R EPORT TO THE PR ESIDENT

R EALIZING THE F ULL POTENTIAL OF 

HEALTH INFOR M ATION TECHNOLOGY

TO IMPROV E HEALTHCAR E

FOR A MER ICANS:

THE PATH FORWAR D

Executive Office of the President

President’s Council of Advisors 

on Science and Technology

December 2010

R EPORT TO THE PR ESIDENT

R EALIZING THE F ULL POTENTIAL OF 

HEALTH INFOR M ATION TECHNOLOGY

TO IMPROV E HEALTHCAR E

FOR A MER ICANS:

THE PATH FORWAR D

Executive Office of the President

President’s Council of Advisors 

on Science and Technology

December 2010

★ i ★

About the President’s Council of 

Advisors on Science and Technology

The President’s Council of Advisors on Science and Technology (PCAST) is an advisory group of the 

nation’s leading scientists and engineers, appointed by the President to augment the science and technology advice available to him from inside the White House and from cabinet departments and other 

Federal agencies. PCAST is consulted about and often makes policy recommendations concerning the 

full range of issues where understandings from the domains of science, technology, and innovation 

bear potentially on the policy choices before the President. PCAST is administered by the White House 

Office of Science and Technology Policy (OSTP).

For more information about PCAST, see http://www.whitehouse.gov/ostp/pcast

★ iii ★

The President’s Council of Advisors on 

Science and Technology

Co-Chairs

John P. Holdren

Assistant to the President 

forScience and Technology

Director, Office of Science and 

Technology Policy

Eric Lander

President, Broad Institute of 

Harvard and MIT

Harold Varmus*

President, Memorial SloanKettering Cancer Center

Members

Rosina Bierbaum

Dean, School of Natural Resources and 

Environment

University of Michigan

Christine Cassel

President and CEO, American Board of Internal 

Medicine

Christopher Chyba

Professor, Astrophysical Sciences and 

International Affairs

Director, Program on Science and Global Security

Princeton University

S. James Gates, Jr.

John S. Toll Professor of Physics

Director, Center for String and Particle Theory

University of Maryland

Shirley Ann Jackson

President, Rensselaer Polytechnic Institute

Richard C. Levin

President

Yale University

Chad Mirkin

Rathmann Professor, Chemistry, Materials 

Science and Engineering, Chemical and 

Biological Engineering and Medicine

Director, International Institute of 

Nanotechnology

Northwestern University

Mario Molina

Professor, Chemistry and Biochemistry

University of California, San Diego

Professor, Center for Atmospheric Sciences 

Scripps Institution of Oceanography

Director, Mario Molina Center for Energy and 

Environment, Mexico City

Ernest J. Moniz

Cecil and Ida Green Professor of Physics and 

Engineering Systems

Director, MIT’s Energy Initiative

Massachusetts Institute of Technology

Craig Mundie

Chief Research and Strategy Officer

Microsoft Corporation

* Dr. Varmus resigned from PCAST on July 9, 2010 and 

subsequently became Director of the National Cancer 

Institute (NCI).
★ iv ★

Ed Penhoet

Director, Alta Partners

Professor Emeritus of Biochemistry

and of Public Health

University of California, Berkeley

William Press

Raymer Professor in Computer Science and 

Integrative Biology

University of Texas at Austin

Maxine Savitz

Vice President

National Academy of Engineering

Barbara Schaal

Chilton Professor of Biology

Washington University

Vice President, National Academy of Sciences

Eric Schmidt

Chairman and CEO

Google, Inc.

Daniel Schrag

Sturgis Hooper Professor of Geology

Professor, Environmental Science and 

Engineering

Director, Harvard University-wide Center for 

Environment

Harvard University

David E. Shaw

Chief Scientist, D.E. Shaw Research

Senior Research Fellow, Center for 

Computational Biology and Bioinformatics

Columbia University

Ahmed Zewail 

Linus Pauling Professor of Chemistry and Physics

Director, Physical Biology Center

California Institute of Technology

Staff

Deborah Stine

Executive Director, PCAST

Mary Maxon

Deputy Executive Director, 

PCAST

Gera Jochum

Policy Analyst 
★ v ★

EXECUTIVE OFFICE OF THE PRESIDENT

PRESIDENT’S COUNCIL OF ADVISORS ON SCIENCE AND TECHNOLOGY

WASHINGTON, D.C. 20502

President Barack Obama

The White House

Washington, DC 20502

Dear Mr. President,

We are pleased to send you this report, Realizing the Full Potential of Health Information Technology to 

Improve Healthcare for Americans: The Path Forward, prepared by your President’s Council of Advisors 

on Science and Technology (PCAST). This report examines how health information technology could 

improve the quality of healthcare and reduce its cost, and whether existing Federal efforts in health 

information technology are optimized for these goals.

To provide a solid scientific and economic basis for our recommendations, the Council assembled a 

Working Group of nongovernmental experts and also met with government officials, industry representatives, information technology experts, and healthcare professionals. PCAST has concluded that 

information technology can help catalyze a number of important benefits including improved access 

to patient data, which can help clinicians as they diagnose and treat patients and patients themselves 

as they strive to take more control over their health; streamlined monitoring of public health patterns 

and trends; an enhanced ability to conduct clinical trials of new diagnostic methods and treatments; 

and the creation of new high-technology markets and jobs. Health information technology can also 

help support a range of healthcare-related economic reforms needed to address our Nation’s long-term 

fiscal challenges.

PCAST has also concluded that to achieve these objectives it is crucial that the Federal Government 

facilitate the nationwide adoption of a universal exchange language for healthcare information and a 

digital infrastructure for locating patient records while strictly ensuring patient privacy. More specifically, 

PCAST recommends that the Office of the National Coordinator for Health Information Technology and 

the Centers for Medicare and Medicaid Services develop guidelines to spur adoption of such a language 

and to facilitate a transition from traditional electronic health records to the use of healthcare data 

tagged with privacy and security specifications.

PCAST hopes that its report will help lay a foundation for the decisions that you and others in the Federal 

Government must make. We are grateful for the opportunity to serve you and the country in this way 

and would be pleased to brief you or your staff if you have questions about our recommendations.

Sincerely,

John P. Holdren Eric Lander

Co-Chair Co-Chair

★ vii ★

Table of Contents

About the President’s Council of Advisors on Science and Technology . . . . . . . . . . . . i

Co-Chairs iii

Members iii

Staff iv

Executive Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1

PCAST Health Information Technology

Working Group . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .7

Co-Chairs 7

Staff 7

I. Introduction and Overview . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9

Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9

The Origins of This Study 10

Analysis of the Problem . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10

The Present Federal Landscape . . . . . . . . . . . . . . . . . . . . . . . . . 12

Structure of This Report . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14

II. The Potential of Health IT . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15

Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15

Potential Benefits of Health IT: An Overview . . . . . . . . . . . . . . . . . . . . 15

The Value of Patient-Specific Data to Patients 18

The Value of Patient-Specific and Aggregated Data to Physicians . . . . . . . . . . . . 19

The Value of Population Data for Research and Public Health . . . . . . . . . . . . . 21

Realizing the Potential of IT: A Data-Centric Approach . . . . . . . . . . . . . . . . 22

Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 24

III. Health IT Today 25

Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25

Historical Barriers to EHR Adoption 25

Limitations of Present-Day EHRs 26

Lessons from Early Adopters . . . . . . . . . . . . . . . . . . . . . . . . . . 28

Health Information Exchanges . . . . . . . . . . . . . . . . . . . . . . . . . 31

New and Emerging Technologies . . . . . . . . . . . . . . . . . . . . . . . . 32

The HITECH Act and Shifting Incentives . . . . . . . . . . . . . . . . . . . . . . 34

Opportunities and Challenges for ONC and CMS . . . . . . . . . . . . . . . . . . 34

Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 37
★ viii ★

T h e Path F o rwa r d

IV. Technology for an Integrated Health IT Ecosystem . . . . . . . . . . . . . . . . . . 39

Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 39

Earlier Models for Enabling Data Exchange . . . . . . . . . . . . . . . . . . . . 39

Universal Exchange Using Metadata-Tagged Data Elements 41

Data Element Access Services 41

Advantages of the Tagged Data Element Approach . . . . . . . . . . . . . . . . . 43

V. Privacy and Security Considerations 45

Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 45

The Present Framework . . . . . . . . . . . . . . . . . . . . . . . . . . . . 45

The Need for Strong, Persistent Privacy Protections . . . . . . . . . . . . . . . . . 46

Deleterious Effects on Medical Research and Care 47

Data Security: How Good Is Good Enough? . . . . . . . . . . . . . . . . . . . . 48

A Health IT Architecture for 21st-Century Privacy and Security . . . . . . . . . . . . . 49

Privacy Protection of Metadata-Tagged Data Elements . . . . . . . . . . . . . . . . 51

VI. Economic and Regulatory Issues . . . . . . . . . . . . . . . . . . . . . . . . . 53

Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 53

Standards and Incentives for Interoperability 53

Creating a Data Exchange Infrastructure . . . . . . . . . . . . . . . . . . . . . 54

A Regulatory Structure for Data Access . . . . . . . . . . . . . . . . . . . . . . 56

Competition to Supply Technology . . . . . . . . . . . . . . . . . . . . . . . 56

Innovation and Markets for Applications . . . . . . . . . . . . . . . . . . . . . 57

The Broader Economics of Healthcare . . . . . . . . . . . . . . . . . . . . . . 58

Estimating Costs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 60

VII. Health Data and the Research Opportunity . . . . . . . . . . . . . . . . . . . . 63

Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 63

The Potential for Real-Time, Real-World, and Comprehensive Data . . . . . . . . . . . 64

Supporting Research Uses . . . . . . . . . . . . . . . . . . . . . . . . . . . 65

VIII. Guidance to Agencies . . . . . . . . . . . . . . . . . . . . . . . . . . . . 69

Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 69

A Feasible Roadmap to the Future . . . . . . . . . . . . . . . . . . . . . . . . 69

Guidance on Necessary Design Choices 71

Guidance on Meaningful Use Requirements . . . . . . . . . . . . . . . . . . . . 73

IX. Recommendations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 77
★ ix ★

Ta b le of Co ntents

Appendix A: Expert Input . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 81

Appendix B: Acknowledgments . . . . . . . . . . . . . . . . . . . . . . . . . . 85

Appendix C: Glossary 87

Appendix D: Abbreviations . . . . . . . . . . . . . . . . . . . . . . . . . . . . 91

★ 1 ★

Executive Summary

Information technology (IT) has the potential to transform healthcare as it has transformed many parts 

of our economy and society in recent decades. Properly implemented, health IT can:

• Integrate technology into the flow of clinical practice as an asset, while minimizing unproductive data entry work.

• Give clinicians real-time access to complete patient data, and provide them with information 

support to make the best decisions.

• Help patients become more involved in their own care.

• Enable a range of population-level public health monitoring and real-time research.

• Improve clinical trials, leading to more rapid advances in personalized medicine.

• Streamline processes, increase their transparency, and reduce administrative overhead, as it 

has in other industries.

• Lead to the creation of new high-technology markets and jobs.

• Help support a range of economic reforms in the healthcare system that will be needed to 

address our Nation’s long-term fiscal challenges.

Despite this great promise, the impact of IT on healthcare over the past decade has so far been modest. 

Currently, almost 80 percent of physicians—the majority in small, independent practices—lack even 

rudimentary digital records. Where electronic records do exist, they are typically limited in functionality 

and poor in interoperability. As a result, the ability to integrate electronic health information about a 

patient and exchange it among clinical providers remains the exception rather than the rule. Compared 

to other industrialized nations, the United States lags far behind in the use of electronic health records.

As we will describe, the Administration and the Congress have recently made major investments to 

ensure that Americans soon enjoy the benefits of electronic health records. The Administration has 

been moving rapidly to promote the adoption by physicians and hospitals of electronic health systems, 

including through recent, important rule-making for 2011. The President’s Council of Advisors on Science 

and Technology has undertaken this report to examine the critical issues for the next phase, which has 

just begun, and to make specific recommendations to the Administration to ensure that the full promise 

of health IT is realized.

In other sectors in which IT has had a transforming effect, rapid progress has been catalyzed by wise 

technology choices that open up markets to competition and innovation. Such technology choices 

include the standardization of simple universal methods for the exchange of information across multiple platforms and organizations. In other sectors, universal exchange standards have resulted in new 

products that knit together fragmented systems into a unified infrastructure. The resulting “network 

effect”1 then increases the value of the infrastructure for all, and spurs rapid adoption. By contrast, health 

1. Network effect is defined as the user externality by which the more people who use a network, the greater its 

value to each of them. The classic example is the rapid adoption of universal telephone service in the early 20th Century.
★ 2 ★

T h e Path F o rwa r d

IT has not made this transition. The market for new products and services based on health IT remains 

relatively small and undeveloped compared with corresponding markets in most other sectors of the 

economy, and there is little or no network effect to spur adoption.

Several identifiable barriers in the healthcare system currently discourage innovation and vigorous 

competition in the market to create effective health IT systems. First, most current health IT systems are 

proprietary applications that are not easily adopted into the workflow of a clinician’s day, and whose 

proprietary data formats are not directly exchangeable from one system to another. It is difficult for 

data to be disaggregated, indexed, searched, and assembled to provide accurate information to treat 

a patient, because the context for individual entries in a record is often implicit at best. Second, most 

healthcare organizations that utilize electronic health records (EHRs) view them as purely internal 

resources, and have little incentive for investment in secondary or external uses, such as making them 

accessible in appropriate form to patients, to a patient’s healthcare providers at other organizations, and 

in de-identified or aggregated form to public health agencies and researchers. Third, legitimate patient 

concerns about privacy and security make patients uneasy about participating in health IT systems or 

granting consent for their information to be used in research. Fourth, health IT has historically been 

oriented toward administrative functions, not better care. This is in part because, under the current 

fee-for-service payment model, the economic benefits of investing in health IT can rarely be realized 

by the provider or organization that makes the investment.

Some healthcare organizations have overcome at least some of these barriers and successfully adopted 

electronic systems that measurably improve care within their own organization. Kaiser Permanente 

and the Veterans Health Administration are notable examples. Other leading hospitals and clinics also 

employ electronic record systems that allow them to consolidate patient health data generated within 

their organizations. However, even these successes, upon closer examination, highlight the limitations 

of current approaches. They are usually “one offs,” designed for the particular organization, not for a wide 

range of other types of practices. They are generally closed, and not designed for the exchange of data 

with a heterogeneous and geographically diverse set of other organizations that may serve the patient 

now or in the future. They typically require capital investments that are beyond the reach of most small 

clinical practices. And, they are too limited in scope, and few in number, to drive a vigorous market in 

technological innovation.

Recent Federal legislation has charted a new path forward. The Health Information Technology for 

Economic and Clinical Health (HITECH) Act, a part of the American Recovery and Reinvestment Act 

(ARRA) of 2009, authorized expenditures of at least $20 billion to promote the adoption and use of EHR 

technologies that would ideally be connected through a national health information network. Hospitals 

and physicians who make “meaningful use” of interoperable EHRs can qualify for extra payments through 

Medicare and Medicaid.

Responsibility for developing policies that implement the overall HITECH Act lies primarily with the Office 

of the National Coordinator for Health Information Technology (ONC). In this role, ONC works closely with 

the Center for Medicare and Medicaid Services (CMS), which is responsible for promulgating policies 

that relate to Medicare and Medicaid payment for meaningful use of EHRs under HITECH. ONC and CMS 

recently released final rules to implement the first phase of the HITECH Act, which begins in 2011. The 
★ 3 ★

Ex ecu ti v e Su m m a ry

ONC rule specifies the standards, implementation specifications and other criteria for EHR systems and 

technologies to be certified under HITECH and thus eligible for the Acts incentive programs while the 

CMS rule specifies how hospitals, physicians, and other eligible professionals must demonstrate their 

meaningful use of these technologies in order to receive Medicare and Medicaid payment incentives. 

Both sets of rules strongly indicate that standards and criteria for achieving meaningful use of EHRs will 

grow more rigorous in subsequent phases (2013 and 2015) as the technology continues to evolve and 

providers gain experience and sophistication in its use.

Given the national priority of health care reform, President Obama asked PCAST how health IT could 

improve the quality of healthcare and reduce its cost, and whether existing Federal efforts in health IT 

are optimized for these goals. In response, PCAST formed a working group consisting of PCAST members 

and prominent experts in both healthcare and information technology. Based on input from the working 

group, additional expert reviewers, and its own discussions, PCAST has reached six major conclusions.

1. HHS’s vigorous efforts have laid a foundation for progress in the adoption of electonic health 

records, including through projects launched by ONC, and through the issuance of the 2011 

“meaningful use” rules under HITECH. ONC has shown itself to be a technologically sophisticated 

agency, with outstanding outreach into the clinical community and good liaison with incumbent 

EHR system vendors. The Nationwide Health Information Network (NHIN) project has convened 

stakeholders and created an appropriate forum for the discussion of options. Strategic Health IT 

Advanced Research Projects (SHARP) in areas including network architectures and data use will 

produce important practical advances, as will work resulting from the establishment of a Federal 

“collaboratory” in clinical decision support. Importantly, the 2011 “meaningful use” rules recently 

released by ONC and CMS provide necessary first steps, and we endorse these rules.

2. In analyzing the path forward, we conclude that achievement of the President’s goals requires 

significantly accelerated progress toward the robust exchange of health information. The 

initial approach to meaningful use has focused on driving physicians to adopt EHR systems that 

perform important quality-improving functions within the practice and, to a lesser extent, on 

developing capabilities for broader sharing. Though the rule expresses an intent to require more 

robust exchange of health information among providers at later stages of meaningful use, its 

initial requirements that EHR systems communicate with each other are very modest. This creates 

a danger that EHR adoption during early stages of meaningful use may exacerbate the problem of 

incompatible legacy systems. What is needed is a simultaneous focus on the capability for universal 

data exchange, able to unleash the power of the competitive market, to produce increasingly better 

and less expensive systems, and to create the “network effect” that spurs further adoption. While 

useful as an initial step, the adopted standards for data vocabulary and messaging will not be sufficient to advance the state of the art either of clinical practice or of a robust health IT infrastructure. 

Going forward, the critical issue is to facilitate progress by healthcare organizations by ensuring 

the creation and dissemination of a universal exchange language for healthcare information and 

an infrastructure for locating patient records, while rigorously protecting privacy and security. This 

would allow patient outcomes to become a larger part of meaningful use much more quickly, and 

make it less onerous for clinicians to generate and report a wide range of different kinds of information about the outcomes of their practice.
★ 4 ★

T h e Path F o rwa r d

3. National decisions can and should be made soon to establish a “universal exchange language” 

that enables health IT data to be shared across institutions; and also to create the infrastructure that allows physicians and patients to assemble a patient’s data across institutional 

boundaries, subject to strong, persistent, privacy safeguards and consistent with applicable 

patient privacy preferences. Federal leadership is needed to create this infrastructure. While 

the ability to exchange and integrate health data offers great advantages to patients, the economic 

benefits of these capabilities do not accrue directly to specific providers, or to providers’ incumbent 

EHR system vendor (if any). As a result, market forces are unlikely to generate appropriate incentives 

for the necessary coordination to occur spontaneously. The nature of this coordination as a public 

good requires Federal leadership in ensuring the creation of the capabilities. The development of 

EHRs themselves should of course be left to the private sector.

4. Creating the required capabilities is technically feasible, as demonstrated by technology 

frameworks with demonstrated success in other sectors of the economy. The best way to 

manage and store data for advanced data-analytical techniques is to break data down into the 

smallest individual pieces that make sense to exchange or aggregate. These individual pieces are 

called “tagged data elements,” because each unit of data is accompanied by a mandatory “metadata tag” that describes the attributes, provenance, and required security protections of the data. 

Universal exchange languages for metadata-tagged data, called “extensible markup languages” are 

widely and successfully used. Indeed, ONC’s clinical document architecture standard (CDA) is such 

a markup language, and is an important step in the right direction. The indexing and retrieval of 

metadata-tagged data, across large numbers of geographically diverse locations, is an established, 

highly developed, technology—the basis of web search engines, for example. With ONC leadership, 

these technologies could rapidly be adapted and standardized for universal use in health IT. Innate, 

strong, privacy protection on all data, both at rest and in transit, with persistent patient-controlled 

privacy preferences, is likewise achievable, and must be designed in from the start.

5. ONC should move rapidly to ensure the development of these capabilities; and ONC and 

CMS should focus meaningful use guidelines for 2013 and 2015 on the more comprehensive 

ability to exchange healthcare information. ONC should act boldly to articulate a clear, common 

framework that will ensure that its various efforts converge into an effective healthcare IT ecosystem 

that serves patients and providers. The steps that must be taken can be accomplished within the 

required time frame. It can be accomplished via an evolutionary transition from traditional EHRs to a 

tagged data element model, along with a more rapid transition for the more limited purpose of data 

exchange by means of a universal exchange language. We note that these steps are not intended 

as an alternative to ONC’s important work in promoting the adoption of electronic health records. 

Rather they are complementary to that work and will accelerate adoption.

6. Finally, as CMS leadership already understands, CMS will require major modernization and 

restructuring of its IT platforms and staff expertise to be able to engage in sophisticated 

exchange of health information and to drive major progress in health IT. This process has 

begun, but needs to be a more urgent priority for the Administration and Congress and should be 

funded as appropriate for an essential component of the Nation’s healthcare quality and afford­
★ 5 ★

Ex ecu ti v e Su m m a ry

ability agenda. A recently initiated National Research Council study of CMS’s IT capabilities should 

result in recommendations that will avoid replacing one inflexible architecture with another (a 

common trap in Federal IT acquisitions), but a successful outcome is at best several years away.

The approach that we describe requires that there be a common infrastructure for locating and assembling individual elements of a patient’s records, via secure “data element access services” (DEAS). 

Importantly, this approach does not require any national database of healthcare records; the records 

themselves can remain in their original locations. Distinct DEAS could be operated by care delivery 

networks, by states or voluntary grouping of states, with possibly a national DEAS for use by Medicare 

providers. All DEAS will be interoperable and intercommunicating, so that a single authorized query 

can locate a patient’s records, across multiple DEAS.

Advantages of focusing on a universal exchange language. Briefly, the approach described in this 

report, focused on the technical ability to exchange data in uniform ways, has multiple advantages:

• It will improve healthcare quality, by making it possible for a physician to integrate accurately 

all of a patient’s medical information.

• It will improve healthcare quality and decrease costs, by making it possible for third-party 

innovators to compete to create widely applicable services and tools serving patients, providers, 

payers, public health officials, and researchers.

• It will provide much stronger privacy protection than available under current approaches, 

allowing persistent privacy assurances (including applicable patient preferences) to be attached 

to different kinds of information and using data-level encryption to prevent access of data by 

unauthorized persons.

• It will not require universal patient identifiers, nor will it require the creation of Federal databases 

of patients’ health information.

• It will simplify the regulatory burden on providers, by decreasing the focus of meaningful use 

regulations on ad hoc list of data items.

• It will help U.S. industry leapfrog to the front of the pack internationally in health IT, by providing 

exchange standards that can be more broadly adopted by others.

• It will facilitate public health and medical research, by providing a secure way to de-identify data.

• It will not require that existing systems be replaced, but only be modestly upgraded or augmented by “middleware.”

In short, the approach is designed to create robust ecosystem to support the needs of patients, providers, payer, researchers and the Nation.

Creating the ability for uniform exchange in an existing marketplace is a coordination problem; it is a 

public good that calls for Federal leadership in coordinating standards for health metadata and in creating economic incentives to adopt the standard. The definition of meaningful use and the rewards for 

being a meaningful user (and penalties for not being one) can be, if properly implemented, powerful 

mechanisms for doing this.
★ 6 ★

T h e Path F o rwa r d

Finally, one must keep in mind that achieving the truly transformative effect of modern health IT infrastructure on the healthcare sector will also require that economic incentives are in place to improve the 

quality of care and reduce costs.

Recommendations. The final chapter of this report offers guidance to ONC and CMS and also makes an 

itemized set of specific recommendations. We urge ONC to augment its current “bottom-up” approach 

with a process that can generate “top-down” design choices that are carefully balanced between the 

goals of convergence and diversity. This is an appropriate government role and requires a more aggressive approach than has been taken in the early stages. We also discuss how ONC might, by standardizing 

a universal exchange language whose semantics is intrinsically extensible, unburden itself of a potentially never-ending and intrusive government role in the harmonization of health record meanings across 

all private sector products. An open, extensible language will allow products to compete, balanced 

with other competitive features, on the basis of the breadth of their abilities to understand multiple 

semantic realms. ONC’s clinical document architecture standard (CDA) is an important step in the right 

direction, but needs more focus on data transmission, on innate privacy features, and on the enabling 

requirements of a more robust marketplace in new and innovative health IT products.

As regards CMS, we suggest specific ways in which the meaningful use process could be used to better 

advance more strategic national goals in health IT. Apropos of the much-needed overhaul of CMS’s 

antiquated IT infrastructure, we emphasize the importance of not replacing one inflexible architecture 

with another and briefly suggest what a modernized, versatile infrastructure might look like. Fortunately, 

CMS now has new leadership, with the appointment of an administrator. A solid technical plan, with the 

necessary resources, will be now required for success.

Although ONC and CMS both lie organizationally within U.S. Health and Human Services (HHS), the 

dimensions of health IT are broadly consequential across multiple Federal departments, including 

Veterans Affairs (VA) and Department of Defense (DoD). Among our recommendations, we therefore 

suggest that the Chief Technology Officer of the United States in coordination with the Office of 

Management and Budget and HHS, develop within 12 months a set of metrics that measure progress 

toward an a operational, universal, national health IT infrastructure that has the desirable features that 

we have discussed. Focusing these metrics on operational progress, as distinct from research, prototype, 

and pilot efforts, will enable a more accurate continuing assessment of whether Federal efforts in health 

IT, including both executive initiatives and legislative mandates, are in fact supportive of the President’s 

goal of increasing the quality, and decreasing the cost, of healthcare.
★ 7 ★

PCAST Health Information Technology

Working Group

Working Group members participated in the preparation of an initial draft of this report. They are not 

responsible for, nor necessarily endorse, the final version of this report as modified and approved by PCAST.

Co-Chairs

Christine Cassel*

President and CEO

American Board of Internal Medicine

Craig Mundie*

Chief Research and Strategy Officer

Microsoft Corporation

Members

Peter B. Bach

Attending Physician and Full Member

Memorial Sloan-Kettering Cancer Center

Basit Chaudhry

Consultant, physician

Molly Joel Coye

Senior Advisor 

Public Health Institute 

John Halamka

Chief Information Officer

Beth Israel Deaconess Medical Center

Chief Information Officer

Harvard Medical School

Staff

Mary Maxon

Deputy Executive Director, PCAST

Eric Lander*

President

Broad Institute of MIT and Harvard

Jonathan Levin

Professor of Economics

Stanford University

Louise Liang

Retired Senior Vice President

Quality and Clinical Systems Support

Kaiser Permanente

William Press*

Professor of Computer Science and

Integrative Biology

University of Texas at Austin

Stephanie L. Reel

Vice President and Chief Information 

Officer

Johns Hopkins University and Johns 

Hopkins Health System

Harold Varmus*2

President

Memorial Sloan-Kettering Cancer Center

* PCAST member

2. Dr. Varmus resigned from PCAST on July 

9, 2010 and subsequently became Director of 

the National Cancer Institute (NCI).

★ 9 ★

I. Introduction and Overview

Introduction

Improving the quality and decreasing the costs of healthcare are among the Nation’s highest priorities. 

