Final Report

November 2002

Department of Health and Human Services Data Council

Centers for Disease Control and Prevention

National Center for Health Statistics

National Committee on Vital and Health Statistics

Shaping a

Health Statistics

for the

Vision

21st Century

iii

Shaping a Health Statistics Vision for the 21st Century

Table of Contents

Table of Contents

Table of Contents . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . iii

Acknowledgments . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . iv

Foreword . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . v

Executive Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . vi

Preface . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . xvi

Chapter One: What are Health Statistics? . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1

Defining health statistics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1

Identifying the purposes of health statistics . . . . . . . . . . . . . . . . . . . . . . . . . . 2

Uses of health statistics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3

Defining the health statistics enterprise . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5

Chapter Two: A Model of the Influences on the Population’s Health . . . . . . . . . 8

Need for and uses of the model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8

Overview of the model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8

Mapping the current enterprise using the model . . . . . . . . . . . . . . . . . . . . . . 13

Using the model to describe issues and gaps . . . . . . . . . . . . . . . . . . . . . . . . 15

Chapter Three: Developing, Evaluating and Improving Health Statistics . . . . . 20

The health statistics enterprise and the Health Statistics Cycle . . . . . . . . . . 20

Elements in the Health Statistics Cycle . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20

Mapping the current system using the model of the Health 

 Statistics Cycle . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26

Major issues and gaps in health statistics development, evaluation, and 

 improvement . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 28

Chapter Four: A Vision for the Health Statistics Enterprise . . . . . . . . . . . . . . . . 35

Mission . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 35

Overarching conceptual framework . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 35

Core values . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 36

Guiding principles . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 36

The health statistics enterprise and the NHII . . . . . . . . . . . . . . . . . . . . . . . . . 47

NCVHS Recommendations for Achieving the Health Statistics Vision for the 

 21st Century . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 49

Developing the recommendations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 49

Overview of recommendations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 49

Detailed recommendations for achieving the ten guiding principles . . . . . . . . . 50

Recommendations for moving toward the adoption of the overarching 

 conceptual framework . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 62

Summary of recommendations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 66

Glossary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 69

Table 1: Approaches for gathering information on influences on health . . . . . . . 72

Table 2: Programs and activities in the Health Statistics Cycle . . . . . . . . . . . . . 80

Appendix: National Committee on Vital and Health Statistics, 2002 

 Membership . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 82
iv

Shaping a Health Statistics Vision for the 21st Century

Acknowledgements

The development, writing, and production of this report involved a collaboration 

of many individuals and organizations, starting with the National Committee on Vital 

and Health Statistics (NCVHS), the Centers for Disease Control and Prevention’s 

(CDC) National Center for Health Statistics (NCHS), and the DHHS Data Council. The 

principal authors of the report were Daniel J. Friedman (NCVHS), Edward L. Hunter 

(CDC/NCHS), and R. Gibson Parrish (CDC). The NCVHS Workgroup on Health 

Statistics for the 21st Century provided invaluable ongoing guidance, editing, and 

commentary: Vickie Mays, Paul Newacheck, and Barbara Starfield (Daniel J. Friedman, 

chair). The report also benefited immeasurably from the generous contributions of the 

many individuals who participated in the extensive national consultative process outlined 

in Figure 1 of the report.

Essential roles in the development of the report were also played by Robert 

Weinzimer, Marjorie Greenberg, Lisa Broitman, and Debbie Jackson who served as staff 

to NCVHS and NCHS; Susan Kanaan, who wrote the executive summary and the policy 

makers’ summary; Judy Kaplan, who provided invaluable editorial advice; and 

Odell D. Eldridge, who coordinated the formatting and production of the report. Finally, 

Don Detmer and John Lumpkin played important roles in encouraging and supporting the 

process as Chairs of the NCVHS, as did NCHS Director, Edward J. Sondik, who initially 

conceptualized the need for such a re-evaluation of American health statistics.

Acknowledgments
v

Shaping a Health Statistics Vision for the 21st Century

Foreword

Foreword

Information is the essential, invisible infrastructure upon which public health and 

health policy is built. Yet, the role of health information is poorly articulated, and the 

processes and mechanisms through which our nation manages information and translates it 

into effective policies and programs are poorly understood.

Two recent reports seek to redress this problem. First, in November 2001 the 

National Committee on Vital and Health Statistics (NCVHS) published Information for 

Health: A Strategy for Building the National Health Information Infrastructure (NHII). 

The NHII report outlines strategic directions to share information and knowledge 

appropriately, when and where needed. The interconnections and utility of a functioning 

NHII can, with foresight, planning and vision, improve the public’s health and health care.

Now, the attached report Shaping a Health Statistics Vision for the 21st Century

describes a strategic vision for health statistics and the health statistics enterprise in the 

U.S. Health statistics are numerical data that characterize the health of the population and 

the influences and actions that affect the health of the population. Health statistics can 

be used to create fundamental knowledge and to guide health policy and programs. This 

report, developed through a partnership of the NCVHS, the Centers for Disease Control 

and Prevention’s National Center for Health Statistics, and the Department of Health 

and Human Services (DHHS) Data Council draws on a national consultative process 

that involved numerous stakeholders in the health statistics enterprise. It also includes 

NCVHS recommendations for implementing this vision and calls for stronger integration 

and coordination in order to improve health statistics and ultimately the nation’s health.

These two reports and their recommendations complement each other in important 

ways; some of these interconnections are described in the body of the attached report. 

The development of the NHII is essential for improving the health statistics enterprise 

and providing the electronic infrastructure through which data can be compiled, 

communicated, and translated into usable statistics. Both reports emphasize the 

importance of improved coordination of efforts, call for the development of standards to 

guide multiple parties, and stress the importance of strong protections for individually 

identifiable health information. 

The tragic events in the country’s recent history underscore the immediate need for 

a fully functioning and effective public health system, which will, in turn, rest on a strong 

health statistics enterprise and NHII. We hope that the principles and recommendations 

cited in this report, along with the recent report on the NHII, can prompt the strategic 

actions required to move forward toward this goal.

 

 

 

 John R. Lumpkin, M.D., M.P.H.

 Chair, National Committee on Vital and Health Statistics
vi

Shaping a Health Statistics Vision for the 21st Century

Executive Summary

Executive Summary

Preface

Health statistics are a cornerstone of our health system. They provide us with critical

data to assess the health of our population and to make informed decisions about how to 

best direct our health-related resources and activities. However, health statistics in the 

United States have been hampered by a lack of clarity about definitions, appropriate foci, 

and agendas. Although health statistics already provide important information for health 

policy and programs, current efforts do not reflect a broad view of population health and 

the factors that influence health, nor coalesce around a shared vision that could bring 

about greater cohesion and efficiency in the development and use of health statistics. 

Because of this, health statistics have not achieved their full potential to support and 

guide policy and programs in the U.S. 

To develop this shared vision for U.S. health statistics, three groups led a national 

consultation process that involved a broad range of stakeholders and lasted more than two 

years. The National Committee on Vital and Health Statistics (NCVHS)∗

, the National 

Center for Health Statistics (CDC/NCHS), and the Data Council of the U.S. Department 

of Health and Human Services (DHHS) offered stakeholders multiple opportunities to 

share their experience and contribute to the vision. The effort, which is summarized in 

Figure 1 on page xviii, was intended to provide broad-based guidance on the future of 

health statistics to federal, state and local governments, as well as to academia and the 

private sector. 

More than 200 stakeholderspolicy makers, public health and health care 

professionals, health statistics practitioners, researchers, and otherstook advantage of 

the following opportunities to give input:

• Four expert discussion groups in Washington, D.C.

• Three local discussion groups in New Mexico, Pennsylvania, and Louisiana

• A National Academy of Sciences workshop

• Four public hearings in Chicago, Raleigh-Durham, San Francisco, and 

Washington, D.C.

• Presentations and town hall meetings at multiple national professional meetings

• Invitations to provide written comments

This document presents the results of the visioning process: a definition of 

health statistics, models of the factors that influence the health of populations and of 

an ideal health statistics cycle, and a vision for the health statistics enterprise. The 

document concludes with NCVHS recommendations for implementing the vision. The 

Committee’s recommendations place special emphasis on building a stronger integrating 

and coordinating “hub” for the health statistics enterprise. 

*NCVHS is the statutorily mandated public advisory body on health information policy to the Secretary of the 

U.S. Department of Health and Human Services. The NCVHS Workgroup on the 21st Century Vision for Health 

Statistics conducted this project for the Committee. 
vii

Shaping a Health Statistics Vision for the 21st Century

Executive Summary

1. What Are Health Statistics

Health statistics are numerical data that characterize the health of a population

and the factors that influence its health. In contrast with the related terms, “health data” 

and “health information,” health statistics are distinguished by their focus on 1) 

quantification, 2) aggregation of data from observations on individuals, their 

communities, and the context of their communities, and 3) population health and 

the influences on it.

Health statistics are based on such information sources as surveys, patient 

encounters with the health care system, registries, and health administrative data. They 

facilitate understanding of the health status of individuals, groups, and society as a whole. 

Health statistics have three major uses: creating fundamental knowledge; guiding the 

assessment, development, and evaluation of health policy; and informing and evaluating 

the impact of population health programs and interventions as well as personal health 

decisions. They provide a basis for public and private decisions at local, state, and 

national levels. 

The health statistics enterprise is the infrastructure and the activities or processes 

that produce health statistics. The highly decentralized and diverse health statistics 

infrastructure in the U.S. consists of public and private organizations and individuals at 

all geopolitical levels. Its activities include the collection, aggregation and compilation, 

analysis and translation, and evaluation of data. The health statistics enterprise in the U.S. 

has these characteristics:

• It focuses on the health of the entire U.S. population and its subpopulations. 

• It serves the public interest and generates products that are public goods.

• It engages in systematic and organized inquiry.

• It strives for scientific objectivity.

• It involves multiple disciplines.

• It links U.S. health statistics activities to those of international partners in health 

and health statistics.

Many factors influence the health of a population, and to be useful, health statistics 

must provide a comprehensive and coherent picture of them all. Gathering and presenting 

data on diseases alone limits understanding of the complex interactions that affect health 

and encourages concentration on the prevention and management of disease instead of a 

more broadly integrated approach to maximizing health and reducing illness. 

In the health statistics visioning process, the participants agreed on the need for a 

model with a broad view of population health and the influences on it. Such a model 

2. A Model of the Influences on the Population's Health
viii

Shaping a Health Statistics Vision for the 21st Century

Executive Summary

could guide the regeneration, ongoing management, and evaluation of the health statistics 

enterprise. It could help identify data gaps and aid in understanding specific health issues. 

Based on the consultative process and the work of several authors, a model (Figure 

2 of the report, found in its full detail on page 9) was developed with three components:

• Measures of a population’s health, i.e., of the entire U.S. population or any 

defined subpopulation 

• Factors acting at community and individual levels (biological characteristics, the 

built environment, social and economic resources, health programs, collective 

lifestyles and health practices, and health services)

• The context or broad setting in which the population exists and acts (the natural 

environment, the cultural context, and the political context)

Influences on the population's health
ix

Shaping a Health Statistics Vision for the 21st Century

This model of the influences on and measures of population health is a useful tool 

for organizing and describing the data gathered and analyzed by the health statistics 

enterprise at national, state, and local levels (as shown in Table 1 on page 72). It reveals 

the unevenness in the enterprise’s capacity to provide data on all influences on population 

health. This unevenness is the result of a number of systemic problems, including:

• A failure to incorporate a broad definition of the population’s health 

• A predominant focus on individual health and its determinants 

• A shortage of state and local data, especially survey data

• Inconsistent quality and quantity of data on vulnerable populations 

• Inadequate longitudinal and life-cycle data 

• A failure to adequately use available data and data sources

3. Developing, Evaluating and Improving Health Statistics 

To support population health effectively, the health statistics enterprise must engage 

in a continuing process of evaluation, improvement, and regeneration. The stages of 

this process are part of a “health statistics cycle” (Figure 3 of the full report, found on 

page 21) that has seven components, ideally tied together by an integrating “hub.” The 

components are:

• Defining data needs and analytic approaches

• Specifying necessary data attributes

• Identifying appropriate data sources and strategies

• Collecting, aggregating, and compiling data

• Analyzing statistics

• Translating statistics for users

• Evaluating the extent to which needs are met

Executive Summary

Table 2 of the full report (page 80) shows the major elements of the health statistics 

cycle with examples of the organizations and entities that carry out its functions at 

national, state and local levels. 

Although the health statistics enterprise has many strengths, and important data 

are collected, the vision process participants repeatedly pointed out major gaps in the 

availability of data and in the ability of the current health statistics enterprise to address 

data users’ needs. The major causes of these gaps are:

• Insufficient connections between producers and users of data

• Lack of geographic and other detail

• Lack of timeliness in making data available

• Difficulty of finding and using existing data

• Lack of resources, jeopardizing major data sources 

• Lack of enterprise-wide coordination and integration
x

Shaping a Health Statistics Vision for the 21st Century

Executive Summary

Health statistics cycle

4. A Vision for the Health Statistics Enterprise

Out of the consultation and collaboration process emerged a vision for 21st century 

health statistics that was refined by NCVHS, CDC/NCHS, and the DHHS Data Council. 

The vision involves a mission, an overarching conceptual framework, core values, and 

guiding principles. This report proposes that the mission of the health statistics enterprise 

is to efficiently provide timely, accurate, and relevant information that can be used to 

improve the population’s health. This can be achieved by operating within an overarching 

conceptual framework, adopting four core values, and implementing ten guiding 

principles.

The hub that is needed to integrate the activities of the health statistics cycle should 

coordinate these activities, stimulate collaborative efforts, set standards, periodically 

review and revise the vision, generate new methods and approaches, and protect privacy, 

confidentiality and security. It was the consensus of participants that new approaches 

to enterprise-wide coordination and integration are needed because existing efforts are 

largely ineffective. 
xi

Shaping a Health Statistics Vision for the 21st Century

The conceptual framework for the 21st century health statistics vision has these 

attributes:

• It focuses on health, the population, and the community.

• It emphasizes the distribution and level of health within the population.

• It delineates major influences on health.

• It guides a research agenda for improving the health of the population.

Briefly stated, the core values for the health statistics enterprise are:

• Maintaining the confidentiality and security of individually identifiable health 

information

• Maximizing the scientific integrity of all aspects of health statistics while 

acknowledging the specific ways in which the political, cultural, and business 

contexts may affect data collection, analysis, and interpretation

• Optimizing the enterprise’s accountability to its users to ensure the availability of 

the information that is needed for improving the nation’s health

• Ensuring the enterprise’s accountability to its data suppliers to minimize their 

burden and to provide them with timely feedback.

Executive Summary

Actualizing these core values requires the implementation of ten guiding principles: 

1. Enterprise-wide planning and coordination to ensure relevance to local, 

 state, and national policy and program decision-making and to an overall

 conceptual framework of the influences on the health of populations

2. Broad collaboration among data users, producers, and suppliers at local, state,

 and national levels to ensure efficiency of the health statistics enterprise and 

 usefulness of the data that it produces

3. Rigorous policies and procedures for protecting the privacy of individuals and 

 the confidentiality and security of data

4. Flexibility to identify and address emergent health issues and needs

5. Use of data standards to facilitate sharing and comparability of data

6. Sufficient detail at different levels of aggregation to support local, state, and 

 national policy and programmatic decision-making

7. Integrated, streamlined data collection for multiple purposes

8. Timely production of valid and reliable health statistics

9. Appropriate access to and ease of use of health statistics 

10. Continuous evaluation of the completeness, accuracy, and timeliness of health

 statistics and of the ability of the health statistics enterprise to support their 

 production
xii

Shaping a Health Statistics Vision for the 21st Century

Executive Summary

NCVHS Recommendations for Achieving the 

Health Statistics Vision for the21st Century

After working closely with its partners to identify a vision for health statistics, 

the National Committee on Vital and Health Statistics developed recommendations for 

realizing the vision. The recommendations, which appear on pages 49-68 of the full 

report, are summarized in a table at the end of this Executive Summary. 

NCVHS believes that the top priority for realizing the vision is to build the 

integrating and coordinating hub for the health statistics enterprise. Four NCVHS 

recommendations relate to this priority: 

• Assign responsibility and authority for health statistics leadership within DHHS

to a reconstituted National Center for Health Statistics, supported by a strong 

Board of Scientific Counselors.

• Establish a national Health Statistics Planning Board with overall responsibility 

for planning and agenda setting for health statistics in the United States. 

• Designate overall responsibility for health statistics planning and coordination 

activities within each state’s government to a single state agency, supported by 

autonomous state Health Statistics Planning Boards. 

• Develop appropriate graduate and in-service training and continuous education 

addressing all elements of the health statistics cycle. 

Carrying out these four recommendations, which relate to guiding principle 1, 

would facilitate the achievement of the Committee’s recommendations for the other 

nine guiding principles. Those recommendations focus on research agendas, data set 

development, health statistics reports, dissemination of best practices, training, and other 

key topics. To ensure that health policy-making keeps its focus on the core influences 

on the health of populations, an overarching conceptual framework must guide the 

enterprise.

Finally, the 21st century health statistics enterprise in the U.S. must be viewed within 

the context of the National Health Information Infrastructure (NHII), which has the 

potential to connect all health decision-makers to sound information and to each other. 

NCVHS recommended a strategy for building the NHII in a November 2001 report.*

The vision for health statistics contributes to the development of the Population Health 

Dimension of the NHII. Participants in the health statistics enterprise must become 

actively and enthusiastically engaged in this wider effort.

* NCVHS, Information for Health: A Strategy for Building the National Health Information Infrastructure, 15 

November 2001.
xiii

Shaping a Health Statistics Vision for the 21st Century

Executive Summary

Summary of NCVHS recommendations

Recommendations on data access

• Use the World Wide Web to improve access to national, state, and local data on 

the population’s health and influences on the population’s health. [GP 9.1]

• Disseminate throughout the health statistics enterprise the best methods for 

maximizing appropriate access to and ease of use of health statistics. [GP 9.3]

• Enhance regularly released health statistics reports to reflect an overarching 

conceptual framework of influences on the population’s health. [CF 4]

Recommendations on data set development

• Develop systems to actively monitor the population’s health and potential 

influences on the population’s health in order to identify emerging problems. 

