTIA

National Telecommunications and Information

Administration

NUBC

National Uniform Billing Committee

OCR (optical character recognition)

Automated scanning and conversion of printed

characters to computer-based text.

OLAP (on-line analytical processing)

A database architecture that supports querying of

complex, multidimensional databases.

ORHP

Office of Rural Health Policy

PACS (Picture Archiving and Communications

System)

A computer-based system of storing and retrieving radiographic and other images in digital form.

Patient record

The repository of information about an individual

patient, usually stored on paper, but more recently

in electronic form in a computer system.

Payer

Insurance company, self-insured employer, administrator, or other entity responsible for paying

for an individual’s health care.

PBM (pharmacy benefit management)

A method of managing pharmaceutical benefits

for insurers and employers that uses disease management, pharmacy networks, negotiated discounts and rebates, lists of preferred drugs, and

online utilization review. Also, an organization

(pharmacy benefit manager) that performs PBM

services.

PBX (private branch exchange)

A institution’s internal phone system, which may

include voice messaging capabilities.

PC

Personal computer

PC card or PCMCIA card

A credit card-sized computer peripheral or peripheral interface used with portable and desktop computers.

PDA (personal digital assistant)

A handheld computer, usually with no keyboard,

that is used for communications or data collection

and analysis.
222 | Bringing Health Care Online: The Role of Information Technologies

PDQ (Physician Data Query)

A system of online (Internet) information regarding various cancers, ongoing clinical trials, and individuals and organizations involved in cancer

care, maintained by NCI.

Pixel

The smallest displayable area on a computer

screen.

PPO

Preferred provider organization

Primary data

Data collected directly from individuals (e.g., survey, observation) or documents (e.g., medical record review).

Privacy Act

The Federal Privacy Act of 1974 (5 U.S.C. Section 552a, 1988), which protects individuals from

nonconsensual disclosure of confidential information by government agencies.

Proprietary standard

A technological standard developed by a single

vendor or vendor group. The standard’s specifications may be publicized or held confidential.

Prospective research

Research in which patients are observed as they

receive health services.

Provider (or health care provider)

Any person (physician, nurse, etc.) or institution

(hospital, nursing home, etc.) that provides health

services to patients.

PTCA

Percutaneous transluminal coronary angioplasty

Purchaser

An organization (usually a large employer) that

purchases health insurance (usually for its own

employees).

Quality assessment

Measurement and evaluation of the quality of

health services delivered to patients, usually focusing on the processes and outcomes of those services.

RAID (redundant array of independent disks)

Multiple computer disks configured as a single

disk to provide either data redundancy or enhanced access speed.

Randomized controlled trial

A form of prospective research in which patients

are randomly assigned to groups that receive different health services and are then observed for

differences in outcome.

RBOC (Regional Bell Operating Company)

A regional telephone company resulting from the

divestiture of the Bell System in the 1980s.

Relational database

A collection of computer-based information that

is organized or accessed according to relationships between data items.

Reliability

The reproducibility of a measure, or the extent to

which the measure yields similar results each time

it is used on similar samples, or the extent to which

its components yield similar results for the same

or similar samples.

Report card

A summary set of indicators of the performance of

health care providers or insurance plans in delivering health services to patients.

Retrospective research

Research in which patients are observed after they

have received health services

Risk adjustment

Statistical control of patient risk factors in the

analysis of the utilization and outcomes of health

services; also, control of financial risk factors

faced by insurance companies.

Risk factors

Key health problems and background characteristics that can affect the patient’s outcome, independent of the specific kinds of services received.
Appendix G Abbreviations and Glossary | 223

RMRS (Regenstrief Medical Record System)

A clinical information system at the Regenstrief

Institute, Indiana University, Indianapolis, Indiana.

RODEO NET

Rural Options for Development and Educational

Opportunities Network

Rule-based expert system

A decision support system based on large numbers of heuristics, or rules of thumb, derived from

analysis of action patterns of experts or from published literature.

Run-length encoding

A data compression scheme in which extended series of repetitive data are replaced by the first item

in the series and a token indicating the length of

the data run.

RUS

Rural Utilities Service (formerly the Rural Electrification Administration)

Secondary data

Data originally collected for one purpose (e.g.,

program administration) and then analyzed for a

different purpose (usually research or evaluation).