In 1960, healthcare expenditures represented about 5 percent of the United States’ gross domestic 

product (GDP).3 Today they represent about 16 percent—the largest share of GDP spent on healthcare 

among all major industrialized countries. Yet on critical measures of healthcare outcomes, such as life 

expectancy, infant mortality, and the number of physicians per capita, the United States ranks behind 

many other countries.4 Our expenditures are not producing the results we should expect.

Information technology has the potential to transform healthcare as it has transformed many parts of 

our economy and society in recent decades. Health information technology5 can allow clinicians to 

have real-time access to complete patient data, and provide them with support to make the best possible 

decisions.6 It can help patients become more involved in their own care, which is especially important in 

managing chronic conditions like diabetes, asthma, or heart disease. It can enable a range of populationlevel monitoring and real-time research such as the detection of developing epidemics, health risks 

in the environment, or adverse events caused by medications. It can improve clinical trials, leading to 

more rapid advances in personalized medicine. It can streamline processes and reduce administrative 

overhead, as it has in other industries. It can lead to the creation of new, high-tech markets and jobs. 

Finally, it can help support a range of economic reforms in the healthcare system that will be needed 

to address our country’s long-term fiscal challenges. As David Blumenthal, the National Coordinator for 

Health Information Technology, has written, “Information is the lifeblood of modern medicine, [and] 

health information technology is destined to be its circulatory system.”7

Despite this great promise, however, the impact of IT on healthcare has so far been modest. Currently, 

almost 80 percent of physicians—the majority in small, independent practices—lack even rudimentary 

digital records.8 Of those who do use electronic systems, most do not make full use of their potential 

functionality. The sharing of health information electronically remains the exception rather than the rule. 

The market for new products and services based on health IT remains relatively small and undeveloped 

compared with corresponding markets in most other sectors of the economy. While recent Federal 

initiatives have made some important advances toward changing this situation, healthcare has taken 

only the first few steps toward an electronic future.

3. Agency for Healthcare Research and Quality. 2010. Health Care Costs Fact Sheet. See 

www.ahrq.gov/news/costsfact.htm

4. Anderson, G., and P. Markovich. 2009. Multinational Comparisons of Health Systems Data, 2009. New York: The 

Commonwealth Fund.

5. Terms in bold-faced type the first time they appear in this report are defined in the glossary.

6. Chaudhry, B., J. Wang, S. Wu, M. Maglione, W. Mojica, E. Roth, S. C. Morton, and P. G. Shekelle. 2006. Systematic 

review: impact of health information technology on quality, efficiency, and costs of medical care. Annals of Internal 

Medicine, 2144:742-752.

7. Blumenthal, D. 2010. Launching HITECH. New England Journal of Medicine, 362:382-385.

8. National Center for Health Statistics. December 2009. Electronic Medical Record/Electronic Health Record Use by 

Office-based Physicians: United States, 2008 and Preliminary 2009.
★ 10 ★

T h e Path F o rwa r d

The Origins of This Study

Given the importance of healthcare to the Nation’s future, the President asked his Council of Advisors 

on Science and Technology how health IT could improve the quality of healthcare and reduce its cost, 

and whether existing Federal efforts in health IT are optimized for these goals. In response, PCAST 

formed a working group consisting of PCAST members and prominent experts in both healthcare and 

information technology.9

The working group held meetings in Washington, D.C., on December 18, 2009, and in Irvine, California, 

on January 14-15, 2010, as well as additional meetings by teleconference. The viewpoints of researchers, 

policy analysts, and administrators from government, healthcare organizations, and universities were 

presented and discussed. Additional analysis of the current state of health IT implementation among 

the 80 percent of physicians who practice outside of large integrated healthcare organizations was 

performed by the Science and Technology Policy Institute (STPI).

A draft report developed by the working group was submitted to the Health and Life Sciences committee 

of PCAST. That committee submitted the draft to several outside reviewers, who made valuable suggestions for improvements. From the working group draft, the additional input, and its own discussions, the 

Health and Life Sciences committee produced the present report, which was discussed and endorsed 

(with some modifications) by the full PCAST in public session on July 16, 2010.

Analysis of the Problem

Several identifiable barriers in the healthcare system currently discourage innovation and vigorous 

competition in the market to create effective health IT systems.

First, the diffusion of IT within healthcare has been slow and oriented toward administrative functions. 

Electronic health records that contain patient information captured in clinical visits, through lab and 

imaging studies, and likely in the future from genetic tests, are a cornerstone of health information 

technology. Many healthcare providers, however, do not have the economic incentives and technical 

expertise to purchase and use EHRs. Physicians who do adopt EHRs often find they are spending extra 

hours each day to type in orders, notes from patient visits, or measures to be reported to CMS without 

receiving commensurate benefits. In addition, the fee-for-service payment model prevalent in U.S. 

healthcare does not create strong incentives to coordinate care, share information, or avoid unnecessary 

treatments, all of which are potential advantages of using EHR systems.

Second, the current structure of health IT systems makes it difficult to extract the full value of the data 

generated in the process of healthcare. Most electronic health records resemble digital renditions of 

paper records. This means that physicians can have trouble finding the information they need, and 

patients often wind up with poor access to their own health data and little ability to use it for their own 

purposes. Electronic records often do not include links to relevant information such as recent research 

findings or data on best practices that physicians and patients could use to make the best possible 

decisions. For reasons we discuss below, market innovation has not yet adequately addressed these 

challenges to the usability of electronic health records.

9. The working group members are listed in page 7.
★ 11 ★

I . Intro d ucti o n a n d Ov erv i ew

Third, standards and infrastructure are lacking that would allow information to be easily shared across 

organizations. Relevant information does not seamlessly move with patients who receive care from 

multiple providers. This leads to duplication and hinders coordination of care. The lack of data exchange 

also means that researchers and public health agencies have limited access to data that could be used to 

improve health systems and advance biomedical research. Present Federal initiatives, described below, 

have the effect of encouraging the development of local and regional health information exchanges 

(HIEs) that involve agreements to exchange data among clusters of organizations. These exchanges are 

hampered by the administrative burdens of developing agreements and by a lack of financial incentives to 

increase coordination and efficiency. It is also unclear how these exchanges might scale to a national level.

Fourth, patients are concerned that the storage of their health information in electronic form will make 

it easier for employers, insurers, government, or malicious electronic intruders to improperly access their 

records. This concern may make them unwilling to participate in health IT systems or grant consent for 

their information to be used in research, even though the aggregation of patient data to compare treatments and providers is a major benefit of health IT. Data can be anonymized by removing all personal 

identifiers from the data. But patients also may want to be re-contacted if analysis of their data reveals 

a problem with a medication they are taking or a treatment that could benefit them.

Some large healthcare organizations have overcome at least some of these barriers and successfully 

adopted EHR systems. The VistA system adopted by the Veterans Health Administration (VHA) has 

helped the Nation’s largest integrated health system provide a highly regarded level of information 

technology supporting better care. Kaiser Permanente’s HealthConnect system links all of Kaiser’s 

nearly 9 million members to all of its more than 14,000 physicians and their hospitals, rehabilitation 

centers and long-term-care facilities, so that Kaiser physicians can retrieve data on any patient who has 

received services anywhere in its network. Other leading hospitals and clinics also employ electronic 

record systems that allow them to consolidate patient health data generated within their organization.

These successes, however, also illuminate the limitations mentioned above. Even the most sophisticated 

organizations generally do not have efficient means to exchange health information with other providers. When exchanges occur, they often take place through limited or pre-formatted messages, such 

as electronic prescription information, or through comprehensive patient care summary documents, 

which cannot easily be searched for timely information such as that needed in an emergency. In addition, the systems employed by these large organizations are engineered to meet the specific needs of 

the organization that owns them, so they do not provide an open and accessible platform for market 

innovation that might lead to improvements in usability or functionality.

The main objective of this report is to argue that if health information technology is to have a truly 

transformative effect, the Federal Government should push ambitiously toward a national health data 

infrastructure in which patient data are readily available to providers in real time, can be accessed in 

de-identified form by researchers and public health agencies, and in which a market for applications 

that enhance EHR usability and patient involvement can flourish, enabling a “network effect” that can 

spur further adoption. The report describes a technological approach that could lead to this vision being 

realized, while at the same time strongly protecting privacy (including, where applicable, respecting the 

persistent privacy preferences of patients), and also describes some of the accompanying economic 

and regulatory steps that are required.
★ 12 ★

T h e Path F o rwa r d

The Present Federal Landscape

Recent Federal legislation offers a promising start toward these objectives. The Health Information 

Technology for Economic and Clinical Health Act, a part of the American Recovery and Reinvestment 

Act of 2009,10 authorized expenditures on the order of $20 billion (with estimates ranging from $9 billion to $27 billion) to promote the adoption and use of EHR technologies connected through a national 

health information network. Under HITECH, hospitals and physicians who make “meaningful use” of 

interoperable EHRs can qualify for extra payments through Medicare and Medicaid.

Responsibility for developing policies that implement the overall HITECH Act lies primarily with the 

Office of the National Coordinator for Health Information Technology; however, ONC also works closely 

with the Center for Medicare and Medicaid Services which is responsible for promulgating policies that 

relate to Medicare and Medicaid payment for meaningful use of EHRs under HITECH. Both ONC and CMS 

recently released final rules to implement the first phase of the HITECH Act, which begins in 2011. The 

ONC rule specifies the standards, implementation specifications and other criteria for EHR systems and 

technologies to be certified under HITECH and thus eligible for the Act’s incentive programs while the 

CMS rule specifies how hospitals, physicians, and other eligible professionals must demonstrate their 

meaningful use of these technologies in order to receive Medicare and Medicaid payment incentives.

Both sets of rules strongly indicate that standards and criteria for achieving meaningful use of EHRs 

will grow more rigorous in subsequent phases (2013 and 2015) as the technology continues to evolve 

and providers gain experience and sophistication in its use. For example, to qualify for meaningful use 

incentive payments in 2011, CMS will require providers to be able to electronically transmit medication 

orders, record patient information and problem lists, demonstrate use of decision support tools, test 

systems to exchange health information with other providers, and submit a small number of clinical 

quality measures; by 2015, CMS expects that to qualify for meaningful use of EHRs, providers will need 

to demonstrate greater use of decision support tools, higher levels of information exchange, and actual 

improvement in care coordination and patient outcomes.

The ONC also has moved to take a number of other useful actions in the short time since passage of 

HITECH. The ONC director and his staff have sparked needed awareness in the provider community, 

galvanized the experts and industry stakeholders, and created a momentum for change through open 

policy committee processes, several pilot frameworks, and the support of research in key areas. In addition, they have directly funded regionally based support systems for physicians and other providers, 

and supported several new programs and research initiatives designed to promote the use of health 

IT and the exchange of health information. ONC has distributed over $564 million to states and statedesignated entities to enlist their leadership in facilitating health information exchange within their 

jurisdictions and across state lines. Moreover, ONC is sponsoring many demonstration projects that 

build useful momentum and develop valuable experience and buy-in. These have helped to create the 

prerequisite conditions where Federal leadership, leading to rapid progress, is now possible. Further 

discussion of ONC’s initiatives and successes is in Chapter Three.

10. P.L. 111-5, “American Recovery and Reinvestment Act of 2009” (ARRA), 111 th Congress.
★ 13 ★

I . Intro d ucti o n a n d Ov erv i ew

Despite this progress, a major finding of this report is that achieving the President’s goals 

depends on accelerating and redirecting current Federal work laying the groundwork for health 

information exchange. While the 2011 rules are an appropriate initial step, the approach underlying 

these rules will not suffice to ensure that the various activities and experiments being supported by 

ONC will converge into an effective healthcare IT ecosystem that serves patients and providers. Going 

forward, the critical issue will be to ensure the creation, dissemination, and use of a universal exchange 

language for healthcare information that enables health IT data to be shared across institutions, along 

with network infrastructure that enables a patient’s data to be located and accessed across institutional 

boundaries, subject to strong, persistent, privacy preferences11. ONC should move rapidly to ensure 

the development of these capabilities; and ONC and CMS should focus meaningful use guidelines 

for 2013 and 2015 on the more comprehensive ability to exchange healthcare information.

We also have an important concern about CMS. CMS is the largest recipient of electronic health information (including data quality measures and measure sets) from hospitals and providers documenting their 

use and the effects of health IT. CMS will require major modernization and restructuring of its IT 

platforms and staff expertise to be able to engage in sophisticated exchange of health information and to drive major progress in health IT. This should be a major priority for CMS’s new leadership, 

and should be funded as appropriate for an essential component of the Nation’s healthcare quality and 

affordability agenda. A recently initiated National Research Council study of CMS’s IT capabilities should 

result in recommendations that will avoid replacing one inflexible architecture with another (a common 

trap in Federal IT acquisitions), but a successful outcome is at best several years away.

Several other agencies within HHS have potentially important roles in health IT. The Agency for Health 

Care Research and Quality (AHRQ) is a small but increasingly important research agency supporting 

health services and delivery system research. Approximately 80 percent of its FY 2009 budget of $372 

million is invested in grants and contracts focused on improving healthcare.12 The Food and Drug 

Administration (FDA), while not currently regulating EHRs, currently does receive voluntary reports 

of death and injury associated with EHR malfunctions. FDA officials have suggested possible future 

regulatory strategies that could include mandatory adverse event reporting, or even classifying EHRs 

as medical devices, which would make them subject to pre-market regulation.13 Other agencies with 

operational experience, such as the Centers for Disease Control & Prevention (CDC), or individuals in 

the Commissioned Corps of U.S. Public Health Service, might have roles to play in the management or 

operation of a future national health IT infrastructure.

11. Foreshadowing discussion later in this report, a more technical description of the common framework is: (1) 

a universal extensible language for the exchange of health information based on “metadata-tagged data elements,” (2) 

a standard for a minimal set of metadata that specifically enforce privacy safeguards on each individual piece of data, 

and (3) the development of a secure national infrastructure, based on the technology of today’s web search engines, for 

locating and assembling all of a patient’s information for clinical encounters and (when de-identified) for public health 

purposes.

12. AHRQ web page at http://www.ahrq.gov/about/ataglance.htm

13. Healthcare IT News (February 26, 2010) at 

http://www.healthcareitnews.com/blog/should-fda-regulate-ehr-safety
★ 14 ★

T h e Path F o rwa r d

Structure of this Report

Chapter Two gives a more thorough description of the benefits that could be realized by developing 

electronic health records to their full potential and integrating health information technology more 

completely into the healthcare system. The main features of the data-centric approach that we recommend are introduced with an initial discussion of metadata-tagged data elements.

Chapter Three describes in more detail the current state of health information technology, starting with 

the historical adoption and use of electronic records, and emphasizing the barriers that have arisen. 

The discussion focuses on specific cases that yield “lessons learned,” both positive and negative. Also 

discussed are the successes and challenges facing the two key agencies ONC and CMS. The chapter 

concludes with a list of technical and market-related criteria against which to test proposed solutions.

Chapter Four outlines a technological approach based on the use of tagged data elements that could 

achieve many, if not all, of the key objectives. This chapter is somewhat more technical, although its 

general argument should be understandable by all readers. The deficiencies of solutions that require 

standardized records, or which rely on service-oriented architectures, are also noted.

Chapter Five summarizes today’s privacy framework and indicates the ways in which it is inadequate 

for the future. Technologies are discussed that can be combined to achieve best-practice security along 

with persistent privacy protections.

Chapter Six discusses economic and regulatory issues, in particular how to reconcile the “public good” 

aspects of a national health IT infrastructure with the need to create vibrant, competitive markets. This 

chapter describes some of the main steps that are needed to complement the technological approach 

described in Chapters Four and Five, and relates health IT initiatives to the broader economics of 

healthcare.

Chapter Seven outlines some of the research opportunities that will be enabled by future health IT, and 

what are the requirements on that infrastructure so that the maximum benefits of that research can 

be achieved.

Chapter Eight brings together this report’s recommendations and guidance to key Federal agencies. We 

offer guidance of both a general and specific nature to ONC and CMS, and also suggest what a longer 

term roadmap should look like. Among our key recommendations is that the Chief Technology Officer 

of the United States should oversee the development of a set of metrics that measure progress toward 

a national health IT infrastructure that is operational and universal (as distinct from experimental and 

pilot programs). 

This chapter’s bottom line: Health information technology has the potential to improve the healthcare system in numerous ways. Yet Federal efforts are not optimized to achieve the President’s goals of 

improving the quality of healthcare and reducing its cost. Challenges differ by agency, but they include 

the need for more focus on the convergence of plans and the modernization of existing Federal IT 

infrastructure.
★ 15 ★

II. The Potential of Health IT

Introduction

In this chapter, we describe some of the potential benefits that could be realized from developing EHRs 

to their full potential and integrating health information technology more completely into the healthcare 

system. The benefits we describe might accrue at the level of individual clinical visits, at the level of 

healthcare organizations, at a broader regional and national level, and finally to patients wishing to have 

more information and more control over their own health and interactions with the healthcare system. 

We provide a series of “use cases” that illustrate the various levels at which information technology can 

improve healthcare delivery and the healthcare system.

We also note that formidable hurdles need to be overcome if these benefits are to be realized. The 

hurdles are both technological and economic. A key point is that current electronic health records, which 

are based on traditional paper records and exist largely within closed health organizations, cannot realize 

many of the potential benefits we have described. In order for health data to be broken down, indexed, 

transmitted across organizations, re-assembled, and aggregated, a more flexible technological approach 

is desirable. This approach is sketched below and described more fully in Chapter Four.

Later chapters expand on some of the other challenges that must be overcome to realize the potential 

benefits of health IT. Some early applications of IT in healthcare have had unexpected costs and consequences, and, despite the existence of commercial products and innovative demonstrations and pilot 

systems, the movement to electronic health records has been slow. The economic incentives to adopt 

and effectively utilize health IT have been weak, and the organizational structure of the healthcare 

system is itself highly fragmented. Current privacy regulation also creates complications for providers 

wishing to adopt and utilize IT. In short, there remain many barriers to achieving the potential of widespread and secure access to accurate, personalized, and comprehensive health data.

Potential Benefits of Health IT: An Overview

As medical practices and technologies have advanced, the delivery of sophisticated, high-quality medical 

care has come to require teams of healthcare providers, including primary care physicians, specialists, 

hospitalists, nurses, and technicians. Each member of the team tends to have specific but inevitably 

limited direct interactions with the patient. Every health provider has a somewhat different view of a 

patient, depending on the expertise the particular specialist brings to the medical team, and no one 

provider knows everything. In effect, the patient has fragmented into disconnected facts and clusters 

of symptoms. To prevent the most basic medical errors, some facts are elicited over and over again, to 

the frustration of patients and healthcare providers alike: “Do you have any drug allergies?” “Have you 

had any surgeries?” “Are you taking aspirin or blood thinners?” This frustrating repetition works, albeit 

inefficiently, if the patient is cognitively intact and well informed, but not all patients fit that description, 

especially in the event of a serious or acute illness.
★ 16 ★

T h e Path F o rwa r d

Health providers need views of the patient that are less fragmented than at present. A cardiologist, for 

example, needs immediate access to a patient’s most recent and significant cardiograms, cardiac imaging 

studies, and lab tests. He or she also needs to know about a family history of heart disease, concurrent 

illnesses being cared for by other specialists, past medical events, recent medications, and activity and 

nutrition changes. A nutritionist needs to know about a patient’s serum cholesterol and also about life 

changes, such as a new job or the illness of a spouse, that may have caused a sudden change in the 

patient’s diet. Health IT can integrate and organize patient information, and facilitate its instantaneous 

distribution among all participants in the healthcare system, so that providers and patients can obtain 

complete up-to-date views of each patient. In simple terms, health IT has the potential to put the patient 

back together again to allow more coordinated care.

Health IT also has the potential to generate valuable new information to improve workflow, safety, and 

efficiency within healthcare organizations. In industries such as manufacturing, retailing, and financial 

services, the efficiency gains from information technology were realized only when companies made 

complementary organizational changes. Today, some health organizations already use IT to track quality 

metrics, deploy reminder systems and checklists for physicians and other caretakers, and provide rapid 

feedback for the organization when changes are made. The widespread adoption of health information 

technology could allow these efforts to spread throughout the healthcare system.

The aggregation of data across organizations offers further possibilities. If the data gathered by healthcare providers and the decisions made at the point of care by providers and patients were gathered 

and aggregated, they could reveal patterns of illness in a community or nationally, identify potential 

epidemics at very early stages, enable comparisons of different treatments or medical devices in large 

and diverse populations, and evaluate the effectiveness of specific treatments and make information 

about hospitals, physicians, and other providers more comprehensive and accurate. Healthcare providers could use the information generated from these data to provide up-to-date and accurate guidance 

for patients, while healthcare recipients could draw on the data to prevent illness and obtain the best 

possible treatments. Data used to be an incidental byproduct of healthcare. In the future, timely information derived from high-quality data should be at the center of efforts to analyze, understand, and 

improve the healthcare system.

The next sections expand on these potential benefits of health IT, in part through simple “use cases.” 

Readers may, and probably should, find some of these cases rather easy or obvious. Indeed, what is 

surprising is that today they are generally not possible in most care delivery environments.
★ 17 ★

II . T h e P otenti a l of He a lth IT

Table 1. The Potential Benefits of Health IT

The ability to capture, store, exchange, and analyze medical information in electronic form could 

improve U.S. healthcare in many ways.

• Quality of care for individual patients. Patients will receive better medical care if they and 

their healthcare providers have access to complete and accurate electronic health records that 

aggregate information across time and organizations. Given the fragmented nature of the U.S. 

healthcare system, such integrated health records are now often not available. Such records could 

improve diagnoses, prevent errors, and save time.

• Engagement of patients in healthcare. The participation of patients in their own healthcare 

could substantially improve their care, especially in the management and treatment of chronic 

conditions such as obesity and diabetes. Access to electronic personal health information and 

interfaces that make it easy for public and private clinical organizations to share health information 

with each other and with patients could enable healthcare providers and patients to collaborate 

in informed decision-making.

• Clinical studies of medical interventions. Sound medicine needs to be based on empirical 

evidence of how well particular interventions work for patients. While some questions can only be 

answered through randomized clinical trials, a tremendous amount could be learned through 

the ability to integrate the combined experience of millions of patients. Aggregated de-identified 

information could enable a wide range of studies on such topics as the efficacy of prevention 

strategies, the frequency of particular complications in particular settings, and the response of 

individuals to specific drugs as a function of genotype.

• Improved population-based knowledge. Aggregated health information can provide invaluable tools for identifying and tracking medical events such as epidemics and adverse events related 

to treatment.

• Development of new tools for medicine. In most industries (such as retail consumer goods, 

shipping, and financial services), the availability of electronic information has led to an outpouring of creative tools that have increased quality and enabled new kinds of services. Healthcare 

could benefit greatly from such tools. Examples include home-based monitoring devices that 

could directly transmit data to physicians, systems that could help increase patient compliance 

with drug regimens, and computerized decision support systems able to incorporate the most 

up-to-date clinical knowledge.

• Increased administrative efficiency. In most industries, electronic information also has led to a 

decrease in administrative costs as many processes became automated. In healthcare, administrative tasks (such as filling out forms and processing billing requests) represent a significant fraction 

of healthcare costs. Health IT could streamline these tasks and significantly decrease costs.
★ 18 ★

T h e Path F o rwa r d

The Value of Patient-Specific Data to Patients

Electronic health information should enable patients to have full and accurate information about all 

medical evaluations, to track the management of their own conditions, to schedule and change appointments as appropriate, and to exchange email with providers. This would give patients and families more 

direct engagement with their care, create an avenue for communication with healthcare providers, 

and identify treatable symptoms early to avoid unnecessary emergency room visits or hospitalizations.

Electronic health information also can improve coordination of care by ensuring that every specialist, 

in every setting, has the same accurate and up-to-date information about a patient. This is especially 

important with patients who are seeing multiple specialists, with patients making transitions between 

care settings, and especially in emergency settings. This kind of data availability will reduce medical 

errors, reduce unnecessary tests, and reduce the chance that a patient’s physician would not know 

about an unrelated but relevant condition being managed by another specialist.

Use Case 1: A patient on warfarin, a blood thinner, strains his calf muscle during a tennis match 

and cannot remember whether it is safe to take Advil or Motrin. He types “Advil” into his personal 

health record list to see if there are any potential interactions with the list of medications in his 

record. Indeed, taking either Advil or Motrin would significantly increase his risk for serious bleeding. He emails his physician, who recommends cold packs and acetaminophen. The next day a 

discoloration and increased swelling occurs. He sends another email to the physician’s office, where 

he is connected to a nurse practitioner who recommends a blood coagulation test. He is able to 

select times online for the test, for follow-up with the physician, and for possible further tests and 

physical therapy.

Use Case 2: A 70-year-old woman with a newly diagnosed lung mass suspicious for lung cancer 

discovered on a CAT scan in a small community hospital is referred to a large academic center in 

a metropolitan area two hours away. The patient’s local hospital automatically makes available 

her electronic health record, enabling the cancer surgeon to pull up the CAT scan images and 

radiologist report at the patient’s consultation. She doesn’t remember all her medications, but her 

electronic record has recently been updated and verified. She may need a lung biopsy, and her 

record notes that she has an unusual cardiac arrhythmia that has been treated by a cardiologist 

in the past but that she is no longer taking medication. The biopsy is positive for lung cancer, and 

she will need both surgery and radiation. She is able to receive some of this treatment closer to 

one of her children, who lives in another state 1,200 miles away, with real-time communication 

electronically between her oncology team and her primary care physician. During this time, she 

is weakened and falls, sustaining a hip fracture. She is taken to the emergency room, where all 

her information is immediately available to sort out the otherwise confusing picture of cardiac 

arrhythmia, anemia from cancer treatment, and recent surgical scars.
★ 19 ★

II . T h e P otenti a l of He a lth IT

The Value of Patient-Specific and Aggregated Data to Physicians

For the majority of U.S. physicians, electronic health information will for the first time enable them to 

query and analyze the “denominator” of their patient population—the full range of patients for whom 

they and their colleagues are responsible. This will make it possible for the physician to identify areas 

where patients are receiving less than optimal care—for example, how many patients with hypertension 

have their blood pressure under control, or how many patients with diabetes have their blood sugar 

measurements in the target range and have had appropriate screening tests.

This same clinical information is also essential to meet the growing number of demands for reporting 

of clinical quality measures for accountability and payment purposes. These demands are currently 

both expensive and cumbersome for most physicians, and to the degree that most of these data come 

from insurance companies, the data are limited to claims-linked information and are inevitably delayed 

and incomplete. Most physicians are very interested in and responsive to accurate evidence. Being able 

to interrogate one’s own data for rates of performance on quality measures could lead to significant 

healthcare improvements.

Payers and consumers are increasingly including the results of patient surveys in performance measures 

used for payment, public reporting, and improvement. A fully functional electronic healthcare information system would enable physicians to contact patients directly, to solicit patient feedback related to 

specific conditions, and to compile actionable feedback to the practice.