[GP 4.1]

• Develop mechanisms to rapidly modify the samples, data collection strategies, 

and data collection instruments of ongoing data collection systems in response to 

emerging issues. [GP 4.2]

• Geocode all ongoing data sets that feed the health statistics enterprise to the 

census block group level. [GP 6.2]

• Develop and validate topic-specific question modules for population-based

surveys to support state and local agencies’ development of small-area health 

statistics. [GP 6.3]

• Identify duplicative data collection efforts and eliminate redundancy. [GP 7.1]

• Support and fund efforts within individual states to integrate or better coordinate, 

as appropriate, discrete data systems. [GP 7.2]

• Support and fund ongoing multi-purpose data collection systems and data 

integration efforts. [GP 7.3]

• Develop and adopt benchmarks for timeliness of release of data and reports 

derived from those data. [GP 8.1]

• Assure that appropriate measures of functional status and well-being are included 

in ongoing systems that are a part of the health statistics enterprise. [CF 1]

• Prepare and provide to staff of state and Federal agencies with health statistics 

responsibilities a manual and a “tool kit” of data sets for use in community-level 

analyses. [CF 2]

• Develop person-based, longitudinal data sets and surveys in order to develop 

portraits of influences on the population’s health throughout the life cycle. [CF 3]
xiv

Shaping a Health Statistics Vision for the 21st Century

Recommendations on data standards

• Harmonize the CDC public health conceptual data model with the overarching 

conceptual framework for the health statistics enterprise in order to facilitate the 

development of standards. [GP 5.1]

• Adopt or, if necessary, develop standards for data elements commonly used in 

all methods of data collection, for electronically transmitting data, for presenting 

and disseminating data, and for providing electronic access to data. [GP 5.2]

• Provide guidance for implementing and auditing the use of standards by the 

health statistics enterprise. [GP 5.3]

• Contribute to the national standards setting process. [GP 5.4]

Recommendations on enterprise structure

• Assign overall responsibility for health statistics leadership within DHHS to 

a reconstituted National Center for Health Statistics, supported by a strong Board 

of Scientific Counselors. [GP 1.1]

• Establish a national Health Statistics Planning Board with overall responsibility 

for planning and agenda setting for health statistics in the United States. [GP 1.2]

• Assign overall responsibility for health statistics planning and coordination 

activities within each state’s government to a single state agency. Establish a

Health Statistics Planning Board in each state with overall responsibility for 

planning and agenda setting for health statistics within the state. [GP 1.3]

Recommendations on evaluation

• Compile feedback on the practical applications of health statistics to policy, 

research, and public health practice and disseminate these findings to providers 

of data, policymakers, and the public. [GP 10.1]

• Conduct periodic evaluations of NCHS’ adherence to the National Academy of

Sciences’ attributes of a Federal statistical agency. [GP 10.2]

Recommendations on privacy policy 

• Develop a code of fair information practices for the health statistics enterprise.

[GP 3.1]

• Develop guidance on the application of the HIPAA Standards for Privacy of 

Individually Identifiable Health Information to health statistics. [GP 3.2]

• Develop model state and Federal privacy, confidentiality, and security statutes for 

government-sponsored health statistics. [GP 3.3]

• Develop a toolbox of privacy, confidentiality, and security best practices for use 

throughout the health statistics enterprise. [GP 3.4]

Executive Summary
xv

Shaping a Health Statistics Vision for the 21st Century

Recommendations on a research agenda 

• Develop and fund a research agenda for the study of methods and technologies to

enhance the privacy, confidentiality, and security of health statistics. [GP 3.6]

• Develop and fund a research agenda to explore new data collection strategies that 

can rapidly and flexibly provide data on emerging influences on the population’s 

health; assess the validity and reliability of items used in key ongoing data 

collection systems; and estimate any loss in accuracy from early publication of 

provisional, incomplete data from ongoing data collection systems. [GP 4.3]

• Develop methods to validly and reliably estimate important indicators of the 

health, and of the influences on the health, of state and local populations. [GP 6.1]

• Develop and implement methods and technologies that will maximize the 

timeliness of release from ongoing data collection systems of regularly scheduled 

reports. [GP 8.2]

• Provide controlled access to potentially identifiable individual-level data on the 

population’s health and influences on the population’s health. Such access would 

be provided, at designated sites, to researchers pursuing approved projects. 

[GP 9.2]

• Support research into how health statistics can be used more effectively to 

understand the causal relationships between specific influences on health and 

functionality and well-being in general and specific high priority diseases. [CF 6]

Recommendations on training

• Expanded graduate, in-service, and continuous training opportunities should be

developed and offered in focusing on all elements of the health statistics 

enterprise. [GP 1.4]

• Develop a model training agenda and training materials for use throughout the 

health statistics enterprise focusing on fair information practices, privacy, 

confidentiality, and security. [GP 3.5]

• Provide training about concepts related to the population’s health and influences 

on the population’s health at professional meetings attended by staff of state and 

Federal agencies with health statistics responsibilities. [CF 5] 

Executive Summary
xvi

Shaping a Health Statistics Vision for the 21st Century

Preface

In 1998, Edward J. Sondik, Ph.D., Director of CDC’s National Center for Health 

Statistics (NCHS), asked the National Committee on Vital and Health Statistics 

(NCVHS), the statutorily mandated 

public advisory body on health 

information policy to the Secretary 

of the U.S. Department of Health and 

Human Services (DHHS), to provide 

guidance on the development of goals 

for health statistics for the next ten to 

fifteen years. NCVHS responded by 

establishing the Workgroup on the 21st

Century Vision for Health Statistics1

and by forming a partnership among 

the Workgroup, NCHS, and the DHHS 

Data Council.2

In 1999, the NCVHS/NCHS/

DHHS Data Council partnership 

initiated a 21st century health statistics 

vision process, which has included both 

fact-gathering and consensus-building. 

Through this process, the three 

partners attempted to identify groups 

and individuals that should become 

stakeholders in the vision process; to 

define health statistics; to delineate 

health statistics needs; and to develop a 

shared vision for health statistics in the 

U.S. This process has involved more 

than 200 participants, who have provided reflections, suggestions, and recommendations 

through national and local discussion groups, a National Academy of Sciences workshop, 

regional public hearings, and presentations and town hall sessions at meetings of 

professional associations.3

 Figure 1 provides an overview of the health statistics vision 

process from 1999 through 2002.

Opportunities for providing input into 

the vision process

• Four expert discussion groups held 

in Washington, D.C.–48 participants 

in total

• Three local discussion groups–held 

in Albuquerque, Harrisburg, and 

New Orleans–40 participants in total

• Workshop held in Washington,

D.C., by the National Academy 

of Sciences’ Committee on National 

Statistics–90 participants 

• Four regional public hearings–

held in metropolitan Chicago, 

Raleigh-Durham, San Francisco,

and Washington, D.C.–74 

participants in total

• Presentations and town hall

meetings held at meetings of the 

Association for Health Services

Research, the Association of

Maternal and Child Health

Programs, and the National

Association for Public Health

Statistics and Information Systems

1

The Appendix contains a list of NCVHS members.

2

The DHHS Data Council coordinates all data collection and analysis activities of DHHS. Its membership 

consists of all Assistant Secretary and Agency Administrator level DHHS officials, the DHHS Privacy Advocate, 

and the Senior Advisor to the Secretary on Health Statistics, a dual position held by the Director of NCHS. 

3

A record of these sessions and hearings, along with lists of many of the individuals making contributions 

to the vision process can be found at http://ncvhs.hhs.gov/hsvision/visiondevelopment.html [accessed 1 

November 2002].

Preface
xvii

Shaping a Health Statistics Vision for the 21st Century

4

NCVHS, Shaping a Vision for 21st Century Health Statistics: Interim Report, June 2000, Available from:

http://www.ncvhs.hhs.gov/hsvision/Vision21stCentury.pdf [accessed 1 September 2002].

Participants in the vision process have generously committed their time and 

expertise. They offered detailed written and oral feedback on the June 2000 interim 

report4

 and were invited to proffer recommendations for inclusion in the report.

The health statistics vision process has revealed that health statistics in the United 

States have been hampered by lack of clarity about what constitute health statistics, about 

what practitioners of health statistics should focus on now, and about what they should 

focus on in the future. Chapter One defines health statistics and provides examples to 

illustrate their use and importance. Chapters Two and Three discuss the factors that 

influence the health of populations, the components of the health statistics enterprise in 

the United States that attempt to measure these factors, and the gaps in the enterprise. 

Following these background chapters, Chapter Four portrays a vision for the U.S. health 

statistics enterprise for the 21st century, including its mission, core values, and guiding 

principles. Chapters One through Four are joint products of the NCVHS/NCHS/DHHS 

Data Council partnership. Finally, the last section of the document presents NCVHS’s 

recommendations for implementing the vision delineated in Chapter Four.

Preface
xviii

Shaping a Health Statistics Vision for the 21st Century

Preface

Figure 1. Joint NCVHS, NCHS, and DHHS Data Council process for 

developing the 21st century vision for health statistics
1

Shaping a Health Statistics Vision for the 21st Century

Chapter 1 What are Health Statistics? 

NCVHS Recommendations for Implementing the vision

Defining health statistics

The collection, interpretation, and use of health statistics in the United States have 

been hampered by lack of clarity about what is included in “health statistics” and what the 

nation’s health statistics priorities should be now and in the future. This lack of clarity is 

illustrated by the absence of definitions of health statistics in the American public health 

literature.1

Health statistics are defined in this report as numerical data that characterize the 

health of a population and the influences and actions that affect the health of a population. 

These influences include the environment; genetic and other biological characteristics; 

health services; community attributes; and the 

political and cultural contexts. Health statistics 

support the study of the interaction of these 

influences as well as the study of the way 

specific elements in each of these areas (such 

as the health services system or environmental 

exposures) influence the health of populations. 

Health statistics are used to design, implement, 

monitor, and evaluate specific health policies and programs. Properly organized 

and communicated, health statistics enable citizens, policy makers, public health workers, 

and health care providers to assess local or national health, mobilize to improve it, and 

evaluate the success of those efforts.

Defining health statistics is difficult because there are other terms that are often used 

interchangeably but have other meanings or connotations. For example, the term “health 

data” is often used to refer both to a single factual observation (such as the age of an 

individual) and to the aggregation of such observations (such as the age distribution of a 

population). Health statistics, which focuses on populations, would only be used to refer 

to the latter.

Similarly, “health information” is very inclusive and may refer to raw, analyzed, 

quantitative, or qualitative observations, records, or other facts on individuals, groups of 

individuals, or populations. For example, health information refers not only to the age 

of an individual or to the age distribution of a population, but also to knowledge derived 

from research on the health effects of aging, and to patient-oriented information on how 

to treat illnesses associated with aging. Although health information includes health 

Chapter One: What are Health Statistics?

Health statistics are numerical 

data that characterize the 

health of a population and the 

influences and actions that 

affect the health of a population.

1

In fact, the only definition of health statistics in a frequently cited public health volume is in John Last’s A 

Dictionary of Epidemiology (Last, J., ed., A Dictionary of Epidemiology, 4th edition, Oxford University Press, 

Oxford and New York, 2001). It is worthy of note that Professor Last is on the faculty of the University of 

Ottawa.
2

Shaping a Health Statistics Vision for the 21st Century

statistics, its broad and multiple uses render it overly general for the purpose of this 

report.2

Health statistics, then, are distinguished by their focus on 1) quantification,

2) aggregation of data from observations on individuals, their communities, and the 

context of their communities, and 3) population health and the influences on it.

Health statistics provide information about aggregations of people, institutions, 

organizations, or health events, rather than information about an individual person or 

event. Health statistics are created at the aggregate population or sub-population levels. 

However, health statistics are typically created from raw data collected on individuals 

(or from the context in which they live and work), and data linkage may occur at either 

geographic area or individual levels. Regardless of whether linkage occurs at the 

individual or aggregate level, health statistics provide information about populations and 

sub-populations, and never about individuals.

Gold standard data sets that are the source of health statistics contain information 

that can be scientifically generalized to the entire population or a designated subpopulation. These gold standard data sets can also be evaluated for completeness of 

ascertainment. In practice, since gold standard data sets are not always available or 

affordable, specific data needs must be evaluated in order to determine the level of 

completeness and quality required.

Health statistics are based upon data sets derived from numerous data sources and 

collected through several different modes of data collection. Health statistics are drawn 

from population-based health surveys (such as the Behavioral Risk Factor Surveillance 

System); surveys of health service institutions and individual health care providers (such 

as the National Health Care Survey); administrative data generated through ongoing 

health service operations (such as Medicaid claims data or state-wide hospital discharge 

data); reportable disease registries (such as state participants in the National Program 

of Cancer Registries); vital records registries; and other data collection systems not 

directly focusing on health. Health statistics may be based upon data originally intended 

to characterize the health of a population and the factors that influence it (such as that 

collected in the National Health Interview Survey) or may be based upon data originally 

intended for other purposes (such as information collected through the Census of 

Population or the Environmental Protection Agency’s Aerometric Information Retrieval 

System). The data sets upon which health statistics are based may be collected on a 

periodic or an ongoing basis. 

Identifying the purposes of health statistics

Health statistics fulfill essential functions for public health, the health services 

system, and our society. Most basically, health statistics enable understanding of where 

Chapter 1 What are Health Statistics? 

2

Another term in common use is “surveillance.” As applied to health, “surveillance is a continuous and

systematic process of collection, analysis, interpretation, and dissemination of descriptive information for 

monitoring health problems (Buehler, J., “Surveillance,” Modern Epidemiology, Rothman, K. and Greenland, S., 

ed., 2nd ed., Lipincott Williams & Wilkins, Philadelphia, 1998, pp. 435-457). The distinction between statistics 

and surveillance is the continuous nature of surveillance, its use of any descriptive information–not just 

numerical data, and its focus on health problems, as opposed to populations.
3

Shaping a Health Statistics Vision for the 21st Century

we stand in terms of health as individuals, as subgroups, and as a society. Through health 

statistics, we gain a collective understanding of our health, our collective experience 

with the health services system, and our public health problems and challenges. Health 

statistics establish a basis for comparisons between subpopulation groups or geographic 

areas. Health statistics enable us to look at the distribution of health in the U.S., 

revealing, for example, the existence of health disparities between racial, ethnic, and 

socioeconomic groups, between Americans with and without substantial functional 

disabilities, and across rural, suburban, and central city areas. Health statistics document 

our current and past reality, and provide us with the ability to identify health trends and to 

anticipate future trends in health and health services.

Health statistics provide us with the information upon which we can base important 

public decisions at the local, state, and national levels. Once we have made those public 

decisions, health statistics make us accountable for the decisions that we have made. 

Health statistics thus enable us to evaluate the impact of health policies and health 

programs on the public’s health. 

In short, health statistics give us the information we need to improve the 

population’s health and to reduce health disparities. 

Uses of health statistics

Health statistics have three major uses. 

First use: creating fundamental knowledge 

about the health of populations and subpopulations, influences on health, and 

interactions among those influences. The 

fundamental knowledge created by health 

statistics is varied, and can contribute to 

increasing our understanding of the health care 

system and the health of populations; of the 

influences on well-being, functional status, and 

disease; of relationships among community 

resources and health; and of changes in the 

health of a population and its health care, 

particularly as major changes are occurring in private markets and Federal and state 

policy.

Uses of health statistics

• Create fundamental knowledge

• Develop information to guide 

health policy development,

assessment, and evaluation

• Generate information to guide

implementation, targeting,

evaluation, and refinement of

population health programs 

and interventions and to guide 

personal health decisions

Chapter 1 What are Health Statistics? 
4

Shaping a Health Statistics Vision for the 21st Century

Use of health statistics to create fundamental knowledge: heart disease

Health statistics provide insight into factors associated with heart disease and 

its impact on the population. Large-scale population surveys yielded some of 

the first evidence of the association between heart disease and cholesterol, 

hypertension, and behaviors such as diet, exercise, and smoking. Statistics 

document the distribution of risk factors among the population, allowing us to 

understand differentials in health. And health statistics provide insight into the 

impact of heart disease on the population and economy through mortality data 

that track trends, surveys that document lost productive time to heart disease, and 

studies that document the burden of illness on the health care system and the 

economy.

Second use: developing information to guide health policy development, assessment, 

and evaluation. Health statistics help to establish health policy priorities, based upon 

assessment of the health of a population and its health trends, disparities, and needs as 

well as the quality and efficiency of health services. Health statistics are used to project 

the impact of alternative policy choices on a population’s health and to measure change 

associated with policy implementation.

Third use: generating information to guide implementation, targeting, evaluation, 

and refinement of health programs and other interventions for populations and to guide 

personal health decisions. Once policy directions have been established, health statistics 

are used to design public health programs that implement those policies. Health statistics 

enable identification and understanding of populations at risk of poor health and targeting 

of public health programs to those groups most in need of them. Once programs have 

been implemented, health statistics are used to evaluate them by determining their impact 

Use of health statistics to inform policy: health insurance

Health statistics provide insights into the health insurance coverage of the 

population, the differences in coverage between subpopulation groups (such 

as between the poor and the non-poor, the employed and the unemployed), 

and the relationship between insurance, access to care, and population health. 

Health statistics help set the health policy agenda and are closely watched for 

their implications for publicly funded health insurance programs. The Federal 

government alone spends more than $400 billion annually on health, primarily for 

its Medicare, Medicaid, and S-CHIP programs. Improving health statistics can 

have real returns in the efficiency and effectiveness of these and other programs.

Chapter 1 What are Health Statistics? 
5

Shaping a Health Statistics Vision for the 21st Century

on target groups. Health statistics also enable information to be made available to inform 

personal decisions about health, helping individuals understand health promotion and 

disease prevention strategies, the consequences of health risk behaviors, and health care 

outcomes associated with personal health care decisions.

These three uses of health statistics must guide and inform both the structure and the 

processes of the health statistics enterprise.

Defining the health statistics enterprise

The health statistics enterprise consists of the infrastructure and the activities 

or processes necessary to produce health statistics. The infrastructure of the health 

statistics enterprise consists of the public and private organizations and individuals 

at all geopolitical levels that perform the processes (that is, carry out the activities) 

of health statistics. The infrastructure of the U.S. health statistics enterprise is highly 

decentralized and diverse, without the overall organization and direction that often 

characterize corporate enterprises. The infrastructure of the health statistics enterprise 

includes the many organizations that collect, analyze, and disseminate data on the health 

of populations and on the factors that influence health: 1) Federal agencies, such as 

CDC/NCHS, the Center for Cost and Financing Studies of the Agency for Healthcare 

Research and Quality, and the Office of Applied Studies of the Substance Abuse and 

Mental Health Services Administration; 2) national organizations, such as the American 

Hospital Association; 3) state and local public agencies, such as state centers for health 

statistics within state health departments, and county public health departments; 4) private 

third-party payers, such as health maintenance organizations and other health plans; and 

5) foundations and their grantees.

Use of health statistics in health programs and interventions: asthma3

Health statistics have played a critical role in improving our understanding of, and 

our attempts to prevent and treat, asthma. Health statistics have shown that the 

prevalence of asthma has increased in the United States, as well as in many other 

developed countries over the past 20 years. They have also provided insight into 

what groups are most affected by asthma and, thereby, facilitated the targeting of 

programs to reduce the prevalence and adverse effects of asthma. For example, 

health statistics have shown that mortality is higher among African Americans 

and those of Puerto Rican heritage than among white non-Hispanics, and specific 

programs have been developed to help these groups.

3

References for asthma example:

a) “Surveillance for asthma--United States, 1960-1995.” Morb Mortal Wkly Rep. 1998;47(SS1):1-28.

b) Homa DM, Mannino DM, Lara M. “Asthma mortality in US Hispanics of Mexican, Puerto Rican, and Cuban 

heritage: 1990-1995.” Am J Respir Crit Care Med. 2000;161:504-509.

c) “Self-Reported asthma prevalence among adults ---United States, 2000.” Morb Mortal Wkly Rep. 

2001;50(32):682.

d) “Asthma hospitalizations and readmissions among children and young adults -- Wisconsin, 1991-1995.”

Morb Mortal Wkly Rep.1997;46(31):726.

Chapter 1 What are Health Statistics? 
6

Shaping a Health Statistics Vision for the 21st Century

The infrastructure of the health statistics enterprise carries out many activities or 

processes that yield health statistics. As explained in greater detail in Chapter Three, 

the activities of the health statistics enterprise include the collection of data from 

institutions, organizations, and individuals; aggregation and compilation of those data 

into health statistics; analysis and translation of health statistics in order to make them 

comprehensible to varied users; and evaluation of health statistics and the health statistics 

enterprise in order to improve them.

The health statistics enterprise, as currently constituted in the U.S., can be described 

by the following major characteristics.

1. Focuses on the health of 

the population and the influences 

and actions that affect the health 

of the population. While different 

organizations, individuals, and processes 

within the health statistics enterprise 

may focus on different influences 

and actions, ultimately all parts of 

the enterprise contribute to better 

understanding and characterizing the 

population’s and sub-populations’ 

health.