Shared decision support systems

Designed to inform patient/provider decisions regarding prevention, diagnosis, management, and

treatment.

Smart card

A plastic device the size of a credit card with an

embedded computer processor and memory.

SMS (Shared Medical Systems)

A vendor of hospital information services and

products.

SNOMED (Systematized Nomenclature of

Medicine)

A system for classifying and coding health problems, symptoms, and services.

Social interface

A human-computer interface design approach in

which users interact with representations of physical objects or, in some cases, anthropomorphic

agents displayed by their computer.

Speech recognition

Automated conversion of spoken words into computer-based text. Some speech recognition systems recognize only one person’s voice; others are

speaker-independent but recognize a more limited

vocabulary. They may recognize continuous

speech or, more commonly, require that slight

pauses be inserted between words.

SSN

Social Security number

STARPAHC

Space Technology Applied to Rural Papago Advanced Health Care, a 1970s cooperative telemedicine project supported by NASA, the Indian

Health Service, and the Papago people.

Statistical control

Control of confounding variables in retrospective

research, either by classifying patients into groups

that are homogeneous with respect to those variables, or by adjusting for the variation in the outcome variable that is accounted for by those confounding variables.

Structured data entry

A data collection technique that constrains the

language and format of clinical descriptions for

the purpose of ensuring uniform, unambiguous,

interchangeable messages.

Symmetric encryption

Encryption of a message with a key derived from a

password that must be known by both the sending

and receiving parties.

Systematic review

Extraction of specific items of information from

numerous research works on a given topic and

comparison of those items across those works using structured methods.
224 I Bringing Health Care Online: The Role of Information Technologies

Tl, T3

See DS-1, DS-3.

Tablet computer

A computer with an integrated display and digitizer, rather than a keyboard. Also known as a clipboard or pentop computer.

TCP/lP (Transmission Control Protocol/Internet

Protocol)

A communications protocol governing data exchanged on the Internet.

Telemedicine

The use of information technology to deliver medical services and information from one location to

another.

UMLS (Unified Medical Language System)

A computer-based system for translating among

disparate clinical nomenclatures, maintained by

the National Library of Medicine (NLM).

UNLS (Unified Nursing Language System)

A system similar to the Unified Medical Language System (UMLS) that focuses on nursing

services.

Validity

The extent to which an observed situation reflects

the true situation. Internal validity is the extent to

which the results of a study reflect the true relationship between an intervention and an outcome.

External validity is the extent to which the results

of a study may be generalized to other settings,

etc.

VAN (value added network)

A data communication network that provides services beyond normal transmission, such as error

correction or message storage and forwarding.

WEDI

Workgroup for Electronic Data Interchange

WHIN

Wisconsin Health Information Network

WHO

World Health Organization

WIC (Women, Infants and Children)

A special supplemental food program administered by the U.S. Department of Agriculture.

Willingness-to-pay approach

A valuation approach used in cost-benefit analysis that assigns monetary value to human life by

considering how much individuals are willing to

pay for a reduction in the risk of death or illness.

SOURCES Some definitions adapted from P.R. Kongstvedt, Essentials of Managed Care (Gaithersburg, MD Aspen Publishers, 1995) Health Care

and the Electron/c Superhighway A Provider Perspective on Electronic Data Interchange and Automated Medical Payment, Research Report No.

92-3 (Faulkner and Gray Washington, DC, 1992)
| 225

ndex

A

Access to care, 76, 163-164

Access to information, 125-127, 130-132, 207-211

Access to records, 115

Administrative activities, 83

providers, 83-84

providers and payers, 84-87

Administrative simplification, 31-32, 80-83

Advanced Research Projects Agency, 170

Agency for Health Care Policy and Research, 72,

73, 127, 129, 131, 154, 157, 188, 203

AHCPR. See Agency for Health Care Policy and

Research

AHSC. See American Hospital Supply Corp.