Use Case 3: A general internist decides to seek approval for her practice to be designated a 

patient-centered medical home (PCMH) under Medicare because she cares for a large number 

of patients with chronic illness, including diabetes, heart disease, and hypertension. This requires 

her to submit a large number of data entry forms and quality measures, including descriptions of 

her patients, their disease profiles, and their demographics. Her office staff is able to do this easily 

by extracting the information from her EHR system, and she receives the designation. Her office 

is also able to file quality of care and utilization reports on a regular basis to 10 other payers apart 

from Medicare, and create reports that aggregate her patient population across all payers. This 

allows her to identify gaps in preventive measures or diabetes and hypertension control and create 

reports to maintain specialty board certification and hospital privileges. When she identifies areas 

for improvement, she implements changes in her practice and later re-measures. For example, she 

and her partners have increased the rate of elderly patients who received preventive falls assessments, and were able to do the follow-up measures electronically because they share EHR data 

with the two retirement homes and several nursing homes in the region. In doing this, they drew 

on patient-specific risk profiles and guidelines available electronically from the National Institutes 

of Health and the American Geriatric Society decision support programs.
★ 20 ★

T h e Path F o rwa r d

As the use of quality measures increases, a question looms about how much real impact these measures 

will have on outcomes that are meaningful to patients. The combination of more efficient and accurate 

physician reporting with population-based outcome data could dramatically enhance critically important research about which of the measures link with desired patient outcomes, which of them lead most 

directly to improvement, and how to streamline the measurement and reporting process to reduce the 

time and financial burden on physician practices and still produce measures relevant to patient values.

Having electronic health information about the entire population of patients served by a given practice 

or provider enables queries about groups of patients who suffer from a specific condition, are eligible 

for spec ific preventive measures, or are currently taking specific medications. Among other things, this 

population-based view enhances the ability of the practice to identify and work with patients to manage specific risk factors or combinations of risk factors. It also can detect patterns of potentially related 

adverse events and enable patients at risk to be quickly and correctly notified. For example, when a 

previously unidentified medication risk comes to light (as in the case of Vioxx), it is easy for the practice 

to identify all the patients taking that medication and to contact them immediately. If fully linked to 

the patient’s personal health record, this function would also apply to over the counter medications. 

Similarly, when a needed vaccine (such as H1N1) is available, the practice can identify the patients at 

greatest risk and communicate with them efficiently. Outreach, patient education, and notification 

about particular risks are made possible by this kind of system.

Use Case 4: A small group practice provides online access to each patient’s medical record and 

communicates regularly with its patients via email. The practice has recently implemented an 

open access scheduling system and is curious to learn how patients feel about the change, so they 

email all patients with a recent office visit a web link to complete a focused satisfaction survey. 

They also participate in the Consumer Assessment of Healthcare Providers and Systems (CAHPS) 

survey authorized by Medicare but would like to add more specific questions related to patient’s 

own conditions such as: “Did the nurse follow up with you about managing your new glucometer?” 

“Did your questions get answered?” They are able to personalize aspects of this survey and at the 

same time have only the needed aggregate data reported to payers.

Use Case 5: A group of cardiology clinics in the Southwest, separated by significant distance, 

decides to work together to improve the care of patients who recently experienced a myocardial 

infarction (heart attack). They link information from each clinic’s electronic medical records to track 

progress, learn what quality interventions work best, and create composite measures that help 

to distinguish what constitutes the best overall care. They are able to identify which sites have 

the best outcomes in certain areas, and they learn from each other how to apply these findings 

through webinars engaging all the staff in each clinic.
★ 21 ★

II . T h e P otenti a l of He a lth IT

The Value of Population Data for Research and Public Health

If real-time concurrent clinical data about every healthcare encounter were stored electronically, such 

data could be combined, without personal identifiers, from a regional or national population to allow 

enormous improvements in the ability to track public health issues and to develop prevention and 

amelioration strategies in a timely manner.

For example, natural epidemics such as H1N1 influenza are currently tracked through a combination 

of voluntary reporting by physicians and emergency rooms to various public health authorities and to 

the Centers for Disease Control and Prevention. Social networking and use of the Internet recently have 

been shown to add significantly to this capability.14 But neither of these methods is impeccably accurate 

and truly comprehensive or able to pick up nuances of epidemics from current clinical data. A fully 

functional health information network that was widely used, interoperable, and able to be aggregated 

with a reasonable degree of accuracy and reliability would dramatically improve the ability to track 

known epidemics, to identify new ones, and to identify at an early stage other threats to public health 

such as bioterrorism or environmental exposures.

With sophisticated modeling expertise, this same database would enable comparative effectiveness 

research by tracking groups of patients taking comparable treatments for similar conditions. The 

results of these virtual clinical trials would be more representative of real-life patient populations, far 

less costly to conduct, and quicker to identify information relevant to the care of specific patient groups. 

Furthermore, as medicine is connected more closely to genetically linked traits and susceptibilities, 

this kind of tracking will accelerate the ability to provide patient-specific information to physicians and 

patients to individualize treatment decisions.

14. Brownstein, J. S., C. Clark, B. S. Freifeld, E. H. Chan, M. Keller, A. L. Sonricker, S. R. Mekaru, and D. L. Buckeridge. 

2010. Information Technology and Global Surveillance of Cases of 2009 H1N1 Influenza. New England Journal of Medicine, 

362:1731-1735.

Use Case 6: A family physician embeds electronic reminders that alert her when the patient she is 

seeing during an office visit needs preventive care. Each fall, the clinic queries the electronic record 

to see which patients will need an influenza vaccine and to automatically generate a reminder 

email and/or text message sent to the patient. When an unusual pandemic strain appears, with 

different risk groups, the database can be queried to identify and communicate with those patients 

who are at highest risk.

Use Case 7: A physician treating a patient with rheumatoid arthritis using TNF (tumor necrosis factor) inhibitors enters the patient into the database of a national clinical study. Because the patient’s 

clinical and genetic information are both known, the physician is able to use specific characteristics 

to predict outcomes and reduce toxicity without relying on the traditional trial and error process. 

This information is available to all physicians and patients and is continually updated.
★ 22 ★

T h e Path F o rwa r d

This de-identified but clinically rich database would also enable post-marketing surveillance for 

FDA-approved medications, which now depend on voluntary reporting by physicians and healthcare 

organizations. An efficient way to track patient populations taking new medications, including other 

prescribed or over-the-counter medications simultaneously being administered, adds tremendous 

power to the ability to pick up adverse events or medication interactions as early as possible. As genetic 

information becomes more routinely available, this kind of post-marketing research capability will 

enable more accurate prescribing. This is especially important for medications such as biological (or 

cell-based) therapies and cancer chemotherapies where potential toxicities are significant and current 

research methods necessitate exposing large numbers of people to toxic side effects when they might 

not benefit from the treatment.

Population-based clinical data will enable communities, states, and regions to track their own health 

statistics in a more timely, reliable, and credible manner. As we consider the potential of setting health 

goals for communities as well as for the Nation, these data would provide a continuous measure against 

which all stakeholders (healthcare providers, community groups, consumer and workforce advocates, 

businesses, and government) could engage around setting targets and tracking progress. Congress 

has established a process to develop national priorities for improving healthcare in the United States, 

engaging all the relevant Federal agencies plus multi-stakeholder public-private collaborations.

Realizing the Potential of IT: A Data-Centric Approach

The use cases above only scratch the surface of what might be possible if market innovation in information technology were to take off. A number of barriers, however, stand in the way. First, current electronic 

health records largely employ proprietary formats that are not directly exchangeable from one system to 

another. Second, it is difficult for data to be disaggregated, searched, and indexed because the context 

Use Case 8: An FDA Commissioner is able to launch a real-time assessment of every patient taking 

newly approved drugs and aggregate clinical patterns to identify adverse side effects of medications. A robust post-marketing electronic registry allows much earlier detection of important 

adverse events for discrete subpopulations of patients and at negligible additional cost to FDA.

Use Case 9: For a particular year, ambitious new goals are set to improve health measures. 

Communities, regions, and states are able to provide comprehensive and accurate annual reports 

on each of these goals, identifying gaps where special focus is needed and key areas for focus in 

coming years. This process does not require extensive additional data gathering by state and local 

public health entities. Rather, it uses the flow of de-identified information generated by regular 

population health and healthcare activities.
★ 23 ★

II . T h e P otenti a l of He a lth IT

(what we will refer to as the metadata) for individual entries in an EHR is often implicit at best.15 Third, 

current EHRs generally exist institutionally within closed healthcare organizations or disconnected small 

practices rather than being accessible in appropriate form to patients, to other healthcare providers, 

and in de-identified or aggregated form to public health agencies and researchers. Strong economic 

incentives and regulatory initiatives are needed to overcome these obstacles. The new economic and 

regulatory programs launched by HITECH may not be sufficient.

In order to foreshadow later chapters of the report, it is useful to engage in a brief discussion of the EHR 

itself. A first point to convey is that in virtually all of our use cases, the “user” of the data does not need to 

be, and indeed should not be, scanning through the entire health record. Instead, the user needs to be 

looking at an application layer that accesses and presents a limited amount of information from a given 

health record or set of records. We refer to the ability of applications to access and utilize data relevant 

to a variety of specific tasks as a data-centric approach. Fortunately, data mining and presentation is 

something that computers, augmented by communications networks and distributed data storage, are 

very good at. Unfortunately, it is not something that current EHR systems are optimized for. Instead, many 

of them function as something closer to an electronic version of the paper record, and communication 

across systems is sorely lacking.

We will argue in this report that to achieve even the more modest goals set out in this chapter will require 

an infrastructure and a “universal exchange language” that allow data to be shared and communicated 

for different purposes among diverse EHRs and other applications. We also believe that there is a natural 

technological approach which will facilitate a move in this direction and which, over time, will also lead 

to beneficial changes in the way that EHRs are structured. This approach begins with the observation 

that the best way to manage and store data for advanced data-mining techniques is to break it down 

into the smallest individual pieces that make sense to exchange or aggregate. We will refer to these 

kinds of data as “tagged data elements,” because each unit of data is accompanied by a mandatory 

“metadata tag” that describes the attributes, provenance,16 and required privacy protections of the data. 

Modern, networked computers are particularly good at indexing, finding, and retrieving data that are 

discrete and “close to the surface,” even when the pieces are distributed widely over many computer 

systems and data-stores. So storing data in this fashion can create an environment in which clinicians can 

access a patient-centric record tailored for each medical encounter, and in which health organizations, 

researchers and public health agencies can aggregate data for a broad variety of uses.

We expand on these points in Chapter Four by arguing for an evolutionary transition from traditional 

EHRs to a tagged data-element model, and a more rapid transition for the more limited purpose of data 

exchange. In the model we will propose, data can easily be aggregated and de-identified, and data do 

not depend on a single provider or a single vendor for use. The entities needed to facilitate this type of 

information-rich environment could be viewed as part of the national health infrastructure, like hospitals 

and clinical laboratories, regulated, but typically not operated by government entities , allowing data to 

be drawn safely for uses in multiple arenas. Embracing this outcome is an important and essential step 

toward leveraging the true power of information technology to improve healthcare.

15. For example, given an entry containing a laboratory test result, one might deduce the name of the physician 

who ordered the test from a case note with a corresponding date (context present, but implicit); but, for the case of an 

equipment recall, one might not at all be able to deduce the brand of medical equipment used (missing context). 

16. Provenance includes information about the data’s source and the processing that the data have undergone.
★ 24 ★

T h e Path F o rwa r d

Conclusion

Information technology, along with associated managerial and organizational changes, has brought 

substantial productivity gains to manufacturing, retailing, and many other industries.17 Healthcare 

is poised to make a similar transition, but some basic changes in approach are needed to realize the 

potential of healthcare IT.

The most significant change is that all healthcare should be organized around the needs and specific 

characteristics of the patient, not around those of the hospital, doctor’s office, insurance company, or 

EHR vendor. Medicine has become an information-rich enterprise, and a larger and more seamless 

flow of information will result in a transformation of care, organized around the patient, wherever he 

or she may be. The healthcare system will be driven by information and at the same time will generate 

information that can be used to improve healthcare. The potential for individualized care, higher quality, 

lower costs, and enhanced safety is immense.

The best way to give clinicians a unified, patient-centric record tailored for each medical encounter is to 

store, maintain, update, and exchange the data as small, distributed, metadata-tagged elements. The 

data element indexing and access services needed to facilitate this type of information-rich environment can be viewed as part of the national health infrastructure, like hospitals and clinical laboratories. 

Embracing and promoting this outcome is an essential step toward leveraging the true power of information technology to improve healthcare.

This chapter’s bottom line: Improved health IT can directly affect, and improve, clinical encounters 

between doctor and patient, healthcare organizations, clinical research, and the monitoring of public 

health. For this to happen, we must be able to “disassemble” the information in electronic health records 

and then “reassemble” it in various ways.

17. Brynjolfsson, E, and L. M. Hitt. 1998. Beyond the Productivity Paradox: Computers are the Catalyst for Bigger 

Changes. See http://ebusiness.mit.edu/erik/bpp.pdf
★ 25 ★

III. Health IT Today

Introduction

Traditionally, electronic records and information technology have played a limited role in healthcare 

delivery. There are a number of reasons for this, both economic and technological. In this chapter, we 

describe some of the historical barriers to health IT adoption, and the current Federal initiatives that are 

beginning to change the health IT landscape. In doing this, we touch on some of the lessons that can be 

drawn from the experience of early IT adopters, predominantly large integrated healthcare organizations, 

as well as the historical and current state of EHR technology.

The final part of this chapter discusses nascent attempts to promote data sharing through local and 

regional health information exchanges. Data sharing and exchange through a national health IT infrastructure is essential to realize many of the potential benefits described in the current chapter. This 

requires the ability to access, assemble, and present data that are potentially being generated across 

a range of organizations. This capability is by and large lacking in the current environment. Moreover, 

current approaches to data exchange and aggregation, which are often bilateral or document-based, 

do not, in our view, present a clear path to scalable national solutions that would trigger transformative 

innovation and use of health IT. In this sense, there is potentially a large gap between the current path 

and the potential for IT to improve health and healthcare.

Historical Barriers to EHR Adoption

Although the promise of EHR systems was recognized decades ago,18 even today the great majority of 

physicians rely on paper records and use electronic data mainly for billing purposes. According to the 

CDC’s National Ambulatory Medical Care Survey (NAMCS, 2009) only 6.9 percent of physicians reported 

having an extensive, fully functional electronic record system. Only 20 percent reported having even a 

basic electronic record system.19 At first glance, this is surprising given that computers and information 

technology are so completely embedded in most industries. One would be shocked to hear of a leading 

manufacturer using paper records to track production or inventories, or of a financial services firm relying 

primarily on faxes and ordinary mail to exchange information with clients and partner firms. Indeed, 

healthcare providers have long used computers and IT for billing and communication with payers. Why 

has the broader adoption and utilization of information technology in healthcare been so slow?

At least part of the explanation lies in the organizational and economic structure of healthcare. Most 

physicians practice in small groups and are reimbursed for care on a fee-for-service basis. Physicians 

operating in this type of environment cannot easily internalize many of the potential benefits of electronic records and health IT, such as improved sharing of patient information, greater coordination of 

18. E.g., Garwin, R. L. 1968. Impact of Information-Handling Systems on Quality and Access to Health Care. Public 

Health Reports, 83(5):346-351.

19. See http://www.cdc.gov/nchs/data/hestat/emr_ehr/emr_ehr.htm Primary care physicians and those practicing 

in large groups, hospitals or medical centers, and the western region of the United States were more likely to use 

electronic health records.
★ 26 ★

T h e Path F o rwa r d

care, and aggregation of data.20 They also have little incentive to undertake the substantial investment 

or money and time to install and adapt to electronic records, particularly when this involves a large fixed 

cost that cannot be spread across a large number of patients or physicians.

The situation has been compounded by a number of additional factors. Lacking demand from providers, 

the market has been slow to provide IT products geared toward small organizations. As we discuss below, 

even the advanced systems geared toward hospitals and large healthcare providers lack capabilities 

that seem rather obvious, such as extensive clinical decision support, or the ability to easily exchange 

data with other providers who share responsibility for the same patients. In addition, privacy and liability 

concerns may be a deterrent for some organizations, or at least for data-sharing initiatives.

Not surprisingly, the healthcare organizations that have adopted electronic health records tend to be 

large organizations that can shoulder the financial burden of installing customized systems and can 

internalize the benefits associated with such systems. These systems also tend to have different financial 

incentives than are prevalent in the broader healthcare system. Some are paid on a capitated basis (a 

fixed amount per patient per year), so they have an incentive to provide care efficiently and reduce 

duplication or extraneous services when possible. However, some tens of thousands of small physician 

practices have also adopted electronic health records. These physician adopters tend to be younger and 

more technologically savvy than their peers. Below we discuss some of the lessons that can be gleaned 

from the experiences of these early adopters.

Limitations of Present-Day EHRs

The most commonly cited reasons for not adopting EHRs include the cost of installing and maintaining 

a system (including both financial and workflow disruption costs) and the lack of perceived benefits 

in terms of enabling higher quality, more efficient care. A frequent complaint is that electronic health 

records do not make the physician’s job easier. In particular, few EHRs deliver the intelligent cognitive or 

decision support that one might hope for. Even where decision support is available, physicians often do 

not take advantage of it. This section describes some of the cost and “usability” concerns around current 

EHR systems, and how a robust technology market could alter the situation.

Workflow Disruption and Documentation Burden: Present-day EHRs often require a substantial increase 

in physician time devoted to documentation. Physicians may complain that they are spending extra 

hours to type in orders and notes from patient visits. Healthcare systems can hire staff to enter data 

into the EHR during the office visit, but this is cumbersome and not economically feasible for small 

practices. Speech-to-text transcription systems exist, but so far they are useful only for specialties with 

circumscribed and highly specific vocabularies. Physicians often are left to design their own “templates” 

to reduce the data entry burden. Streamlined data entry via checklists, customizable templates, and 

other structured means is an area of opportunity for software and systems designers.

Lack of Decision Support Functionality: Many EHRs were developed as electronic facsimiles of existing 

paper records. They were created largely without the assistance of experts in human factors and design 

and they do not fully leverage the ability of computers to retrieve and analyze data to provide useful 

20. A growing literature demonstrates a positive return on investment for EHRs in small practices, but the larger 

part of the benefit is not captured.
★ 27 ★

III . He a lth IT T o day

guidance, safety checks, and decision support. There have been some useful advances in this area, 

such as modules that cross-check for drug interactions, provide warnings about allergies, or generate 

reminders for preventive services. Nevertheless, this is an area ripe for innovation. Recently, the National 

Research Council proposed a comprehensive research agenda for the development of new approaches 

to EHRs that would provide cognitive support for clinicians and draw on human factors engineering.21

As just one example of the potential, research over the past decade has raised the possibility that diagnostic errors may be far more extensive than therapeutic errors. As much as 15 percent of all diagnoses 

may represent clinically significant errors.22 Clinical decision support that could assist physicians in 

making effective diagnoses might represent a significant opportunity if it could be integrated with the 

electronic record.

Lack of a Platform for Innovative Applications:Many healthcare systems use enterprise systems customized to fit the needs of the particular provider. Other organizations rely on idiosyncratic “legacy” systems 

that often were initially used primarily for billing or pharmacy refills. Neither type of system provides an 

open and robust platform for software developers to build applications to improve data entry processes, 

provide decision support, or other functionality. The fact that existing systems often use record formats 

based on messages and page formats also makes it harder to access, retrieve, and analyze individual 

data elements. In addition, existing systems typically are not interoperable, so that data cannot easily 

be shared or aggregated across organizations. Although we discuss below some new technologies that 

may improve this situation, these limitations stand in the way of innovation that could help to alleviate 

some of the usability problems described above.

21. Stead, W. W., and H. S. Lin, Eds. 2009. Computational Technology for Effective Health Care: Immediate Steps and 

Strategic Directions. Washington, DC: National Academies Press. http://www.nap.edu/catalog.php?record_id=12572

22. Schiff, G. D, and D. W. Bates. 2010. Can Electronic Clinical Documentation Help Prevent Diagnostic Errors? New 

England Journal of Medicine, 362:1066-1069.

Technology-Enabled Diagnoses

Imagine a patient with the history of hepatitis C who presents to a primary care physician complaining of an itchy rash. When the physician dictates or types the words “new rash” into the record, 

the record instantly reminds the physician that hepatitis C has associations with certain diseases, 

including a condition known as lichen planus that triggers an itchy rash. The decision support 

system can remember all of the associations between patient clues and medical diagnoses. It then 

becomes the job of the clinician to navigate the evidence and assess the situation with the richer 

information that is instantly available. In another example, imagine a veterinarian presenting with 

new symptoms. The decision support engine would immediately display diseases associated with 

veterinarian exposures. Such functionality is feasible today, but the burden and costs of deploying 

the record, and the use of “first generation” decision support by vendors, have hindered critical 

innovations needed to reduce diagnostic and therapeutic errors.
★ 28 ★

T h e Path F o rwa r d

Concerns about Security and Privacy: Finally, a major concern with healthcare information, as with 

financial and other highly sensitive personal data, involves security and privacy. The Privacy and Security 

Rules issued under the Health Insurance Portability and Accountability Act (HIPAA) of 1996 provided 

the first broadly applicable Federal protections for health information. These Rules, along with multiple 

state laws, create a complex network of laws and regulations that address patient privacy and consent 

for the use of identifiable personal health information. The resulting regulatory framework, in current 

implementations, imposes significant costs on healthcare providers. Moreover, although HIPAA has 

usefully raised awareness of the need to protect health information, the Rule has become obsolete in 

many ways given advances in technology. A recent Institute of Medicine (IOM) report concluded that the 

law needs to be fundamentally reconsidered to reflect new information technologies and to enhance 

personalization and the quality of care.23 Chapter Five expands on this point and discusses how emerging capabilities in metadata, encryption, and identity systems enable promising new ways to protect 

Internet-based information that were not envisioned when HIPAA was passed.

Lessons from Early Adopters

The healthcare organizations that have adopted electronic health records are mainly large integrated 

health systems that can internalize the benefits of EHRs as well as fund the initial investment and ongoing 

maintenance. Although these organizations are not necessarily representative of the broader healthcare 

system, their experience provides some important lessons.

The Kaiser and VA Experience

Two of the Nation’s largest healthcare systems—the Veterans Health Administration (VHA) medical 

system and Kaiser Permanente—were among the earliest adopters of integrated EHR systems.

The VHA’s adoption of its VistA system is credited with playing a major role in enabling the Nation’s largest integrated health system to provide a highly regarded level of information technology supporting 

better care.24 For example, the use of electronic reminders and performance measurement to improve 

pneumonia vaccination rates probably saved the lives of 6,000 veterans with emphysema.25 VHA’s 

vaccination rate became the national benchmark as pneumonia hospitalizations were halved even 

while VHA’s patient population doubled—all while reducing taxpayer costs by $40 million.26 VistA also 

has enabled the VHA to reduce medication errors to a rate of 7 per million prescriptions written, well 

below the national average of 1 error in 20.27 VistA has been made available in open source but lacks the 

flexibility of other commercial systems, so it is not widely adopted except by some safety net organizations. It currently does not connect easily with other systems or with personal health records (PHRs, 

23. Nass, S. J., L. A. Levit, and L. O. Gostin, Eds. 2009. Beyond the HIPAA Privacy Rule: Advancing Research, Improving 

Health Through Research. Washington, DC: National Academy Press. http://www.nap.edu/catalog.php?record_id=12458

24. Asch, S. M., et al. 2004. Comparison of Quality of Care for Patients in the Veterans Health Administration and 

Patients in a National Sample. Annals of Internal Medicine, 141:938-945.

25. VistA: Winner of the 2006 Innovations in American Government Award. 2006. See 

http://www.innovations.va.gov

26. VA Receives 2006 Innovations in Government Award. 2006. See 

http://www1.va.gov/opa/pressrel/pressrelease.cfm?id=1152

27. VistA: Winner of the 2006 Innovations in American Government Award. 2006. See 

http://www.innovations.va.gov
★ 29 ★

III . He a lth IT T o day

discussed below). Nor is it strong at creating searchable databases that web-based models promise. A 

descendent of VistA, the Armed Forces Health Longitudinal Technology Application (AHLTA), contains 

medical records of nearly 10 million military service personnel and their families. However, VistA and 

AHLTA have diverged to the extent that they are no longer cross-compatible.

Kaiser Permanente’s HealthConnect system is based on the Epic EHR, the most widely used of current 

vendors. Kaiser’s implementation connects all 8.6 million Kaiser Permanente members, over nine states 

and the District of Columbia, to 14,000 physicians28 in Kaiser’s 431 medical offices and 36 hospitals.29

Physicians can retrieve data on any patient who has received services within their network. Kaiser has 

used the system to improve preventive care and the management of chronic conditions. Specialists 

are alerted if a patient is overdue for preventive screening (such as mammography), and often the test 

can be scheduled for that same day. Kaiser’s system also produces quality measures and feedback for 

physicians, medical centers, and hospitals,30 and is able to aggregate population-level data to track 

adverse events and trends. It was the first to identify the link between Vioxx and increased risk of heart 

attack and to remove the drug from its formulary.31 It can also track early cases, predicting epidemics, 

such as influenza, across its offices.

An additional feature of Kaiser’s IT system is that it allows patients to access online data and communicate with their physicians using secure messaging. More than 3 million Kaiser patients are registered 

for this feature, and over 100,000 access the system on a given day.32 Kaiser attributes this part of the 

system with improving both quality and efficiency of care delivery. Findings from a 2009 study showed 

that patients’ use of secure messaging and scheduled phone “visits” enabled by HealthConnect led to a 

26.2 percent decrease in total office visits over four years.33 Over the same four years, most measures of 

healthcare effectiveness and patient satisfaction improved significantly. Despite this useful functionality, 

however, Kaiser’s system is a closed one that does not communicate easily with other systems or networks. Only recently have Kaiser and the VA begun to collaborate to share data about patients who use 

both systems, and efforts so far are limited to one geographic area (San Diego). Kaiser also is exploring 

further interactions with health information exchanges in some regions.

Experiences at Other Organizations

The experiences of some other health systems help to illustrate the use of EHRs and the variety of issues 

involved in deploying IT in very different organizational and economic environments. In each of them, 

one can see the advantages to the patients within that system, but also the limits to models that are 

enterprise based rather than based on Internet technology.

The Palo Alto Medical Foundation (PAMF) is a highly-regarded multi-specialty group in Northern 

California that is affiliated with Sutter Health. In 1999, it deployed an Epic electronic record system similar 

28. R. Kahn. 2010. Kaiser Permanente Completes Electronic Health Record Implementation. Available at 

http://xnet.kp.org/newscenter/pressreleases/nat/2010/030310ehrcomplete.html

29. Fast Facts about Kaiser Permanente. Available at http://xnet.kp.org/newscenter/aboutkp/fastfacts.html

30. Weissberg, J. Perspective: Electronic Health Records in a Large, Integrated Health System: It’s Automatic....NOT! 

At Least, Not Yet. National Quality Measures Clearinghouse.

31. Kweder S. 2004. Vioxx and Drug Safety. Available at 

http://www.fda.gov/NewsEvents/Testimony/ucm113235.htm

32. Chen, C., T. Garrido, D. Chock, G. Okawa, and L. Liang. 2009. The Kaiser Permanente Electronic Health Record: 

Transforming and Streamlining Modalities Of Care. Health Affairs, 28: 323-333.

33. Ibid.
★ 30 ★

T h e Path F o rwa r d

to Kaiser’s.34 Physicians can pull up notes written by other PAMF physicians, access lab and imaging 

results, and send messages to patients. Physicians and administrators also have access to populationlevel quality measures. PAMF has used IT to alter the scheduling system so that many routine visits are 

scheduled just one or two days in advance. Because PAMF does not own its own hospitals and recently 

merged with two other large groups in the Sutter system, it has been attempting to make its systems 

compatible with its partners and integrate data fully across its component groups. Even today, however, 

it has not achieved full integration.