2. Serves the public interest and 

generates products that are public 

goods. The health statistics enterprise 

includes both public and private sector entities, all of which can contribute to collection, 

aggregation, analysis, and translation of data. Government agencies, private sector 

health care providers, insurers, and purchasers develop health statistics. Each of the 

organizations and individuals comprising the health statistics enterprise ultimately 

contribute to better understanding and characterizing the population’s health. Data made 

available in the public domain by these entities become public goods in the economic 

sense, in that once made available multiple users can use them for multiple purposes.

3. Engages in systematic and organized inquiry. The health statistics enterprise 

relies upon systematic data collection, aggregation, analysis, and translation. Health 

statistics entail organized inquiry and not unsystematic collection of anecdotes and 

personal impressions.

The U.S. health statistics enterprise

1. Focuses on the health of the

population and subpopulations

2. Serves the public interest and 

generates products that are public 

goods

3. Engages in systematic and 

organized inquiry

4. Strives for scientific objectivity

5. Involves multiple disciplines

6. Links U.S. health statistics activities 

to those of international partners in 

health and health statistics

Chapter 1 What are Health Statistics? 
7

Shaping a Health Statistics Vision for the 21st Century

4. Strives for scientific objectivity. The health statistics enterprise strives for 

scientific objectivity in data collection, aggregation, analysis, and translation, and 

attempts to minimize or eliminate any explicit political biases in its activities. The choice 

of priorities within the health statistics enterprise is necessarily based upon a series of 

choices about what constitutes and how to measure the health of a population, and what 

influences on health merit study and how to assess their influences.4 Such choices are 

inherently based upon values and judgments; health statistics practitioners make scientific 

objectivity a preeminent concern.

5. Involves multiple disciplines. The practice of health statistics necessarily 

involves multiple disciplines, including statistics, epidemiology, health services research, 

demography, public health informatics, information technology, and economics.

6. Links U.S. efforts to those of international partners in health and health statistics. 

The U.S. is guided by international health statistics standards and policies, such as 

periodic revisions to the International Classification of Diseases codes. The U.S. health 

statistics enterprise also contributes to international discussions of health statistics 

methods and provides health statistics to international agencies for comparative purposes.

4

Krieger, N., “The Making of Public Health Data: Paradigms, Politics, and Policy,” Journal of Public Health 

Policy, 1992, pp. 412-427.

Chapter 1 What are Health Statistics? 
8

Shaping a Health Statistics Vision for the 21st Century

Chapter Two: A Model of the Influences on 

the Population’s Health

Need for and uses of the model

Many factors influence the health of a population. In order to develop useful health 

statistics that accurately characterize the health of a population and the influences and 

actions that affect the health of a population, it is essential to have a comprehensive and 

coherent representation of these factors. Through the extensive health statistics vision 

consultative process, clear agreement emerged on the need for a model that takes a 

broad view of the health of populations and the factors that influence their health. This 

model should guide the development, ongoing management, and evaluation of the health 

statistics enterprise so that it can provide data that are comprehensive and useful for 

characterizing health at all geopolitical levels. When applied to a population of interest 

at any geopolitical level for a specific time period, this model can serve to identify gaps 

in data for the given population.5

 In addition to being used to identify gaps, the model 

can be applied to a specific health issue (such as lung cancer, homicide, or depression) 

in order to identify the principal factors influencing it and potential approaches to 

preventing or ameliorating it.

Figure 2 presents a model of the factors that influence health that grew out of the 

health statistics vision consultative process and the work of several authors.6

 This chapter 

describes this model and uses it to evaluate the gaps in the health statistics currently 

available in the U.S. In Chapter Four, this model is used to guide the presentation of the 

vision for health statistics in the 21st century. Definitions of key terms in Figure 2 are 

included in the Glossary.

Overview of the model

The model has three components: 1) the context or broad setting in which the 

population exists and acts, 2) factors acting at the community and individual levels, 

and 3) measures of a population’s health. The model positions a population’s health as 

the central outcome variable (central oval in Figure 2). The health of a population is 

described by measures of disease, functional status, and well-being that reflect both the 

level and distribution of health in the population.

5

Black, C., Roos, N., Roos, L., “From health statistics to health information systems: a new path for the 21st

century, Available from http://www.ncvhs.hhs.gov/hsvision/CP--Black.pdf [Accessed 18 October 2002].

6

For example, see: Lalonde, M., A New Perspective on the Health of Canadians: A Working Document, 

Government of Canada, Ottawa, 1974; Evans, R. and Stoddart, G., “Producing health, consuming health 

care,” Why Are Some People Healthy and Others Not? Evans, R., Morris L. Barer, and Marmor, T., ed., Aldine 

de Gruyter, New York, 1994; Starfield, B., Primary Care: Balancing Health Needs, Services, and Technology, 

Oxford University Press, Oxford and New York, 1998; Berkman, L. and Glass, T., “Social integration, social 

networks, social support, and health,” Social Epidemiology, Berkman, L. and Kawachi, I., ed., Oxford University 

Press, Oxford and New York, 2000; and U.S. Department of Health and Human Services, Healthy People 2010: 

Understanding and Improving Health, U.S. Department of Health and Human Services, Washington, D.C., 

2000.

Chapter 2 A Model of the Influences on the Population’s Health 
9

Shaping a Health Statistics Vision for the 21st Century

Chapter 2 A Model of the Influences on the Population’s Health Figure 2. Influences on the Population’s Health
10

Shaping a Health Statistics Vision for the 21st Century

All variables in this model are either “aggregate” or “ecological.” Aggregate 

measures represent those community attributes that are derivable from the attributes 

of individual members of the community, such as the community age structure or the 

incidence rate for sexually transmitted diseases. Aggregate measures represent either 

averaged data on behaviors or attributes (such as the mean or median household income 

or the poverty rate) or a function of the distribution of behaviors or attributes (such 

as the ratio of the mean or median household income of the lowest fifth in the income 

distribution to the mean or median household income of the highest fifth). Ecological 

measures represent those community attributes that are not derivable from the attributes 

of individual members of the community. Levels of air or water pollutants, public 

policies, or the structure of health services are examples of ecological variables.

Social attributes, biological characteristics, the built environment, health services, 

economic factors, population-based health programs, and collective lifestyles and 

health practices (the major categories in the “community attributes” band immediately 

surrounding the population health oval in Figure 2) are factors that immediately affect 

the health of a population. Depending upon the specific health issue, these factors 

may interact in different ways, and may influence the population’s health in different 

ways. The built environment, health services, social attributes, and health programs for 

populations function predominantly as ecological variables in their influences on health. 

Biological characteristics, individual or family economic resources, and collective 

lifestyles and health practices function predominantly as aggregate variables.

The natural, cultural, and political contexts (the major categories within the 

outermost, “context”, band in Figure 2) are ecological variables that affect both the 

population’s health and the health of individuals.

Finally, it is important to recognize that the influences portrayed in Figure 2 must 

be used to describe a particular place and time.7, 8 The configuration of the influences on 

the population’s health will differ from place to place (in other words, from geopolitical 

area to geopolitical area) and will also differ depending upon the particular time frame 

(in other words, the year or historic era). The location of a particular population in place 

and time will determine the specific constellation of contextual influences and community 

resource influences that most strongly affect the population’s health.

The model does not presume causality, directionality, or interactions among its 

components. As indicated above, the purpose of Figure 2 is to provide a picture of the 

influences on a population’s health for use in evaluating the availability of data and 

gaps in data at the national, state, and or local levels. A variety of research hypotheses 

can be developed to test the existence and direction of causality among elements in the 

model. Similarly, the model does not posit the relative weight or importance of different 

7

Hayes, M., “Evidence, determinants of health and population epidemiology: humming the tune, learning the 

lyrics,” The Determinants of Population Health: A Critical Assessment, Hayes, M., Foster, L., and Foster, H., ed., 

Department of Geography, University of Victoria, Victoria, British Columbia, 1994.

8

Hayes, M. and Dunn, J., Population health in Canada: a systematic review, Canadian Policy Research 

Networks, Inc., Ottawa, 1998.

Chapter 2 A Model of the Influences on the Population’s Health 
11

Shaping a Health Statistics Vision for the 21st Century

influences or combinations of influences. It leaves this work to analysts and researchers. 

The contribution of the health statistics enterprise is to ensure the availability of data to 

support such analysis and research.

The next section of this chapter provides a more detailed description of the elements 

within each of the three components of the model.

Model Overview – Context

The “context” band consists of three major elements: the natural environment, the 

cultural context, and the political context. The natural environment has a strong overall 

influence on the population. Climate, topography, and water resources affect the animals 

and plants that can live in the area. These, in turn, affect food resources and the size 

and density of the populations that can be supported. Proximity to waterways, seas, and 

oceans and topography determine trade routes and the extent of interaction with other 

peoples.9

 All of these influence health. The cultural context refers to the norms and 

values of a population; these, in turn affect the level of competition and cooperation both 

within a population and between the population and other neighboring populations. The 

presence and extent of advantages held by or discrimination against particular population 

groups are manifestations of norms and values that can affect the health services 

utilization, health practices, and health of these groups.

The political context is the expression of norms and values in the overall political 

culture of a given population and geopolitical area. A society codifies its norms and 

values as the public policies and laws that guide the actions of its members. Thus, the 

political context can significantly shape the society’s impact on the natural environment 

and how the society functions socially and economically. Policies and laws may also 

determine the availability and nature of health programs for the population and of health 

services. Finally, the extent to which individuals and groups within the population are 

enfranchised and participate in the political culture of a society has a strong influence on 

the responsiveness of the society to their health needs and other needs.

Model Overview – Community Attributes

Community attributes exist within and are determined by their environmental, 

cultural, and political context and the population that shares in this context. These 

attributes include the community’s social attributes, biological characteristics of the 

population, the built environment, health services, economic resources, population-based 

health programs, and collective lifestyles and health practices of people in the community.

The social attributes of the community consist of the type and extent of social 

networks, the overall social cohesion of the community, and the support provided by the 

9

Diamond, J., Guns, Germs, and Steel: The Fates of Human Societies. New York, W. W. Norton, 1999.

Chapter 2 A Model of the Influences on the Population’s Health 
12

Shaping a Health Statistics Vision for the 21st Century

community or by subpopulations within the community to its members. Discrimination 

against particular groups within the community may adversely affect the health of these 

groups by excluding them from important social networks and support.

The community’s biological characteristics include its age and gender structures, 

the genetic make-up of its membership (such as the prevalence in the population of 

genes associated with hemoglobinopathy or hemochromatosis), and the immune status 

of its membership (such as the level of immunity to measles as a result of widespread 

childhood vaccination or infection). The community age structure affects the health 

outcomes of the population; for example, communities with relatively older populations 

are likely to have higher prevalences of chronic diseases.

The built environment refers to modifications of the natural environment to support 

human habitation and activity, such as housing, roads and canals, telecommunications 

infrastructure, work places, and schools. These have a profound influence on the health 

of the community by determining the level of protection from weather and climate and 

the ability of the community to interact and trade with other communities. The quality 

of the physical structures available for schooling and work also influence the nature and 

quality of these activities. Some of these structures also provide the setting for important 

familial, community, and other social interactions (for example, housing, schools, and 

work places).

The economic attributes of the community consist of the overall wealth of the 

community and its members, the distribution of this wealth, and the type, extent, and 

stability of employment of its members. As with social attributes, the extent of equity 

in the distribution of, and access to, economic attributes for individuals and groups is 

an important influence on community health. Furthermore, the control that members 

of the community can exercise over their work and economic status can profoundly 

affect health. Finally, educational opportunities for children and adults, and the level of 

education of members of the community are both important influences on, and markers 

of, the economic and health status of the community.10

The cultural and political contexts and the social and economic attributes of a 

community exert a profound effect on the type, availability, and quality of health services 

and health programs for populations. The overall effectiveness or quality of health 

services depends on their structure and capacity (including factors such as the number, 

type, and training of personnel; the quality and availability of facilities; the method and 

level of financing), their processes (organization of the delivery system, professional 

behaviors, and utilization), and accessibility.

In addition to health services, which are usually delivered on an individual basis, 

population-based health programs and the provision of health-related information to 

the community exert important influences on health. Population-based health programs 

10It has been suggested that child development be included as an influence on health. (Hertzman, C., “The 

case for child development as a determinant of health,” Can J Public Health, 1998: 89 Supplement 1,pp. S14-

9). The model in Figure 2 views child development as an outcome of influences on health and, therefore, as 

being a characteristic of the population’s health (e.g., a sub-category of functional status). The model attempts 

to include all of the important influences on child development (e.g., nutrition, early childhood experience and 

education, and social support).

Chapter 2 A Model of the Influences on the Population’s Health 
13

Shaping a Health Statistics Vision for the 21st Century

include systems for providing clean drinking water, waste disposal, or vector control 

and community health promotion and education programs, including those designed 

to influence personal health practices, such as smoking, sexual practices, and physical 

exercise.

Collective lifestyles and health practices include diet, wellness behaviors, physical 

activity, sexual practices and abstinence, smoking, violent behavior, and substance 

use.11,12 Collective lifestyles and health practices vary across communities as well as 

among individual members of those communities, and all of these attributes impact 

directly upon the population’s health.

Model Overview – The Population’s Health

The health of a population, the central focus of our model, is assessed using 

measures of disease, functional status, and well-being. These reflect both the level and 

distribution of health in a population. Measures of disease include rates of particular 

diseases within a population and how these rates vary over time, by place, and within 

subgroups of the population. The International Classification of Diseases provides a 

framework for undertaking and presenting these measurements.13 Functional status refers 

to the ability of people to engage in the activities of daily living and social life.14 The 

International Classification of Functioning, Disability and Health15 presents a framework 

for assessing function that takes into account the social aspects of functional status and 

provides a mechanism to document the impact of the social and physical environment 

on a person’s functioning. The concept of well-being reflects the subjective aspects of 

health. Unlike measures of disease and function, the measurement of well-being is less 

well defined and lacks an internationally agreed upon framework.

Mapping the current enterprise using the model

Table 1 provides for each component of the model an overview of typical 

approaches for gathering relevant information and associated data collection systems 

at national, state, and local levels. Table 1 indicates many strengths of the U.S. health 

statistics enterprise. The U.S. health statistics enterprise collects national data through 

internationally renowned ongoing national surveys, surveillance and registration systems, 

and administrative data systems. Some of these systems, and especially the surveillance, 

registration, and administrative data systems, also provide much needed state- and local11Frohlich, K. and Potvin, L., “Collective lifestyles as the target for health promotion,” Can J Public Health, 1999:

90,Supplement 1, pp. S11-S13.

12Frohlich, K., Corin, E., and Potvin, L., “A theoretical proposal for the relationship between context and

disease,” Sociology of Health and Illness, 2001:23,6, pp. 776-797.

13World Health Organization, International Statistical Classification of Diseases and Related Health Problems, 

Revision10th rev. ed. (revised by the National Center for Health Statistics), NCHS, Hyattsville, Maryland, 

October 1998.

14Starfield, B., “Basic concepts in population health and health care,” Journal of Epidemiology and Community 

Health, 2001;55(7): 452-4.

15World Health Organization, International Classification of Functioning, Disability, and Health, short version, 

World Health Organization, Geneva, 2001.

Chapter 2 A Model of the Influences on the Population’s Health 
14

Shaping a Health Statistics Vision for the 21st Century

level data. Drawing upon Table 1, the following sections highlight examples of the 

strengths of the current U.S. health statistics enterprise, organized by the components in 

the model.

Current Enterprise – Context

Natural environment: The U.S. health statistics enterprise can draw upon ongoing 

national, state, and local monitoring of the natural environment, especially through 

systems maintained by the National Oceanographic and Atmospheric Administration, 

the National Weather Service, the U.S. Geological Survey, and the U.S. Environmental 

Protection Agency. These systems provide data on such influences on health as climate, 

topography, and air and water quality.

Cultural and political contexts: At the national level, the General Social Survey,16

a personal interview survey of U.S. households conducted since 1972 by the National 

Opinion Research Center, provides data on various cultural, political, and economic 

aspects of society, such as political viewpoints, sociopolitical participation, and social 

trends.

Current Enterprise – Community Attributes

Health services: The U.S. has a wealth of high quality data collection systems 

providing ongoing national and state data on the structure, processes, and use of health 

services. These include, among others, the National Health Care Survey, the Annual 

Survey of Hospitals, the Healthcare Cost and Utilization Project, the National Medical 

Expenditure Survey, and the National Immunization Survey, which collect data through 

population, provider, client, and institutional surveys and ongoing administrative data 

systems. These systems provide data on aspects of health services, such as data on the 

adoption of new medical technologies and procedures, on the use of prescription drugs, 

and on the relationships among health insurance, access to care, health status, and health 

care costs and financing.

Built environment: Relevant ongoing data are available from Federal and state 

agencies. Especially noteworthy are ongoing data on land use, housing, air quality, and 

urbanization from the U.S. Department of Housing and Urban Development, the Census 

Bureau, and the U.S. Environmental Protection Agency.

Biological characteristics: Since 1790, the U.S. has collected decennial census data 

describing the age and sex distribution of the population at all geopolitical levels. Since 

the early 20th century, states have collected and provided to the Federal government 

data on births and deaths; again, these data are available at all geopolitical levels. The 

National Health and Nutrition Examination Survey, conducted by NCHS, collects 

detailed biological data pertaining to the health status of Americans on an ongoing basis.

16The National Opinion Research Center, General Social Survey Codebook, Available from: 

http://www.icpsr.umich.edu/GSS/ [accessed 1 September 2002].

Chapter 2 A Model of the Influences on the Population’s Health 
15

Shaping a Health Statistics Vision for the 21st Century

Economic attributes: Ongoing and periodic data on employment, individual and 

household income, income inequality, and educational attainment are collected by the 

decennial Census of Population, the ongoing American Community Survey, and the 

Current Population Survey.

Population-based health programs: Studies by the National Association of County 

and City Health Officials, the Association of State and Territorial Health Officials, 

CDC, and others periodically assess the status of the public health infrastructure and the 

preparedness of state and local public health organizations.

Collective lifestyles and health practices: Ongoing data on health practices are 

collected by such national surveys as the National Health Interview Survey, while at the 

state level, the Behavioral Risk Factor Surveillance System and the Youth Risk Behavior 

Survey collect health practices data in each state.

Current Enterprise – The Population’s Health

Disease: Disease incidence and prevalence data are collected through registries 

and reportable disease surveillance systems, population-based and event-based surveys, 

and administrative data systems. The Vital Statistics Cooperative Program provides 

nearly complete data at all geopolitical levels on mortality by cause. Morbidity data are 

collected through various national disease-specific surveillance systems with differing 

levels of completeness of case ascertainment, such as the HIV/AIDS Surveillance System 

and the National Notifiable Disease Surveillance System; these systems also collect data 

at all geopolitical levels. Other data on morbidity are collected through ongoing national 

surveys such as the National Health Interview Survey. Morbidity manifested in health 

care encounters is collected at the national level through surveys such as the National 

Ambulatory Medical Care Survey and the National Hospital Discharge Survey, and at 

all geopolitical levels through administrative data systems such as the Medicaid and 

Medicare files.

Functional status: At the national level, functional status data are collected through 

the National Health Interview Survey, the National Survey of Children with Special 

Health Care Needs, and systems designed to assess patients in nursing and home health 

care.