AITN. See Arizona-International Telemedicine

Network

AMA. See American Medical Association

American Hospital Supply Corp., 93

American Medical Association, 155, 156, 157

American Self-Help Clearinghouse, 25

American Society for Testing and Materials, 68, 138

American Telemedicine Association, 179, 187

Analytic Systems Automated Purchasing, 93

ANSI, 68

ANSI X12, 69

Arizona-International Telemedicine Network, 173

ARPA. See Advanced Research Projects Agency

Artificial neural networks, 51-52

ASAP. See Analytic Systems Automated Purchasing

ASTM. See American Society for Testing and

Materials

Australia, telemedicine, 176-177

Authentication, 116

Automated data collection, 46, 50-51

B

Brigham and Women’s Hospital, 46

C

Canada, telemedicine, 176

CancerNet, 131

Cards, 55, 99-100

CBA. See cost-benefit analysis

CDC. See Centers for Disease Control and

Prevention

CD-ROMs, 131

CEA. See cost-effectiveness analysis

Centers for Disease Control and Prevention, 73, 103

CHESS. See Comprehensive Health Enhancement

Support System

CHI. See Consumer health informatics

CHIN. See Community Health Information Network

CHMIS. See Community Health Management

Information System

Claims inquiry, 87

Claims services, 91

Claims submission, 86

Client-server architecture, 66-67

Clinical decision support, 52-54, 124-142, 197-200

applications of, 197-200

effectiveness and safety, 138-140, 153-155

evaluation, 140-142

information content, 136-138

standards, 136-138, 155-158

technology development, 135-136

Clinical information systems, 35-38

Clinical literature, 126

Clinical practice guidelines, 127-129

Clinical practice improvement, 134

Clinical protocols, 127-129, 133-134

Clinical research, 126

Clinical Telemedicine Cooperative Group, 179, 181,

203

Cochrane Collaboration, 131

Communications primer, 63-65

Community Health Information Network, 16, 63,

95-96, 108-109
226 | Bringing Health Care Online: The Role of Information Technologies