Geisinger Health System is a prominent health system in central Pennsylvania that encompasses both 

Geisinger’s own health plan and affiliated clinicians. Geisinger has extended its EHR to include the 

private practice physicians in the community, allowing them to access information about their patients 

hospitalized at Geisinger Hospitals, and allowing hospital-based physicians to get access to records from 

the community practitioners. Geisinger maintains a corporate research center that aggregates data from 

all the providers in the system to produce clinically based measures of quality of care, help physicians 

establish benchmarks, and monitor quality for external reporting. The distributed aspect of Geisinger’s 

system involves additional challenges such as the standardization of data elements and data systems 

that are integrated into central data repositories. It has been easier for Geisinger to do this because they 

it is essentially the sole hospital provider in a large geographic area, and it does not face the competitive forces that might deter community physicians from signing onto a EHR system that only provided 

information from one hospital system and not others where their patients might receive care.35

Lessons and Challenges

The experiences described above demonstrate how health IT can be successfully deployed and used, 

but they also reveal some of the challenges that remain.

A first point is that each of the organizations above has developed a system specifically tailored to its 

own needs. Each system has been expensive to deploy and requires substantial resources to maintain, 

as well as a significant and sustained effort to extract and utilize the information for organizational and 

care process improvements. While the organizations we have described also realize corresponding 

benefits, this kind of enterprise solution is inappropriate for small physician groups. Also, the patchwork 

nature of organizational solutions does not provide a scalable model for the effective flow of information centered around a patient, wherever that patient may be, or for a market for innovative electronic 

information solutions to everything from patient empowerment, to patient specific clinical decision 

support, to real time aggregated clinical data for robust quality assessment and public health purposes.

Second, the systems we have discussed are not mutually interoperable, meaning that patient information cannot easily be shared between providers with different systems or in different networks without 

a significant up-front investment to make this possible. Interoperability is important to improve and 

coordinate care delivery. Currently in the United States, most patients receive care from a variety of 

providers. One recent study found that the typical Medicare patient receives care from seven physicians 

34. “Sutter Health and Affiliated Palo Alto Medical Foundation Praised by U.S. Health and Human Services for IT 

Innovation.” 2005. See http://www.sutterhealth.org/about/news/news_pamf-ehr.html

35. Academy Health. “HIT and HSR for Actionable Knowledge: Description of Partnering Health Systems. Partner:

Geisinger Health System.” See http://www.academyhealth.org/files/HIT/Geisinger%20Health%20System_1wfs.pdf
★ 31 ★

III . He a lth IT T o day

spread across four organizations in a single year.36 The lack of interoperability at the network level means 

that physicians do not easily have access to complete records for patients, nor does there exist a “master 

record” that is complete at any point in time. Chapter Six goes into more detail about the economic 

incentives for interoperability and how they can be better structured in the future.

Health Information Exchanges

Data exchange and aggregation are central to realizing the potential benefits of health IT. We have 

already seen the limitations of current systems in this regard. In this section, we describe some nascent 

efforts to create health information exchanges that allow for a degree of local and regional data sharing. 

We also discuss why these exchanges do not provide an obvious or immediate path toward a national 

health IT infrastructure.

Health Information Exchanges are entities often built on a series of often bilateral legal agreements 

between different, often proprietary information systems to be able to share certain kinds of data. Many 

HIEs were developed for the purpose of aggregating health measures at the community level, such 

as those supported by the Robert Wood Johnson Foundation (RWJF) in its Aligning Forces for Quality 

initiative.37 Within this RWJF-funded group and in other instances, these HIEs have been termed regional 

health information organizations (RHIOs). Originally conceived in response to the fact that physicians, 

hospitals, insurers, and other healthcare entities have been reluctant to share data beyond their corporate boundaries, they are typically state or regional entities set up to facilitate health information 

exchange in a region or market area. Their primary responsibility historically has been to establish “trust 

relationships” among these entities in order to enable the broadest possible health data exchange. 

They also facilitate the governance, data-sharing agreements, scope, technology, and financial models 

needed to support that exchange.

Conceptually, HIEs might be considered the mirror image of the enterprise EHR model. Their purpose is 

to locate all currently available electronic information on a patient from any source, in that community 

or region, and present it in an integrated format to any physician who is authorized to view it. Current 

electronic sources for these data are national and regional laboratories, pharmacies, and clinical claims 

data. The physician sees, therefore, information from other physicians caring for their patient, records 

on medications, lab test results, and, as it is made available, copies of hospital discharge summaries and 

eligibility and claims status. However, HIEs have been limited by the administrative burdens of obtaining 

data-sharing agreements at every practice and every hospital or nursing home. They also have been 

hampered by a lack of financial incentives to develop more coordinated and efficient use of resources 

(including information resources), as described later in this chapter. In addition, the level of clinical detail 

in these contractual agreements does not match the richness of information available from a clinical 

record. Nevertheless, they do provide the treating physician with the information that generally is most 

important to know about a patient, which can make a very big difference in patient outcomes. As regards 

privacy and security, HIEs demonstrate the reluctance of providers to share data with users they do not 

know—generally, users outside the communities in which providers reside.

36. Pham, H. H., D. Schrag, A. S. O’Malley, B. Wu B, and P. B. Bach. 2007. Care Patterns in Medicare and Their 

Implications for Pay for Performance. New England Journal of Medicine, 356(11):1130-1139.

37. Robert Wood Johnson Foundation. Aligning Forces for Quality. See http://www.forces4quality.org/welcome
★ 32 ★

T h e Path F o rwa r d

It is important to note that participation in an HIE does not require the physician to participate in any 

proprietary system or to invest in a fully functional EHR. The information summary for a patient can 

be presented through a browser or computer screen “dashboard” in the physician’s office, faxed, or 

deposited into an EHR if the physician has one. Most HIEs provide a portal through which physicians can 

“plug into” an EHR to view information. While ultimately physicians would be expected to exchange, not 

simply view, patient health information, some have argued that HIEs provide an important “on ramp” 

for small practices and independent physicians and their staff to integrate the use of health IT into their 

practices prior to full EHR implementation.

Nevertheless, HIEs have drawbacks that make them ill-suited as the basis for a national health information architecture. One major concern is their durability. As a Federal strategy to support health information exchange, HIEs began in 2005-2007 with a small amount of Federal demonstration funding to states; 

a few also received private grant support. Barriers to their success were substantial, including complex 

governance, the lack of a sustainable business model, continuing provider reluctance to share data, the 

lack of readiness to accept and use data in many organizations and practices, and technical limitations 

in knitting together the many disparate IT systems within most medical communities. As a result, only 

a handful of the original HIEs have managed to establish exchanges that functioned beyond the initial 

funding and limited scope of their initial pilots. Recent legislative support for new state-designated HIEs 

and requirements for information exchange and reporting will clear away a few of these hurdles, but the 

lack of a clear business case for communities to sustain HIEs over time remains a daunting challenge.

Interoperability also remains a concern. HIEs are subject to differing regional and state-based governance 

frameworks. Also, limitations result from a lack of standards to connect multiple proprietary systems. 

There is no guarantee that a patient who has received care in two or three hospitals, has recuperated in 

a nursing home, and is now receiving home care and seeing several different specialists will necessarily 

have all her data available to a treating physician during an office visit or at an emergency event such 

as a fall and hip fracture.

New and Emerging Technologies

A number of new technologies offer significant potential for addressing the challenges described in the 

preceding sections. In this section, we describe three of them: cloud-based EHR products that are suitable for small providers, personal health records aimed at patients, and middleware products designed 

to make legacy systems interoperable. This discussion provides background for the next chapter of the 

report, which explains the technology issues associated with creating a health data platform that can 

facilitate innovation and broader transformation in healthcare.

“Cloud-Based” Technologies for Small Providers

As discussed above, the enterprise solutions used by early adopters are not obvious solutions for the 

smaller healthcare organizations that still make up a large fraction of the U.S. healthcare system. Small 

organizations need low-cost off-the-shelf products and services that can allow them to capture the 

benefits of health IT without having to undergo a costly customization and maintenance process. The 

incentives created by HITECH have already led to substantial innovation and competition in this area.
★ 33 ★

III . He a lth IT T o day

The new products often rely on cloud-based technology that allows software to be run and data to be 

stored on remote servers. The cloud model reduces individual maintenance responsibilities and allows 

even small organizations to benefit from the scale economies in data storage and processing. In this 

model, much of the responsibility for maintaining security is shifted from the small health care organization to the cloud-based service provider. It is also advantageous from the perspective of promoting 

data exchange because data from many organizations are stored and processed in a more uniform way. 

In the future, more extensive cloud-based solutions and services are likely to provide small or underresourced practices with everything from general practice management to advanced decision support 

to analytical tools for public health reporting and basic clinical research.

Personal Health Records

PHRs are patient-controlled repositories of individual health data. They may contain excerpts or summaries of physician records generated from clinical encounters, claims data, lab and imaging results, 

prescription information, and (importantly) patient-entered data. Some PHRs, such as those offered by 

Dossia, Google, and Microsoft are available via the web, while others are software packages that allow 

consumers to store and maintain data on personal computers, mobile phones, or other digital devices. 

PHRs can include functions such as decisions support, appointment making, referral requests, medication refills, and bill paying. Patients also can contribute their own data to the PHR and can determine 

what data will be accessible to clinicians and others.

To date, most PHRs are not standards based, and few support an easy way to transport records among 

different EHR products. However, Google and Microsoft, the two largest vendors of web-based PHRs, 

recently agreed on mechanisms to enable the free exchange of information between their respective 

PHR systems, and others may follow.

An important feature of PHRs is that they are patient controlled and “travel with” the patient. In this 

sense, they represent a route to interoperability. A patient could schedule a visit with a new physician, 

or a specialist, and allow access to his or her PHR. PHRs can also allow increased patient involvement in 

their own healthcare by enabling them to input their own data, research health issues, and potentially 

meet and share information with patients who have similar conditions. Of course, one question about 

this type of technology is how much interest patients will actually have in utilizing these capabilities. 

They seem to have particular promise for patients with chronic conditions.

Data Aggregation “Middleware”

An important feature of today’s environment is that there is relatively little standardization in the health 

data captured and stored by different providers of healthcare services. Although a great deal of data 

already exist in the form of claims data, prescribing information, lab and imaging results, and clinical 

records, much of this data is trapped in different, incompatible databases. The last few years have seen 

the emergence of new middleware products designed to extract data from disparate legacy systems 

and put them in a compatible format. Examples include products and companies such as dbMotion, 

ICA CareAlign, Medicity MediTrust, Microsoft Amalga, Oracle HTB, and Orion Health. These technologies 

can play a role in making the transition from the current environment with little interoperability and 

document-based data exchange to an environment where data can be easily accessed and queried and 

assembled for a broad variety of uses.
★ 34 ★

T h e Path F o rwa r d

The HITECH Act and Shifting Incentives

The discussion so far has highlighted barriers to the effective use of information technology in healthcare. Recent legislation, however, has started the Nation on what is potentially a new trajectory. In 2009, 

the HITECH Act (part of the American Recovery and Reinvestment Act, or ARRA) authorized expenditures on the order of $20 billion (with estimates in the range $9 billion to $27 billion) over five years to 

promote the adoption and use of EHR technologies that would be connected through a national health 

information network. The legislation sets forth a plan for the “meaningful use” of health IT to improve 

the quality of care and enable changes in delivery systems essential to healthcare reform.

The HITECH Act attempts to create incentives for all hospitals and eligible providers, not just those associated with large systems, to adopt and use electronic information. A centerpiece of the Act is to put in 

place strong financial incentives for hospitals and physicians to adopt and meaningfully use electronic 

health records. Physicians who adopt electronic records by 2014 can qualify for Medicare bonus payments of up to $44,000. Beginning in 2016, physicians who have not adopted electronic records will be 

penalized in the form of reduced Medicare reimbursements. Similarly, Medicaid providers can receive 

up to $63,750 over the five years. These payments and penalties depend on the provider meeting the 

requirements for meaningful use.

The definition of meaningful use under HITECH involves both ONC and CMS, but CMS is the principal 

rule-making body since payment will be linked to the reporting of meaningful use measures. The statute leaves CMS broad discretion, requiring only that the definition include e-prescribing, the ability to 

exchange information with other healthcare providers to improve care, and the reporting of clinical quality measures to CMS. With input from several Federal advisory committees, CMS has proposed to phase 

in meaningful use criteria in three stages. Stage 1 criteria, to take effect in 2011, focus on electronically 

capturing health information in a coded format, implementing decision support, sharing information 

with patients, testing the ability to exchange information, and initiating the reporting of clinical quality 

measures to CMS. Stage 2 criteria, to take effect in 2013, would require more robust exchange of information and other high value uses of EHRs. Stage 3 criteria, to take effect in 2015, would require physicians 

to demonstrate the use of EHR technology in ways that improve the outcomes of care. The broad goal 

is to gradually acclimate providers to workflow changes and practice improvement opportunities that, 

ideally, will accompany the adoption of technology.

Responsibility for implementing many other parts of the HITECH Act resides with the Office of the 

National Coordinator, discussed in the introductory chapter. In particular, ONC is responsible for developing policy guidance and a broader future vision for health IT. As we discuss below, it has already begun 

a series of important initiatives to further IT innovation and standards in a variety of areas. It also must 

work together with CMS and other Federal agencies. Indeed, as we now discuss, the division of authorities and responsibilities poses significant challenges.

Opportunities and Challenges for ONC and CMS

In the short time since the HITECH Act was signed, ONC has moved forward on several important 

initiatives. Perhaps the closest to this report is ONC’s recasting of the Nationwide Health Information 

Network project. The NHIN is composed of standards and services that enable secure exchange of 
★ 35 ★

III . He a lth IT T o day

health information over the Internet, combined with a strong policy and trust framework that enables 

organizations to share health information with strong consent and governance to improve healthcare 

delivery while strongly protecting privacy and security. As we elaborate in Chapter Four, we believe that 

this initiative could benefit from a more aggressive focus on a universal, extensible exchange language 

and the development of associated national infrastructure.

The ONC has also moved forward in the important area of clinical decision support and enhancing 

usability of electronic record systems. With AHRQ and the Office of the Secretary, it has established 

a Federal “collaboratory” whose members now number more than 150 across more than 15 Federal 

agencies. The collaboratory has developed an inventory of federally supported CDS efforts, promoted 

sharing of best CDS practices, and identified needs and strategies that have resulted in new projects 

sponsored by ONC, AHRQ, and other agencies. Notable among these new projects is an effort to develop 

generalized representations of important medical logic (rules) that enables these rules to execute in 

the same way even if installed in different vendor systems. The ONC also has awarded a contract to the 

RAND Corporation to advance CDS. Work performed under the contract will advance the Nation toward 

a CDS knowledge repository, including the implementation of best practices and tools for sharing CDS 

interventions. It also will address the “alert fatigue” problem (the problem of too many inessential “popups”) by, for example, identifying those drug-drug interactions that are of highest priority. Another ONC 

initiative aimed at improving EHR usability is a collaboration with the National Institute of Standards and 

Technology (NIST) to develop usability testing programs that may become a part of EHR certification.

In addition to these efforts, ONC administers HITECH funding for Strategic Health IT Advanced Research 

Projects and has awarded four cooperative agreements totaling $60 million. An award to the University 

of Illinois at Urbana-Champaign addresses the challenges of developing security and risk mitigation 

policies and the technologies necessary to build and preserve the public trust as health IT systems 

become ubiquitous. An award to the University of Texas Health Science Center at Houston addresses 

the challenge of harnessing the power of health IT to integrate with, enhance, and support clinicians’ 

reasoning and decision-making, rather than forcing them into a mode of thinking that is natural to 

machines but not to people. An award to Harvard University focuses on the development of a platform 

architecture that will facilitate substitutable applications—enabling the equivalent of the iTunes App 

Store for health—as well as supporting the electronic exchange and use of health information in a 

secure, private, and accurate manner. And an award to the Mayo Clinic College of Medicine focuses on 

strategies to make use of data that will be stored in EHRs for improving the overall quality of healthcare, 

while maintaining privacy and the security of the data.

CMS plays a rather different, yet pivotal, role in the national health IT effort, in large part due to its broader 

centrality in the Nation’s healthcare system. As the Nation’s largest payer, CMS has substantial leverage 

over healthcare providers. For example, it is often argued that the fee-for-service payment system used 

by CMS tends to reward volume over patient-centered goals like coordination and personalization. 

As noted above, some of the leading adopters of health IT, such as Kaiser and the VA, are systems with 

very different financial structures. Recent healthcare legislation (the Patient Protection and Affordable 

Care Act, or PPACA) supports many initiatives to reform healthcare payment and to advance CMS 

projects such as Medical Homes and Accountable Care Organizations, which aim to create incentives 

for coordination and more efficient care. As we discuss in Chapter Six these types of innovations can 

significantly complement health IT efforts.
★ 36 ★

T h e Path F o rwa r d

Even more directly related to EHR adoption and use, CMS exercises substantial influence over the type 

of data that providers must collect. For instance, payment reforms based on quality of care measures 

require providers to collect and report these measures. This type of data plays a key role in current 

attempts to define meaningful use, where the idea is to create consensus “measures of quality,” the collection of which can be translated into requirements for “meaningful use” incentive payments.

One concern with this approach, however, is that most quality measures depend on strict specifications 

that limit the flexibility to describe complex care coordination and functional outcome goals. Indeed, at 

this point, most are related only to individual specific conditions. The reason for this is that many of the 

validated, existing quality measures reflect medicine’s traditional focus on treating particular illnesses, 

rather than on care coordination and health maintenance. Furthermore, most EHRs were designed 

around billing codes, not around rich clinical information that would give a more patient-centered 

view of the context and the true outcomes of care, especially as it occurs over longer periods of time. 

Legislation allows the Secretary of HHS to approve alternative pathways for these CMS payments. Thus, 

if more robust clinical data were available and easier for a sophisticated system to gather and report, 

the use of these data ought to be encouraged.

A second concern is the ability of CMS to receive and process any complex forms of clinical data. The 

historically underfunded IT infrastructure of CMS has not kept up with the constant new legislative 

demands for new programs, especially those requiring quality-of-care data for numerous value-based 

purchasing programs. The culture and structure of CMS, and the demanding time frames of each legislative mandate, have led to multiple separate data platforms and different administrative approaches to 

each of them. Thus, even within CMS, it is not currently possible to aggregate data, and (for example) 

physicians are required to double-enter specific codes to be eligible for quality incentive payments. 

Through certification standards for EHRs, ONC is trying to require that EHR vendors supply a short cut 

for physicians to do this, but even if this occurs, the specific data elements will not provide a full clinical 

picture of patient care, and will therefore provide limited constructive feedback to providers about areas 

for improvement and about the value of the aggregated data.

CMS has not been able to invest in the infrastructure needed for the enormous scope of its growing 

database and quality-of-care requirements. For example, a 2002-2003 data modernization plan that 

would integrate data across CMS programs was not funded until 2006, and now proceeds only slowly 

and incrementally. CMS recognizes that this work is far from complete. In planning stages, CMS has high 

level concepts for a transformed and modern payment system and an Enterprise Data Environment that 

could, if appropriately implemented, contribute to the goals of this report. However, lacking funding, 

implementation work has been stalled. Congress now recognizes that CMS must upgrade its own IT 

systems in order to handle clinical and other performance information and to ensure program integrity, 

and it has begun to authorize these important upgrades. Notably, PPACA charges CMS to accelerate 

work on the CMS Integrated Data Repository to incorporate into the model data from all Federal health 

programs. It also directs CMS to enter into data sharing agreements with the Department of Defense, 

the VHA, and the Social Security Administration.

While we have not investigated these issues further, it seems likely to us that a complete overhaul of 

CMS’s IT infrastructure will be needed in the foreseeable future, not because of future health IT requirements but simply for it to comply with existing legislative mandates. The National Research Council has 
★ 37 ★

III . He a lth IT T o day

recently begun work on a study of the CMS information system capability, with a preliminary report 

due by December 2010 and a final report due at the end of 2011. Because CMS’s operational mission of 

payment processing must proceed without interruption, and because it is starting from a technologically outmoded base, it seems likely that any rebuilding of CMS’s infrastructure will be a difficult and 

lengthy process.

This is an ideal time for the leadership of CMS to assess the overall capability of CMS to take advantage 

of modern computing and to set in place a plan to upgrade systems, break down silos, and reduce 

unnecessary barriers to state-of-the-art computing capability. Federal IT projects frequently incur cost 

overruns and schedule slippages,38 and it will be a significant management challenge for CMS to avoid 

the fate of other government IT modernization and software development projects.39, 40 There is clearly 

a danger that rapid and otherwise achievable progress in health IT, as envisioned by ONC and (even 

more aggressively) by this report, could be forestalled or derailed if it becomes tied to CMS’s formidable 

IT challenges.41 This must be avoided.

Conclusion

The state of health IT today can be summed up as a mix of “the good, the bad, and the ugly.” This diversity, and especially the fact that perhaps 80 percent of physicians still do not use electronic records at all, 

except possibly for billing functions, creates a dilemma. Given the difficulty of bringing the healthcare 

system forward into the computer age, should we focus on small incremental steps? Or, having seen 

the remarkable adoption rates and advances of Internet-based technologies in other sectors, should 

we push for a more radical advance that risks leaving some providers behind?

Fortunately, there is a bridge between these two extremes. It is the fact that the Internet-based technologies create a platform for “disruptive innovation,” meaning innovations that upset the status quo and 

can broadly expand markets. Cloud-based technologies and PHRs are potential examples of disruptive 

technologies in health IT. These types of technologies might allow the 80 percent of physicians who 

are non-digital to leapfrog some of the existing limitations of EHR systems directly into more modern 

technologies. Indeed this is precisely what we want to happen, and it is a direction in which ONC and 

CMS could concentrate their efforts.

38. GAO. 2009. “Social Security Administration: Effective Information Technology Management Essential for Data 

Center Initiative,” GAO-09-662T.

39. See, for example, GAO, 2008, ”Information Technology: Agencies Need to Establish Comprehensive Policies to 

Address Changes to Projects’ Cost, Schedule, and Performance Goals,” GAO-08-925; GAO, 2008, “DOD Business Systems 

Modernization: Progress in Establishing Corporate Management Controls Needs to Be Replicated Within Military 

Departments,” GAO-08-705; and GAO, 2008, “Environmental Satellites: Polar-Orbiting Satellite Acquisition Faces Delays, 

Decisions Needed on Whether and How to Ensure Climate Data Continuity,” GAO-08-518.

40. Elm, J.P., Goldenson, D., El Emam, K., Donitelli, N., and Neisa, A. 2008. Survey of Systems 

Engineering Effectiveness—Initial Results. Carnegie Mellon University/SEI, CMU/SEI-2008-SR-034, at 

http://www.sei.cmu.edu/library/abstracts/reports/08sr034.cfm 

41. Kibbe, D. C. 2010. Should Doctors Reject the Government’s EHR Incentive Plan? Family Practice Management,

17:8.
★ 38 ★

T h e Path F o rwa r d

In setting up a roadmap for how we might move in this direction, it is useful to specify a clear set of 

mid-term goals. These should include:

1. Universal access by clinicians and patients to the current frontier of EHR functionality.

2. A robust platform for developers to create user interfaces, decision support, storage, and archiving 

services that will be broadly available to end-users and will not require major capital investments.

3. Seamless, user-transparent, cross-organizational data exchange.

4. Innate, strong privacy protection on all data, both at rest and in transit.

5. Efficient means for the aggregation of de-identified data for public health and research purposes.

As already indicated in Chapter Two, we believe that there is at least one technical approach that can 

achieve all of these requirements. The approach that we favor, based on the exchange of metadatatagged data elements, is described in detail in the next chapter.

This chapter’s bottom line: Despite success stories from some early adopters, the current level of IT 

use in healthcare is uninspiring.42 Recent initiatives, particularly by ONC, are shifting the incentives 

and may stimulate substantial EHR adoption. But a substantial advance and concentrated focus are 

needed to develop a scalable, national health IT infrastructure. New technologies can assist in taking 

the required steps.

42. There are exceptions, however. For example, in Massachusetts, 50% of all providers have comprehensive EHRs, 

and 33% of all medications are electronically prescribed.
★ 39 ★

IV. Technology for an Integrated 

Health IT Ecosystem

Introduction

The current health IT landscape is dominated by enterprise systems based on proprietary formats. These 

systems lack ability to communicate and aggregate health information in the ways needed to serve 

patients, doctors, and researchers. The systems have been designed primarily to enable point-to-point 

communication of administrative information rather than clinical data. Importantly, the nature of current 

systems makes it difficult for innovators to develop new tools to improve the use of health information. 

There are few policies or governance models to drive innovations, such as research, advanced clinical 

decision support, or benchmarking. In short, there is no fuel for an ecosystem of economically selfsustaining healthcare innovation.

The overarching goal is to have a national health IT ecosystem in which every consumer, doctor, 

researcher, and institution has appropriate access to the information they need, and in which these 

groups are served by a vibrant market of innovators. At the end of the previous chapter, we listed a 

set of technical and market-related requirements for enabling this overarching goal. Here, we look at 

several possible technological approaches and describe in some detail an approach that, we think, has 

the greatest likelihood of rapid forward progress.

Earlier Models for Enabling Data Exchange

Over the last 20 years or so, an era dominated by vertically integrated, proprietary EHRs, one approach 

has been to seek to create standardized health records. Because the medical system has long relied 

on filling in paper records, it was natural to assume that exchange or reuse of data would be impossible without establishing standardized record formats that would be comparable across providers. 

However, we believe that any attempt to create a national health IT ecosystem based on standardized 

record formats is doomed to failure. First, there is too much diversity and incompatibility for any kind of 

a priori standard to emerge. With so many vested interests behind each historical system of recording 

health data, achieving a natural consolidation around one record format for any particular subset of data 

would be difficult, if not impossible. Second, systems based on fixed records are inherently limited in 

their functionality. Consider, for example, a health record in which all types of blood test information are 

always stored. When a new type of blood test is developed, it is difficult to expand the record to include 

it. Moreover, it is difficult to exchange only parts of such an electronic record according to a patient’s 

choice (for example, blood glucose measures but not HIV status).

A second approach to health IT, spurred by the emergence of the Internet, has focused on serviceoriented architecture (SOA) as a way to solve the problems inherent in standardized record formats. SOA 

essentially involves using software policies, practices, and frameworks to enable one user to access sets 
★ 40 ★

T h e Path F o rwa r d

of “services” on another party’s computers and data.43 For example, two hospitals, using two different 

systems, might create bilateral arrangements that enable them to run “services” on each other’s systems 

to execute transactions or access data. The approach could be expanded to small networks, and even 

to networks of networks.

As an analogy, one might consider two libraries with completely different systems for filing books. Each 

library’s users have no idea how to find books in the other library. But if each library sets up a “service 

desk” with an actual librarian, then the other library’s users can get what they need by lining up at the 

service desk for assistance. This analogy also makes clear one of the big limitations of SOAs, namely 

scalability. A library’s own users can all be looking for books on the shelves at the same time; but users 

from the other library must queue for the librarian “service.”

There have been extensive efforts to implement the above approaches in local and regional HIEs that 

seek to connect multiple organizations. By 2009, there were more than 190 HIE initiatives in the United 

States—although only about one-third were fully operational.44 These HIEs report lower costs, improved 

outcomes, reduced staff time spent on process-oriented work, and increased data exchange—demonstrating the benefit of health information exchange. But despite these benefits, these approaches fall far 

short of what is needed. Most HIEs are based on standardized record formats or integrated care systems 

that cannot readily scale. Others link a range of proprietary systems. If a patient moves between two 

hospitals even within an HIE, critical tests done at the first hospital must often be repeated.