Using the model to describe issues and gaps

The examples of data collection systems provided in Table 1 indicate substantial 

unevenness in the capacity of the U.S. health statistics enterprise to provide data to 

characterize the health of its population and those factors that influence its health. While 

excellent and comprehensive data exist for some measures of the influences on health 

at some geopolitical levels, little or no ongoing data are available for other measures or 

Chapter 2 A Model of the Influences on the Population’s Health 
16

Shaping a Health Statistics Vision for the 21st Century

influences. An overview of the issues related to the current capacity of the U.S. health 

statistics enterprise to provide the information needed to develop a full understanding 

of its population’s health is presented below. This overview is followed by a summary 

of the gaps in the capacity of the enterprise to provide the needed information. The 

reflections on issues and gaps are based upon the testimony delivered at our regional 

public hearings; local and national discussion groups; commissioned papers; the National 

Academy of Sciences/Committee on National Statistics workshop; and a review of 

Table 1.

Underlying issues

Analysis of the capacity of the U.S. health statistics enterprise to monitor the health 

of the U.S. population reveals several underlying issues that affect the health statistics for 

all aspects of health and its influences.

Broad definition of the population’s health: The first issue is the failure of the health 

statistics enterprise to incorporate a broad definition of the population’s health.17 The 

multifactorial nature of the influences on the population’s health is not currently reflected 

in our ongoing data collection systems, especially at the state and local levels.18 Ongoing 

data collection systems are now largely disease-driven and disease-specific and generally 

do not operationalize health in a way that integrates disease, functional status, and wellbeing. Minimal ongoing data on functional status are collected, and almost no data are 

collected on well-being. Data sources that do exist do not lend themselves to linking and 

merging in a way that can easily address this multifactorial nature of health.

Units of analysis: Ongoing analyses conducted by state and national agencies focus 

largely on individual health and the determinants of individual health, rather than on 

populations and communities as units of analysis. Many state-level analyses reported 

in ongoing Federal publications focus on comparing individual health at the state level, 

rather than incorporating a population perspective to understand health.

State and local data: The availability of health statistics data varies greatly across 

geopolitical levels. During each of the local discussion groups and at all of the regional 

public hearings, repeated pleas were voiced by state and local public health practitioners, 

health care providers, and community organizations for more extensive state and local 

data, especially survey data.

Subpopulation data: Another theme repeatedly heard at the local discussion groups 

and regional public hearings revolved around the inconsistent quality and quantity of 

data on vulnerable populations.19 This issue is particularly evident for subpopulations 

17“Vision” discussion group, Albuquerque, 1 March 2000, Available from: http://www.ncvhs.hhs.gov/hsvision/

Albuquerque.pdf [accessed 1 September 2002]; “Vision” discussion group, Harrisburg, 11 November 1999, 

Available from: http://www.ncvhs.hhs.gov/hsvision/111699.pdf [accessed 1 September 2002].

18Fielding, J., National Center on Vital and Health Statistics public hearing testimony on: “21st Century Vision 

for Health Statistics,” San Francisco, 30 October 2000, Available from: http://www.ncvhs.hhs.gov/001030tr.htm 

[accessed 1 September 2002].

19“Vision” discussion group, Albuquerque, 1 March 2000, Available from: http://www.ncvhs.hhs.gov/hsvision 

Albuquerque.pdf [accessed 1 September 2002]; Giachello, A., NCVHS public hearing testimony on: “21st

Century Vision for Health Statistics,” Rosemont, Illinois, 10 July 2000, Available from: 

http://www.ncvhs.hhs.gov/000710tr.htm [accessed 1 September 2002].

Chapter 2 A Model of the Influences on the Population’s Health 
17

Shaping a Health Statistics Vision for the 21st Century

that may be small in numbers nationally but relatively large locally as well as for 

subpopulations that may be relatively small in numbers in any individual local area 

but relatively large nationally. Also evident were concerns about the dearth of data on 

especially vulnerable subgroups within racial and ethnic minority populations, such 

as the minority elderly. Finally, concerns were expressed about inconsistent efforts to 

recognize and provide information on the diversity within minority populations, such as 

distinctions between subgroups of Asian Americans or Latino Americans. For example, 

while the new standard certificate of live birth promotes self-identification for Hispanics 

and Hispanic subgroups, no such self-identification of ethnicity is promoted for Blacks; 

similarly, many other data collection systems go no further than collecting broad data on 

Hispanic ethnicity but no data on specific Hispanic origin or ancestry.

Longitudinal and life cycle data: Partially due to not employing a broad definition of 

health, the U.S. health statistics enterprise does not adequately collect data describing the 

course of health throughout the lifecycle, and differential influences on health at different 

stages in the lifecycle.20 When data collection systems exist in unconnected “silos,” it 

becomes difficult or impossible to link those silos at the individual person level in order 

to develop over-time lifecycle health biographies. Different surveillance, administrative 

data, and survey systems can be difficult or impossible to link with each other for 

individual data subjects, even if the surveillance systems contain data on the same 

individual. Linkage of individual record data from different lifecycle stages at the person 

level across surveillance, administrative, and surveys is rare. Consequently, diseases and 

health events are largely analyzed as isolated episodes of illness.

Data availability versus data use: The U.S. health statistics enterprise is lacking 

both in the availability of data on some components of and influences on the population’s 

health, and in the use of available data. Table 1 suggests the existence of a plethora of 

potentially important data sources available to the health statistics enterprise that are 

rarely utilized. This is especially true in regard to the lack of use of areal data pertaining 

to the natural and built environments.

Data gaps

This section provides an overview of the major gaps in available data for specific 

influences on and measures of the U.S. population’s health.

Context: The U.S. health statistics enterprise collects and utilizes little data 

pertaining to either the cultural or political contexts of the population’s health. Data 

collection systems provide minimal data on such important elements of the cultural 

context as racism, sexism, competition and cooperation, and norms and values. While 

data systems are used to measure the relationship of “race” and ethnicity to health 

outcomes, they generally do not include information needed to disentangle how 

20Kalsbeek, W., NCVHS public hearing testimony on: “21st Century Vision for Health Statistics,” Research 

Triangle Park, 20 November 2000, Available from: http://www.ncvhs.hhs.gov/001120tr.htm [accessed 1 

September 2002].

Chapter 2 A Model of the Influences on the Population’s Health 
18

Shaping a Health Statistics Vision for the 21st Century

race/ethnicity, socioeconomic status, discrimination, race-as-perceived-by-others, and 

other factors affect health.21 The enterprise generally fails to monitor the political context 

and rarely tracks on an ongoing basis the impacts of public policies and laws, the political 

culture, and political enfranchisement on the population’s health.

Community attributes: Despite a substantial and increasing body of U.S. and 

international literature on the relationship of community social attributes to the health of 

individuals and populations, data on these attributes are not incorporated into ongoing 

analyses of health data at the national or state levels. The U.S. health statistics enterprise 

collects no ongoing data pertaining to such key community attributes as social cohesion, 

social influence, social networks, social support, and social change.

Similarly, data pertaining to economic attributes of communities are rarely 

incorporated into ongoing analyses of the health of their populations. While such 

ongoing surveys as the National Health Interview Survey and the Behavioral Risk Factor 

Surveillance System do collect data on individual and household income (although rarely 

on assets), disease- and condition-specific surveillance systems and administrative data 

systems do not collect such data.22 Data on economic attributes are available on an 

ongoing basis from such data sources as the American Community Survey. Such data 

have been widely incorporated into research on the relationship of income inequality 

to a population’s health, both in the United States and abroad. Yet ongoing analyses of 

the health of populations in the U.S. conducted by Federal and state governments do not 

regularly incorporate statistics on community economic resources.

The U.S. health statistics enterprise collects a wealth of data on the structure and 

processes of, and access to, health services. Yet these data are rarely related to the 

health of a population as the dependent variable. The contribution of our investments in 

health services to improvements in the population’s health has not been thoroughly or 

systematically explored.

Data on the built environment are routinely available, but these data–pertaining 

to such key elements of the built environment as housing, school, transportation, 

communication infrastructure, and equity of access to these elements–are not used on an 

ongoing basis in analyses of health by national and state governments.

The relationship of population-based health programs to a population’s health at the 

local or state level has also been largely absent from ongoing analyses.

The population’s health: The operationalization and ongoing measurement of the 

U.S. population’s health by the U.S. health statistics enterprise is largely confined to the 

incidence and prevalence of individual diseases and health conditions. Incidence and 

21Krieger, N., “Discrimination and health,” Social Epidemiology, Berkman, L. and Kawachi, I., ed. Oxford 

University Press, Oxford and New York, 2000.

22Krieger, N., Chen, J., and Ebel, G., “Can we monitor socioeconomic inequalities in health: a survey of U.S. 

health departments’ data collection and reporting practices,” Public Health Reports, 1997;112:481-491.

Chapter 2 A Model of the Influences on the Population’s Health 
19

Shaping a Health Statistics Vision for the 21st Century

prevalence are generally measured in isolation, with little ability and few attempts to link 

incidence or prevalence of a specific disease to incidence or prevalence of another disease 

measured during the same life cycle stage through another data collection system, or to 

another disease or condition measured at a different life cycle stage. The measurement of 

functional status is confined largely to national surveys, and this important component of 

health is not typically addressed in ongoing surveillance or administrative data systems. 

Well-being is minimally measured in national surveys, and not measured at all in 

surveillance or administrative data systems. As a result, the working definition of health 

in the U.S. health statistics enterprise has been all but reduced to disease, which both 

reflects and reinforces the tendency of the health services system to focus on the treatment 

of disease.

The restricted working definition of health has important consequences for the 

practice of public health, leading to the concentration of public health programs on 

disease prevention and management, rather than on a more broadly integrated approach 

to promotion of health. This also limits the ability of decision-makers to employ a fully 

integrated model of the influences on the health of a population and its influences to help 

guide decision-makers. Making disease the primary focus of health services and public 

health programs oversimplifies the complex interactions that affect the health of people 

individually and the population as a whole.

Chapter 2 A Model of the Influences on the Population’s Health 
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Shaping a Health Statistics Vision for the 21st Century

Chapter 3 Developing, Evaluating and Improving Health Statistics 

Chapter Three: Developing, Evaluating and 

Improving Health Statistics

The health statistics enterprise and the Health 

Statistics Cycle

The health statistics needed to understand the dynamics of and influences on the 

U.S. population’s health involve the efforts of a diverse and decentralized enterprise. 

Individually, the organizations and people that are involved in the American health 

statistics enterprise are responsible for specific data systems and focused efforts to use 

and disseminate data, with the measure of success often defined as meeting a specific 

need or use. The success of the overall health statistics enterprise (as defined in Chapter 

1) depends upon the extent to which these individual components work in concert to meet 

the broader agenda of understanding the population’s health and influences on it.

The performance of the health statistics 

enterprise, as well as of many individual 

programs that collect data and manage statistics, 

involves a number of key elements that are 

described in the “Health Statistics Cycle” 

(Figure 3). This model can be used to describe 

the steps required to define and meet data needs, 

to evaluate the strengths and weaknesses of 

current programs, and to suggest ways in which 

different components of the health statistics 

enterprise can be tied together into a more 

cohesive whole. The model draws upon the 

insights, suggestions, and observations of the 

broad range of participants in the health statistics 

vision process.

Elements in the Health 

Statistics Cycle

Figure 3 depicts seven elements in the health statistics cycle, arrayed in a circle, 

with each element leading to the next. Importantly, there is no first or last step; the model 

recognizes that the health statistics enterprise needs to be in a constant state of evolution, 

evaluation, and regeneration. The model is applicable both to the development of new 

statistical efforts and to efforts to make existing data systems that produce health statistics 

more effective. The model is also equally applicable to looking at the overall health 

statistics enterprise and to focusing on individual data systems or data needs.

Health Statistics Cycle

Hub–Integrating the health

statistics enterprise

Elements:

• Defining data needs

• Specifying necessary data 

attributes

• Identifying appropriate data 

sources and strategies

• Collecting, aggregating, and 

compiling data

• Analyzing statistics

• Translating statistics for users

• Evaluating extent to which 

needs are met
21

Shaping a Health Statistics Vision for the 21st Century

Chapter 3 Developing, Evaluating and Improving Health Statistics Figure 3. Health statistics cycle
22

Shaping a Health Statistics Vision for the 21st Century

Defining data needs

In the aggregate, the data needs to be met by the health statistics enterprise are 

determined by an ongoing and iterative process. The overall data needed to promote 

understanding of the population’s health and the influences on the population’s 

health are reflected by the scope of Figure 2. In working to address more specific 

needs, organizations that collect and compile statistics work with data providers (e.g., 

respondents to surveys, managers of health care records) and data users to focus on 

developing detailed definitions and specifications of data needs in areas including:

Health policies: for example, data to document the lack of health insurance or the 

relationship between the lack of health insurance and access to care;

Research and hypothesis testing: for example, information on the relationship 

between a risk factor and a health effect;

Health program needs: for example, data to define high-risk populations for an 

intervention;

Monitoring and accountability: for example, data that can be used in performance 

monitoring or tracking and reporting on high visibility health indicators; and

Health practitioners and health service providers: for example, data that can be 

used to assess the quality and efficiency of health care.

Specifying necessary data attributes

Each of these data needs can be further specified in terms of the data attributes 

required to meet the need. This greater specificity is needed so that alternative data 

sources or strategies can be evaluated, along with the process of matching data needs to 

available resources. Data attributes include the:

• Characteristics of the populations under study, such as racial/ethnic and 

socioeconomic subgroups, age/sex breakdowns;

• Degree of geographic detail, such as national, regional, community, or even more 

granular levels; 

• Depth and complexity of information required to meet the need, such as number 

of questions to be asked regarding a particular topic in a telephone survey or the 

level to which data are coded in a classification system;

• Length of time to be observed, ranging from a single point in time to a full 

calendar year to a range of years;

• Timeliness of reporting of results, both in terms of the turnaround time for data 

processing and the currency of the time period for which data are collected;

• Type of respondent or data source, such as individual interviews, administrative 

records, or secondary use of data collected for another purpose;

• Measurement approach, such as direct observation, computer-assisted interview, 

telephone survey, laboratory analysis, and so forth;

Chapter 3 Developing, Evaluating and Improving Health Statistics 
23

Shaping a Health Statistics Vision for the 21st Century

• Extent to which observations need to be validated, verified, tested for reliability 

or subjected to other methods of ensuring data quality; and

• Degree of sensitivity and specificity needed to meet user needs.

Identifying appropriate data sources and strategies

With detailed specifications, various data sources or strategies can be evaluated in 

order to rapidly and efficiently meet user needs. Strategies, in increasing order of cost 

and complexity, may include:

• Identifying data that already exist in a format that meets user specifications and is 

already accessible for analysis;

• Extracting data from existing data sets;

• Identifying opportunities to use data initially collected for non-statistical purposes 

(such as administration or patient care);

• Adapting existing data collection systems to meet new needs; and 

• Designing and implementing new data collection systems.

Collecting, aggregating, and compiling data

Depending on the strategy selected, this element in the cycle includes steps ranging 

from simple data acquisition to the management of complex, ongoing data 

systems:

• Establishing data use agreements with (or purchasing data from) organizations 

that manage existing data systems, such as an agreement between a state health 

department and HMOs in the state to compare the health of HMO enrollees and 

non-enrollees;

• Creating user-accessible analytic files from existing data sets;

• Aggregating statistics from multiple sources and creating new statistical products 

that, because of the synergy created by combining sources, have analytic 

usefulness beyond that of any one component data set;

• Managing ongoing surveys and other data collection systems to meet the needs of 

multiple users; and

• Launching surveys or other data collection approaches to meet specific user 

needs.

Analyzing statistics

Once data are in usable form, analysts must carefully define and apply analytic 

approaches. Individual components of the health statistics enterprise devote considerable 

resources to developing analytic packages and tools that can be directly applied to specific 

data sets, or data that are derived from individual data systems. Fewer efforts have been 

devoted to development of more widely applicable analytic tools and approaches that 

minimize the learning curve for individual users.

Chapter 3 Developing, Evaluating and Improving Health Statistics 
24

Shaping a Health Statistics Vision for the 21st Century

Translating statistics for use

Organizations that collect and compile health statistics bear responsibility for 

ensuring that the data collected are translated into forms that maximize their appropriate 

and successful use. Professional statisticians and data processing specialists typically 

staff organizations that collect and compile data, while many users are untrained in 

statistics and techniques for accessing them. The translation function seeks to bridge 

this gulf. For systems geared toward meeting narrowly defined needs of specific users, 

this element of the cycle involves a direct relationship between producer and user. More 

generally, the health statistics enterprise is responsible for steps including:

• Making data available in forms appropriate to the level of sophistication of 

 potential users, ranging from raw micro-level data (for example, a detailed 

 individual-level file from the National Medical Expenditure Survey that could 

 be downloaded from the Internet for analysis and use in microsimulation 

modeling) to tabular or graphic presentations of the same data (for example, a 

table depicting health expenditures by source of payment);

• Providing easy access for potential users, for example through interactive World 

Wide Web systems designed to provide community users with access to health

statistics data, such as Massachusetts’ MassCHIP system, Missouri’s MICA 

system, and Seattle/King County’s VISTA/PH system.23

• Making it easier for users to locate available data, for example through World 

Wide Web portals that provide users with topical listings of data sources, such as 

www.fedstats.gov, a Federal government effort to direct users to statistical 

resources. In effect, this simplifies the task of “Identifying appropriate data 

sources” described earlier in the cycle;

• Providing technical assistance, training, and coaching to users, for example 

through distance training techniques such as World Wide Web-based interactive

courses, through video-based training resources such as CDC’s “Public Health 

Data: Our Silent Partner,” through in-person training in conducting community 

health assessments, or through providing adequate explanations of statistical 

concepts such as confidence intervals in written reports.24

Many of these steps will be facilitated by further development of an overall National 

Health Information Infrastructure (NHII), which will provide greater interconnectivity 

between health providers and establish a framework for data access and exchange.25

23Friedman, D., Anderka, M., Krieger, J., Land, G., and Solet, D., “Accessing population health information 

through interactive systems: lessons learned and future directions,” Public Health Reports, 2001;116:132-141.

24Centers for Disease Control and Prevention, Public Health Data: Our Silent Partner, Centers for Disease

Control and Prevention, Atlanta, October 1999.

25National Committee on Vital and Health Statistics, Information for Health: A Strategy for Building the National 

Health Information Infrastructure, 2001, Available from: http://ncvhs.hhs.gov/nhiilayo.pdf [accessed 24 

September 2002].

Chapter 3 Developing, Evaluating and Improving Health Statistics 
25

Shaping a Health Statistics Vision for the 21st Century

Evaluating the extent to which needs are met26

An integral component in the Health Statistics Cycle is the continuing evaluation 

of the extent to which needs are met and the identification of improvements that can be 

made. Without this explicit and self-conscious step, systems for collecting or compiling 

health statistics risk stagnation and irrelevance. This element involves multiple strategies 

and approaches, relying on direct feedback from users and extensive links outside the 

health statistics enterprise. Questions to be addressed in such an evaluation include:

• Are individual data collection systems meeting defined analytic objectives? (Are 

they addressing the questions asked?)

• Are the specific data attributes necessary or sufficient for addressing analytic 

objectives? (Are we collecting too much detail, or not enough?)

• Have analytic objectives changed, requiring change in (or elimination of) data 

collection systems? (If other systems have evolved since the initial selection of a 

data strategy, can they meet these needs?)

• Are data accessible enough for users, and are the tools available to support a level 

of analysis that meets user needs?

• Is the health statistics enterprise as a whole meeting its mission and addressing 

the broadly defined data needs described in Chapter One?

• Is the health statistics enterprise as a whole operating in an efficient manner?