Community Health Management Information

System, 16, 95-96

Community networking, 26, 95-103

Community Services Network, 26

COMPASS, 172

Comprehensive Health Enhancement Support

System, 25, 174

ComputerLink, 25

Computer software, 67-68

Confidentiality, 114-118, 183

Congressional interest, 9

Connect System, 25, 175

Consumer health informatics, 24-26

Consumer information sources, 208

Continuous quality improvement, 134, 144

Coordination, 78

Cost containment, 11-13

Cost-benefit analysis, 12-13

Cost-effectiveness analysis, 12-13

Cost management, 5-6

Cost reduction, 16, 75

CPT-4, 155, 156, 157

CQI. See Continuous quality improvement

D

Databases, 42

Data distillation, 49-54

Data security, 115-118, 183

Data sets, maximum, 120

Decision support system. See Clinical decision

support

Demand management system, 24, 65

DEMPAQ. See Developing and Evaluating Methods

to Promote Ambulatory Care Quality

Department of Commerce, 203-204

Department of Defense, 188, 189, 204

Department of Health and Human Services, 9, 121,

159, 183, 202-203

Department of Veterans Affairs, 179, 188, 190, 205

Developing and Evaluating Methods to Promote

Ambulatory Care Quality, 145, 154

DHHS. See Department of Health and Human

Services

DICOM, 58

Direct data entry, 87

Dxplain, 139

E

East Carolina University School of Medicine,

170-171, 174

EDI. See Electronic data interchange

EDI standards. See Standards

EFT. See Electronic funds transfer

Electronic commerce, 79, 82

Electronic data interchange, 81-83, 87-95, 103-122

cost savings, 104-109

system costs, 103

Electronic funds transfer, 92

Electronic health information sources, 207-211

Electronic house call, 168, 173-175

Electronic order entry, 93

Electronic publishing, 132

Electronic signatures, 114

Eligibility, 87

Encounter reports, 87

Encryption, 116

Enrollment, 87

Enterprise information systems, 35

Enterprise networks, 102-103

EOE. See electronic order entry

Evidence-based medicine, 131

Expert systems, 52-54, 132-133

F

FDA. See Food and Drug Administration

Fee-for-service plan, 81, 143

Financial institutions, 92-93

Food and Drug Administration, 67-68, 76, 141, 154

Forms, standardized, 93

G

General Accounting Office (GAO), 108

Grassroots computer networking, 26-27

H

Handwriting recognition, 46-47

Harvard Community Health Plan, 174

HCFA. See Health Care Financing Administration

Health care expenditures, 5-6

Health Care Financing Administration, 13, 17, 19,

36, 87, 90, 104, 110, 112, 119, 121, 145, 154,

155, 157, 171, 177, 178, 188, 191, 202-203

Health care reform, 6

Healthcare Open Systems and Trials consortium, 72

Health Evaluation through Logical Processing

System, 52-54, 133, 137

Health Informatics Standards Planning Panel, 72

Health information, life cycle, 34-42

Health information, regulatory environment for,

112-115, 121

Health information sources, electronic, 207-211

Health maintenance organization, 8, 81

Health Plan Employer Data and Information Set,

145-147, 154

HEDIS. See Health Plan Employer Data and

Information Set

HELP system. See Health Evaluation through

Logical Processing system
Index | 227

High-Performance Computing and Communications

Program, 73, 179, 203

HISPP. See Health Informatics Standards Planning

Panel

HL7 standard, 70, 84

HMO. See Health Maintenance Organization

Hospital information systems, 37

HOST. See Healthcare Open Systems and Trials

consortium

HPCC. See High-Performance Computing and

Communications Program

I

ICD-9-CM standard, 70, 107, 156, 157

Identifiers, 111-112, 120-121

IITF. See Information Infrastructure Task Force

Iliad, 139

Imaging systems, 41

compression, 56-58

techniques, 55

IMSystem, 146-149

Indian Health Service, 159

Industry fragmentation, 109-110

Information Infrastructure Task Force, 8, 25, 62,

160, 181, 188, 189, 201

Information needs, complexity of, 110

Information Network for Public Health Officials,

103

Information sources, electronic, 207-211

Information technologies, 29-78

adoption levels, 2, 3

challenges and opportunities, 2

compression, 54-58

data distillation, 49-54

data security, 60-62

display and retrieval, 58-60

distributed computing, 66-68

high-bandwidth communications, 62-66

object-oriented software, 67-68

storage, 54-58

INPHO. See Information Network for Public Health

Officials

Integrated delivery system, 84

Integration of health services, 6, 8

Internet, 63, 207-211

Islands of automation, 1, 30-34

J

Job roles. See Workforce effects

Joint Commission on Accreditation of Healthcare

Organizations (JCAHO), 38, 146, 184

K

Kansas University Medical Center, 168-170

Knowledge-based systems, 52-54, 132-133

L

LDS Hospital, 129, 133

Legacy systems, 35

Legislative activities, 9-10, 122, 160, 187, 188

Lewin-VHI, 104

Liability, physician, 184

Licensing, physician, 183-184

Little, Arthur D., Inc., 104

M

Managed care, 6, 7, 81, 143

Mayo Clinic, 170

MDIS. See Medical Diagnostic Imaging Support

Medicaid, 8, 87, 154, 155, 177

Medical College of Georgia, 166-168

Medical Diagnostic Imaging Support, 204

Medical informatics, 30

Medical Information Bus, 50-51

Medical logic modules, 137

Medicare, 8, 87, 112, 114, 121, 154, 155, 177

Medicare Transaction System, 110, 112

Meditel, 139

MEDLINE, 130

MIB. See Medical Information Bus

MTS. See Medicare Transaction System

N

NACHA. See National Automated Clearing House

Association

NASA. See National Aeronautics and Space

Administration

National Aeronautics and Space Administration, 73,

159, 170, 189, 204-205

National Automated Clearing House Association, 92

National Center for Health Services Research, 153,

154

National Committee for Quality Assurance, 145

National Committee on Vital and Health Statistics,

156, 157, 158

National Consortium for Telemedicine Evaluation,

179-180

National Council for Prescription Drug Programs,

69, 76, 95

National Information Infrastructure, 8, 103, 160,

181, 188, 201

National Information Infrastructure Testbed, 188,

189

National Institutes of Health, 73
228 | Bringing Health Care Online: The Role of Information Technologies