Most HIEs face the administrative burden of requiring adoption of legal agreements at each provider 

organization to share data. In addition, HIEs that began as pilot projects do not appear to be spreading 

or scaling up beyond their initial scope because they were launched without significant attention to 

long-term business models, a problem that the meaningful use incentives may not overcome. Most HIEs, 

moreover, are not currently interoperable across regions and markets to other HIEs, and thus remained 

closed and proprietary even as patients seek and require care outside their confines.45 Because each HIE 

system is different, there is little incentive for entrepreneurs who make middleware and other innovative 

tools to serve this marketplace.

While such systems can surely be incrementally improved, we believe that such approaches will not 

solve the fundamental need for data to be universally accessed, integrated, and understood while also 

being protected. In a sector as fragmented and rapidly evolving as healthcare, we believe it is impossible to build a national implementation of SOA solutions and directories that could be used and scaled 

indefinitely into the future. (To draw a loose analogy, the approach is like trying to enable free trade 

among hundreds of entities by negotiating a huge number of bilateral trade agreements. Or it is like 

trying to promote dialog among speakers of a thousand different languages by training one million 

translators, each knowing a pair of tongues, instead of enabling them to speak a common language. 

The idea is laudable but impractical.) Moreover, the approaches will not overcome the barriers to entry 

for innovators wishing to develop new solutions. We believe that a steady supply of such innovators in 

the ecosystem is essential for increasing quality and decreasing cost.

43. Sprott, D., and L. Wilkes. January 2004. Understanding Service-Oriented Architecture, Microsoft Architect 

Journal.

44. eHealth Initiative. 2009. Migrating Toward Meaningful Use: The State of Health Information Exchange.

45. However, a few interesting examples of HIEs working across state boundaries are starting to emerge.
★ 41 ★

IV. T ech n o l o g y fo r a n Inte g r ated He a lth IT Eco s y stem

Universal Exchange Using Metadata-Tagged Data Elements

The best way to achieve a national health IT ecosystem is to ensure that all electronic health systems 

can exchange data in a universal exchange language. The systems themselves could be designed in any 

manner desired — they could accommodate legacy systems that prevail or new recordkeeping systems 

and formats. The only requirement would be that the systems be able to send and receive data in the 

universal exchange language.

We believe that the natural syntax for such a universal exchange language will be some kind of extensible markup language (an XML variant, for example) capable of exchanging data from an unspecified 

number of (not necessarily harmonized) semantic realms. Such languages are structured as individual 

data elements, together with metadata that provide an annotation for each data element.

With some risk of oversimplifying, let us give an example. Imagine that an elderly patient has lived in 

several different cities and, over the years, has had mammograms done at various hospitals and clinics. 

Her physician now needs to retrieve images of her breast tissue over the previous decades to determine 

whether a current lump is of concern. In a health IT ecosystem where tagged data elements make up a 

universal language, the data elements the doctor could retrieve about this patient would include the 

mammograms themselves from all of the various places the patient has sought treatment regardless of 

provider network, geographic location, or whether the patient remembers them. The physician would 

be able to securely search for, retrieve, and display these privacy-protected data elements in much the 

way that web surfers retrieve results from a search engine when they type in a simple query.

What enables this result is the metadata attached to each of these data elements (mammograms), which 

would include (i) enough identifying information about the patient to allow the data to be located 

(not necessarily a universal patient identifier), (ii) privacy protection information—who may access 

the mammograms, either identified or de-identified, and for what purposes, (iii) the provenance of the 

data—the date, time, type of equipment used, personnel (physician, nurse, or technician), and so forth.

Most of the time, the metadata will not be needed by the physician; this information will be invisibly in 

the background. Occasionally, as in the case of a false positive or false negative in a particular image, 

the physician may want to dig deeper: The metadata will be there.

The metadata will also be important for researchers who may have access only to de-identified data. 

They might use it, for example, to determine whether a certain type of imaging equipment for breast 

cancer is yielding excessive numbers of wrong diagnoses. This could result in improvements or recalls 

of particular devices and improvements in software.

Data Element Access Services

In the example above about retrieving multiple mammograms, we assumed more than simply a universal exchange language. We also assumed the existence of certain national infrastructure for finding

health data, and for controlling access to it. (Importantly, though, we have not assumed a national 

repository for storing health data, which would be a more difficult and politically problematic issue.) 

We call this infrastructure, collectively, data-element access services. The services would include those 
★ 42 ★

T h e Path F o rwa r d

associated with crawling, indexing, security, identity, authentication, authorization, and privacy. As 

proposed, these DEAS and their components would have no right to use the data being exchanged; in 

fact, they would probably not even see the data.46Rather, they would act much like today’s web search 

engines, but with additional levels of responsibility for exposing only those data elements authorized 

by applicable privacy rules and policies (including a patient’s persistent privacy choices) and only to 

authorized, authenticated users. A patient would have the right to restrict the types of data elements 

indexed at all, or could opt out of the DEAS completely (although such a choice might negatively impact 

that patient’s future care). We discuss privacy protection and security in more detail in Chapter Five.

Today, when a user views a web page, the data that make up the various parts of the page (text, images, 

ads, audio, video, etc.) are dynamically aggregated in real time from numerous computers in a range 

of physical locations and are then presented to the user as a single logical entity: the web page being 

viewed. The individual elements are not routed through any central server or repository. Rather, a set 

of access services enables the browser to query many distant computers simultaneously. Similarly, for 

health IT, a query submitted to the data-element access services would result in the seamless, dynamic 

aggregation of all the data requested. For example, a doctor’s request for patient information could 

involve an indexing system identifying all the physical locations on the network of the data; real-time 

aggregation of the data; and analysis, translation, and presentation by the software application that 

the doctor is using.

The health IT ecosystem we envision does not require the existence of a uniform patient identifier. 

Instead, it could use associations of intrinsic patient-related information to link the appropriate data to 

specific patients. This method is used now to create patient record locators within local closed systems 

and regional health exchanges, but as employed today, it can be plagued by human error.47 Since an 

automated system can use many more than the two factors (such as name and birthdate) now often 

used, it can be correspondingly more accurate.48 Indeed, “identity resolution” is an established technology, with commercial offerings available.49 For greater accuracy and convenience in the record-keeping 

associations, some patients (e.g., those named “John Smith”) might elect to index their records by an 

email address or a reference to a personal health record account, but this would be optional.

How should DEAS be brought into existence and operated? There are several viable options: Individual 

states (or self-formed groups of states) could establish and operate DEAS. Federal funds might be used 

in the manner of a “race to the top,” to support the best state’s proposals, or to create an additional 

interoperating and intercommunicating DEAS for use by Medicare providers. DEAS could be established 

in large health delivery networks (including those operated by the Federal Government, such as the 

Veterans Administration). They could emerge from a more aggressive push toward achieving interoperability among existing HIEs. Or, their growth could be left to the private sector, perhaps seeded by some 

start-up funds in response to requests for proposals.

46. As a privacy choice, a patient might choose to hide even the existence of certain data from the DEAS, for 

example the fact that he/she had received treatment at a particular facility. In making such a choice, the patient would 

understand that his/her own future physicians would be unaware of this data, with possible negative effect on their 

ability to deliver the best care. 

47. World Health Organization 2007“Patient Identification”, Patient Safety Solutions, vol. 1, solution 2, at 

http://www.ccforpatientsafety.org/common/pdfs/fpdf/presskit/PS-Solution2.pdf 

48. Markle Foundation 2005 Linking Health Care Information: Proposed Methods for Improving Care and 

Protecting Privacy, at http://www.connectingforhealth.org/assets/reports/linking_report_2_2005.pdf

49. See, e.g., J. Jonas, 2006, Threat and Fraud Intelligence, Las Vegas Style, IEEE Security and Privacy.
★ 43 ★

IV. T ech n o l o g y fo r a n Inte g r ated He a lth IT Eco s y stem

As a matter of engineering, fewer DEAS providers is better, since communication between DEAS in 

response to queries is an additional overhead, but this must be weighed against socio-technical, governance, and policy forces favoring a more distributed network of DEAS.

In any case, all DEAS would need to be interoperable and intercommunicating in conformance to a single 

Federal standard, and would need to be audited for compliance with privacy and security policies. In 

response to a HITECH mandate, ONC has already begun a process for establishing governance of the 

NHIN.50 This process might also explore how best to operate DEAS.

Advantages of the Tagged Data Element Approach

Because of its multiple advantages, we advocate a universal exchange mechanism for health IT that is 

based on tagged data elements in an extensible markup language. If there were another equally good 

solution, it should also be considered; we have collectively been unable to think of one.

Tagged data elements can be combined for a single patient to produce the equivalent of an EHR, and 

organized around the needs of that patient at the time of care. At the same time, the data can be analyzed 

and combined with links to other information to provide physicians with clinical decision support, delivering patient-specific information to their fingertips to make the best possible decision for a patient given all 

of the information available. Tagged data elements from aggregated populations can also be combined 

to analyze comparative effectiveness of aspects of healthcare and improve efficiency and quality.

Since the language of metadata-tagged data elements is extensible, not fixed, it can itself evolve in 

response to the development of new applications and new medical knowledge. As already mentioned, 

extensible exchange languages exist today and are already used within health IT in specialized niches—

and are used widely in other sectors. A main finding of this report is that the time is ripe for such a 

language to be declared as a universal exchange language for health IT, and that doing so will catalyze 

a large number of immediate and longer term advances.

Tagged data elements can be extracted by special software (known as middleware) from existing clinical 

systems. Or they can be produced from enhanced versions of those systems, or by completely new and 

innovative applications. In this way, all data could be exchanged among all systems no matter the origin 

or internal record formats of the data, and without the necessity of replacing existing legacy software.

A universal data exchange language can scale up to any level. It can allow retrieval by patients and 

physicians of information from different providers, in different parts of the country, to improve safety 

and coordination. It can deal with the diversity and complexity of both the underlying business and 

clinical systems. New types of data and associated metadata can be added at any time, since new data 

elements do not have to fit into a particular format. Data can be converted to whatever form best supports their intended use, from clinical diagnosis to medical research. This approach can create a fully 

interoperable, less costly, more effective national health IT ecosystem.

The availability of a universal exchange language can dramatically accelerate the entry of third-party 

innovators, because they can create applications that rely on uniformly described data elements and 

can access a larger market. These new applications could include cloud-based subscription services for 

individual doctors, small healthcare practices, long-term care facilities, large practices, and hospitals to 

50. Government Health IT. June 25, 2010. ONC to issue “rules of the road” for NHIN Exchange. See 

http://www.govhealthit.com/newsitem.aspx?nid=74064
★ 44 ★

T h e Path F o rwa r d

handle practice management (e.g., registration, scheduling, and billing); sophisticated medical systems 

(e.g., decision support, integrated lab ordering, medication management, allergy tracking); integrated 

medical-image management; integration engines to facilitate data exchanges with personal health 

records and other types of EHR in the cloud; and population health management (e.g., analytical tools 

for public health reporting, clinical research, and outcomes analysis).

The approach that we describe is consistent with existing market trends. Innovative companies are 

emerging that can access data from existing records and rearrange, store, and exchange the data as 

desired. Other companies are offering advanced software applications, information, and other services 

via the Internet. PHRs allow patients to store and monitor all of their health information and research 

their conditions using the full range of electronic resources.

The approach described does not require the creation of a uniform patient identifier or a national 

repository for healthcare data. The data, protected by strong encryption, can be stored on existing 

legacy systems or in the rapidly evolving “cloud” of distributed data stores.51 Data involving a particular 

person can be stored in many different places and then aggregated, just as individual web pages are 

constructed from elements stored on many different computers. Specialized and secure search engines 

can crawl and index the metadata while actual access to the underlying data remains constrained by 

privacy protections.

This system can provide much greater security and privacy protection than can the current system. The 

attached metadata would describe the use and access provisions of the data, in accordance with law, 

policy, or the patient’s privacy preferences where applicable. For example, in a circumstance where 

consumers give their consent for particular uses of their data and prohibit other uses, this information 

would be encoded in the metadata. For example, privacy restrictions embedded in the metadata could 

permit a physician to send a pharmacist the data required to fill a prescription and permit de-identified 

data to be used for clinical research, but restrict other uses of the data. Privacy considerations are discussed in greater detail in the following chapter.

This chapter’s bottom line: A universal language for the exchange of health data is needed. An extensible markup language, where individual pieces of data can be tagged with context-setting metadata, 

is a straightforward solution and is superior to other proposed architectures.

51. Currently installed systems that do not encrypt data “at rest” can be upgraded evolutionarily over time, but 

would be required to encrypt data “in transit” when it is shared with another system.
★ 45 ★

V. Privacy and Security Considerations

Introduction

A key advantage of the tagged data element approach is that it will allow a more sophisticated privacy 

model, one where privacy rules, policies and applicable patient preferences are innately bound to each 

separate tagged data element and are enforced both by technology and by law. In this chapter, we 

briefly review the present situation as regards the privacy protection of medical information, and then 

explain the technology building blocks that will enable better approaches.

The Present Framework

American ambivalence about integrating health IT into the healthcare system is rooted in significant part 

to concerns about privacy and security. Even though a large majority of Americans believe that electronic 

health records will improve the coordination and quality of care,52 many Americans also believe that 

there is a reasonable likelihood that unauthorized users will view such records.53 For example, a 2006 

survey for the Markle Foundation found that 88 percent of Americans believe digital records will reduce 

the number of unnecessary or repeated tests and procedures they undergo.54 However, this survey 

also found that 80 percent of respondents were “very concerned” about theft or fraud, 77 percent were 

equally concerned about use of their records for marketing purposes, 56 percent were worried that 

employers would see their health records, and 53 percent expressed concerned that insurers would, too. 

A solution to this perceived privacy problem must underpin any overhaul of the medical-data ecosystem.

Concern about the privacy of medical data is predicated on a range of factors. First is the potential for 

discrimination—in access or economic terms—that might influence health insurance or employment. 

Second, for some consumers there is a sense that medical data are “different” than other personal data. 

From this perspective, financial data involve something an individual has, whereas medical data involve 

what an individual is. Third, the use of personal medical data by others is potentially exploitative. People 

may be comfortable with having their de-identified data used for beneficial purposes like disease 

research, but not if they believe that commercial interests may use such information to try to sell them 

something or otherwise exploit it. Finally, Americans harbor deep-seated fears about possible government access to any personal data.55

The HIPAA Privacy and Security Rules, which went into effect in 2003, establish a Federal floor of protections for health information. The Privacy Rule, as amended by HITECH, regulates the use and disclosure 

of identifiable health information held by health plans, including employer-sponsored; health clearinghouses; and health care providers who engage in certain administrative electronic transactions (such as 

52. NPR, Kaiser Foundation, and Harvard School of Public Health. March 2009. Cost, Privacy Top Health Care 

Concerns.

53. Electronic Privacy Information Center. Medical privacy public opinion polls.

54. Lake Research Partners and American Viewpoint. November 2006. Survey Finds Americans Want Electronic 

Personal Health Information To Improve Own Health Care.

55. McGraw, D., J. X. Dempsey, L. Harris, and J. Goldman. 2009. Privacy as an Enabler, Not an Impediment: Building 

Trust into Health Information Exchange. Health Affairs, 28(2):416-27.
★ 46 ★

T h e Path F o rwa r d

submitting claims electronically (collectively called “covered entities”) and their business associates.56

In general terms, the Privacy Rule permits, but does not require, the disclosure of identifiable health 

information for treatment, payment and various health care operations without the express written 

permission of the patient. The Rule also permits the disclosure of identifiable health information for 

research and public health without patient permission, as long as a number of other specific, detailed 

conditions are met. As a Federal floor of protection, the Privacy Rule does not supersede state laws 

that are more stringent, such as those that require patient consent to exchange health information for 

treatment purposes.

The Need for Strong, Persistent Privacy Protections 

To build and maintain the public’s trust in health IT requires comprehensive privacy and security protections that are based on fair information practices and set clear rules on how patient data can be accessed, 

used and disclosed, and that are adequately enforced. An individual’s right to have some meaningful 

choice in how their information is shared is one important component of a comprehensive set of protections. Where such choices are provided, either in law or by policy, they must be persistently honored.

A patient cannot make meaningful privacy choices unless he or she understands the flows and uses 

of information and can therefore make informed choices. That is not the reality today. In practice, 

the current consent model mandated by HIPAA rarely allows fully informed choices. HIPAA allows 

many common disclosures (for example, for treatment, payment, and healthcare operations) without 

any consent at all. Some other disclosures are allowed unless the patient specifically opts-out. Some 

particular transactional flows of data require patient approval, but patients have little real information 

about those flows or the uses to which they will be put. As seen by the patient, HIPAA protection is 

often little more than “sign here to acknowledge that you understand your rights under HIPAA,” which, 

of course, few patients do.

Some provisions of HITECH are intended to remedy this situation and give patients more control over 

the flow of their health information. For example, patients now have the right to restrict a provider from 

disclosing identifiable health information to a health plan when the information relates to treatment 

for which the patient has paid out of pocket. In general, however, patients have limited control over 

the way their health information is shared.

An exchange language based on tagged data elements allows for privacy rules and policies to be more 

effectively implemented; it also allows for more finer grained individual privacy preferences to be 

more persistently honored57, and it can potentially allow patients to make better informed, persistent 

privacy choices not just in the rush of a medical encounter but reflectively and in an informed manner. 

For example, in circumstances where patient consent is required by law, policy, or practice, as part of 

enrolling with a primary care physician, a new patient might be asked questions like these: Do you want 

your primary care physician to be able to see your complete medical record, including from other places 

that you have been treated in the past? Do you want this to be automatic for places where you may 

be treated in the future? Do you want your physician to be able to consult with other physicians and 

56. 45 CFR Parts 160 and 164. Summaries at http://www.hhs.gov/ocr/privacy/hipaa/understanding/index.html

57. See, for example, Health IT Policy Committee, Privacy and Security Tiger Team, transcript of Consumer Choice 

Technology Meeting (June 29, 2010), at 

http://healthit.hhs.gov/portal/server.pt?open=512&mode=2&objID=2833&PageID=19477
★ 47 ★

V. P r i vacy a n d Secu r it y Co n s i d er ati o n s

share relevant records with them at his or her discretion? If you are brought to a hospital emergency 

room, do you want them to be able to access your medical records without asking you? What if you 

are unconscious? Do you have a personal health record, and do you want your medical information 

to be automatically synchronized with it? Are there parts of your health history that you do not want 

disclosed to another doctor, such as treatment for mental illness? Do you want to be notified (or have 

your physician notified) when research using your data suggests new options for your own care?

There are pros and cons to the different possible answers to the questions in this example, and patients, 

in consultation with their physicians or other counselors, must understand these. For example, a physician must be able to know when a patient has chosen to withhold data and may not ethically be able 

to treat a patient who withholds medically necessary information. As a general principle, the more 

information that patients consent to make available in clinical situations, the more likely they are to 

benefit from better diagnosis and treatment options, especially those that may depend on their specific 

personal histories or genetic makeup.58 Similarly, in sharing their information for research purposes, 

patients participate in a social contract that benefits everyone in general, but may also (with the help of 

an enabling health IT infrastructure) benefit themselves directly. Privacy and security protections need 

to be seen as enabling population research, not unnecessarily limiting it.

While face-to-face counseling on privacy choices should be available whenever choice is either required 

by law, policy or practice, most patients will probably educate themselves on the issues and make privacy 

choices through a web interface, where they will also be able to change their choices at any time. An 

important point is that, when patients have a meaningful opportunity to choose, a patient’s choices will 

be persistent, that is, continuing until changed. Most patients ideally will have elected privacy choices 

at a time when they are healthy and competent. This is truer to the principal of informed consent than 

is a rushed signature at the time of a medical emergency, or when the patient’s physical or mental 

competency is compromised.

Deleterious Effects on Medical Research and Care

The HIPAA Privacy and Security Rules, as well as sometimes more stringent state laws and regulations, 

were intended to enhance the privacy of health information. However, they have had the unintended 

consequence of freezing its exchangeablity. The complex mandates of both HIPAA and state laws and 

regulations leads organizations to equate protection to sequestration, with little or no provision for 

either access based on roles (for example, the needs of an emergency room physician) or for legitimate 

secondary uses of data (for example, epidemic tracking), although HIPAA itself actually does allow 

disclosures in many such cases.

Even before HITECH, some organizations’ interpretations of HIPAA had proved detrimental to medical 

research and, potentially, care. For example, a 2005 study by the University of Michigan found that 

implementation of the HIPAA Privacy Rule was followed by a drop from 96 percent to 34 percent in the 

percentage of follow-up surveys completed by patients being monitored after a heart attack.59 The report 

concluded that the Privacy Rule “significantly decreasesthe number of patients available for outcomes 

58. The need to have an unbiased second opinion may be an exception to this principle.. Henriksen K. and H. 

Kaplan, H. 2003. Hindsight bias, outcome knowledge and adaptive learning Quality and Safety in HealthCare 12:ii46-ii50,

59. Armstrong, D., E. Kline-Rogers, S. M. Jani, et al. 2005. Potential Impact of the HIPAA Privacy Rule on Data 

Collection in a Registry of Patients with Acute Coronary Syndrome. Archives of Internal Medicine, 165:1125-1129.
★ 48 ★

T h e Path F o rwa r d

research and introducesselection bias in data collection for patient registries.” Similarly, a 2006 study by 

the U.S. Government Accountability Office found that healthcare providers were “uncertain about their 

privacy responsibilities and often responded with an overly guarded approach to disclosing information 

to ensure compliance with the Privacy Rule.60

It seems likely that the modifications to HIPAA enacted in Subtitle D of the HITECH Act—in particular 

those that require covered entities to track all disclosures to associates61—will further stifle innovation 

in the health IT field while offering little additional real-world privacy protection. The limitations of 

HIPAA and the HITECH provisions (sometimes referred to as HIPAA II) should be reformulated so that 

they ensure both patient privacy and patient benefit from medical research, in a world where medical 

data are increasingly in electronic form and where there is a growing need for real-time or near-real-time 

aggregated data to improve healthcare. A recent report from the Institute of Medicine suggests that 

these policies need a major overhaul to enter the electronic age.62

Data Security: How Good Is Good Enough?

An exchange language based on tagged data elements enables a fine-grained model for addressing 

privacy, including honoring a patient’s privacy preferences. However, this model is only as good as the 

level of security applied to the data itself. If an unauthorized user can compromise data security, and 

not get caught in doing so, then he can also compromise any patient privacy model.

In data security, the perfect is often very much the enemy of the good. It is important that criteria for 

electronic security measures not be overspecified to the point of impossibility. A useful point of comparison is the degree of security inherent in old-fashioned paper records stored in folders in a medical 

file room. These paper records are completely secure against large-scale, remote electronic “phishing” 

to sift through the records to find particular nuggets of information. File rooms seem in practice to be 

fairly secure against massive compromises even by physical means: breaking and entering to steal large 

numbers of paper medical files would not be a difficult criminal exploit, but it occurs virtually never.63

By contrast, paper records provide much less protection against unauthorized compromise (e.g., by 

copying) of the medical record of a single, targeted individual. We can infer from publicized cases that 

this happens regularly (for example, in the case of celebrities64). While private investigators cannot in 

most cases obtain a third party’s medical records legally, they appear to have a significant ability to do 

so nonetheless. There is no reason to think that paper records are more secure than electronic records 

in the scenario of targeted individuals, since the exploit is typically enabled by suborning an insider 

with access to both paper and electronic records, or by social engineering (e.g., wearing a doctor’s gown 

and walking into an unattended file room). In fact, paper records lack intrinsic security that is provided 

60. J.F. Wilson. 2006. Health Insurance Portability and Accountability Act Privacy Rule Causes Ongoing Concerns 

Among Clinicians and Researchers. Annals of Internal Medicine 145(4):313-316.

61. Public Law 111-5 (2009), especially Sec. 13405 (42 USC 17935), 

at http://www.hhs.gov/ocr/privacy/hipaa/understanding/coveredentities/hitechact.pdf#page=39

62. Nass, S. J., L. A. Levit, and L. O. Gostin, Eds. 2009. Beyond the HIPAA Privacy Rule: Advancing Research, Improving 

Health Through Research. Washington, DC: National Academy Press. http://www.nap.edu/catalog.php?record_id=12458

63. But see, for example, PI Newswire, “Medical Records Found in DMV’s Dumpster,” June 3, 2010, 

at http://www.pinewswire.net/2010/06/medical-records-found-in-dmvs-dumpster

64. For examples, see “Celebrity Medical Records in Massive UCLA Breach” at 

http://www.huffingtonpost.com/2008/08/05/celebrity-medical-records_n_116968.html, and “Exposed: Clooney’s 

Medical Records” at http://abcnews.go.com/GMA/story?id=3711136&page=1
★ 49 ★

V. P r i vacy a n d Secu r it y Co n s i d er ati o n s

by even the most elementary electronic security protections. There is no way to tell if a paper record 

has been read or copied, for example. By contrast, an electronic system with basic authentication (by 

username and password) and auditing (of file accesses) preserves a record of who accessed what.

We can draw several conclusions: A health IT infrastructure needs to provide significantly better security 

than traditional paper records in all respects. It must be designed with very strong technical protection 

against remote, bulk attacks that compromise large numbers of records, because paper records do not 

have this vulnerability. The security of a single individual’s information needs both technical protection 

and also protection by regulation and criminal law. Technical protection alone cannot prevent the 

suborning of otherwise authorized individuals, but it can greatly raise the bar by making them likely 

to get caught.

In today’s healthcare sector, there is an astounding range of security practices in handling electronic 

data, ranging from excellent to poor. Importantly, there is little consistency in security practices. Sloppy 

practices have led to system failures at multiple levels, such as the massive compromise of personal 

data in a stolen laptop computer65 or a burglarized hard disk drive.66 In a well-designed system, as one 

example, it should be technically impossible for any individual to aggregate large numbers of records in 

an exportable format, and there should be multiple layers of real-time auditing to be sure that it is not in 

fact happening. We next turn to the question of whether it is possible to design appropriate protections 

for the privacy of electronic health records.

A Health IT Architecture for 21st-Century Privacy and Security

We believe that a universal exchange language based on tagged data elements will allow the design 

of much better privacy and security protection than currently exists for either paper or electronic systems, for two principal reasons. First, the ability to tag an individual piece of data with privacy-related 

information, as part of its metadata, enhances privacy safeguards. Second, because tagged data element exchange protocols are designed to be efficient for the rapid exchange of small pieces of data, 

it is feasible to use security protocols that involve multiple exchanges of challenge and response. We 

illustrate these points in this and the next subsection.

How would this all work behind the scenes technically? Here we review briefly some of the technologies 

that can be combined to produce a well-designed system for protecting patient privacy, and indicate 

some of the design choices that will need to be made in creating such a system.

Encryption is the basic technology of making data completely unreadable unless it is brought into 

contact with a separate, smaller piece of data called the encryption key. Each piece of data can have its 

own key, or multiple pieces can have the same key. There can be several different keys that unlock the 

same data—for example, one for ordinary use and another (kept somewhere else) for rare emergencies.