Hub–integrating the health statistics enterprise

At the core of the health statistics enterprise is a set of activities and functions that 

collectively represent an integrating “hub.” These efforts are key to ensuring that the 

diverse and decentralized set of organizations and individuals that are involved with 

health statistics can work in concert to meet a broader agenda. An effective hub, which 

may involve multiple organizations, approaches, and influences, can serve as a center of 

gravity for diverse elements, holding the health statistics enterprise together and ensuring 

that the cycle of development and improvement continues to move in constructive ways. 

If the movement from element to element in Figure 3 can be viewed as driven by the 

winds of a hurricane, the integrating hub is the “eye” around which these elements move.

Critical functions of the integrating hub include:

• Fostering information sharing among diverse players spanning different levels of 

government, public and private entities, etc.;

• Stimulating collaborative statistical efforts;

• Facilitating the process of locating and accessing data from diverse sources;

• Developing and maintaining common definitions, technical standards, 

classifications, methodological benchmarks, etc., that facilitate data sharing, 

systems integration, and comparability of data;

26Lafata, J., NCVHS public hearing testimony on: “21st Century Vision for Health Statistics,” Rosemont, Illinois, 

10 July 2000, Available from: http://www.ncvhs.hhs.gov/000710tr.htm [accessed 1 September 2002].

Chapter 3 Developing, Evaluating and Improving Health Statistics 
26

Shaping a Health Statistics Vision for the 21st Century

• Renewing and revisiting the overall vision for the health statistics enterprise at

defined intervals and evaluating whether the overall enterprise is meeting its 

mission; 

• Stimulating research and development directed toward new methods and 

approaches;

• Providing guidance and policy on privacy, confidentiality, and security as they 

apply to health statistics and the organizations that collect, compile, and 

disseminate them; and

• Ensuring user and wider public input into decisions that affect the overall 

performance of the health statistics enterprise and of its individual component 

systems.

Mapping the current system using the model of the 

Health Statistics Cycle

The diversity and number of organizations and entities that are involved in the 

health statistics enterprise make a simple categorization difficult. A large number of 

organizations are involved in defining data needs, analyzing data, and using health 

statistics. A comparatively smaller number are involved in the direct operation of 

data collection systems, while still fewer are involved in the process of defining and 

integrating health statistics from an enterprise-wide perspective. In this section, these 

organizations are described in order to aid in identifying functional gaps in the overall 

health statistics enterprise.

Table 2 reflects the major functional elements in the Health Statistics Cycle, and 

provides examples of the organizations and entities carrying out these functions at the 

national, state, and local levels.

At the national level, data needs are often expressed in broad terms by the Congress 

and the Executive Branch; by advocacy groups; by the business community; by the 

research community; and by managers of Federal health programs. These broadly 

stated needs are translated into specifications for individual data collection systems by 

a wide number of public and private entities that are engaged in data collection and 

dissemination. Federal statistical agencies are charged with the continuing operation of 

large-scale national data systems that are geared toward meeting multiple (as opposed 

to specific, categorical) data needs, but these agencies are augmented by many other 

research and programmatic entities. NCHS is the only Federal agency with a singular 

mission of providing health statistics, but NCHS is actually responsible for only about 

one-tenth of spending on health statistics by its parent department, DHHS.27 Other 

centers, institutes, and offices within CDC also maintain major ongoing surveys and 

27Office of Management and Business, Statistical Programs of the United States Government, fiscal year 2002, 

Washington, D.C., 2001.

Chapter 3 Developing, Evaluating and Improving Health Statistics 
27

Shaping a Health Statistics Vision for the 21st Century

data collection systems. Ongoing national health-related data systems are managed by 

virtually every other agency within DHHS, and administrative data from the Medicare 

program and other federally administered programs are often made available for research 

and statistical purposes. Data from non-health agencies, such as the Census Bureau 

(for example, data on population demographics, health insurance coverage) and the 

Bureau of Labor Statistics (for example, data on work-related injury and employee 

health benefits) are important for the study of health, and private data sources, often 

funded by foundations, provide data frequently used by policy analysts and researchers. 

Professional associations, such as the American Medical Association or the American 

Hospital Association, provide widely used information from surveys of their members. 

Similarly, private organizations, often supported by foundations, frequently conduct 

significant efforts, such as the Center for Studying Health Systems Change’s Community 

Tracking Study and the Urban Institute’s National Survey of America’s Families.

At the state level, the complexity of interaction within the health statistics enterprise 

is similar. All states have a vital statistics function and conduct population surveys 

of behavioral risk factors, maintain ongoing surveillance systems for communicable 

diseases, and collect data on newly diagnosed cases of cancer. Many state health 

departments have well-developed health data centers that produce or integrate data from 

multiple sources. As providers or financers of care, states maintain systems from which 

statistical information can be derived, collecting data as byproducts of the Medicaid 

and the State Children’s Health Insurance Program (SCHIP) and patient-level data from 

the provision of clinical care. As protectors of the public’s health and as regulators of 

health care providers, state agencies also maintain systems that gather public health 

surveillance reports as well as data collected through the oversight and enforcement arms 

of state government (licensing, certification, insurance oversight, worker compensation 

enforcement, overseeing nursing home quality, etc.). At the state level, non-public 

sources also play an important role; for example, in many states, hospital associations 

aggregate data on hospital discharges and make them available for statistical analysis.

At the local and community level, statistical efforts are much more episodic and 

sporadic. The health departments in larger cities and counties–such as New York City, 

Boston, Seattle/King County, and Los Angeles County–have well-developed health 

statistics offices. For the most part, due to the expense associated with primary data 

collection, smaller local governments and community organizations are consumers of data 

produced by others.

Finally, a number of organizations are involved in efforts to integrate and coordinate 

efforts across the health statistics enterprise. At the national level, the NCVHS provides 

advice to the DHHS Secretary and serves as a bridge to the private sector on statistical 

issues, while the internal DHHS Data Council brings together the DHHS agencies 

Chapter 3 Developing, Evaluating and Improving Health Statistics 
28

Shaping a Health Statistics Vision for the 21st Century

to coordinate statistical efforts. Individual agencies have funded data planning and 

integration efforts, such as CDC’s National Electronic Disease Surveillance System. 

National standards development organizations, such as the American National Standards 

Institute and its subject-matter oriented subgroups, facilitate processes for arriving at data 

standards that transcend public and private organizations and functions, and professional 

associations such as the National Association for Public Health Statistics and Information 

Systems, the Association of Maternal and Child Health Programs, the Council of State 

and Territorial Epidemiologists, and the Association of State and Territorial Health 

Officers, undertake data planning initiatives that have impact in all states. The Public 

Health Data Standards Consortium is a coalition of more than 30 national and state 

organizations committed to promoting and developing common data standards for pubic 

health and human services research. Both nationally and in many states, some health 

statistics agencies influence the coordination and integration of data collection efforts, 

including NCHS and some state centers for health statistics. Finally, foundations often 

provide leadership in data planning and coordination; for example, the Robert Wood 

Johnson Foundation has funded the Information for State Health Policy program and the 

recently established State Health Access Data Assistance Center.

Major issues and gaps in health statistics development, 

evaluation, and improvement

Participants in the vision process provided a great deal of positive feedback on the 

importance of health statistics in their work, examples of improvements in the availability 

and usability of selected data sets, and evidence of steps underway to improve the quality 

and relevance of health statistics. Many commented on the completeness and usefulness 

of data systems in the U.S., and some expressed the opinion that sufficient data were 

already available for a large number of specific policy and programmatic purposes. 

Particular attention was focused on the gains made in making data more widely available 

through the Internet and other electronic media, and on the nascent efforts to develop data 

standards through the Health Insurance Portability and Accountability Act (HIPAA) and 

other mechanisms.

Despite the strengths of the health statistics enterprise, and despite the masses of 

data collected by various systems, the participants in the vision process also repeatedly 

pointed out major gaps in the availability of data and in the ability of the current 

components of the health statistics enterprise to fully address needs expressed by data 

users. In a sense, the testimony and comments submitted by participants indicated that 

the health statistics enterprise is rich in data but poor in information. These comments, 

discussed in more detail below, focused on the difficulty in identifying appropriate data 

resources and in translating raw data into information useful for action at appropriate 

Chapter 3 Developing, Evaluating and Improving Health Statistics 
29

Shaping a Health Statistics Vision for the 21st Century

geographic levels. The major issues, and resulting gaps in the health statistics cycle, are 

described here and addressed separately in recommendations from NCVHS (see page 49).

1) Insufficient connections between data sources (the suppliers of data, such as 

individual respondents to surveys, hospitals holding patient records, and so forth), 

organizations that collect or aggregate data (such as organizations that conduct surveys 

or compile data from administrative systems), and data users.28 The historical view of 

health statistics has been limited to the collection, compilation, analysis, and processing 

of data – a static view that lacks explicit connections to users on both the front end 

(defining data needs and specifying necessary attributes) and the back end (translating 

statistics and evaluating the extent to which needs are met).

In recent years, there has been a constructive trend toward more formal reviews of 

data needs associated with important health issues. More often than not, however, these 

reviews focus on a specific subject matter area (such as a GAO study on environmental 

health statistics), or the statistical aspects are but one of many topics addressed in the 

context of a more broadly focused study of a health issue (for example, a discussion of 

issues in racial and ethnic data was included in the recent Institute of Medicine report 

on disparities in health care. 29,30 While these efforts are valuable, they are not useful in 

evaluating priorities across different health data needs or in integrating the efforts of data 

collection mechanisms that address multiple topics. Few are formally established as 

ongoing mechanisms that address enterprise-wide issues more broadly.

2) Lack of geographic detail and other specificity.

31 As noted in Chapter Two, it is 

clear that some data are available on most influences on the population’s health and on 

many aspects of the working of the health services system. While such data may exist at 

the national level for many research purposes, it is clear that these data are not sufficiently 

detailed to meet most research, policy, or programmatic purposes.

The relative lack of data on major health issues and trends at the state and 

community levels is a clear concern, and participants in the vision process made clear that 

this lack of data has hampered the effective pursuit of public health goals.

28This issue was raised frequently in discussion groups sponsored by the vision development process in 

Albuquerque, NM; New Orleans, LA; and Harrisburg PA. Summaries are available at 

http://www.ncvhs.hhs.gov/hsvision/Abuquerque.pdf, http://www.ncvhs.hhs.gov/hsvision/NewOrleans1.pdf, and 

http://www.ncvhs.hhs.gov/hsvision/111699.pdf See also Rice, D, “Health Statistics: Past, Present, and Future.” 

National Research Council . Toward a Health Statistics System for the 21st Century: Summary of a Workshop. 

Committee on National Statistics, Edward B. Perrin, William D. Kalsbeek, and Terri M. Scanlon, Editors. Division 

of Behavioral and Social Sciences and Education. Washington, D.C: National Academy Press, 2001; Atkinson, 

D., NCVHS public hearing testimony on “21st Century Vision for Health Statistics, Washington DC, Available 

from http://www.ncvhs.hhs.gov/010111tr.htm; and Bethell, C,. NCVHS public hearing testimony on “21st 

Century Vision for Health Statistics, San Francisco, CA, Available from http://www.ncvhs.hhs.gov/001030tr.htm 

[all websites accessed September 2002].

29U.S. General Accounting Office, “Long-Term Coordinated Strategy Needed to Measure Exposures in 

Humans,” Report GAO/HEHS-00-80, May 2000.

30National Academy of Sciences, Institute of Medicine, Smedley, B., Stith, A., and Nelson, A., ed., Unequal 

Treatment: Confronting Racial and Ethnic Disparities in Health Care, National Academy Press, Washington, 

D.C., March 2002.

31See Giachello, A., and Zangri, A., Chicago, NCVHS public hearing testimony on “21st Century Vision for 

Health Statistics, Chicago IL, Available from http://www.ncvhs.hhs.gov/000710tr.htm [accessed September 

2002]

Chapter 3 Developing, Evaluating and Improving Health Statistics 
30

Shaping a Health Statistics Vision for the 21st Century

Similarly, numerous studies have documented the lack of sufficient detail on 

race/ethnicity, income, and other socio-demographic factors in existing health statistics, 

even in large national efforts to collect health-related data. The lack of such detail has 

hampered research into the underlying causes of differentials in health; limited efforts to 

target interventions to groups at greatest risk for poor health; and made more difficult the 

task of monitoring and evaluating the effectiveness of public programs to improve health.

3) Lack of timeliness in making data available.32 Data users express frustration with 

the chronic inability of existing systems at all levels of geography and detail to produce 

results that can be used to rapidly identify and address current health problems. While 

progress has been made in many areas (for example, NCHS has cut times to produce 

results in vital statistics and surveys; in the case of the National Health and Nutrition 

Examination Survey the time it takes to produce results was cut from 3 years to 6 months 

after a completed survey year), many systems lag decades behind in implementing 

technology that is in widespread use in other sectors. For example, state vital statistics 

systems often rely on either paper-based records or DOS-based PC programs to process 

some of the most widely used health statistics.

4) Existing data are unnecessarily difficult to locate, access, and use.33 For the 

health statistics enterprise to be efficient and to avoid unnecessary duplication of effort, 

it is important to make maximum use of all relevant data that are collected. Three major 

impediments exist: First, knowledge of data resources is limited, and there are few 

comprehensive and readily available “guides” to finding existing data. While some data 

collection agencies make data available on the Internet in searchable formats, others do 

not; even when data are available, it is not readily apparent to many users how to search 

the Internet to find it. Data collected for specific analytic purposes–or for proprietary 

purposes–are often not widely publicized or referenced in searchable form. Second, once 

found, data are often not available in a user-friendly format, placing burdens on the user 

that can discourage use or make it more likely that a new data collection mechanism will 

be developed to meet the user’s need. Making data widely and easily available can be 

expensive for data collection organizations, limiting access even to data collected for 

public purposes and for the public good. Third, barriers due to legal, administrative, and 

proprietary concerns as well as to organizational practices inhibit the use of existing data 

resources.

32See Lafata, J., NCVHS public hearing testimony on “21st Century Vision for Health Statistics, Chicago, IL, 

Available from http://www.ncvhs.hhs.gov/000710tr.htm [accessed September 2002]

33“Vision” discussion groups, New Orleans, LA, 22 March 2000, Available from: 

http://www.ncvhs.hhs.gov/hsvision/NewOrleans1.pdf, and Albuquerque, NM, 1 March 2002, available from: 

http://www.ncvhs.hhs.gov/hsvision/Albuquerque.pdf; Upshaw, V., NCVHS public hearing testimony on “21st 

Century Vision for Health Statistics, Raleigh, NC, Available from http://www.ncvhs.hhs.gov/001120tr.htm [all 

websites accessed September 2002]; and Spar, E., written comments on Interim Vision Report.

Chapter 3 Developing, Evaluating and Improving Health Statistics 
31

Shaping a Health Statistics Vision for the 21st Century

34See Rice, D, “Health Statistics: Past, Present, and Future.” National Research Council. Toward a Health 

Statistics System for the 21st Century: Summary of a Workshop. Committee on National Statistics, Edward 

B. Perrin, William D. Kalsbeek, and Terri M. Scanlon, Editors. Division of Behavioral and Social Sciences and 

Education. Washington, D.C: National Academy Press, 2001; and Lee, P., NCVHS public hearing testimony on 

“21st Century Vision for Health Statistics, San Francisco, CA, Available from 

http://www.ncvhs.hhs.gov/001030tr.htm [accessed September 2002].

35

This observation based on extensive discussions in “Vision” discussion groups, notably Albuquerque, NM, 

1 March 2002, available from: http://www.ncvhs.hhs.gov/hsvision/Albuquerque/pdf; Nelson, M., Lafata, J., and 

Merryweather, P, NCVHS public hearing testimony on “21st Century Vision for Health Statistics, Chicago, IL, 

Available from http://www.ncvhs.hhs.gov/000710tr.htm; Hajat, A, NCVHS public hearing testimony on “21st 

Century Vision for Health Statistics, Washington, DC, available from http://www.ncvhs.hhs.gov/010111tr.htm; 

and Rodrian, M., NCVHS public hearing testimony on “21st Century Vision for Health Statistics, San Francisco, 

CA, Available from http://www.ncvhs.hhs.gov/001030tr.htm [all websites accessed September 2002].

5) Resource constraints have placed the performance and usefulness of major 

data collection systems at risk.34 Multi-purpose, shared data systems maintained by 

public agencies are efficient mechanisms for meeting data needs. By sharing a basic 

infrastructure, these systems address multiple issues and can often be used to meet 

specialized needs for more detailed data. For example, many of DHHS’s major surveys 

include a core of content designed to meet general needs, along with supplements or 

specialized components developed to meet a defined research or programmatic need. 

Yet these shared systems face chronic resource limitations, and have in some cases 

deteriorated to the point where they are at risk. Losing these workhorse data systems 

would cause an interruption in the data needed to monitor trends, lead to a lack of 

comparability across years, reduce opportunities for integration of diverse data activities, 

and spawn multiple, less efficient efforts more narrowly focused on specific needs or 

uses.

Reflecting these major issues, the vision process arrived at a consensus that existing 

enterprise-wide coordinating and integrating efforts were largely ineffective,

35 hampering 

potential collective efforts of the diverse elements in the health statistics enterprise to 

move toward needed improvements in health statistics. A great deal of effort has been 

devoted to such mechanisms in recent years, and organizations at the national and state 

levels have made progress in bringing about greater cohesion in the health statistics 

enterprise. Nonetheless, the need for new approaches was a clear theme throughout the 

vision process. A consensus exists that:

First, there is insufficient attention to developing consensus approaches and 

standards that would simplify collecting, protecting, and accessing data and make more 

efficient the process of developing methods, software, and specifications for individual 

data systems. Important topics to be addressed include, for example, standards for 

systems architecture, comparable questionnaires, common classification and coding 

systems, standards for the way in which data will be exchanged over the Internet, and 

conventions for presenting and formatting data that reduce the learning curve for users of 

multiple data sets.

Second, the health statistics enterprise, because it is decentralized as well as 

underfunded, has insufficiently invested in new methods (such as more efficient sampling 

approaches), technologies (such as Web-enabled, meta-data repositories, electronic data 

Chapter 3 Developing, Evaluating and Improving Health Statistics 
32

Shaping a Health Statistics Vision for the 21st Century

access initiatives) and integrated approaches (e.g., combining survey field operations, 

unifying data entry systems for clients served by multiple state programs) that could 

reduce cost, improve data quality and availability, and provide added confidentiality 

protection.

Third, insufficient attention has been given within the health statistics enterprise 

specifically and within public health more generally to developing and implementing 

training in health statistics. For example, testifiers at the NCVHS public hearings could 

cite no U.S. school of public health that currently offers even an introductory course 

devoted to health statistics. Graduate level training is needed to introduce health statistics 

to masters and doctorate level students. Additionally, expanded in-service training is 

needed for professionals already engaged in any elements of the health statistics cycle, 

beyond the valuable training already offered to state department of health employees by 

NCHS. In order to be most useful, such in-service training should rely upon a range of 

training modalities, including short courses at regular professional meetings and Webbased courses. 

Fourth, participants in the health statistics enterprise have not been effective at 

working with decision-makers who influence the processes that ultimately determine the 

availability of much of the data needed for studying health related issues. The sources 

for health statistics are often the by-product of decisions made primarily for non-health 

or non-statistical reasons: the structure or content of a medical claim; the laws and 

regulations governing access to medical records for research and statistical purposes; 

the standards for legal or administrative records; or the data elements included in data 

systems focused on the labor force or population demographics. Given the wide scope 

of influences on health, the ability to use non-health data sources is a strength of the 

health statistics enterprise; however, this often requires a major task in piecing together 

a patchwork of data resources. The current health statistics enterprise lacks the ability to 

develop and articulate effective positions and to engage with the producers of non-health 

sources of data that is important to understanding health, and also lacks the ability to 

effectively pursue opportunities to use data that flow from these other producers.