National Library of Medicine, 72, 131, 137, 153,

155, 157, 158, 159, 179, 188, 190, 203

National Networks of Libraries of Medicine, 130

National provider file, 112

National Provider Identifier, 112, 121

National Science Foundation, 73

National Telecommunications and Information

Administration, 171, 203-204

National Uniform Billing Committee, 93

NCPDP. See National Council for Prescription Drug

Programs

NCQA. See National Committee for Quality

Assurance

Networks, 79-122

Neural networks, 51-52

NIH. See National Institutes of Health

NII. See National Information Infrastructure

NLM. See National Library of Medicine

Norway, telemedicine, 176

NPI. See National Provider Identifier

NSF. See National Science Foundation

NUBC. See National Uniform Billing Committee

O

Office of Rural Health Policy, 171, 172, 179, 188,

190, 202

OncoLink, 63, 131

Optical character recognition (OCR), 42, 46

Order entry, electronic, 93

Oregon ED-NET, 172

Organizational change, 3-4

ORHP. See Office of Rural Health Policy

P

PACS. See Picture Archiving and Communications

Systems

Patient data management systems, 58-60

Patient information, entering and retrieving,

129-132

Patient information, limitations, 124-125

Patient records

computer-based, 41-42

contents, 39

paper-based, 38-41

storage, 41

weaknesses, 40-41

Patients, information for, 208

Pattern recognition, 49-51

PDQ, 131

Pen and quill laws, 4, 43

Performance assessment, 142-152

Performance Indicator Projects. See Report cards

Personal digital assistants, 45

Pharmaceutical benefit managers, 76

Pharmaceutical industry EDI, 94-95

Picture Archiving and Communications Systems,

58, 173, 204

Portable computers, 45

Practice guidelines. See Clinical practice guidelines

Practice management systems, 84

Prisons, telemedicine, 175

Privacy, 17, 114-118, 183

Privacy Act, 117, 118

Professional organizations and journals, 210

Protocols. See Clinical protocols

Provider assessment. See Performance assessment

Providers, access to information, 125-127

Public health networking, 103

Public Health Service, 145

Publication bias, 126

Q

QMR, 139

Quality of care, 18-20, 123-158

Clinical decision support, 124-142

Performance assessment, 142-152

R

REACH-TV, 171

Regenstrief Medical Record System, 36, 133

Regional networking, 95-103

Regulatory environment for health information,

112-115, 121

Reimbursement, telemedicine, 177-178, 191

Remittance advice, 86

Report cards, 144-150

RODEO NET, 171-172

Rural area networks, 181-182

Rural Utilities Service, 188, 203

S

Scope of the study, 10-11

SCORPIO, 130

Security. See Data security

Shared decision support, 24

SNOMED, 72

Software, 67-68

Space Technology Applied to Rural Papago

Advanced Health Care, 159, 203, 204

Speech recognition, 46-47

Standards, 13-14, 17, 68-72, 77, 110-111, 136-138,

210

DICOM, 58

EDI, 88-89, 110-111, 119

Forms, 93

HL7, 70, 84

ICD-9-CM, 70, 107, 156, 157

Identifiers, 111-112, 120-121
Index | 229

Messaging, 42, 68-69, 70, 72, 136

of care, 126

STARPAHC. See Space Technology Applied to

Rural Papago Advanced Health Care

Structured data entry, 42

SUPPORT model, 139

T

Tablet computers, 45

Telecommunications and Information Infrastructure

Assistance Program, 203-204

Telemedicine, 20-23, 159-191, 209

Access, 163-164

Applications, 165-177

Costs, 161-163, 180

Development costs/financing, 185

Evaluation, 178, 179

Executive branch activities, 201-207

Government role, 188-191

Home-based, 173-175

Human infrastructure, 186

IITF subgroup on, 160, 189, 190-191, 201

Legal/regulatory, 181, 183-184

Other countries, 176-177

Other sites, 175-176

Potential effects, 160-165

Quality of care, 164-165

Research, 178-179, 190

Technology and implementation, 185-186

Telecommunications infrastructure, 179-180

Teleconsultations, 166-172

Teleradiology and telepathology, 172-173

Telemedicine Information Exchange, 190, 203

Texas Telemedicine Project, 168

Tiber Group, 104

TIE. See Telemedicine Information Exchange

TIIAP. See Telecommunications and Information

Infrastructure Assistance Program

Tri-Service Telemedicine Testbed Project, 204

U

Unified Medical Language System (UMLS), 72,

137, 155, 157

Urban telemedicine, 176

User interfaces, 99, 101

V

Value-added network (VAN), 83, 92

W

Wisconsin Health Information Network (WHIN), 63

Workforce effects, 4, 5

Workgroup for Electronic Data Interchange

(WEDI), 93, 104, 116, 117

World Health Organization (WHO), 157

World Wide Web (WWW), 63, 207