A likely design decision would be that all patient information should always be encrypted either when 

stored or transmitted. Encrypting all “data at rest” (stored as on hard disk drives) protects against physical 

65. InformationWeek January 30, 2008. “Laptop Stolen With Personal Data On 300,000 Health Insurance Clients,” at 

http://www.informationweek.com/news/security/showArticle.jhtml?articleID=206100526

66. WBBM Chicago May 27, 2010. “Nearly 200,000 Are Potential ID Theft Victims,” at 

http://cbs2chicago.com/investigations/ID.theft.2.2.1719905.html
★ 50 ★

T h e Path F o rwa r d

data breaches like misappropriation of hardware from healthcare IT data centers. Encrypting data “on 

the wire” (transmitted over networks), and authenticating the endpoints of every network connection, 

help defend against various network attacks, such as eavesdropping and misdirection of sensitive data 

to unauthorized parties.67

Another design decision could be to specify that a key for patient information is never stored (or even 

present) on the same computer system that holds its corresponding patient data. That would enforce 

technically that there be a transaction whenever data are to be used: the data must come from one 

computer system, and the key from another. The two computer systems can be physically distant, and 

managed by different organizations, so as to make insider threats much less likely. Transactions (which 

can themselves be encrypted) can be monitored and audited by a security infrastructure that is also 

independently managed.

Crucially, each encrypted datum carries metadata governing its specific use and access. These metadata 

are inseparable from the data and are inviolable, protected by a digital signature. While metadata are 

themselves likely encrypted (another design choice), their keys are, by design, known to an authorized 

set of secure search engines so that, for example, all the records of a particular patient can be located. 

However, the search engine has no access to the (differently encrypted) actual patient data.

Identity is also a crucial aspect of security. Determining the identity of a principal is commonly called 

authentication. Except for patient-consumers, all of the principals in the health IT system can be 

authenticated using physical credentials (such as smartcards), biometrics (such as fingerprints), and a 

secret such as a password. Requiring two of these three methods, a possible design choice, is termed 

“two-factor authentication.” Credentials could be issued to healthcare professionals by participating 

institutions and medical-certification agencies. Whenever data are accessed, an audit mechanism records 

the actions taken by principals, along with the information used to authorize those actions. Credentials 

can be revoked when necessary.

An authenticated principal has the right to perform actions in the system. Some rights might come from 

the identity of the principal (e.g., a patient has the right to see her records), while others might come 

from the role held by the principal (e.g., an emergency-room doctor has the right to see the medical 

record of an unconscious patient). Determining the rights of an authenticated principal is commonly 

called authorization. In the healthcare security system, a range of designated, authorized roles can be 

pre-consented, and anybody who presents the role credential will get appropriate access for a particular 

situation. This credential does not attach to the individual; it attaches to each specific role. For example, 

when an emergency-room doctor leaves for home, his or her role-based authorization is deactivated.

Finally, an audit mechanism records the actions taken by principals in the system along with the information used to authorize those actions. A secure audit mechanism must provide strong protection so 

that audit records cannot be tampered with or deleted. For example, an audit system must record any 

access, modification, or deletion of a patient’s health records and any changes to the associated authorization policies. In case of an error in a patient’s health record, the audit mechanism would reveal the 

67. While the breach notification requirements of HITECH provide significant incentives for encryption, they do not 

require it. 
★ 51 ★

V. P r i vacy a n d Secu r it y Co n s i d er ati o n s

principal who introduced the mistake and the authorization information for that access. Strong audit 

mechanisms can be implemented using cryptographic and other techniques.68 Patients should have 

the right to review audit records pertaining to their data.

A well-designed combination of encryption, authentication, authorization, and, for research uses, deidentification can yield a health IT infrastructure that is secure, and where all principals are auditable. It 

can have strong protection against bulk data theft (for example, using real-time audit mechanisms on 

top of all the other controls), and be significantly better protected against insider threats to individual 

patient privacy than present paper or EHR-based systems. As already noted, technical security, no matter 

how effective, must also be augmented by administrative, civil, and criminal penalties. Because technical 

measures can never be perfect (especially against insider threats), it is ultimately these penalties that 

deter willful misuse by individuals or negligence by institutions. What well-designed technical measures 

can do is to make data compromises very difficult to perpetrate, and thus very rare.

Privacy Protection of Metadata-Tagged Data Elements

By way of example, let us look somewhat more closely at how the general technologies described 

above might be combined in an infrastructure based on tagged data elements. For the purposes of this 

example we will make an arbitrary set of design choices, not necessarily those that might be made after 

a careful systems study. Suppose that the data elements in question are, as in a previous example, the 

mammogram history of a particular patient, Abigail.

In a first scenario, suppose that Abigail’s physician, Dr. Jones, queries to bring up all of Abigail’s previous 

mammograms. The data element access services (DEAS) described in Chapter 4 first check that Dr. Jones 

has properly authenticated herself to the system and that she is in a role (e.g., primary care physician) 

that allows her to issue queries of this type. It then assembles (based on Abigail’s name, date of birth, 

present and previous addresses, and so forth) a list of locations at which Abigail has medical records and 

has given prior consent for them to be locatable (assuming that rules or policies are in place requiring 

such consent).69 If Abigail has consented to have the nature of her medical records also indexed (e.g., 

that some locations hold mammogram records, while others hold blood test records) then the list of 

locations can be pruned to a smaller number; otherwise the DEAS has no medical information and does 

no pruning. The DEAS now sends the locator information list (analogous to the web’s “https://” universal 

record locators) to the EHR system on Dr. Jones’s computer. That system, not the DEAS, then fetches the 

actual tagged data elements, each one containing a previous mammogram. It is important to note that 

the DEAS never has access to the mammograms themselves (the clinical data), and has access to even a 

description of the clinical data (the fact that it is a mammogram) only with patient consent. While most 

patients may elect a default choice that allows more efficient indexing and location of their records, the 

DEAS is designed to also serve (albeit with reduced efficiency) patients who choose to impose greater 

privacy restrictions on their data. 

68. Markle Foundation (2006) Implementing a Trusted Information Sharing 

Environment: Using Immutable Audit Logs to Increase Security, Trust, and Accountability. at 

http://www.markle.org/downloadable_assets/nstf_IAL_020906.pdf

69. Abigail has chosen to exclude from indexing, for example, that as a teenager she was once treated for a drug 

overdose.
★ 52 ★

T h e Path F o rwa r d

Can Abigail’s mammogram images now be displayed? No, because they are still encrypted. For each 

data element, Dr. Jones’s computer now queries another service of the DEAS for the required decryption 

keys. These requests include, again, Dr. Jones’s own authentication data and role. They now also include 

the digitally signed (and therefore unforgeable) patient privacy preferences that accompany each mammogram as metadata. The DEAS examine whether Dr. Jones’s credentials and role are consistent with 

Abigail’s privacy choices. If they are, the DEAS send back the individual keys, and Dr. Jones’s computer 

displays the mammograms. If they are not, then an explanatory message is sent and the mammograms 

are not displayed. In either case, the entire transaction is summarized in an audit record that goes, in 

real time, to a layer of security checking designed to look for anomalous signs of misuse. Such signs 

might include the collection of more patient records by a single supposed clinician than can plausibly 

make sense in that clinician’s role, or a pattern of requests from a single facility for data on patients with 

whom they have no previous relationship and for whom they cannot supply any required evidence of 

patient interaction.

Notice that, in this and all scenarios, data and key are brought together only in the clinician’s computer, 

and only for the purposes of immediate display; decrypted data are not replicated or permanently stored 

locally. Note also that the multiple data storage locations never had access to the keys, so compromise 

of their data, even by an insider with physical access, is impossible. Similarly, the DEAS that managed 

the keys never saw the data.

In a second scenario, suppose that an NIH researcher, Dr. Garcia, is studying the comparative effectiveness of two different mammography techniques. His credential and role identify him to the DEAS as 

authorized to receive only de-identified data from patients. When Dr. Garcia queries for data, he receives 

100,000 locator records for mammograms meeting these criteria. However, these locator records are 

different from those returned to Dr. Jones’s in the first scenario. Their unforgeable digital signature 

specifies that they may only be used to locate de-identified data. When Dr. Garcia’s computer now sends 

out for the 100,000 mammograms (and their accompanying metadata), they come back de-identified, 

and they contain a digital signature that so certifies. Dr. Garcia’s new DEAS queries for the individual 

decryption keys must now contain (i) his own authentication and role as researcher, (ii) the digitally 

signed privacy requirements and preferences (where applicable), and (iii) the certification that the data 

have already been de-identified. Only if everything matches do the DEAS provide Dr. Garcia’s computer 

with the decryption key for each piece of de-identified data.

These examples are intended only as illustrations. In fact, the computer exchanges would be even 

more complicated than indicated. The fields of computer security and data protection are sophisticated and highly developed. While the web will continue to be full of reports of data compromises in 

badly designed systems, or systems subverted by bad management practices, there is no reason that 

a national health IT infrastructure should be designed and managed at less than state-of-the-art best 

practice. Our judgment is that such best practice can yield much better privacy and security for health 

IT than today’s scattered approach, and also can be much more enabling of secondary data uses such 

as public health and research.

This chapter’s bottom line: The tagged data element approach allows for a sophisticated, fine-grained 

model of implementing strong privacy controls (including honoring patient-controlled privacy preferences where applicable) and strong security protection.
★ 53 ★

VI. Economic and Regulatory Issues

Introduction

Many economic and regulatory steps need to be taken to realize the technological opportunities 

described in this report. This chapter offers a succinct discussion of some of the main issues. An important 

consideration here is that many aspects of health IT, particularly those associated with data exchange 

and aggregation, have “public good” characteristics. Because the benefits of a networked health infrastructure will be distributed widely, while costs are borne locally, market forces may fail to generate 

appropriate incentives for providers to invest in interoperability or to allow their data to be indexed 

and accessed. The public good nature of the problem calls for coordinated leadership to implement 

standards for interoperability and to enable indexing and retrieval of patient records. At the same 

time, policy makers need to create market conditions that reward information exchange, and enable 

market innovation to deliver the IT services and applications that can ultimately have a major effect on 

healthcare systems.

The technological approach described in Chapters Four and Five relies on two key elements. The first is 

the adoption by providers of interoperability standards that enable data to be shared across institutions. 

The second is the creation of network infrastructure and administration that enable distributed data 

to be indexed and accessed subject to appropriate data access restrictions. Both have the public good 

features mentioned above, in much the same way as investments in transportation or communications 

networks. We argue that Federal leadership exercised by ONC and CMS can play an important role in 

furthering both interoperability investments and network infrastructure development.

Standards and Incentives for Interoperability

As described in Chapter Four, one way to enable scalable data exchange and new application development is through the adoption of standardized metadata that enable patient data to be indexed, queried, 

transmitted, and re-assembled for different uses. This route to interoperability does not mean that every 

provider has to adopt a standard health record format or reconfigure its approach to inputting and 

managing patient records. Indeed, we pointed out that technology already exists and is offered by a 

variety of middleware providers that enables existing systems to become interoperable in this fashion.70

Nevertheless, the economic environment poses substantial roadblocks for investments in interoperability. There is not yet a recognized standard for health metadata, and healthcare organizations and 

technology providers considering adoption of a standard face a coordination problem. Even for the 

healthcare systems that are leaders in using information technology, there is little private incentive to 

focus on widespread interoperability unless other providers are making the same investment and there 

is a clear path toward productive data exchange.

70. Halamka, J. November 11, 2009 The Magic of Middleware. Life as a Healthcare CIO, at 

http://geekdoctor.blogspot.com/2009/11/magic-of-middleware.html
★ 54 ★

T h e Path F o rwa r d

Furthermore, the economic incentives of healthcare providers may not be strongly aligned with making 

patient data exchangeable. Healthcare providers with their current closed data systems may view their 

data at least partly as a proprietary strategic asset. A hospital may have an incentive to exchange data 

with local clinicians, improving patient care and tethering the clinicians more closely to the hospital. 

But the incentives become less clear if the hospital is contemplating exchanging data with competing 

hospitals or with providers who are not local and with whom it shares few patients.

The local and regional health information exchanges discussed in Chapter Three have gone some 

distance toward promoting data transfer between institutions. But these models in their current form 

do not use a tagged data element approach that enables parties to flexibly assemble and re-assemble 

data elements in different ways to respond to different types of patient encounters, address population 

questions, track drug effects or epidemics, or enable clinical research. Moreover, as described earlier, 

local and regional exchanges will not provide a clear route toward national interoperability if they adopt 

different standards or settle on different governance models for regulating data access.

Federal leadership, therefore, has a clear role to play in coordinating standards for health metadata and 

in creating economic incentives to adopt the standard. The definition of meaningful use and the rewards 

for being a meaningful user (and penalties for not being one) are powerful mechanisms for doing this. 

Current work on meaningful use already has begun to incorporate interoperability standards. The initial 

recommendations by the Health IT Standards Committee that were transmitted to ONC in March 2010 

do describe data exchange standards that providers must adopt to qualify as meaningful users, but 

they are far less ambitious than the objectives laid out in this report. In the next chapter, we will make 

some specific recommendations for how these standards can be developed over time so that the lever 

of meaningful use can help promote an effective architecture for widespread data exchange.

We emphasize that there is a potential concern with pushing too many requirements into meaningful 

use. The concern is that this will create too onerous a burden for many healthcare providers, especially 

smaller physician offices that already may lag behind in adoption. However, the initial experience with 

meaningful use suggests that providers of the IT systems have a strong incentive to compete by ensuring that their products qualify under meaningful use. If meaningful use is expanded in a moderate way 

to require standardized metadata, technology providers likely will incorporate the standards into their 

products, and competition between technology firms will rapidly bring down the costs of middleware 

that will allow legacy systems to meet the standard.

Creating a Data Exchange Infrastructure

The second component to the technological model we have outlined is the network infrastructure that 

links healthcare providers, patients, labs, researchers, and other stakeholders and enables qualified 

users to query distributed data stored by partners in the network. In thinking about the development 

of such an infrastructure, an important economic point is that communication networks are very often 

characterized by increasing returns. One reason is user externalities: the more parties sharing data in a 

network, the more valuable is membership to any given party. A second is the spreading of fixed costs. 

On a per-member basis, the costs of creating an indexing and data retrieval service may be large if only 

a few providers are participating in the network, but many of the costs are fixed and hence decrease on 

a per-member basis with increasing participation.
★ 55 ★

VI . Eco n o m ic a n d Re g u l ato ry Is s u e s

Current efforts at health data networking are at relatively small scale. As we have described, they 

consist of local and regional health information exchanges and narrower initiatives between particular 

institutions (hospitals and affiliated local physicians, or Kaiser Permanente and the Veterans Health 

Administration). The ONC is offering important support to these efforts—for instance, through cooperative agreements with all 56 states and territories to lead and promote health information exchange and 

through its Beacon Community grants program, which provides funding to 17 communities to build 

systems by which hospitals, clinicians, and patients use technology to improve health.71 An important 

strategic question, however, is whether local experimental projects are the appropriate approach if the 

end goal is a national infrastructure.

One way to achieve this is to ensure that pilot projects are scalable and employ sufficiently flexible and 

interoperable technology. There are several ways in which Federal agencies might take this approach. 

One possibility is that CMS, the VHA system, or the Department of Defense (DoD) could initiate scalable 

pilot exchanges using the type of tagged data element model described in Chapter Four. The ONC also 

could use its grant funding to promote exchanges with the same type of flexible and scalable architecture. Finally, meaningful use guidelines that require providers to expose certain data to qualified users 

over approved networks are a powerful incentive mechanism. We make specific recommendations 

about meaningful use in the final chapter.

Regardless of how the network takes shape, an essential piece of the approach described in Chapter 

Four is a service that would index data available to the network and allow approved parties to locate 

a patient’s data and assemble data elements, in both cases subject to access regulations. We termed 

this the data element access services model. The provider or providers of these services do not need to 

physically possess or store patient records in a central repository. But the providing entity does need 

to index data stored in a distributed fashion and retrieve and transmit data elements in response to 

qualified user queries, in much the same way that Internet search engines index data on the web and 

assemble data elements in response to queries.

The economic and regulatory issues around this service require careful consideration. Because privacy 

concerns are paramount with patient data, any provider of indexing and retrieval services must be able 

to maintain the trust of patients and clinicians. While such services might evolve in response to market 

forces, it seems likely that, at a minimum, regulatory oversight by ONC will be important for preserving 

patient trust. For instance, one possible regulatory requirement might be that providers of indexing and 

retrieval services have no commercial interest in the data and operate in ways that seek to maximize 

benefits for patients and the general public.

Compared with the broader costs of health IT adoption, the costs of creating indexing and retrieval services are likely to be low provided that the network reaches sufficient scale. Nevertheless, if the entities 

providing the service are prohibited from making commercial use of the data, they will need a funding 

mechanism. One possibility would be for the Federal Government to provide initial funding. Ultimately 

a variety of models might work. Funding could come from small charges on queries or from a small fee 

assessed to insurers on the basis of their enrolled members. One potential advantage of having payers, 

rather than providers, be the source of funding is that payers are in the best position to pass the costs 

71. Office of the National Coordinator. May 26, 2010. Beacon Community Program. Available at http://healthit.hhs.

gov/portal/server.pt?open=512&objID=1805&parentname=CommunityPage&parentid=2&mode=2&cached=true
★ 56 ★

T h e Path F o rwa r d

on to the general population, who ultimately will have to bear the costs for any technology investment. 

Also, obtaining funding from payers would not impose a direct financial burden on providers, labs, or 

pharmacies whose participation would be important for making the system valuable.

A Regulatory Structure for Data Access

The national health IT infrastructure we envision would also require a carefully considered system to 

control access and ensure patient consent. As described in Chapter Five, an important benefit of the 

tagged data element approach is that different data elements can have different levels of security. This 

means that a single system can allow a treating physician to access a complete patient record, a payer 

to access summary statistics from a physician, and a researcher to access de-identified data to enable 

clinical research on different treatments.

With a tiered system for data access, applications used by providers, patients, and researchers might 

be assigned roles that enable them to retrieve and use different types of data. Patients and providers 

could then consent to share data for certain purposes but perhaps not for others. For instance, they 

might consent to allow data to be accessed by other providers for direct clinical care or allow certain 

data elements to be accessed by researchers in other than de-identified form. But they might prohibit 

access to firms seeking to market pharmaceuticals unless they wanted to be targeted for advertising.

There are inherent trade-offs in formulating a regulatory policy for data access. Patients with privacy 

concerns and providers with an economic interest in maintaining proprietary data may prefer a tighter 

policy that limits data sharing and the ability of third parties to develop applications that make use of 

networked health data. On the other hand, such applications have the potential to yield substantial 

general benefits in terms of increasing the quality and consistency of care, informing patients, and 

facilitating research. In this sense, ensuring data access has some of the same public good aspects as 

interoperability and network investment—in particular, widespread general benefits and more targeted 

costs to privacy. It is important to keep this trade-off in mind in formulating regulatory policy.

Competition to Supply Technology

So far, we have focused mainly on the government’s role in bringing about a national health data 

infrastructure. In our view, however, one of the advantages of moving in this direction is to invigorate 

market innovation. Indeed, developing a networked infrastructure likely will involve the expansion of 

several of the nascent technology markets mentioned in Chapter Three. These include the markets for 

cloud-based electronic record and clinical decision support systems tailored to smaller providers, for 

middleware products that allow disparate legacy systems to be made compatible, and for new applications that enable patients and providers to leverage newly available data.

The economic incentives created by ARRA have already generated substantial innovation and competition in cloud-based electronic record products. More than 300 companies are offering some form of 

EHR product for physicians. Competition among these companies already has led to more affordable 

systems and improved products. Some of the companies in this market also are offering guarantees 

that physicians who adopt their system will qualify for meaningful use payments.72 These cloud-based 

72. Stytz, M., et al. 2010. Electronic Patient Health Record Technology: Status and Challenges. Washington, DC: STPI.
★ 57 ★

VI . Eco n o m ic a n d Re g u l ato ry Is s u e s

products are likely to become increasingly powerful as data exchange increases because physicians in 

smaller practices will be able to take advantage of data integration and tools that currently are available 

only to physicians in large integrated practices. This market therefore has an important role in ensuring 

that all physicians and patients benefit from advances in health IT and data exchange.

As noted above, moving from the current system to a tagged data element architecture will require 

that existing systems be upgraded to achieve interoperability. If providers have sufficiently strong 

incentives to upgrade, either because of the benefits of data exchange or because of meaningful use 

requirements, large EHR vendors are likely to move to interoperability. For organizations with legacy 

systems, we observed earlier that middleware products already exist that can extract data from existing 

systems and put them into tagged element form. The products might also provide an alternative for 

clients of large vendors who want a competitively priced alternative to upgrading their current system. 

To ensure that providers have multiple options, it is important that Federal policies are consistent with 

this market remaining competitive and innovative.

One further technology issue that arises in envisioning the future path of health IT relates to the problem of data storage and aggregation. Providers using electronic records are currently adding roughly 

80 megabytes of data per person per year.73 This rate is likely to increase as imaging and genetic data 

expands over time. As datasets expand, there could be substantial efficiencies in archiving large amounts 

of data in aggregated repositories. Indeed, this may be one advantage of cloud-based products. As we 

emphasized earlier though, the networked environment we envision is not dependent on the physical 

location of data storage. In this sense, it is consistent with a scenario under which data remain physically 

located with individual providers and labs, and one where technology evolves to favor a regime where 

data are stored in more aggregated forms.

Innovation and Markets for Applications

Transforming large amounts of linked data into information that improves healthcare delivery and benefits patients and other stakeholders will require a sophisticated layer of application software. Chapter 

Three described in some detail the limitations of today’s EHR systems that could be remedied with 

innovative applications. But because providers currently create and store data in many different ways 

and typically in closed systems, there is no common data “substrate” that application developers can 

use. Furthermore, short of individual time-consuming sales, there is no easy way to make data-centric 

products available to providers or patients.

An important advantage of the technological approach we have described is that it would enable new 

markets where firms compete to provide services and tools to patients, healthcare providers, payers, 

public health officials, and researchers. These tools might include products for patients to gather information about diseases using their personal health data, to input data from home health monitors, or 

to compare healthcare providers. Providers might benefit from improved tools for data entry, clinical 

decision support, or e-prescribing. Commercial products could also emerge to serve the general health 

system. For example, providers could benchmark their patient population and outcomes with peer 

provider organizations, enabling new forms of quality measurement.

73. John Halamka, personal communication, based on 2000-2010 Beth Israel Deaconess Medical Center data.
★ 58 ★

T h e Path F o rwa r d

Many of these tools might function by combining individual data with a broader reference database. 

Analogous products are common on the Internet. Map-based products that provide directions or help 

consumers locate businesses or services combine individual information (a person’s location and interest) with an underlying population database (maps with GPS coordinates, traffic data, and inventories of 

businesses). Personal finance tools use a combination of individual financial data and broader publicly 

available data on financial markets. The Internet also offers a model for market creation. As increasing 

amounts of data have become available (real estate transaction prices, financial market data, search 

and browsing data, and social network data), companies have emerged to build applications that use 

the data and market these applications to consumers and businesses.

One set of applications might address the problems with usability of EHRs described in Chapter Three. 

One way to understand some of the usability challenges is that current systems do not necessarily format 

information in a way that reflects the decision-making and information-flow processes of medical care. 

The problem is acute if a patient is seen by several providers who have to exchange clinical notes or lab 

results in document form. A system based on tagged data elements, coupled with the ability to query 

remote data stored by other providers, can allow for new software products that would deliver the data 

that the physician and patient require at the point of care, including the ability to intelligently retrieve 

information for advanced clinical decision support (evidence-based guidelines, genetic information, 

clinical trial access, and so on).

Patients also stand to benefit from applications that would allow them to collect information on treatments and physicians or share information with those who have similar conditions. For example, with 

the infrastructure we have outlined, a patient with a new diagnosis might be able to search instantly 

for the local specialist who has seen the most patients with similar conditions and prognoses. While it is 

possible that many patients may be uninterested in this form of engagement or these types of tools and 

will prefer to rely on a physician’s advice, there are likely to be a large set of patients, particularly those 

with chronic health problems, who are interested. Patients with chronic illnesses already benefit from 

being able to search the Web or share information through discussion boards and social networking 

sites. Many might have a strong interest in applications that would allow them to access information 

culled from underlying health records.

A further class of applications might help users compile and aggregate population-level data on health 

outcomes, physician performance, or population health. These applications could be geared toward provider organizations, insurance companies, public-health companies, and researchers, broadly defined.

The Broader Economics of Healthcare

A central point to keep in mind in thinking about the future of health IT is that the mere adoption of 

EHRs, and even the creation of a technological infrastructure for data exchange, is unlikely to have a truly 

transformative effect on the healthcare sector unless the appropriate economic incentives are in place 

to improve the quality of care and reduce costs. Indeed the same organizational and economic factors 

that have blunted the incentives to adopt IT will also affect the incentives of healthcare providers to 

use IT as they begin to adopt EHRs. In this sense, it is difficult to separate health IT issues from broader 
★ 59 ★

VI . Eco n o m ic a n d Re g u l ato ry Is s u e s

economic issues relating to the healthcare system. While addressing the broader economic structure of 

the healthcare system is far beyond the scope of this report, it is useful to highlight a few of the issues 

and mention some current Federal initiatives that may complement health IT efforts.

To see the issues we have in mind, consider the common claim that EHRs can eliminate duplication 

and reduce healthcare costs. While it may be true that, for instance, networked EHRs could allow access 

to recent lab tests, one also needs to remember that in the healthcare system, one person’s costs are 

another person’s income. There often can be a fine line between duplication and a useful safeguard, 

and to the extent that providers have strong financial incentives pushing in one direction, the mere 

installation of IT systems may not reverse behavior.

Taking this example up a level, it is widely understood that the dominant fee-for-service model does 

not provide much incentive to streamline care, and also that the fragmented organizational structure of 

healthcare makes it challenging to move away from this model, because each small practice or hospital 

is a “tub on its own bottom” financially and therefore is not rewarded for interactions with other providers. This puts some of the major potential benefits of health IT, such as the ability to coordinate care 

across physicians, or to share and aggregate data from clinical encounters, somewhat at odds with the 

prevailing economics of the healthcare system. From this perspective, it is clear that the vision of health 

IT we have described needs to be supplemented by a broader set of reforms in payment and healthcare 

organization to realize the full potential of these technologies.

Several of the CMS initiatives funded under the Patient Protection and Affordable Care Act (PPACA) 

are notable in this regard, because they potentially complement health IT efforts. One such initiative is 

the primary care medical home model, which would put the patient and primary care physician at the 

center of a virtual organization that is paid a fee to coordinate all care the patient receives from specialists and other providers. In this model, the primary care physician would need to be able to exchange 

patient information seamlessly with other providers and assemble a complete record of the patient to 

successfully coordinate care. Another is the accountable care organization model, which would group 

hospitals and physicians into larger organizations that would contract with payers to care for an entire 

population. In this model, physicians and hospitals would need to share patient data and information to 

coordinate care, reduce unnecessary emergency room and hospital use, engage patients and families 

to enhance self-care, and track patient outcomes in a continuous manner. Both of these models would 

seem to require the type of coordination and data exchange that health IT can provide.

Advances in health IT are also likely to facilitate many proposed innovations in healthcare payment. Many 

of these innovations, and particularly those authorized as pilots under the PPACA, revolve around either 

pay-for-performance or bundled payments. With pay-for-performance, providers would be rewarded 

or penalized for patient outcomes relative to some quality benchmark. Bundled, or episode-based, 

payments would shift payment away from fee for service toward payment for all treatment following a 

diagnosis or for a set of procedures and subsequent care.
★ 60 ★

T h e Path F o rwa r d

Estimating Costs

PCAST has not performed a detailed analysis of the system-wide costs associated with implementing 

the recommendations of this report. However, some general comments on costs are in order here. 