Fifth, the health statistics enterprise lacks an overall confidentiality and datasharing framework that would facilitate the integration and linkage of information while 

protecting the privacy of individual data. Current systems for health data, as well as 

underlying health records, are covered by a patchwork of state and Federal laws and 

regulations. These protections rarely address issues associated with the creation and use 

of large databases with both the potential for important public purposes and the risk of 

individual disclosure.

Sixth, there is insufficient support, training, and assistance available to users of 

health statistics. Most data are released in a form that requires users to have a high level 

of statistical sophistication as well as direct experience with the individual data set. 

Chapter 3 Developing, Evaluating and Improving Health Statistics 
33

Shaping a Health Statistics Vision for the 21st Century

Comparatively few resources are devoted to “help desks,” to the development of materials 

accompanying a data file that give users a clear description of how the data were collected 

and its limitations, or to training of users. Many system managers invest resources in 

meeting the specialized needs of their own users, but few address more general issues of 

building a competent user community that can effectively use data resources to inform 

policy and program management. While NCHS offers the University Visitation Program 

and the biennial NCHS Data Users Conference, these programs are directed toward a 

relatively narrow band of technically sophisticated users.36

Seventh, a sub-optimal allocation of resources–or an undue burden on providers 

of data–results from the lack of coordination among elements of the health statistics 

enterprise. If users are unable to identify and use existing data or work with organizations 

to modify existing data systems, there is a tendency to initiate new, single purpose data 

collection systems. This can lead to duplication of effort, lost opportunities for efficient 

shared systems, and the failure to gain maximum value from data that are collected.

Eighth, the health statistics enterprise lacks flexibility and adaptability. For a 

number of reasons, it is difficult for organizations that operate systems that produce 

health statistics to quickly adapt to meet new needs. The funding for health statistics 

is distributed throughout the decentralized health statistics enterprise, and many key 

data sources are not principally designed to address health issues. As a result, it is often 

difficult to reallocate funding to emerging health needs. Managers of data systems must 

balance the need for stable trend data against the need to address new issues. Further, in 

the absence of new resources, data system managers may choose to tinker with existing 

systems rather than to introduce fundamental changes.

Finally, these issues–and the data gaps outlined in Chapter Two–are evidence of 

a fundamental lack of an enterprise-wide planning forum. Some entities have gained a 

measure of success in planning for specific elements of health statistics. For example, 

public/private standards development organizations are effective forums for developing 

consensus standards in specific areas, such as uniform billing records and standards 

for electronic transactions. The role of NCVHS has expanded in providing advice to 

DHHS on the implementation of the data standards aspects of recent Congressionally 

mandated administrative simplification initiatives. And the DHHS Data Council provides 

a forum for coordinating activities within the Department, playing a role in reviewing 

agency budget initiatives. However, there is no single place where these efforts are all 

tied together. While the existence of these and other separate planning and coordination 

efforts can be taken as an indication of the widespread view that such functions are 

needed, these multiple initiatives and forums themselves add to the perception of 

fragmentation and disorganization in the overall health statistics enterprise.

36National Center for Health Statistics, Invitation and Registration, Available from: 

http://www.cdc.gov/nchs/events/2002duc/invitation.htm [accessed 1 July 2002].

Chapter 3 Developing, Evaluating and Improving Health Statistics 
34

Shaping a Health Statistics Vision for the 21st Century

An effective planning and decision-making effort can improve integration and 

coordination, help set system-wide goals and expectations, establish common frameworks 

and standards, and find ways to develop funding sources to ensure that the enterprise 

meets the needs of users in an effective and efficient manner. NCVHS recommendations 

in the final section of this report address how this effort can be implemented.

Chapter 3 Developing, Evaluating and Improving Health Statistics 
35

Shaping a Health Statistics Vision for the 21st Century

Chapter 4 A Vision for the Health Statistics Enterprise

Chapter Four: A Vision for the Health 

Statistics Enterprise

This chapter puts forth the joint vision of the NCVHS, CDC/NCHS, and the DHHS 

Data Council, described in terms of a mission, core values, and guiding principles. 

Achieving this vision will require the concerted efforts of multiple organizations 

and individuals at the national, state, and local levels, in both the public and private 

sectors. The partners in developing this vision look to the NCVHS for more specific 

recommendations on how to implement the vision, and to DHHS for continuing 

leadership and support from the national level for steps toward achieving the vision. 

NCVHS recommendations are included following this chapter.

Mission

The mission of the health statistics

enterprise is to provide timely, accurate, and 

relevant information that can be used to improve 

the population’s health, including information 

about the status of the population’s health, 

information that can be used to formulate 

and evaluate the effects of health policy, and 

information that can be used to manage health 

interventions and programs. Health statistics 

must be easily accessible to a wide range of professional and community users.

The mission of the health statistics enterprise can be achieved through utilization of 

an overarching conceptual framework, adoption of four core values, and implementation 

of ten guiding principles.

Overarching conceptual framework

An overarching conceptual framework 

that helps to maintain a focus on needed data 

must guide the health statistics enterprise.37

The conceptual framework should delineate 

major influences on health and place them in an 

overall context; emphasize the distribution and 

the level of health in populations; and yield a 

research agenda relevant to improving the health 

of populations. The use of an overarching 

conceptual framework will concentrate the 

health statistics enterprise on its mission, reduce 

efforts that are tangential to its mission, and 

help to accomplish needed changes within the enterprise. Most important, the use of 

Mission of the health statistics 

enterprise

To efficiently provide timely, 

accurate, and relevant information 

that can be used to improve the 

population’s health.

Attributes of an overarching 

conceptual framework

• Focuses on health, the 

population, and the community

• Emphasizes distribution and 

level of health

• Delineates major influences on 

health

• Defines a research agenda 

for improving the health of the 

population

37Black, C., Roos, N., Roos, L., “From health statistics to health information systems: a new path for the 21st

century, Available from http://www.ncvhs.hhs.gov/hsvision/CP--Black.pdf [Accessed 18 October 2002].
36

Shaping a Health Statistics Vision for the 21st Century

such a framework will focus health policy-making on core influences on the health of 

populations.

Various alternative conceptual frameworks of the influences on the health of a 

population have been developed, especially in Canada and within the World Health 

Organization. Awareness of the historical and intellectual roots of these frameworks can 

help participants in the health statistics enterprise to better understand them, and why 

they include or omit various influences. A vigorous debate about the most appropriate 

conceptual framework and the redirection of focus that it might suggest could enliven the 

U.S. health statistics enterprise, as it has in Canada, Australia, and the United Kingdom 

and other European countries. Figure 2 may stimulate such a discussion.

Core values

The health statistics enterprise rests upon four core values:

1. Maintaining the confidentiality and security of individually identifiable health 

information

2. Maximizing the scientific integrity of all aspects of health statistics while 

acknowledging the specific ways in which the political, cultural, and business 

contexts may affect data collection, analysis, and interpretation

3. Optimizing the enterprise’s accountability to its users to ensure the availability of 

the information that is needed for improving the nation’s health

4. Ensuring the enterprise’s accountability to its data suppliers to minimize their 

burden and to provide them with timely feedback.

Guiding principles

In order to actualize its four core values, the current U.S. health statistics enterprise 

must reinvigorate itself by implementing ten guiding principles:

1. Enterprise-wide planning and coordination to ensure relevance to local, state, 

and national policy and program decision-making and to an overall conceptual 

framework of the influences on the health of populations.

Enterprise-wide planning and coordination are needed to ensure that the individual 

components of the U.S. health statistics enterprise collectively fulfill the mission 

of efficiently developing, analyzing, and providing timely, accurate, and relevant 

information for improving the population’s health. Without enterprise-wide planning 

and coordination, the individual components of the health statistics enterprise–those 

operating at the national, state, and local levels, and in both the public and private 

sectors–may undertake overlapping and duplicative activities. Enterprise-wide planning 

and coordination can help to concentrate resources on the highest priority policy and 

programmatic issues, can contribute to efficient use of scarce health statistics resources, 

and can maximize transfer of new methods and best practices.

Chapter 4 A Vision for the Health Statistics Enterprise
37

Shaping a Health Statistics Vision for the 21st Century

Some planning and coordination already 

occurs, most notably at the national level. The 

CDC’s National Electronic Disease Surveillance 

System activities, DHHS’s Healthy People 

goal-setting efforts, and the implementation 

of HIPAA have engendered some public and 

private sector planning and coordination at 

all geopolitical levels. At the state and local 

levels, several attempts to foster planning 

and coordination have occurred, including 

Louisiana’s Turning Point Partnership,38

Arkansas’ Health Improvement Process39, and the National Association of County and 

City Health Officials and CDC’s Mobilizing for Action through Planning and Partnerships 

process.40 However, most planning and coordination efforts at all geographic levels are 

episodic and largely confined to compilation of data on individual diseases or groups 

of diseases. Current planning and coordination efforts tend to involve unequal dyadic 

relationships, with a Federal or state agency essentially determining the health statistics 

agenda, priorities, and methods of state or local health departments.

Enterprise-wide planning and coordination will necessarily involve organizations 

and individuals at all levels of government and in the public and private sectors. Planning 

and coordination will entail establishing enterprise-wide expectations regarding standards 

for data collection, management, and exchange; for the timeliness, validity, and reliability 

of data; for access to and use of data; and for the ongoing evaluation of the individual 

components of the health statistics enterprise. Planning and coordination will also 

involve joint agenda-setting for health statistics organizations throughout the enterprise, 

in such areas as addressing new and emerging health problems, building sampling frames 

that can produce data generalizable to different units of analysis, expanding and validating 

the array of survey questions usable by different organizations within the health statistics 

enterprise, and integrating surveys, registries, surveillance systems, and administrative 

health data systems.

2. Broad collaboration among data users, producers, and suppliers at local, state, 

and national levels to ensure efficiency of the enterprise and the usefulness of

the data that it produces.

The corollary to enterprise-wide planning and coordination is broad collaboration 

and integration to ensure efficiency of the enterprise’s efforts and the usefulness of data 

Enterprise-wide planning 

and coordination can help 

to concentrate resources on 

the highest priority policy and 

programmatic issues, can 

contribute to efficient use of 

scarce health statistics resources, 

and can maximize transfer of new 

methods and best practices.

38Louisiana Turning Point Partnership, “Public health improvement plan: a catalyst for change,” April 2000, pp. 

38-40, Available from: http://www.lphi.org/turning.html [accessed 6 February 2002].

39Nugent, R., NCVHS public hearing testimony on: “21st Century Vision for Health Statistics,” Washington, D.C., 

11 January 2000, Available from: http://www.ncvhs.hhs.gov/010111tr.htm [accessed 1 September 2002].

40Upshaw, V., NCVHS public hearing testimony on: “21st Century Vision for Health Statistics,” Research Triangle 

Park, 20 November 2000, Available from: http://www.ncvhs.hhs.gov/001120tr.htm [accessed 1 September 

2002]; National Association of County and City Health Officials, Available from: http://www.naccho.org, 

[accessed 1 September 2002].

Chapter 4 A Vision for the Health Statistics Enterprise
38

Shaping a Health Statistics Vision for the 21st Century

provided by the enterprise. Collaboration must occur in ways, among partners, and 

on issues that have not typically occurred in the past. Collaboration must occur at all 

geographic levels among those originally supplying data; those responsible for compiling, 

analyzing, and disseminating data; and those using the data, whether they are in the 

public or private sector.

Collaboration must rest upon mutual recognition of and respect for the needs of 

different organizations and different functions within the enterprise, as well as clear 

definitions of roles and responsibilities of organizations within the enterprise. Working 

toward the shared goal of producing information for improving the population’s health, 

collaboration between those supplying data (e.g., community members and health care 

providers) and those who collect and process these data can result in increased awareness 

among data collectors of the demands and burdens on data suppliers and adjustment of 

data collection procedures to reduce those burdens. Collaboration among data users and 

data producers can also result in providing information that more closely meets the needs 

of data users.

3. Rigorous policies and procedures for protecting the privacy of individuals and 

the confidentiality and security of data.41

In protecting data confidentiality, we must distinguish between the confidentiality 

and security of individual record data and that of aggregate data. The most basic 

confidentiality and security issues around potentially identifiable individual record data 

include ensuring that the data are collected, released, and used only for specific approved 

purposes directly related to improving the population’s health. The data must be held 

securely, so as to maximize both the privacy of the data subjects and the integrity of the 

data themselves. Only the minimum data necessary for specific approved uses must 

be employed, whether those uses involve creating knowledge, making health policy, or 

developing programs. The process for determining which uses of potentially identifiable 

individual record data improve the population’s health, which uses are approved, and 

which data are minimally necessary may vary from data set to data set and from use to 

use. However, clear laws, regulations, or administrative or programmatic rules must 

delimit all uses of potentially identifiable individual record data.

The most basic confidentiality issues around the use of aggregate data include 

guaranteeing the privacy of individual data subjects through ensuring that their 

identities cannot be determined from electronic data files, tables, charts, maps, or 

written documents. This can be accomplished through a variety of disclosure limitation 

techniques, such as algorithms for suppression of cells with potentially high disclosure 

risk.

41“The terms privacy, confidentiality, and security are used in many different ways to discuss the protection 

of personal health information.” In this report privacy refers to “an individual’s desire to limit the disclosure 

of personal information.” Confidentiality refers to “a condition in which information is shared or released in a 

controlled manner. Organizations develop confidentiality policies to codify their rules for controlling the release 

of personal information in an effort to protect patient privacy.” Security consists of “a number of measures 

that organizations implement to protect information and systems. It includes efforts not only to maintain 

the confidentiality of information, but also to ensure the integrity and availability of that information and the 

information systems used to access it.” Source: Committee On Maintaining Privacy And Security In Health 

Care Applications Of The National Information Infrastructure, For the Record: Protecting Electronic Health 

Information. National Academy Press, Washington, D.C., 1997, page 1.

Chapter 4 A Vision for the Health Statistics Enterprise
39

Shaping a Health Statistics Vision for the 21st Century

The health statistics enterprise confronts new challenges in ensuring the 

confidentiality and security of individually identifiable health information. Some 

challenges will require novel solutions, and some challenges will require rededicating 

ourselves to stringent implementation of existing policies and procedures.

New confidentiality and security challenges include:

• the increasing availability of aggregated health statistics on the World Wide Web;

• the increasing interest in and opportunities for linkage of multiple data sets

containing identified or de-identified individual records and for linkage of 

multiple data sets containing aggregated data;

• the increasing use of standard formats for data collection, enabling easier linkage 

of identified and de-identified individual record data;

• the emphasis upon greater efficiency in data collection through use of data for 

more than one purpose; and 

• the need to harmonize health statistics confidentiality and security laws, policies, 

and practices in the private and public sectors at all levels of government with 

those mandated under HIPAA.

All of these challenges provide the health statistics enterprise with opportunities for 

more successfully fulfilling its fundamental mission. But addressing these challenges 

will require that the health statistics enterprise find and maintain an appropriate balance 

between–on the one hand–maximizing the confidentiality of data and the privacy of data 

subjects and–on the other hand–collecting and providing information for improving the 

population’s health. Improved security systems can go a long way toward establishing 

confidence in the integrity of health statistics systems.

The health statistics enterprise must rely upon privacy, confidentiality, and security 

policies and procedures that are clear-cut, easily understandable to the public and to data 

subjects, and open to external review. Oversight of policies and procedures and their 

implementation is necessary, and external review of policies and procedures and their 

implementation should be encouraged or mandated.

4. Flexibility to identify and address emergent health issues and needs.

The health statistics enterprise must develop the capacity to identify health issues for 

the population both before and as they emerge. These issues could include the emergence 

of new at-risk subpopulations; new health services structures such as Integrated Delivery 

Networks,42 expanded use of certain types of health services, such as alternative medicine 

approaches, and newly identified health needs. The enterprise should not restrict itself to 

continually refining retrospective measurements of already-identified health problems of 

the population. Ongoing data collection efforts must have the flexibility to prospectively 

identify new influences on the population’s health, changing patterns in health, and health 

42An “Integrated Delivery Network” is a network of affiliated health care providers and institutions with the 

capability of offering comprehensive and coordinated health services within a defined geographic area. 

Integrated delivery networks are often associated with a major metropolitan teaching hospital as the hub of 

the network and usually include physician offices, community health centers, and community hospitals. The 

network often has fully or partially centralized financial and administrative systems.

Chapter 4 A Vision for the Health Statistics Enterprise
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Shaping a Health Statistics Vision for the 21st Century

issues in new subpopulations. This flexibility should be incorporated into all ongoing 

data collection efforts, including registries and administrative data sets. 

5. Use of data standards to facilitate sharing and comparability of data.

The recent NCVHS report Information for Health: A Strategy for Building the 

National Health Information Infrastructure describes standards as “the fundamental 

building blocks of effective health information systems...essential for efficient and 

effective public health and health care delivery systems.”43 In Every Manager’s Guide to 

Information Technology, Peter Keen offers a more technical definition: “Standards are 

formats, procedures, and interfaces that ensure the equipment and software from a range 

of vendors will work together.”44

Standards and consensus approaches can be developed for individual data elements 

(addressing, for example, definition, nomenclature, taxonomy, vocabulary, and coding); 

content of specific data sets; the structure of data files (field type and order, file formats, 

database structures); collection of data (questionnaire design, sampling protocols, 

laboratory methods, validation of data entry); storage, manipulation, and processing 

(security and integrity of data, rules for aggregating and analyzing); transmission of data 

(message format, format and content for each field, format for electronic data interchange 

security); and the presentation and dissemination of data.

Standards and consensus approaches for the 21st century health statistics enterprise 

must meet five criteria: 

First, standards should be applicable to and implemented for multiple purposes on 

a truly enterprise-wide basis. The standards should apply to all geographic levels and to 

both the public and private sectors. The standards should cut across present disease- and 

issue- specific data silos, which have historically been fostered by categorical Federal 

funding streams. Standards should be equally appropriate for administrative health data 

systems, surveillance data systems, survey data, and registries.

Second, standards should extend beyond the health statistics enterprise itself to 

incorporate multiple purposes. In keeping with the recommendations in Information 

for Health: A Strategy for Building the National Health Information Infrastructure, 

standards should be equally applicable for the population health, personal health, and 

healthcare provider dimensions.45

Third, standards should facilitate data linkage and data sharing while protecting the 

confidentiality and security of identifiable individual records. Facilitation of data linkage 

should occur even in the absence of the implementation of the national health identifier 

43National Committee on Vital and Health Statistics, Information for Health: A Strategy for Building the National 

Health Information Infrastructure, 2001, Available from: http://ncvhs.hhs.gov/nhiilayo.pdf [accessed 24 

September 2002].

44Keen, P., Every Manager’s Guide to Information Technology, Harvard Business School Press, Cambridge, MA,

Available from: http://www.peterkeen.com/emgit002.htm [Accessed 18 October 2002]. 

45National Committee on Vital and Health Statistics, Information for Health: A Strategy for Building the National 

Health Information Infrastructure, 2001, Available from: http://ncvhs.hhs.gov/nhiilayo.pdf [accessed 24 

September 2002].

Chapter 4 A Vision for the Health Statistics Enterprise
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Shaping a Health Statistics Vision for the 21st Century

initially mandated by HIPAA; data linkages can be accomplished at the community level 

even before they are accomplished at the individual level.

Fourth, standards should enhance the comparability of data and results across states, 

across governmental levels, and between the public and private sectors.

Fifth, standards should be flexible and responsive to the needs of different 

components of the health statistics enterprise, including local and state health needs.

In short, standards must be intelligently developed and applied for the 21st century 

health statistics enterprise. The development and application of these standards must 

constantly return to the touchstones: the purpose of the standards and the five necessary 

criteria.

The development of enterprise-wide standards and consensus approaches and 

the adoption of standards recommended by national or international organizations are 

facilitated by numerous factors. There is a rich and long history of the use of standards 

in health statistics, including the early 20th century development of the International 

Classification of Diseases and the U.S. standard certificates of live birth and death. 

Laws and policies, such as HIPAA and the Office of Management and Budget’s release 

in 1997 of its revisions to the Standards for the Classification of Federal Data on Race 

and Ethnicity, mandate the use of standards for specific data collection and transmission 

efforts. Federal and state initiatives, such as the CDC’s National Electronic Disease 

Surveillance System, its Public Health Conceptual Data Model and the activities of the 

Public Health Data Standards Consortium provide an impetus and a framework for the 

development of enterprise-wide standards. Finally, the continued recommendations, 

oversight, and encouragement of NCVHS itself will also prove essential to development 

and implementation of enterprise-wide standards and consensus approaches.

6. Sufficient detail at different levels of aggregation to support local, state, and 

national policy and programmatic decision-making.

Health policy-making and implementation, as well as the development and 

management of health programs, occur at the local, state, and national levels. Health 

statistics must support both policy and program functions at all three governmental levels. 

Similarly, health statistics must support research employing various units of analysis. 

Research involving health statistics can employ neighborhood, city or country, state, or 

national units of analysis. The specific policy, programmatic, and research uses of each 

data set must dictate the needed level of detail at different levels of aggregation.

The gold standard for data collection is a data set that can be “rolled up” seamlessly 

from the neighborhood level, to the city or county level to the state level to the regional 

level and to the national level. Such data sets allow the simultaneous development, 

implementation, and evaluation of policies and programs at the local, state, and national 

Chapter 4 A Vision for the Health Statistics Enterprise
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Shaping a Health Statistics Vision for the 21st Century

levels. Some data collection systems of this kind currently exist within the U.S. 

health statistics enterprise, although they are almost exclusively limited to registries, 

surveillance systems, or administrative health data systems. Other existing data 

collection systems, such as population-based surveys, have the potential to be adapted to 

allow aggregation from local to state to national levels.

In developing data sets with sufficient detail at different levels of aggregation, 

consideration must be provided to both nationally small subpopulations with large local 

presences and subpopulations with small numbers in local areas but with measurable 

national presences. Examples of nationally small subpopulations with large local 

presences include many ethnic groups whose historical migration patterns have resulted 

in substantial concentrations in small numbers of U.S. cities or counties. Examples 

of subpopulations with small numbers in local areas but with measurable national 

presences include groups of individuals with specific chronic conditions or disabilities. 

Methodological issues inherent in developing data sets with sufficient detail to represent 

both of these types of subpopulations must be systematically addressed.

The ability to return useful information to data suppliers is an additional 

consideration in designing data sets at sufficient levels of detail. Through returning 

information to those who have employed their time, energy, and resources to supply 

data for statistical purposes, we can show the utility of health statistics generally as well 

as of a specific data collection effort. Demonstrating such a return on investment is a 

necessary step in improving the validity, reliability, and completeness of health statistics.

The U.S. health statistics enterprise must devote concentrated and coordinated 

attention to increasing the number of data sets providing detail at multiple levels 

of aggregation. This can occur only through the enterprise-wide planning, broad 

collaboration and integration, and compatible standards described in guiding principles 

#1, 2, and 5 above.

7. Integrated, streamlined data collection for multiple purposes.

Data collection within the current health statistics enterprise is distinguished by 

multiple, separate data collection systems. These systems operate at all governmental 

levels, cover many diseases, and use various types of data, including administrative 

health data, surveillance data, survey data, and data from disease or vital event registries. 

Because most of these systems are not integrated–or even coordinated–an individual data 

supplier often provides the same data to different data systems within the same health 

agency. For example, for each birth the obstetric hospital will provide overlapping data 

on the standard certificate of live birth, the hospital discharge record, claims forms for 

third party payment, newborn screening forms, the birth defects registry, and perhaps 

to condition-specific surveillance systems as well. All of these distinct data collection 

Chapter 4 A Vision for the Health Statistics Enterprise
43

Shaping a Health Statistics Vision for the 21st Century

systems require similar data on infant’s and mother’s name, place of birth, date of birth, 

address, race, ethnicity, and so forth, often including overlapping clinical data. Figure 4 

uses a workplace injury as the health event to illustrate the wide range of health records 

that might be generated as an injured worker seeks treatment from an expanding range of 

health providers, along with administrative records related to the event, to payment for 

treatment, and to possible death. This demonstrates how multiple systems are used to 

aggregate health statistics. Few of these efforts to aggregate statistics can currently rely 

on standardized or integrated systems.

Chapter 4 A Vision for the Health Statistics Enterprise
44

Shaping a Health Statistics Vision for the 21st Century

Figure 4. Multiplicity of data sources and statistical systems

Chapter 4 A Vision for the Health Statistics Enterprise
45

Shaping a Health Statistics Vision for the 21st Century

The 21st century health statistics enterprise must rationalize and systematize 

presently disparate and distinct data collection systems. Multiple purposes or uses for 

data collection need not necessitate multiple data collection systems. By designing 

integrated, streamlined data collection for multiple purposes, greater efficiencies at 

reduced costs will be achieved.

The goals of integrated, streamlined data collection systems are threefold: First, to 

reduce the burden on data suppliers currently engendered by multiple overlapping data 

collection systems, by collecting the same data only once and then making it available to 

other data users;

Second, to minimize–where appropriate–the technical and administrative barriers 

between different data collection systems: administrative systems, surveillance systems, 

surveys, and registries; and

Third and finally, to enable the use of health data for different purposes by different 

users, rather than different uses requiring the establishment and maintenance of different 

data collection systems.

Integrated, streamlined data collection for multiple purposes need not imply a 

loss of confidentiality and security for individually identifiable data. With appropriate 

laws, policies, procedures, and technologies, the replacement of multiple data collection 

systems with integrated, streamlined data collection systems can enhance confidentiality 

and security.

8. Timely production of valid and reliable health statistics.

Timely production of valid and reliable data is inherent to the mission of the health 

statistics enterprise. Expectations and standards for the timeliness of health statistics have 

been changing over the last several years. Although in past years birth data were accepted 

as timely if published more than one year after the conclusion of the data year, individual 

states and NCHS now routinely publish birth data within 12 months of the conclusion of 

the data year. While previously cancer incidence data were routinely published two or 

even three years after the conclusion of the data year, CDC is now moving states toward 

publishing cancer incidence data within 12 months of the conclusion of the data year. 

The production of more timely health statistics may require careful consideration of 

whether the considerable investments currently made to achieve small increments in data 

quality are effective use of resources.

9. Appropriate access to and ease of use of health statistics.

To fulfill its mission, the health statistics enterprise must provide full and easy 

access to health statistics to a broad variety of users. The type and extent of the access 

must be appropriate for both the particular user and the particular use. Access to the 

detailed data needed by a health services researcher studying disparities across ethnic 

Chapter 4 A Vision for the Health Statistics Enterprise
46

Shaping a Health Statistics Vision for the 21st Century

groups in the utilization of different treatment modalities for advanced breast cancer 

would be inappropriate for community users conducting a local needs assessment.

The ready availability of data produced by the health statistics enterprise is a 

significant community resource for improving health. A wide variety of modes of access 

to health statistics must be employed, including the Internet, other forms of electronic 

access, public use data sets where feasible, and print media. Different modes of access 

must be viewed as complementary rather than as mutually exclusive. The increasing 

use of the World Wide Web as the backbone for interactive systems for disseminating 

public health data will provide the health statistics enterprise with new opportunities for 

customizing access to meet the distinct needs of different communities of users.46 As is 

already the case in some of the more advanced Web-based interactive systems maintained 

by state health departments, customization would include providing alternative user 

interfaces for access to the same data, matched to different levels of user technical skills 

and goals.

10. Continuous evaluation of the scientific integrity, accuracy, and timeliness of 

health statistics and of the ability of the health statistics enterprise to fulfill its 

mission.

Continuous evaluation will aid in ensuring that new and emerging health statistics 

needs are identified and responded to on an ongoing basis. Evaluation efforts relevant to 

the health statistics enterprise are now largely limited to peer reviews of articles submitted 

to professional journals, the review process for competitive applications for Federal and 

foundation grants and cooperative agreements, and legislative review of health statistics 

programs. Mechanisms must be developed for continually evaluating the extent to which 

user needs are met, for assessing the scientific integrity, accuracy, and timeliness of health 

statistics, and for identifying improvements that must be made to meet future user needs. 

New metrics for evaluating the ability of the health statistics enterprise to meet future 

needs must be developed. New training is also needed so that those engaged throughout 

the health statistics enterprise are equipped with the appropriate methods to conduct 

continuous evaluation. Continuous evaluation must rest upon enterprise-wide planning 

and coordination in order to assure independence and openness.

As pointed out in Chapter One, the health statistics enterprise rests upon choices 

about what to study and how to study it. These choices are based on judgments about 

what issues merit data collection and analysis. Through aiming for and exercising 

self-awareness about values and choices, through inviting public scrutiny, and through 

following practices that ensure openness, the health statistics enterprise can maximize its 

scientific objectivity and its integrity.

46Friedman, D., Anderka, M., Krieger, J., Land, G., and Solet, D., Accessing population health information 

through interactive systems: lessons learned and future directions, Public Health Reports 2001;116: 132-141.

Chapter 4 A Vision for the Health Statistics Enterprise
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Shaping a Health Statistics Vision for the 21st Century

The health statistics enterprise and the NHII

In its recent report on Information for Health: A Strategy for Building the National 

Health Information Infrastructure, the NCVHS defines the NHII as including “not just 

technologies but, more importantly, values, practices, relationships, laws, standards, 

systems, and applications that support all facets of individual health, health care, and 

public health.”47 As emphasized in the NCVHS report, the purpose of the NHII is 

“sharing information and knowledge appropriately so it is available to people when they 

need it to make the best possible health decisions.” The report points out that the NHII 

consists of three dimensions: the population health dimension, the healthcare provider 

dimension, and the personal health dimension. The health statistics enterprise draws 

upon data collected from all three NHII dimensions. The data utilized and analyzed by 

the enterprise fall within the loose boundaries of the population health dimension. As 

indicated in Figure 5, substantial overlap exists among the three NHII dimensions, and 

many health statistics fall in those areas of overlap. For example, vital statistics data can 

be used both for clinical purposes within the healthcare provider dimension and for health 

statistics purposes within the population health dimension. Mandatory disease reporting 

data can be used by authorized clinicians in the health care provider dimension, by 

affected individuals in the personal health dimension, and for health statistics within the 

population health dimension.

The 21st century health statistics enterprise in the U.S. must be viewed within the 

context of the NHII and its participants must become active and enthusiastic participants 

in the development of the NHII. Participation in the development of the NHII can help 

the health statistics enterprise to implement its core values and guiding principles. For 

example, the rigorous policies and procedures for protecting the privacy of individuals 

and the confidentiality and security of data developed within the health statistics 

enterprise can only be effective if they reflect those developed within the broader 

NHII. Similarly, the data standards utilized within the health statistics enterprise should 

wherever possible mirror those employed in the broader NHII. The NHII also provides 

the conceptual framework and ultimately the tools with which to transform integrated, 

streamlined data collection for multiple purposes from solely a guiding principle into a 

reality.

Chapter 4 A Vision for the Health Statistics Enterprise

47National Committee on Vital and Health Statistics, Information for Health: A Strategy for Building the National 

Health Information Infrastructure, 15 November 2001, page 1, Available from: http://ncvhs.hhs.gov/nhiilayo.pdf 

[accessed 24 September 2002].
48

Shaping a Health Statistics Vision for the 21st Century

Figure 5. The National Health Information Infrastructure

Chapter 4 A Vision for the Health Statistics Enterprise
49

Shaping a Health Statistics Vision for the 21st Century

NCVHS Recommendations for Achieving the 

Health Statistics Vision for the 21st Century

Developing the recommendations

NCVHS worked closely with its partners, CDC’s NCHS and the DHHS Data 

Council, through a consensus process to identify a vision for health statistics. That shared 

vision is reflected in the preceding chapters of this report. Achieving this vision will 

require leadership from a variety of sources and resolution of a large number of scientific, 

interagency, and policy issues. As an advisory body charged with providing advice to the 

Secretary of Health and Human Services, NCVHS elected to exercise its independence in 

presenting its own recommendations for achieving this vision.

The NCVHS recommendations presented here are based on suggestions that 

emerged through the vision process. The recommendations address the problems 

identified in Chapter Two of this report relating to the lack of capacity of the U.S. health 

statistics enterprise to fully describe the population’s health and the factors that influence 

the population’s health. The recommendations also address the challenges outlined in 

Chapter Three relating to the ability of the enterprise to capture all appropriate data and to 

translate raw data into information useful for action.

Overview of recommendations

NCVHS recommendations are provided for implementing the vision described 

in Chapter Four. Thirty recommendations are included for moving the ten guiding 

principles from vision to reality, and six recommendations are included for moving the 

overarching conceptual framework for the health statistics enterprise from vision to 

reality. The recommendations relate to data access and use, data set development, data 

standards, enterprise structure, evaluation, policy, research agenda, and training.

NCVHS believes that in order to realize the vision priority must be placed on 

strategies for building a stronger integrating and coordinating “hub” for the health 

statistics enterprise, as described in Chapter Three. Implementation of the four NCVHS 

recommendations pertaining to enterprise-wide planning and coordination (Guiding 

Principle 1) is essential for constructing a strong health statistics enterprise “hub”:

• Assignment of responsibility and authority for health statistics leadership within 

DHHS to a reconstituted National Center for Health Statistics, supported by a 

strong Board of Scientific Counselors. [GP1.1]

• Establishment of a national Health Statistics Planning Board with overall 

responsibility for planning and agenda setting for health statistics in the United 

States. [GP1.2] 

NCVHS Recommendations
50

Shaping a Health Statistics Vision for the 21st Century

• Designation of overall responsibility for health statistics planning and 

coordination activities within each state’s government to a single state agency, 

supported by autonomous state Health Statistics Planning Boards. [GP 1.3]

• Development of appropriate graduate and in-service training and continuous 

education addressing all elements of the health statistics cycle. [GP 1.4]

These recommendations require structural and cultural changes within the health statistics 

enterprise, starting at the Federal level and extending both to state governments and the 

private sector. NCVHS regards it as critical for DHHS to assert leadership by quickly 

establishing a locus of responsibility for follow-up on these recommendations, addressing 

organizational issues raised in these recommendations, and providing for adequate 

advisory input and structures for collaboration across elements of the enterprise.

Recommendations relating to Guiding Principle 1 are essential first steps toward 

achieving the health statistics vision, and are highlighted because of their importance. 

However, they only enable the achievement of the nine other guiding principles and the 

overarching conceptual framework. The remainder of this chapter provides detailed 

NCVHS recommendations. Prior recommendations from the NCVHS and other sources 

that were developed during earlier efforts to assess population health information needs in 

the U.S. and other countries are referenced where appropriate.

Detailed recommendations for achieving the ten guiding 

principles

Guiding principle 1. Enterprise-wide planning and coordination to 

ensure relevance to local, state, and national policy and program 

decision-making and to an overall conceptual framework of the 

influences on the health of populations.

GP recommendation 1.1: Enterprise structure – reconstituted NCHS, 

with a strong Board of Scientific Counselors

Planning and coordination among Federal agencies contributing to the health statistics 

enterprise must be significantly strengthened to ensure that duplication and overlap 

are minimized and that the Federal government efficiently and effectively advances 

the mission of the health statistics enterprise.48 Historically, this goal has been elusive 

due to the highly decentralized nature of Federal health statistics programs. Achieving 

this goal requires that the Secretary should designate a reconstituted NCHS as the lead 

agency for health statistics within DHHS, with responsibility and authority for statistical 

leadership, health statistics standards, health statistics coordination, and health statistics 

48This point was made repeatedly by participants in the process for developing health statistics vision for the 

21st century. For example, see: Rice, D, “Health Statistics: Past, Present, and Future.” National Research 

Council. Toward a Health Statistics System for the 21st Century: Summary of a Workshop. Committee on 

National Statistics, Edward B. Perrin, William D. Kalsbeek, and Terri M. Scanlon, Editors. Division of Behavioral 

and Social Sciences and Education. Washington, D.C: National Academy Press, 2001; and comments by 

Atkinson, D., NCVHS public hearing testimony on: “21st Century Vision for Health Statistics,” Washington, D.C., 

11 January 2000, Available from: http://www.ncvhs.hhs.gov/010111.tr.htm [accessed 1 September 2002].

NCVHS Recommendations
51

Shaping a Health Statistics Vision for the 21st Century

agenda planning.49 In order to maximize its contribution to the NHII generally and the 

health statistics enterprise specifically, the reconstituted NCHS should be strengthened so 

that it can provide greater national leadership for integrating and coordinating the health 

statistics enterprise, serving as an integral part of the “hub” described in Chapter Three. 

The responsibilities of the reconstituted NCHS must stretch far beyond the collection 

and analysis of a limited number of data sets and include the interpretation of data on 

population health and influences on population health from a wide variety of DHHS and 

non-DHHS Federal agencies, state agencies, and private organizations. The reconstituted 

NCHS must establish a strong ongoing link to any DHHS office and senior position 

instituted (as recommended previously by the NCVHS) to provide strategic leadership for 

developing and setting the agenda for the NHII. The reconstituted NCHS must also work 

closely with its counterpart agencies in the states, providing support and leadership to 

help states fulfill their potential as key components of the health statistics enterprise.

The reconstituted NCHS must be supported by a Board of Scientific Counselors, 

established by the Secretary of Health and Human Services.50 This board would advise 

NCHS on carrying out its expanded responsibilities. In close coordination with NCVHS 

(which would continue to advise the Secretary on overall health information policy, 

HIPAA implementation, and related health statistics activities), the Board would provide 

direct advice and oversight for NCHS in the conduct of its statistical programs, in efforts 

to integrate statistical efforts across DHHS and the wider Federal government, and in 

constructive roles that NCHS and its partners can play in advancing the overall vision for 

the health statistics enterprise.

49Prior recommendations and related models:

a) NHII recommendation 1 for the federal government. Source: NCVHS, Information for Health: A

strategy for building the National Health Information Infrastructure, U.S. Dept of Health and Human

Services, Washington, D.C., November 2001, page 39, Available from: http://ncvhs.hhs.gov/nhiilayo.pdf

b) NHII recommendation 2 for the Federal government. Source: NCVHS, Information for Health: A

strategy for building the National Health Information Infrastructure, U.S. Dept of Health and Human 

Services, Washington, D.C., November 2001, page 40.

c) Recommendation on “strengthening the statistical system through organizational change.” Source

Norwood, J. Organizing to Count: Change in the Federal Statistical System. Urban Institute Press, 

Washington, D.C., 1995, pp. 71-76.

d) Bradburn, N. “The future of federal statistics in the information age,” The 1997 Morris Hansen Lecture, 

22 October 1997, page 14.

e) Recommendation for new Health Information, Communication, and Data Agency. Source: 

Milbank Memorial Fund, Bufford, J. and Lee, P., “Health policies for the 21st century: challenges and 

recommendations for the U.S. Department of Health and Human Services,” September 2001, page 18. 

Available from: http://www.milbank.org/01091healthpolicies.html [accessed 7 November 2001].