Overall, the approach recommended in this report is expected to improve healthcare quality, decrease

the cost of health IT systems (due to increased competition) and lay the foundation for systemic reforms 

to increase the efficiency of healthcare. These benefits are likely to be distributed widely throughout the 

healthcare system and persist over a long period of time. The transition costs to achieve these savings are 

expected to be small, both compared to the broad societal benefits and to the overall $20 billion scale 

of the Federal health IT effort. These costs will be borne more narrowly, at least initially, by EHR vendors, 

healthcare providers, and government agencies. It is useful to distinguish several components of cost:

1. An initial cost for developing standards for the universal exchange language and its associated privacy and security protocols. Based on this group’s examination of a range of analogous 

activities from other sectors of the economy and a survey of the literature and colleagues, we 

estimate the engineering cost of developing the actual standards to be in the range of $20 million 

to $40 million.

2. For healthcare providers with installed EHR systems, a cost to upgrade their systems, or to 

add middleware, so as to enable the exchange of data by means of the new protocols. Based 

on the current cost of middleware products, we estimate the incremental cost might be 5 to10 

percent of providers’ current EHR costs. On the other hand, this estimate may be overstated, because 

a nationwide move to adopt the new communication protocol would likely result in significant 

competition to supply upgrade products, which would place price discipline on incumbent EHR 

providers. We estimate that to upgrade their products, existing EHR vendors might have to make 

one-time engineering investments on the order of $5 million to $20 million per vendor, based on 

estimates of private investment in companies now offering products with similar levels of controls 

and privacy. The duplication inherent in these costs can be reduced by the Federal Government 

developing, and putting into the public domain, reference implementations for key processes (such 

as security functions).

3. For healthcare providers with no current EHR system, the additional cost associated with the 

new requirements of the universal exchange language. We expect this cost to be minimal or 

absent. The proposed approach will likely to result in a more competitive and innovative market for 

EHR solutions, for example cloud-based products that are well-suited for smaller providers.

4. Capital and operating costs to the government associated with the infrastructure for indexing 

and searching patient healthcare data, and for related trusted security processes. Here, we note 

that multiple companies such as Google, Microsoft, Yahoo, Baidu, and some that preceded them, 

have made private investments in building and provisioning search systems for the entire Internet, 

which dwarfs the quantity of information in health IT. We estimate the proposed costs as being on 

the order of $100 million to $300 million per year, probably ramping up from the lower figure as the 

use of these services ramps up correspondingly, producing greater national cost savings. Included 

in the costs is an assumption of 0.1 GB per person, which would today be $0.20 per person per year, 

a total of $62 million in storage costs. One possibility is that the Federal government would bear the 

cost for the initial capital investment, and that the costs ultimately would be borne by either all users 

of the service, or by healthcare payers, including the government in its role as a payer.
★ 61 ★

VI . Eco n o m ic a n d Re g u l ato ry Is s u e s

This chapter’s bottom line: Some aspects of the new health IT infrastructure will enable new, competitive, entrepreneurial markets. Some other aspects are “public goods” and will require government 

leadership. The benefits of health IT affect, and are affected by, other aspects of healthcare reform, 

especially payment models.

★ 63 ★

VII. Health Data and the 

Research Opportunity

Introduction

Today, most information about the effectiveness of therapies such as drugs derives from small-scale 

observations of a handful of patients (often a few hundred, sometimes fewer) in clinical studies. The most 

convincing clinical studies incorporate design elements, such as randomization of subjects to alternative 

treatments, to reduce the impact of unmeasured confounders on the treatment effect. These studies 

are appropriately considered to produce the highest quality evidence regarding a particular agent’s 

efficacy, but they also suffer from well-recognized problems.

Efficacy, not effectiveness: Clinical research studies usually focus on highly selected and often nonrepresentative patients. They are designed to detect differences in the main outcome of interest, which 

means they are often too small to pick up less common but potentially important outcomes (such 

as serious adverse events) and are too brief to capture fully the long-term consequences of different 

treatment strategies.

For efficiency’s sake, the studies often exclude patients with complex medical histories or many illnesses. 

This is problematic in that the treatments are needed by patients with complex illnesses where multiple 

different conditions make the range of choices greater than the usually simple comparison of a single trial.

Out of date before they are even finished: Today’s clinical research studies are not carried out in real 

time. Instead, they take years to design, fund, launch, and complete. Sometimes, by the time they are 

completed the question under investigation is obsolete. For instance, it is quite common for multiple 

clinical trials in cancer to be occurring simultaneously. New drugs can then be approved that have never 

been compared with each other, so the physician and patient do not have any way of knowing which is 

best. They only know that each is better than some other drug that is no longer used.

Burdensome and costly: Today’s clinical research enterprise is, at best, a sidecar loosely tethered to 

the clinical care enterprise. What is done in clinical research has its own expense structure and funding 

stream. The oversight of research is separate and apart from the oversight for clinical care. Its participants—both patients and investigators—are involved in sometimes redundant or repetitive activities. 

For instance, data often are collected twice for patients in clinical research studies: once for the patient’s 

chart, and again for the research database.

Narrow focus: Most research focuses on a narrow set of questions regarding therapeutic choices. Yet 

many important questions in healthcare stretch far beyond the choice between drug A or drug B. For 

example, healthcare research needs to evaluate operational aspects of the delivery system and evaluate 

arrays of therapeutic choices side by side. Ideas for new directions for research can and should come 

from observations about health trends independent of specific hypotheses.
★ 64 ★

T h e Path F o rwa r d

The Potential for Real-Time, Real-World, and Comprehensive Data

Numerous questions that clinical research is poor at addressing today could be answered using large 

datasets gathered through ongoing medical care, particularly if the data were available in near real time. 

A list of questions that could be addressed illustrates the promise.

Syndromic surveillance and public health monitoring: Our infrastructure for monitoring public health 

is spotty and slow, depending on individual offices reporting data locally or regionally. Health IT and 

real-time data on the use of the healthcare system have the potential to address this deficiency. Today, 

the ability to follow cancer trends, asthma and other environmentally sensitive conditions, antibiotic 

resistance, or flu-like symptoms requires additional infrastructures layered on top of the healthcare 

delivery system (such as cancer registries or emergency room reporting).These infrastructures are costly 

and incomplete. In many cases, they also are unable to produce details related to the entire population 

(the denominator) against which this information should be compared.

Routine collection of data could eliminate redundancy, be far more comprehensive, and overcome 

the denominator problem. Case ascertainment (such as detecting new cases of cancer or new cases of 

antibiotic resistance) would grow naturally out of data capture during routine clinical care. Moreover, 

the denominator (or denominators) would grow out of the same resource. For instance, it would be 

straightforward to assess the prevalence of antibiotic resistance across all cultures of a certain bacterium 

in a geographic area during a certain period of time. Those data could be married to data on prescriptions of different antibiotics in ways that cannot be achieved today.

There are working examples of such real-time data collection. New York City monitors pharmacy 

purchases as a way of capturing early signs of flu-like symptoms.74 This activity is important for routine 

decisions about vaccinations and also for such factors as bio-terrorism preparedness. Current search 

engines also can identify a flurry of inquiries about flu, but they cannot identify whether the queries 

resulted from symptoms or from media exposure.

Adverse event monitoring: An ongoing concern for drug and device safety is the lack of a routine system 

of data collection for adverse events. The Food and Drug Administration mostly relies on ad hoc reporting 

of events. It does not have a good way to estimate the relative frequency of atypical events among all 

patients exposed to a drug or device or to separate association from causation. With extensive use of 

health IT and aggregated data, the data would be sufficiently rich to identify patterns and to separate 

events caused by particular drugs and devices from those that occur purely by coincidence.

Many examples of such event detection exist. The most frequently cited is the linking of Vioxx to cardiovascular events—something achieved through analyses of data captured by Kaiser Permanente 

and reported by several insurers as well.75 Other examples include the detection of cardiovascular complications associated with the diabetes drug Avandia and with several calcium channel blockers used 

for treating high blood pressure.76 Yet these represent relatively rare cases of adverse events detected 

74. USA Today. October 25, 2009. “R.I. Tracks H1N1 with Electronic Data,” at 

http://www.usatoday.com/news/nation/2009-10-25-rhode-island-flu-tracking_N.htm

75. Kweder S. November 18, 2004. “Vioxx and Drug Safety.” Available at 

http://www.fda.gov/NewsEvents/Testimony/ucm113235.htm

76. Nissen, E., and K. Wolski. 2007. Effect of Rosiglitazone on the Risk of Myocardial Infarction and Death from 

Cardiovascular Causes. New England Journal of Medicine, 356(24):2457-2471.
★ 65 ★

VII . He a lth Data a n d th e Re s e a rch Oppo rtu n it y

through clinical databases. Other serious adverse events, such as those observed in randomized trials 

measuring the effect of erythropoeisis stimulating agents on cancer progression, were not detected in 

administrative data even though the effects were large, because there was not enough clinical detail 

in the information. This limitation could be overcome by greater data availability.

Assessments of dissemination and utilization: The gap between knowledge and the delivery of care, 

branded as the “quality chasm” by the Institute of Medicine a decade ago, remains a serious concern. 

The shortfalls disproportionately affect members of minority groups and individuals who lack insurance.77 Currently, numerous redundant and sometimes conflicting systems aim to monitor utilization 

and quality as a way to mitigate these problems. Through programs such as quality measurement and 

reporting, chart review, and auditing, providers are increasingly being asked to report on what they 

are doing. This set of approaches, although conceptually attractive, has many problems. Any quality 

measurement collection involves large costs and burden. It also involves choosing the quality measures 

before creating a structure to capture the measures, which means both that the domains of quality that 

can be assessed are logistically limited and that the speed of change is sub-optimal.

The potential of data to monitor quality and the use of evidence-based approaches is immense. At 

scale, health IT will provide insight into the quality of care in all settings without actually having to 

design systems to report a particular element. The initial standards for meaningful use emphasize this 

potential benefit. If clinical systems capture sufficient data about patients, including both their eligibility 

for particular treatments and their contraindications, along with physician orders, e-prescriptions, and 

other delivery data, continuous quality monitoring and feedback could become part of routine care 

rather than the add-on it is today.

Comparative effectiveness research: Perhaps the greatest potential of the data that can be captured 

using health IT lies in the potential to fuel comparative studies of diagnostic and therapeutic approaches. 

Comparing treatment and management approaches in a way that can easily be accessed by both 

physicians and patients could improve patient outcomes and reduce healthcare spending. Funding 

for comparative effectiveness research is already growing. Electronic health information, in the easily accessible form enabled by metadata-tagged data element collection, aggregation, and security 

standards, would enable this kind of research to advance much more rapidly than with the traditional, 

institutional EHR model.

Supporting Research Uses

The uses described above, although they all hinge on data collected through EHRs, require somewhat 

different types of data, falling broadly into one of three categories: Effective syndromic surveillanceand 

other public health monitoring could be achieved through collection of data that are already regularly 

recorded in patient charts but are not currently aggregated. Separation of adverse events from coincidence 

and ascertainment of quality measures may require more detailed information than is currently routinely 

captured in most patient charts today, but likely possible to capture within the system that we envisage. 

However, comparative effectiveness studies, particularly those that build in some experimental design or 

77. Alliance for Health Reform. March 2006. “Racial and Ethnic Disparities in Health Care.” Available at 

http://www.allhealth.org/publications/pub_38.pdf
★ 66 ★

T h e Path F o rwa r d

require additional data elements or assessments, would require more data than are routinely captured 

and also would require a framework of two-way interaction with the clinician and patient. We will 

illustrate this in an example below. And there are many other types of clinical research, not just clinical 

trials, in which two-way interactions between research and clinicians are desirable.

Methodological issues will need to be considered as data from EHRs become available for research 

studies of increasing sophistication. Practicing physicians are busy, not necessarily trained in research, 

and not always ideal collectors of patient data for research. Patients, exercising their right to opt in or 

out of studies, will cause data to be collected from incomplete, or incompletely defined, populations. 

Effects like these complicate the design and validation of research results. But the availability of data 

in quantities orders of magnitude larger than today will allow subtle and sophisticated experimental 

designs, more than compensating, we think, for the data’s complexities.

Committing to only one level of data collection at a national level would be a mistake. A lot can be 

achieved based on clinical data gathered during routine care only, while some research requires additional data gathered during healthcare encounters. Other research may require experimental designs

that entail additional steps such as informed consent, data categorization, follow-up questionnaires, and 

the like. To accommodate different levels of data collection, the infrastructure should be designed while 

considering the tradeoffs of collecting research-quality data against possible burdens. These burdens 

include a higher level of training for the providers involved and possible additional costs and processes 

required for high-quality research data, but the burdens can be limited and the advantages enhanced 

Linking Patients to Clinical Studies

To see the potential for interactive data collection in EHRs to lead to the enrollment of patients in 

clinical trials, consider an oncologist who, upon seeing a patient with a new diagnosis of cancer, 

could be asked by the interactive program to upload detailed information about disease type, 

stage, other conditions, and performance status. Depending on that information, lists of eligible 

ongoing studies could be presented to the treating physician and patient, and enrollment in 

the study could occur during that visit. As an intermediate step, a more intensive data collection 

could be initiated, along with patient enrollment into a registry when enriched data are needed 

to address a particular question.

The value of such a system is clear. More information generated in clinical care could be used to 

accelerate learning, and many biases that exist in observational data could be overcome through 

the use of several types of experimental designs (such as randomization or block assignment). 

Providers and the patients would know all of the available opportunities to participate in clinical trials, and the physician could manage the patient through the process, with real-time data exchange 

to and from the research team. Not all providers would be authorized investigators in any trial, but 

electronic access to every available study would include the real-time ability to query the study 

about its appropriateness for the interested patient and any additional information. Much of this 

could be done without the patient having to transfer care to another provider.
★ 67 ★

VII . He a lth Data a n d th e Re s e a rch Oppo rtu n it y

with access to a tagged data element environment. The implied trade-offs are matters of policy, to be 

codified only after careful consultation with all stakeholders, and to be justified not by the abstract 

desirability of research, but by explicit consideration of how research feeds back to better patient care.

Some opportunities and challenges in observational data: Observational data first uncovered the 

cardiovascular side effects of Vioxx, long before randomized trials demonstrated the same findings. 

Likewise, the apparent benefits of some unusually effective cancer treatments, such as Gleevec for 

chronic myelogenous leukemia, were apparent based on outcomes of studies using single specified 

therapies, well before randomized trials documented the actual size of the beneficial effect.78 Yet 

observational studies can be hindered by biases that can be hard to detect, and sometimes findings are 

disproved by randomized trials or observational studies that contain more granular data. For instance, 

numerous observational cohort studies suggested that beta-carotene supplementation would reduce 

the risk of developing lung cancer, but randomized trials of the intervention showed the opposite 

effect.79 A recent observational analysis of radiation treatment for women with DCIS (ductal carcinoma 

in situ, an early stage breast cancer) suggested that delays in radiation reduced overall survival, even 

though the underlying disease has a very low mortality rate and randomized trials of radiation for it 

had shown no mortality benefit.80 The potential, and the limitations, are one motivator for providing an 

infrastructure that will eventually allow more than one approach to EHR-driven research.

78. Cohen, H., G. Williams, J. Johnson, J. Duan, J. Gobburu, A. Rahman, K. Benson, J. Leighton, S. Kim, R. Wood, 

M. Rothmann, G. M. Chen, M. Staten, and R. Pazdur. 2002. Approval Aummary for Imatinib Mesylate Capsules in the 

Treatment of Chronic Myelogenous Leukemia. Clinical Cancer Research, 8(5):935-942.

79. National Cancer Institute. Beta-Carotene Supplements Confirmed as Harmful to Those at Risk for Lung Cancer. 

Available at http://www.cancer.gov/clinicaltrials/results/final-CARET1204

80. Gold, T., T. Do T, and W. Dick. 2008. Correlates and Effect of Suboptimal Radiotherapy in Women with Ductal 

Carcinoma in Situ or Early Invasive Breast Cancer. Cancer, 113(11):3108-3115.

Real-Time Patient Benefits from Comparative Effectiveness Research

Making patient clinical data available to researchers clearly has long-range benefits to patients. 

Until now, this has been a linear process with a timescale of years, since it requires performing the 

research, submitting it for peer review, publication, and ultimately the adoption of new clinical 

practices that benefit future patients.

Health IT can make it possible to get benefits to patients much faster. Indeed, patients could benefit 

directly from a research study to which they are concurrently contributing.

If patient progress and outcomes were routinely captured in data and made available in near 

real time, partial data can be used in sophisticated ways to assign treatments to new patients in 

optimal ways. These data also could be used to personalize treatment for patients already enrolled 

in a study.
★ 68 ★

T h e Path F o rwa r d

A patient-physician interaction in an adaptive comparative study might proceed along these lines:

1. Using the physician’s diagnosis, the physician’s computer identifies a comparative effectiveness study relevant to the patient’s condition and advises the physician.

2. The physician asks the patient whether he is interested in participating. The patient is advised 

that, by participating, he will receive a treatment recommendation based on, literally, today’s 

best weighted judgment of all the accumulated data. However, the recommended treatment 

might not be the brand name drug that he expects.

3. The patient agrees to participate in the study.

4. Through the physician’s computer and the physician, the patient is asked if he wants to allow 

the study to access his personal genotype data, in which case a more personalized treatment 

recommendation might be made.

5. The patient agrees to this.

6. The study recommends a treatment, for example a prescription which is sent through the 

physician’s computer (with patient and physician concurrence) to the patient’s local pharmacy.

This example demonstrates a synergistic combination of three health IT opportunities, each 

potentially revolutionary. The first is real-time decision support to the physician based on evidencedriven best practice. The second is the real-time interaction of that decision support with completely current clinical data, without months or years of lag. The third is seamless integration of the 

clinical setting with the enrollment of patients into the clinical and comparative studies that will 

generate the next round of new data. Importantly, because these studies are adaptive (that is, they 

assign patients to treatments not arbitrarily, but rather based on the partial accumulated study 

data), they are consistent with the physician’s duty to give each patient the treatment believed to 

be best for him or her on the basis of the most current evidence.81

81. W. H. Press. 2009. Bandit Solutions Provide Unified Ethical Models for Randomized Clinical Trials and 

Comparative Effectiveness Research. PNAS. 106:22387-22392.

This chapter’s bottom line: A national health IT infrastructure will enable new kinds of research and 

will also create opportunities for the faster coupling of research to clinical practice.
★ 69 ★

VIII. Guidance to Agencies

Introduction

In this final chapter, we discuss what needs to be done if rapid progress toward the realization of a 

national health IT infrastructure is to be achieved. Because of the complexity of the issues, we give 

recommendations at several levels of specificity. First, as an example, we sketch a possible roadmap for 

getting all the way to the transformative future that we envision. Next, in narrative format, we give some 

overall short-term guidance relevant to the two key agencies, ONC and CMS. In the next chapter, we 

give a list of specific recommendations to several agencies that can (and, we think, should) be tracked 

by senior policy makers within the Executive Office of the President as to progress achieved.

A Feasible Roadmap to the Future

An important feature of the tagged data element model advocated in this report is that there is a 

natural transition path from present EHRs and from existing demonstrations of information exchange. 

As an illustration, we sketch a possible way—though by no means the only possible way—in which 

that transition might unfold. Key to this roadmap is its leveraging of universal data exchange, and the 

network effect, to spur EHR adoption.

First, HHS would define by regulation the most basic features of the tagged data element exchange. 

This would include the specification of an extensible markup language, most likely a variant of the existing language XML. ONC’s clinical document architecture standard is important foundational work for 

this. However, additional focus is needed on aspects that relate to data transmission, to innate privacy 

features, and (perhaps most importantly) to facilitating the disaggregation of complex records into the 

smallest possible data elements, suitable for use by a broad range of new health IT products in a new, 

entrepreneurial marketplace. The universal exchange language is more than just an extensible wrapper 

for the exchange of documents, each in its own fixed format. It needs to facilitate (if not directly require) 

the exposure of the underlying semantics of individual data elements for new uses, including many not 

anticipated by the original data producer.

Also defined from the start would be a minimal initial set of requirements for the metadata that will 

accompany each piece of data. These might include, for example, the patient’s name and birthdate, the 

applicable privacy rules and policies, including any patient’s pre-consented privacy choices (e.g., “data 

may be used in research but only when fully de-identified”), an identifier of the originating physician 

or institution, a provenance within that institution (for example, a reference to a type of equipment or 

standard clinical procedure), and a time-stamp. Since the language is extensible, only a minimal set of 

metadata needs to be standardized at this stage; more will naturally evolve at later stages of adoption 

or as features added by individual software vendors.

A part of the specified metadata—for example, the patient name and birthdate—would be specified 

as “indexable” items that are made visible to authorized data element access services for indexing and 

data locating as they become available in stages of the transition.
★ 70 ★

T h e Path F o rwa r d

Next, ONC and existing standards groups would publish mappings of existing vocabularies and 

content standards (for example, the HL-7 vocabulary standards for electronic exchange of healthcare 

information82 and the ICD-9 and ICD-10 international disease classifications83) into the adopted markup 

language.84 This straightforward step immediately expands the semantically meaningful realm of 

tagged data exchanges to include data that are coded in these existing standards. It incorporates these 

standards into the new architecture, leveraging the work done by thousands of people for decades.

In parallel, vendors of existing EHRs would be encouraged to rapidly publish mappings of their existing 

exchange mechanisms into the extensible markup language. For example, if a product is now able to 

exchange prescriptions, whole medical records, or other information, the vendor should easily be able 

to map that exchange at the existing level of aggregation into the markup language. This is only a first 

step toward an infrastructure of fully tagged data elements, because the individual data units are not 

yet the smallest pieces that make sense to exchange and aggregate. However, it is an important step, 

because it immediately allows the development of middleware that is able to exchange and display 

information from multiple vendor systems. It also is an important first step toward creating the kind of 

competitive marketplace that we envision. Data from patient-controlled personal health records can 

likewise easily be mapped into the new framework.

Many, if not all, of the meaningful use exchanges that are posited for the near future can and should also 

be mapped into exchanges of tagged elements within the framework of the markup language. Also 

important is a standard metadata markup for physicians’ clinical summary records and case progress 

notes. There is no requirement at this stage for any exotic natural language processing or coding of 

these items. Their textual contents are exchangeable data elements in their own right whose exchange 

can add valuable clinical context.

After only these steps, we would already begin to see the value added of a single framework for tagged 

data element exchanges. At this point in the transition, the data are not yet in the smallest pieces that 

make sense and are not yet accompanied by all the metadata that will ultimately be needed. But the 

data will already have become universally exchangeable and universally privacy-protected, and the data 

will already incorporate large, widely recognized semantic realms. This is where the power of emergent 

markets, and the network effect, will first be felt.

Next in the transition sequence, ONC would define standards for the surfacing of metadata for use by the 

data element access services—that is, for finding and requesting patient clinical data (e.g., data relevant 

to a particular patient who presents in an emergency room) and also research data (e.g., anonymized 

data for a particular study by a state public health agency). In parallel, ONC (or another agency under 

ONC’s policy direction) would would encourage the development of intercommunicating and interoperable DEAS. The DEAS will initially be much like any of today’s web search engines, but they will be secure 

and specialized to privacy-protected data exchanges within the health network.

82. “Health Level Seven International” at http://www.hl7.org/

83. World Health Organization. “International Classification of Diseases (ICD)” at 

http://www.who.int/classifications/icd/en/ 

84. The United States Health Information Knowledgebase (USHIK), maintained by AHRQ, maintains 

metadata on many healthcare-related data standards that could be considered for rapid incorporation. See 

http://ushik.ahrq.gov/index.html
★ 71 ★

VIII . Gu i da nce to Ag enci e s

This is the point at which patients and clinicians would see tangible benefits from “putting the patient 

back together.” Aided by new software applications, physicians will start to see tailored, unified views of 

all of a patient’s interactions with the healthcare system, seamless across institutional and geographical 

boundaries.

In parallel, both as the market for health IT becomes more competitive and also to meet new government 

or payer requirements, vendors of existing EHRs would start to break down their data exchanges into 

smaller, more elemental units. For example, a regulatory requirement for metadata that includes the 

model and calibration of the instrument used in a specific lab test will cause the data to be exposed as 

tagged elements, rather than as part of an unwieldy integrated EHR. If there are new entrants into the 

EHR business, they should see a competitive advantage in producing systems that use metadata-tagged 

data elements by original design. At the same time, existing vendors, or unrelated middleware vendors, 

will provide add-on software to expose existing EMR information in an exchange interface where it 

appears as tagged data elements, regardless of how it is internally represented. The feasibility of such 

middleware is demonstrated by the fact that, as we have noted, in special cases it already exists today.

Over time, deliberatively and by appropriate processes, ONC and CMS would require (by means of 

the meaningful use or certification regulatory mechanisms) that smaller meaningful units of tagged 

data, and more extensive metadata tagging, be exposed at the interface, so as to be encouraging the 

development of new software applications and new benefits to the physician and patient. We will 

have gotten to this point by incorporating into the new framework, and then incrementally upgrading, 

health IT systems that exist today. Also, by creating a universal framework, new markets will be created 

for innovative software applications whose internal representations of the data, and thus capabilities, 

may be amazingly different from those available today.

Guidance on Necessary Design Choices

The development of a complex information infrastructure, such as that required for health IT, requires 

many design choices at many levels, and with appropriate ordering in time. Early conceptual design 

choices may have large, and even unanticipated, effects on later implementation-related choices. 

An important concept is that every choice limits the possible design space of subsequent choices. 

Sometimes this is desirable, because it forces convergence to desired goals. Other times, and especially 

early in the design process, it is important that design choices preserve a wide range of subsequent 

design options. Good systems design consists of finding the golden path between the extremes.

One often hears it said that “government should not dictate IT architectures,” and we agree. The word 

“architecture” implies a series of decisions extending far down into the design process. What government 

does need to dictate, or at least facilitate the early standardization of, are those early design choices that 

will enable interoperability. These choices do not specify architectures, but rather “high-level protocols,” 

or “data exchange languages,” or even just common ways of thinking about the problem from a global 

perspective. Here government, both by its convening powers and by its regulatory authorities, has a 

crucial role to play, for the reasons already discussed in Chapter Six.85

85. The crux of the argument in Chapter Six is that this is a public good problem. Market incentives are lacking for 

private firms to invest in universal exchange capabilities, because they cannot appropriate the benefit.
★ 72 ★

T h e Path F o rwa r d

ONC leadership recognizes (as do we) that complete interoperability in the entirety of the domain of 

healthcare is a massive undertaking. This has led to an approach that is iterative and incremental, focused 

on producing the specific, limited solutions that bring the greatest immediate value. The problem with 

this seemingly sensible approach is that it can result in a set of ad hoc solutions, rather than in high-level 

design decisions that could be both convergent and preserving of a wide range of possible subsequent 

design options. A key example, previously discussed, is the rapid establishment of a universal, extensible 

exchange language. As a more general statement, we think that ONC needs to augment its current multifaceted approach with a process that can generate design choices at a national level that are carefully 

balanced between the goals of convergence and diversity. This is an appropriate government role and 

requires a more aggressive approach than is visible at present.

As a related issue, ONC’s current approach has the effect of postponing the development of a genuinely universal “syntax” (that is, the formatting of data that are exchanged and the details of exchange 

protocols) until after the government has harmonized the “semantics” (that is, the clinical or operational 

meaning of the data, or its human understanding) from many different health IT-related realms. This 

approach implies a focus on achieving some harmonization between taxonomies for diagnosis, for test 

results, for genetic information, for billing codes, for the particulars of medical instrumentation, and so 

forth. We urge reconsideration of this approach.

A large body of experience in other domains suggests that creative and entrepreneurial energies are 

best unleashed by standardizing a syntax that is broadly extensible into different semantic spaces. A 

much-studied historical example86 is the language XML (“extensible markup language”) and its many 

off-shoots. If an XML-like universal exchange language for health IT were even minimally standardized, 

then many existing semantic taxonomies could immediately be mapped to it. Would these be instantaneously harmonized? No. But there would be immediate market incentives toward harmonization, 

because vendors could compete on how broadly their products “understand” the existing semantic 

spaces. Rather than a never-ending, Sisyphean government approach to harmonization, the existence 

of an extensible standardized syntax would promote a market-driven, largely nongovernment, ongoing 

process. This is a case where government needs to define a (syntax-based) approach that opens the 

market to new players, and then largely get out of the way.

As mentioned, ONC’s CDA is a foundational step in the right direction. However, the thrust of CDA seems 

largely that it be an extensible wrapper that can hold a variety of structured reports or documents, each 

with vocabulary-controlled metadata. While this shares many features with the universal exchange 

language that we envisage, it lacks many others. In particular, it perpetuates the record-centric notion 

that data elements should “live” inside documents (albeit metadata tagged). We think that a universal 

exchange language must facilitate the exchange of metadata tagged elements at a more atomic and 

disaggregated level, so that their varied assembly into documents or reports can itself be a robust, 

entrepreneurial marketplace of applications. In a similar vein, we view the semantics of metadata tags 

as an arena in which new players can participate (by “publishing”), not as one limited to a vocabulary 

controlled by the government.

ONC’s cautious approach on these two issues is understandable: the problem itself is inherently complex, and the Office is under pressure from parties who would like the bar for receiving payments under 

86. Gray, J., “A Conversation with Tim Bray.” February 16, 2005. http://queue.acm.org/detail.cfm?id=1046941
★ 73 ★

VIII . Gu i da nce to Ag enci e s

ARRA to be set low. However, we are concerned that this direction, pace, and actions are not currently 

sufficient to achieve, in the necessary time frame, the President’s goal that the Nation have a health IT 

system adequate to support efforts to increase the quality and decrease the cost of healthcare. Some 

additional guidance for ONC relates to its support of CMS and is discussed in the next section.

Guidance on Meaningful Use Requirements

Earlier we discussed the broad discretionary powers given to CMS, under ARRA, to define what constitutes meaningful use of EHR technology. In Chapters 4 and 5, we outlined a vision of what ought to be 

achievable, over the mid- and long-term, as a state-of-the-art national health IT infrastructure. Here, we 

put these pieces together to suggest what CMS should be doing now.

To accelerate the adoption of a universal exchange language, HHS should specify that meaningful use 

measures reported to CMS be captured in a tagged data element format.87 To meet these criteria in the 

short term, some healthcare providers with legacy EHR systems would probably add middleware to 

extract and operate on data-level clinical information. Large vendors of EHR systems would likely offer 

upgrades to meet the CMS requirements.

Such a meaningful use data policy would accomplish several things. First, it would advance EHR technologies in the direction of being able to generate data needed to support other aspects of meaningful 

use, for example, advanced clinical decision support. Second, this substrate of data will catalyze a host 

of new IT applications for physicians and hospitals to improve the quality and efficiency of care. Third, 

this policy eliminates the incentive for vendors to “hard wire” into EHRs the specific quality measures 

currently required to qualify for meaningful use, instead motivating them to provide a flexible framework 

into which specified reporting items can be easily inserted. This is important because meaningful use 

measures will change over time as the art and science of quality measurement improve and as more 

clinically meaningful measurement constructs become available. If providers are required to pay for 

expensive system upgrades as new measures are implemented, their support for both the technology 

and for quality assurance programs will quickly dissipate. Moreover, providers need flexibility in their 

EHRs to respond to the unique quality-reporting requirements of different health plans and to satisfy 

licensure, certification, and accrediting organizations with the least possible added burden.

To support this type of meaningful use policy, ONC should issue reference standards with which EHR, 

software, and middleware vendors would need to comply. The original set of standards for EHR certification88 implementing HITECH relies heavily on existing standards for the interoperability of health 

information technologies, including those established and/or promoted by the Health Level 7 standards 

organization (HL7), NIST, and Integrating the Healthcare Enterprise (IHE). These standards were chosen 

in an attempt to provide a “minimum set of transport, content, and vocabulary standards required to 

drive or enhance the predictability of data exchange when used in EHR technologies, in order to drive 

adoption”. We would like to see ONC focus on enabling and accelerating health information exchange 

at the level of the datum, rather than the message or document, while developing a corresponding 

87. Although the reported data consists of aggregated counts, not individual patient data, a tagged metadata 

format can also be applied to this type of data.

88. Health Information Technology: Initial Set of Standards, Implementation Specifications, and Certification 

Criteria for Electronic Health Record Technology at http://HealthIT.HHS.gov/standardsandcertification
★ 74 ★

T h e Path F o rwa r d

reference implementation to verify interoperability. This conceptually straightforward approach to 

certification would allow flexibility and continued innovation in quality measurement and reporting 

without adding an extra administrative burden.

For its part, CMS’s approach to innovation in quality assessment will need major structural and technical 

overhauls, and to share the visionary and strategic goals of ONC and the President, so that it advances 

the state of the art in both clinical practice and health IT. Now, for Stage 1 of meaningful use, CMS will 

require a set of objectives/measures for eligible professionals and 23 for hospitals. In selecting clinical 

quality measures for physicians, CMS chose to use a subset of measures from its Physician Quality 

Reporting Initiative. These measures are highly specified and can be submitted to (and received by) 

CMS only through specific, limited, technical methods.

PCAST has two concerns with this approach. The first concern is that although isolated, condition-specific 

measures such as “percent of patients with blood pressure under control” are relevant to population 

health, they are not adequate to assess the broad range of competencies required for physicians and 

healthcare organizations to deliver safe and effective care. There is good evidence that real improvements in quality will result only from generating and acting on data that reflect the multidimensional 

aspects of the clinical practice.89 Today, large integrated group practices can often generate more 

sophisticated quality metrics and feedback to physicians than what CMS plans to require. It would be 

unfortunate if CMS were to re-focus these organizations on less effective measures. As another example, 

some medical specialty boards and health plans are creating comprehensive assessments of a physician’s skills in a particular clinical area.90 These assessments might combine clinical data elements from 

a physician’s practice with results from a test of knowledge, a review of clinical practice systems, and 

patient experience surveys, all while testing the psychometric properties of new or different combinations of these various data elements. Such innovation in quality measurement and feedback should lead 

to innovation in practice improvement cycles comparable to other modern engineering standards.91

CMS should develop a roadmap for expanding its quality measures to reflect improvements in both 

information technology and methods of quality assessment.

Our second concern is that clinical quality reporting to CMS is limited to the technical specifications 

of a single designated consensus body, the National Quality Forum (NQF). This in turn limits both the 

scope of kinds of measures and the technical specifications that CMS is able and willing to accept. The 

law contains language allowing an alternate pathway for measures if justified by the Secretary of HHS, 

but that pathway has not been used. We think that wider use of this alternate pathway provision would 

allow for more innovation and more meaningful quality assessment than is possible using only computable data that have been electronically “defined” for some other purpose. Moving to a tagged data 

element environment would allow much greater flexibility of quality assessments. It also would require 

improvement in CMS’s ability to receive more complex data as described above. With new resources 

and the charge from the PPACA, CMS should ensure that this flexibility is built into its future rulemaking.

89. Leatherman, S., and A. Epstein. 2010. Performance Measurement for Health System Improvement. Cambridge, UK: 

Cambridge University Press.

90. Darves, B. June 2008. “Ensuring—and Tracking—Physician Competence.” New England Journal of Medicine 

Career Center. at http://www.nejmjobs.org/career-resources/ensure-physician-competence.aspx

91. Gawande, A. 2009. The Checklist Manifesto: How to Get Things Right. New York: Metropolitan Books.
★ 75 ★

VIII . Gu i da nce to Ag enci e s

CMS’s attempt to synergize the Physician Quality Reporting Initiative and meaningful use programs 

and reduce the reporting burden on physicians is a very reasonable approach during the first years of 

implementation, and is required by legislation. Going forward, however, quality improvement information 

will be richer, more secure, and timelier if gathered and delivered through Internet-accessible systems.

CMS needs to take specific actions that will demonstrate the value of tagged data element exchange. 

Adjusting fee-for-service payments based on currently reportable quality measures may spur at least 

some providers to become more sophisticated users of health IT. But it will not bring healthcare closer 

to the vision described in Chapter Two if the goal is only to achieve higher scores on specific measures. 

In Chapter Six, we discussed how CMS demonstrations projects such as the primary care medical 

home and accountable care organization models would shift the payment focus toward coordinated, 

integrated care. These models are potentially highly complementary to investments in health IT. CMS 

could further this connection and perhaps make these models more likely to succeed by requiring that 

demonstration sites have EHR technologies capable of more than reporting specified measures. These 

capabilities should include delivering and retrieving metadata-tagged, patient-centered, and patientauthorized information with other networks and sources such as PHRs and public health data aggregators. In addition, it will be important for CMS to document and publicly share what is learned about the 

contributions of such exchanges to the effectiveness of these new models and the results they achieve.

CMS needs a more aggressive program to support the growth of clinical decision support and secondary 

data uses. Chapter Three discussed the many problems with the “usability” of EHRs from the clinician’s 

perspective. Most of today’s systems do not format information in such a way that it reflects the decisionmaking and information-flow processes of medical care. Instead, their information display is codified 

in a series of “pages” that can hamper care while providers work through an electronic version of their 

written record. Software is needed that is more flexible and can deliver the relevant data that the physician and patient require at the point of care, including the ability to intelligently retrieve information 

for advanced clinical decision support (such as evidence-based guidelines, genetic information, and 

clinical trial results).

Federal policies also could seed the development of applications that can improve the capabilities 

of Federal and public health agencies to leverage large stores of electronic data to advance national 

health system objectives. Specifically, the Department of Health and Human Services should jumpstart 

an applications market through both requests for proposals and technology transfer agreements for 

the secondary use of EHR data. This market could result in the development of a very wide range of 

applications, including software to support pilot projects for benchmarking, coordination of new ONC 

objectives toward tagged data element ecosystems with entities developing adverse event and syndromic surveillance networks, tools and training to enable the gathering and input of research-quality 

data within a fully functional EHR, and the development of a test network for comparative effectiveness 

research.

Finally, we return to the serious challenge posed by CMS’s antiquated IT infrastructure, and the pressing 

need for its modernization, as has already been recognized by CMS leadership. CMS needs to ensure 

that it does not replace one inflexible architecture with another. While it is outside of our charge to 

anticipate the conclusions of a recently initiated National Research Council study of CMS information 
★ 76 ★

T h e Path F o rwa r d

system capability, we would be surprised if a modern solution did not include most of the following 

elements: (1) a hardware infrastructure based on continuously upgradeable commodity data center technology; (2) a distributed, redundant, reliable storage system that logically presents as a unified, global 

file system; (3) a software infrastructure based on standard tools and APIs for distributed computing; (4) 

data consistency maintained by well-understood distributed transaction management protocols; (5) a 

well-specified protocol stack (most likely with remote procedure calls on top of TCP) and carefully specified interface formats. As discussed in Chapter Three, Federal IT projects of this magnitude frequently 

incur cost overruns and schedule slippages, and can take many years to complete. Rapid and otherwise 

achievable progress in health IT, as envisioned by ONC and (even more aggressively) by this report, could 

be forestalled or derailed if it becomes tied to CMS’s formidable IT challenges.
★ 77 ★

IX. Recommendations

A number of specific recommendations for the short- and mid-term follow from the discussions contained in this report.

The Chief Technology Officer of the United States should:

• In coordination with the Office of Management and Budget (OMB) and the Secretary of HHS, and 

using technical expertise within ONC, develop within 12 months a set of metrics that measure 

progress toward an operational, universal, national health IT infrastructure. Research, prototype, 

and pilot efforts should not be included in this metric of operational progress.

• Annually, assess the Nation’s progress in health IT by the metrics developed, and make recommendations to OMB and the Secretary of HHS on how to make more rapid progress.

The Office of the National Coordinator should:

• Move more boldly to ensure that the Nation has electronic health systems that are able to 

exchange health data in a universal manner based on metadata-tagged data elements. In particular, ONC should signal now that systems will need to have this capability by 2013 in order to 

be deemed as making “meaningful use” of electronic health information under the HITECH Act.

• Act to establish initial minimal standards for the metadata associated with tagged data elements, 

and develop a roadmap for more complete standards over time.

• Facilitate the rapid mapping of existing semantic taxonomies into tagged data elements, while 

continuing to encourage the longer-term harmonization of these taxonomies by vendors and 

other stakeholders.

• Support the development of reference implementations for the use of tagged data elements 

in products. Certification of individual products should focus on interoperability with the reference implementations.

• Set standards for the necessary data element access services (specifically, indexing and access 

control) and formulate a strategic plan for bringing such services into operation in an interoperable and intercommunicating manner. Immediate priority should be given to those services 

needed to locate data relating to an individual patient.

• Facilitate, with the Small Business Administration, the emergence of competitive companies 

that would provide small or under-resourced physician practices, community-based long-term 

care facilities, and hospitals with a range of cloud-based services.

• Ensure that research funded through the SHARP (Strategic Health IT Advanced Research 

Projects) program on data security include the use of metadata to enable data security.
★ 78 ★

T h e Path F o rwa r d

The Centers for Medicare & Medicaid Services should:

• Redirect the focus of meaningful use measures as rapidly as possible from data collection of 

specified lists of health measures to higher levels of data exchange and the increased use of 

clinical decision supports.

• Direct its efforts under the Patient Protection and Affordable Care Act toward the ability to 

receive and use data from multiple sources and formats.

• In parallel with (i.e., without waiting for) the NRC study on IT modernization, begin to develop 

options for the modernization and full integration of its information systems platforms using 

modern technologies, and with the necessary transparency to build confidence with Congress 

and other stakeholders.

• When informed by the preliminary and final NRC study reports, move rapidly to implement one 

or more of the options already formulated, or formulate new options as appropriate, with the 

goal of making substantial progress by 2013 and completing implementation by 2014. CMS 

must transition into a modern information technology organization, allowing integration of 

multiple components and consistent use of standards and processes across all the provider 

sectors and programs it manages.

• Exercise its influence as the Nation’s largest healthcare payer to accelerate the implementation 

of health information exchange using tagged data elements. By 2013, meaningful use criteria 

should include data submitted through reference implementation processes, either directly to 

CMS or (if CMS modernization is not sufficiently advanced) through private entities authorized 

to serve this purpose.

• By 2013, provide incentives for hospitals and eligible professionals to submit meaningful use 

clinical measures that are calculated from computable data. By 2015, encourage or require that 

quality measures under all of its reporting programs (the Physician Quality Reporting Initiative, 

hospitals, Medicare Advantage plans, nursing homes, etc.) be able to be collected in a tagged 

data element model.

The Department of Health and Human Services should:

• Develop a strategic plan for rapid action that integrates and aligns information systems through 

the government’s public health agencies (including FDA, CDC, NIH, and AHRQ) and benefits 

payment systems (CMS and VA).

• Convene a high-level task force to align data standards, and population research data, between 

private and public sector payers.

• Convene a high-level task force to develop specific recommendations on national standards that 

enable patient access, data exchange, and de-identified data aggregation for research purposes, 

in a model based on tagged data elements that embed privacy rules, policies and applicable 

patient preferences in the metadata traveling with each data element.
★ 79 ★

IX. Reco m m en dati o n s

• As the necessary counterpart to technical security measures, propose an appropriate structure 

of administrative, civil, and criminal penalties for the misuse of a national health IT infrastructure 

and individual patient records, wherever such data may reside.

• Appoint a working group of diverse expert stakeholders to develop policies and standards for 

the appropriate secondary uses of healthcare data. This could be tasked to the Interagency 

Coordinating Council for Comparative Effectiveness Research.

• With FDA, bring about the creation of a trusted third-party notification service that would identify and implement methods for re-identification of individuals when data analysis produces 

important new findings.

Other or multiple agencies:

• AHRQ should be funded to develop a test network for comparative effectiveness research. The 

FDA, and also other HHS public health agencies, should enable medical researchers to gain 

access to de-identified, aggregated, near-real-time medical data by using data element access 

services.

• HHS should coordinate ONC activities with CDC, FDA, and any other entities developing adverse 

event and syndromic surveillance networks.

• The Department of Defense and the Department of Veteran Affairs should engage with ONC 

and help to drive the development of standards for universal data exchange of which they can 

become early adopters.

★ 81 ★

Appendix A: 

Expert Input

Expert Input into Health Information Technology Report. PCAST is grateful for the input of these individual experts. Listing here does not imply endorsement of this report or its recommendations.

Jonathan Bush

Chief Executive Officer

Athenahealth

David Blumenthal

National Coordinator

Office of the National Coordinator for

Health Information Technology

Department of Health and Human Services

Julie Boughn

Director and Chief Information Officer, Office of 

Information Services

Centers for Medicare & Medicaid Services

Aneesh Chopra

Chief Technology Officer

Associate Director for Technology

Office of Science and Technology Policy

Janet Corrigan

President and Chief Executive Officer

The National Quality Forum

Peter Cullen

Chief Privacy Strategist

Microsoft Corp.

Nancy-Ann DeParle

Director, White House Office of Health Reform

Mary Durham

Senior Investigator

Director, Center for Health Research

Vice President for Research

Kaiser Foundation Hospitals

Spike Duzor

Director, Division of Survey Management & Data 

Release

Centers for Medicare & Medicaid Services

Carl Dvorak

Executive Vice President

Epic

Sean Eddy

Group Leader

HHMI Janelia Farm Research Campus

Colin Evans

President and Chief Executive Officer

Dossia

Craig Feied

Professor of Emergency Medicine at Georgetown 

University

Chief Health Strategy Officer, Microsoft Corp.

Douglas Fridsma

Acting Director, Office of Interoperability and 

Standards

Office of the National Coordinator for

Health Information Technology

Department of Health and Human Services

Charles Friedman

Chief Scientific Officer

Office of the National Coordinator for

Health Information Technology

Department of Health and Human Services
★ 82 ★

T h e Path F o rwa r d

John Glaser

Senior Advisor

Office of the National Coordinator for

Health Information Technology

Department of Health and Human Services

Arthur Glasgow

Senior Vice President and General Manager of 

Health Information Networks

Ingenix

Richard Hodes

Director

National Institute on Aging

U.S. National Institutes of Health

Marjorie Kanof

Managing Director, Health Care

Government Accountability Office

Martha Kelly

Assistant Director, Health Care

Government Accountability Office

Carl Kesselman

Professor of Industrial and Systems Engineering

Fellow in the Information Sciences Institute 

Viterbi School of Engineering

University of Southern California

David Kreiss

Senior Executive

Athenahealth

David C. Kibbe 

Senior Advisor, American Academy of Family 

Physicians

Chair, ASTM International E31Technical 

Committee on Healthcare Informatics

Principal, The Kibbe Group LLC

Robert Kocher

Special Assistant to the President for Health Care

National Economic Council

S. Lawrence Kocot

Deputy Director, Engelberg Center for Health 

Care Reform

The Brookings Institution

Rebecca Kush

Founder, President, and Chief Executive Officer

Clinical Data Interchange Standards Consortium 

(CDISC)

Kipp Lassetter

Chairman and Chief Executive Officer

Medicity

Kenneth Mandl

Associate Professor

Children’s Hospital Boston|Harvard Medical 

School Harvard-MIT Health Sciences and 

Technology

Mark McClellan

Director, Engelberg Center for Health Care 

Reform

Leonard D. Schaeffer 

Chair in Health Policy Studies

The Brookings Institution

Deven McGraw

Director, Health Privacy Project

Center for Democracy and Technology

Andrew McLaughlin

Deputy Chief Technology Officer

Office of Science and Technology Policy

Farzad Mostashari

Senior Advisor

Office of the National Coordinator for

Health Information Technology

Department of Health and Human Services
★ 83 ★

Appen d i x A: Expert Inpu t

Sean Nolan

Chief Architect, Health Solutions Group

Microsoft Corp.

Betty Otter-Nickerson

President

Sage

Healthcare Division

Todd Park

Chief Technology Officer

Office of the National Coordinator for

Health Information Technology

Department of Health and Human Services

Daniel Pelino

General Manager, Health Care and Life Sciences

IBM

Richard Platt

Professor and Chair, Harvard Medical School 

Department of Population Medicine

Harvard Pilgrim Health Care Institute

Thomas Reilly

Deputy Director, Office of Research, 

Development, and Information

Centers for Medicare & Medicaid Services

Andrew Slavitt

Chief Executive Officer

Ingenix

Jean Slutsky

Director, Center for Outcomes and Evidence

Agency for Healthcare Research and Quality

U.S. Department of Health and Human Services

Barry Straub

Chief Medical Officer

Centers for Medicare & Medicaid Services

Marilyn Tavenner

Principal Deputy and Chief Operating Officer

Centers for Medicare & Medicaid Services

Tony Trenkle

Office of E-Health Standards & Services

Centers for Medicare & Medicaid Services

Adindu Uzoma

Senior Fellow and Chief Scientist

Ingenix

Thomas Valuck

Senior Vice President, Strategic Partnerships

National Quality Forum

Janet Woodcock

Director, Center for Drug Evaluation and 

Research

U.S. Food and Drug Administration

★ 85 ★

Appendix B: 

Acknowledgments

Joe Alper

Writer

Aman Bhandari

Policy Analyst

Office of Science and Technology Policy

Kathleen Black

Intern

Office of Science and Technology Policy

Judith Hautala

Core Research Staff Member, Life Sciences

Science Technology Policy Institute

Peter Haynes

Senior Director, Advanced Strategies and 

Research

Microsoft Corp.

Steve Olson

Writer

Christina Viola Srivastava

Research Associate

Science Technology Policy Institute

Mark Shankar

Intern

Office of Science and Technology Policy

Leslie Tucker

Policy Director

American Board of Internal Medicine

★ 87 ★

Appendix C: 

Glossary

Anonymize–Removing all personal identifiers from data

Authentication–Determining the identity of a principal

Authorization–Determining the rights of an authenticated principal

Clinical decision support–Bringing relevant information to the clinician, at the right time and place, 

to enable optimal health care

Cloud-based–A technology that allows software to be run and data to be stored on remote servers

Comparative effectiveness research–Research that informs clinical decisions by comparing evidence 

on the benefits, harms, and effectiveness of different treatments

Data element access services–Services that are associated with crawling, indexing, security, identity, 

authentication, authorization, and privacy

Data-centric–A focus on the specific data relevant to a given task

Data element indexing–Process and infrastructure for locating data elements, similar to today’s web 

search engines

De-identified–Data with all patient identifying information removed, but with the possibility of providing information back to the patient under specified circumstances

Digital signature–Cryptographic method for ensuring that data cannot be altered except by the person 

who created them.

Electronic health record–An electronic record of health-related information for an patient that contains 

information captured in clinical visits, lab and imaging studies, and other information important to the 

patient’s medical past

Encryption–Technology of making data completely unreadable except by a person in possession of 

the corresponding “key”

Genotype–The genetic makeup of a specific human being

Health information exchange–The mobilization of electronic healthcare information across organizations within a community, region, or hospital system

Health information technology–Technologies that manage and transmit health information for use 

by providers, consumers, payers, insurers, and all the other pertinent groups

HITECH Act–An act passed by Congress in 2009 that authorizes expenditures of approximately $20 

billion over five years to promote the adoption and use of electronic health record technologies that 

would be connected through a national health information network
★ 88 ★

T h e Path F o rwa r d

Integration engines–An application of a universal exchange language that can facilitate data exchanges 

with personal health records and other types of EHRs in a cloud

Key–A piece of data that can unlock and make readable cryptographically protected information

Meaningful use–Still pending an official definition from CMS, but ARRA requires that the definition 

include e-prescribing, the ability to exchange information with other healthcare providers to improve 

care, and the reporting of clinical quality measures to CMS

Metadata–Information that characterizes data, such as contextual information

Metadata tag–A tag accompanying each piece of data describing the attributes, provenance, and 

required security protections of that piece of information

Middleware–Software used to extract and reformat data elements from existing clinical systems

Patient-centric–Healthcare organized around the needs, capabilities, and desires of patients, with the 

goal of optimizing care in part through greatly improved uses of data

Personal health record–An electronic record of health information that is maintained, controlled, and 

shared by a patient-consumer

Personalization–Tailoring medical care to be optimized for the unique individual characteristics of the 

particular patient

Physician Quality Reporting Initiative–Established under the 2006 Tax Relief and Health Care Act, 

the initiative provides physicians with a financial incentive to voluntarily provide CMS with a report on 

three or more chosen quality measures that applies to their Medicare patient base

Post-marketing surveillance–A system by which to identify adverse events that did not appear during 

the drug approval process

Primary care medical home–A model of care that places the patient and primary care physician at 

the center of a virtual organization that is paid a fee to coordinate all care the patient receives from 

specialists and other providers

Randomized clinical trials–A type of clinical trial in which participants are randomly assigned to different forms of treatment

Semantics–The clinical or operational meaning of data

Service-oriented architecture–An approach to health IT that involves using software policies, practices, 

and frameworks to enable one user to access sets of “services” on another party’s computers and data

Standardized health records–Health records that follow a standardized format that is comparable to 

all other formats and can be accessed by all necessary parties

Syndromic surveillance–Surveillance using health-related data that precedes diagnosis and signals a 

sufficient probability of a case or an outbreak to warrant a further public health response

Syntax–The formatting of data that are exchanged, as well as the details of the exchange protocols, 

including privacy protection and other important aspects
★ 89 ★

Appen d i x C : Gl o s s a ry 

Tagged data elements–Data accompanied by metadata describing the attributes and privacy protections of the data

Two-factor authentication–The use of two of the following three in determining the identify of a 

principal: physical credentials (such as smartcards), biometrics (such as fingerprints), and a secret (such 

as a password)

Universal exchange language–A common language and format in which all electronic health systems 

can exchange data

Usability–The ease with which physicians and other healthcare providers can learn to use electronic 

records, capture data from clinical encounters, and then make use of the data to improve care delivery

Value-based purchasing–The concept that buyers should hold providers of health care accountable 

for both the cost and quality of care

VistA–An integrated system of software applications that directly supports patient care at Veterans 

Health Administration facilities

XML–Also known as extensible markup language, a set of rules for encoding documents in machinereadable form

★ 91 ★

Appendix D:

Abbreviations

ACO–Accountable Care Organization

AHRQ–Agency for Health Care Research and Quality

ARRA–American Recovery and Reinvestment Act

CDA–Clinical Document Architecture

CDC–Centers for Disease Control & Prevention

CDS–Clinical Decision Support

CMS–Centers for Medicare & Medicaid Services

EHR–Electronic Health Record

FDA–Food and Drug Administration

HIE–Health Information Exchange

HHS–U.S. Department of Health and Human Services

HIPAA–Health Insurance Portability and Accountability Act

HL7–Health Level 7, Inc.

IHE–Integrating the Healthcare Enterprise

IOM–Institute of Medicine

ONC–Office of the National Coordinator

NHIN–Nationwide Health Information Network

NIST–National Institute of Standards and Technology

PCIP–Primary Care Information Project

PCMH–Primary Care Medical Home

PHR–Personal Health Record

PPACA–Patient Protection and Affordable Care Act

RHIO–Regional Health Information Organizations

SHARP–Strategic Health IT Advanced Research Projects

VHA–Veterans Health Administration


President’s Council of Advisors on Science and Technology

http://www.whitehouse.gov/ostp/pcast