50In 2000, a charter was approved for a Board of Scientific Counselors for NCHS; however, the Secretary has 

not yet appointed members. The charter and membership for this Board would need to be revisited in light 

of the additional responsibilities proposed for NCHS in these recommendations. For example, the expanded 

responsibilities of the reconstituted NCHS will necessitate that the Board’s membership be drawn from a broad 

spectrum of the health statistics enterprise, including NCHS’ state counterpart agencies.

NCVHS Recommendations
52

Shaping a Health Statistics Vision for the 21st Century

GP recommendation 1.2: Enterprise structure – autonomous Health 

Statistics Planning Board 

Planning and coordination between private and public sectors and Federal, state, and 

local levels of government should occur through a national Health Statistics Planning 

Board (HSPB).51,52 The HSPB should be initially Federally funded but autonomous. 

Its membership should consist of representatives from throughout the health statistics 

enterprise, including representatives of organizations that serve as data sources; 

representatives of organizations that collect, aggregate, and compile data; representatives 

of Federal, state, and local governments; data analysts; and a broad range of health 

statistics users. Consideration should be given to a high level Federal mandate that would 

establish its roles and responsibilities, but the Board would ultimately be a collaborative 

effort of multiple member organizations. The HSPB will be an enterprise-wide forum 

that fosters intersectoral collaboration and integration. Its functions should include:

• establishing the agenda for the enterprise and identifying high priority population 

health issues requiring data and analysis;

• periodically evaluating the extent to which the enterprise is fulfilling its mission;

• resetting the vision as necessary;

• engaging in consensus planning for correcting deficiencies in the enterprise’s 

capacity to fulfill its mission;

• recommending adequate resources to support the enterprise;

• proposing changes in existing data collection systems, new uses of existing data

collection systems, and new data collection systems to provide needed 

information on high priority population health issues; and

• fostering the development of enterprise-wide standards.

51The NCVHS reports to the Secretary of DHHS and provides overall advice on health information policy. The 

BSC would report to the Director of NCHS, and provide advice on NCHS activities. The HSPB would be a nongovernmental forum, providing overall direction to all levels of the health statistics enterprise in the public and 

private sectors. As the health statistics enterprise evolves and is strengthened, the respective roles of related 

advisory bodies will need to be assessed.

52Prior recommendations and related models:

a) National Research Council, Kalsbeek, W. and Perrin, E., “Some new directions,” Toward a Health Statistics 

System for the 21st Century: Summary of a Workshop, National Academy Press, Washington, D.C. National 

Academy Press, 2001, pp. 62-64.

b) NHII recommendation 1and 2 for state and local government. Source: NCVHS, Information for Health

A strategy for building the National Health Information Infrastructure, U.S. Dept of Health and Human 

Services, Washington, D.C., November 2001, page 42.

c) Australian Institute of Health and Welfare, “Developing public health information capacity, an infrastructure 

for managing the national development of public health information;” National Public Health Information 

Development Plan, recommendation 3.5, 1999; Source: Australian Institute of Health and Welfare and the 

National Public Health Information Working Group, National Public Health Information Development Plan, 

Australian Institute of Health and Welfare, Canberra, 1999, page vi.

d) National Health Information Agreement for Australia. Source: Australian Institute of Health and Welfare, 

“Sharing the fruits of coordination of health statistics in Australia,” presented at Rome, Italy, 14-16 October 

1998.

e) A Network for Health Surveillance in Canada. Source: Health Canada, A Network for Health Surveillance in 

Canada, July 1999.

f) Recommendation on Canadian Population Health Information structure. Source: Canadian Institute for 

Health Information, Roadmap Initiative . . .Launching the Process, Canadian Institute for Health Information, 

Ottawa, March 2000, pp. 19-21.

NCVHS Recommendations
53

Shaping a Health Statistics Vision for the 21st Century

GP recommendation 1.3: Enterprise structure – coordination of 

state health statistics activities by a single state agency, supported 

by autonomous state Health Statistics Planning Boards

Within each state, planning and coordination among state agencies contributing to the 

health statistics enterprise should be assigned to a single state agency. This agency 

should have the leadership and technical expertise needed for state government-wide 

planning, budgeting, and agenda setting. Such agencies, often referred to as State Centers 

for Health Statistics, should be parallel in responsibility and capability to the strengthened 

Federal counterpart described in Recommendation GP 1.1. These agencies should be 

supported by autonomous state HSPBs, which will provide parallel functions at the state 

level to those described for the national HSPB in GP recommendation 1.2.53

GP recommendation 1.4: Training – expanded graduate, in-service, 

and continuous education training opportunities in health statistics

Expanded training opportunities should be developed and offered addressing all elements 

of the health statistics enterprise. The national HSPB, together with the reconstituted 

NCHS and its Board of Scientific Counselors, should assume leadership for conducting 

an enterprise-wide training needs assessment and for developing a training strategic plan.

Guiding Principle 2. Broad collaboration among data users, 

producers, and suppliers at local, state, and national levels to ensure 

the efficiency of the enterprise and the usefulness of the data that it 

produces.

Recommendations GP 1.1–1.3 address this principle.

53Prior recommendations and related models: 

a) NHII recommendation 1 for state and local government. Source: NCVHS, Information for Health: A 

strategy for building the National Health Information Infrastructure, U.S. Dept of Health and Human Services, 

Washington, D.C., November 2001, page 42, Available from: http://ncvhs.hhs.gov/nhiilayo.pdf [accessed 24 

September 2002].

b) Recommendation for Health Assessment Panel. Source: Louisiana Turning Point Partnership, “Public health 

improvement plan: a catalyst for change,” April 2000, pp. 38-40, Available from: 

http://www.lphi.org/turning.html [accessed 6 February 2002].

c) Center for Health and Environmental Statistics, Kansas Department of Health and the Environment, Phillips, 

L., “Health care data governing board,” January 2000 presentation.

d) Kansas Health Care Data Governing Board, “Executive Summary,” Kansas Health Care Data Governing 

Board Annual Report 2001, 2001. Data Governing Board Annual Report, 2001.

NCVHS Recommendations
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Shaping a Health Statistics Vision for the 21st Century

Guiding Principle 3. Rigorous policies and procedures for protecting 

the privacy of individuals and of the confidentiality and security of 

data.

GP recommendation 3.1: Policy – Code of Fair Information Practices

A model code of fair information practices for the health statistics enterprise should be 

debated and developed by the national HSPB, focusing on:

• individual rights of access to data pertaining to themselves;

• procedures for authorizing disclosure of individually identifiable data from data 

subjects and data sources;

• model privacy impact statements for new data collection systems, data linkages, 

and reuse of data collected for purposes other than those specifically mandated in 

statutes;

• policies related to the re-release of identifiable, de-identified, or anonymous data 

for policy, programmatic, or research purposes;

• re-release of identifiable, de-identified, and anonymous data for any purposes 

other than policy, program, and research;

• accountability for inappropriate use of identifiable and de-identified data;

• oversight of privacy, confidentiality, and security procedures and practices within

the health statistics enterprise, including the roles of human rights review

committees and privacy boards such as those approved by the Office of Human 

Research Protections; and

• public responsibility for determining a proper balance between use of identifiable 

and de-identified data, on the one hand, and societal priorities for improving the 

population’s health through improving health statistics, on the other hand.54

GP recommendation 3.2: Policy - HIPAA guidance on privacy

Specific guidance should be developed by the Office for Civil Rights within DHHS 

to make clear how the Standards for Privacy of Individually Identifiable Health 

Information55 adopted under the HIPAA relate to health statistics. This guidance should 

specify responsibilities of public and private producers of health statistics for protecting 

records and should provide clarity to health care providers on the appropriate uses of 

health information for statistical purposes under various elements of the Standards.

54Prior recommendations and related models:

a) Recommendations 1 and 3.1, source: National Research Council, For the Record: Protecting Electronic 

Health Information, National Academy Press, Washington, D.C., 1997, pp. 7-13. 

b) Confidentiality Recommendations, source: National Committee on Vital and Health Statistics, “Health 

Privacy and Confidentiality Recommendations,” 25 June 1997.” 

c) Bruening, P., NCVHS public hearing testimony on: “21st Century Vision for Health Statistics,” 

Washington, D.C., 11 January 2000, Available from: http://www.ncvhs.hhs.gov/010111tr.htm [accessed 1 

September 2002].

55Department of Health and Human Services, "Standards for Privacy of Individually Identifiable Health 

Information; Final Rule," 45 CFR Parts 160 and 164, Federal Register: August 14, 2002, Volume 67, Number 

157, pp. 53181-53273.

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Shaping a Health Statistics Vision for the 21st Century

GP recommendation 3.3: Policy – model privacy, confidentiality, and 

security statutes

Model state and Federal privacy, confidentiality, and security statutes should be 

developed for public sector–sponsored health statistics efforts. The model statutes should 

apply to a wide range of data collection systems and uses of health statistics. The model 

statutes should provide definitions of key terms, establish protection from subpoena of 

data for statutorily mandated data uses and users, specify rules and procedures for rerelease of identifiable data specifically collected for health statistics purposes, and specify 

penalties for misuse of data.56

GP recommendation 3.4: Policy – best practices privacy, 

confidentiality, and security

A toolbox of privacy, confidentiality, and security best practices should be developed for 

use throughout the health statistics enterprise, based upon the code of fair information 

practices, the DHHS guidance on the relationship of the HIPAA privacy standards, and 

the model statutes.57

GP recommendation 3.5: Training – privacy, confidentiality, and 

security

A model training agenda and training materials on privacy, confidentiality, and security 

for use throughout the health statistics enterprise should be developed to accompany the 

code of fair information practices and the tool box of privacy, confidentiality, and security 

best practices.58

GP recommendation 3.6: Research agenda – privacy, confidentiality, 

and security

A research agenda for the study of privacy-, confidentiality-, and security- enhancing 

statistical methods and technologies should be developed and Federally funded, 

addressing such issues as disclosure avoidance and cell size suppression, re-release 

of aggregated data through interactive Web systems, techniques for de-identifying or 

56Prior recommendations and related models: Norwood, J., “an alternative approach if needed: passage of a 

new national statistical law,” Organizing to Count: Change in the Federal Statistical System, Washington, D.C., 

1995, pp. 76-80.

57Prior recommendations and related models: Klein, S., letter to NCVHS, 14 November 2001.

58Prior recommendations and related models:

a) Recommendations 3.4 and 5.2, source: National Research Council, For the Record:

Protecting Electronic Health Information, National Academy Press, Washington, D.C., 1997, pp. 13-14, 

16-17.

b) Kibbe, D., NCVHS public hearing testimony on: “21st Century Vision for Health Statistics,” Research 

Triangle Park, 20 November 2000, Available from: http://www.ncvhs.hhs.gov/001120tr.htm [accessed 1 

September 2002].

NCVHS Recommendations
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Shaping a Health Statistics Vision for the 21st Century

59Prior recommendations and related models:

a) Recommendation 5-6, source: Institute of Medicine, Protecting Data Privacy in Health Services 

Research, National Academy Press, Washington, D.C., 2000, pp. 84-88.

b) Bruening, P., NCVHS public hearing testimony on: “21st Century Vision for Health Statistics,” 

Washington, D.C., 11 January 2000, Available from: http://www.ncvhs.hhs.gov/010111tr.htm [accessed 1 

September 2002].

60Prior recommendations and related models: Fowler, J., letter to NCVHS, 13 November 2001.

making data anonymous, and ways of improving access to data for analytic purposes 

without sharing of identifiable information.59

Guiding Principle 4. Flexibility to identify and address emerging 

health issues and needs.

GP recommendation 4.1: Data set development – early warning 

systems

Early warning systems should be developed that actively monitor the population’s 

health and potential influences on the population’s health in order to identify emerging 

issues requiring data collection and analysis. These warning systems may rely on 

less statistically rigorous data than other data collection systems utilized by the health 

statistics enterprise.

GP recommendation 4.2: Data set development – flexible data 

collection

Organizations responsible for ongoing data collection systems that feed data into the 

health statistics enterprise should develop mechanisms to regularly and rapidly modify 

the specification of target populations, data collection strategies, and data collection 

instruments in response to emerging issues. Revision cycles for these ongoing data 

collection systems should be shortened so that modifications can occur more rapidly and 

more flexibly.

GP recommendation 4.3: Research agenda – emergent health needs

A research agenda should be developed and funded to:

• explore new data collection strategies that can rapidly and flexibly provide data 

on emerging influences on the population’s health.

• assess the validity and reliability of items used in key ongoing data collection 

systems that feed the health statistics enterprise.60

• estimate any loss in accuracy from early publication of provisional, incomplete 

data from ongoing data collection systems.

NCVHS Recommendations
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Shaping a Health Statistics Vision for the 21st Century

Guiding Principle 5. Use of data standards to facilitate sharing and 

comparability of data.

GP recommendation 5.1: Data standards – harmonizing NEDSS and 

the overarching conceptual framework

The public health conceptual data model and the National Electronic Disease 

Surveillance System (NEDSS) logical data model developed by the CDC should be 

harmonized with the overarching conceptual framework for the health statistics enterprise 

in order to facilitate the development of standards.

GP recommendation 5.2: Data standards – population health

Enterprise-wide standards should be developed for classifications of the influences on 

population health, for data elements commonly used in all data collection modes (such 

as demographics and identifiers), for methods of electronically transmitting data, for 

presenting and disseminating data, and for providing electronic access to data. Standards 

should be common across all geographic levels. These standards should reflect where 

possible and be coordinated with those adopted for the NHII, and developed by private 

sector standards development organizations and international organizations.61

GP recommendation 5.3: Data Standards – implementation guidance

Implementation guidance and procedures and provisions for implementation audits 

should accompany all standards developed for use in the health statistics enterprise.

61Prior recommendations and related models:

a) NHII recommendation 4 for Federal government, source: NCVHS, Information for Health: A strategy for

building the National Health Information Infrastructure, U.S. Dept of Health and Human Services, 

Washington, D.C., November 2001, page 41, Available from: http://ncvhs.hhs.gov/nhiilayo.pdf [accessed 

24 September 2002].

b) NHII recommendation 2 for state and local government, ibid, page 42. 

c) Recommendation on integration of health information systems, source: National Institute of Standards

and Technology, Highway to Health: Transforming U.S. Health Care in the Information Age–Executive 

Summary, 1996, pp. 13-14.

d) Recommendation on common data standards, source: Canadian Institute for Health Information, Health 

Information Roadmap: Responding to Needs, Canadian Institute for Health Information, Ottawa, 1999, 

page 9.

e) Rodrian, M., NCVHS public hearing testimony on: “21st Century Vision for Health Statistics,” San

Francisco, 30 October 2000, Available from: http://www.ncvhs.hhs.gov/001030tr.htm [accessed 1 

September 2002].

f) Klein, S. letter to NCVHS, 14 November 2001.

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Shaping a Health Statistics Vision for the 21st Century

GP recommendation 5.4: Data standards – participation in standards 

development

Participants in all components of the health statistics enterprise should actively contribute 

to the national standards setting process, through such mechanisms as the Public Health 

Data Standards Consortium.62,63

Guiding Principle 6. Sufficient detail at different levels of 

aggregation to support local, state, and national policy and 

programmatic decision-making.

GP recommendation 6.1: Research agenda – measures of population 

health

A national research agenda should be developed and funded to determine those measures 

of the population’s health and influences on the population’s health for which state and 

local data are required in order to develop valid and reliable estimates, and to determine 

those measures from which state and local area estimates can be reliably imputed from 

national data or data available from other locales.64 This research agenda should provide 

for the development of such methods that could be implemented by agencies with varying 

levels of health statistics expertise.65

GP recommendation 6.2: Data set development – geocoding

All ongoing health statistics data sets should be geocoded to at least the census block 

group level, in order to facilitate geographic aggregation and disaggregation of data.66

62Centers for Disease Control and Prevention, “Public Health Data Standards Consortium,” National Center for 

Health Statistics, Hyattsville, Maryland, June 2001.

63Prior recommendations and related models:

a) NHII recommendation 4 for Federal government, NCVHS,. Information for Health: A strategy for

building the National Health Information Infrastructure, Ibid. page 41, Available from: 

http://ncvhs.hhs.gov/nhiilayo.pdf [accessed 24 September 2002].

b) NHII recommendation 2 for state and local government, NCVHS, Information for Health: A strategy 

for building the National Health Information Infrastructure, Ibid. page 42, Available from: 

http://ncvhs.hhs.gov/nhiilayo.pdf [accessed 24 September 2002].

64Prior recommendations and related models: “Vision” discussion group, Albuquerque, 1 March 2000, 

Available from: http://www.ncvhs.hhs.gov/hsvision/Albuquerque.pdf [accessed 1 September 2002]. 

65Prior recommendations and related models: Recommendation 2.1.1, source: Australian Institute of Health 

and Welfare and the National Public Health Information Working Group, “improving the use and delivery 

of public health information–analysis and presentation of information,” National Public Health Information 

Development Plan, Australian Institute of Health and Welfare, Canberra, 1999, page v.

66Prior recommendations and related models: 

a) Recommendation on geographic infrastructure, source: Canadian Institute for Health Information, 

Roadmap Initiative . . . Launching the Process, Canadian Institute for Health Information, Ottawa, March 

2000, pp. 16-17.

b) “Vision” discussion group, New Orleans, 22 March 2000, Available from: 

http://www.ncvhs.hhs.gov/hsvision/NewOrleans1.pdf [accessed 1 September 2002].

NCVHS Recommendations
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Shaping a Health Statistics Vision for the 21st Century

GP recommendation 6.3: Data set development – topic-specific 

question modules

Federal agencies should develop and validate topic-specific question modules for 

population-based surveys, drawing upon the collaborative experiences of the Behavioral 

Risk Factor Surveillance System, in order to support state and local agencies’

development of small-area health statistics.

Guiding Principle 7. Integrated, streamlined data collection for 

multiple purposes.

GP recommendation 7.1: Data set development – assessing ongoing 

data sets

Ongoing data collection systems should be regularly assessed to identify overlap and 

duplication in samples, topics, and data sources. For areas of overlap and duplication, 

the most appropriate data source and data collection mode should be identified, and 

redundancy should be eliminated in data collection.67

GP recommendation 7.2: Data set development – integrated state 

collection systems

Building upon mechanisms established under Guiding Principle 1, efforts within 

individual states to develop integrated data collection systems combining presently 

discrete systems should be strongly supported and funded. These integrated systems 

will contain individual-based, longitudinal data from presently discrete reporting, case 

management, administrative, bill payment, and health statistics data collection systems. 

Where possible, common portals, business rules, and coordinated databases should be 

developed across presently discrete data collection systems.68 Coordination of Federal 

resources and programs should occur to support development of integrated state data 

collection systems.

GP recommendation 7.3: Data set development – ongoing multipurpose data collection systems

State and Federal government agencies should strongly support and fund ongoing 

multi-purpose data collection systems (such as the National Health Interview Survey, 

the National Health and Nutrition Examination Survey, the Behavioral Risk Factor 

Surveillance System, the Vital Statistics Cooperative Program, and state surveys) and 

67Prior recommendations and related models:

a) Recommendation on a common Web-based reporting architecture, source: California HealthCare 

Foundation, Web-based Public Health Reporting in California: A Feasibility Study, December 2001.

b) Recommendation on National Health Surveillance Infostructure, source: Health Canada, Building 

partnerships to improve health surveillance tools and connections across Canada, 16 September 1999.

68Prior recommendations and related models: Rodrian, M., NCVHS public hearing testimony on: “21st Century 

Vision for Health Statistics,” San Francisco, 30 October 2000, Available from: 

http://www.ncvhs.hhs.gov/001030tr.htm [accessed 1 September 2002].

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Shaping a Health Statistics Vision for the 21st Century

data integration efforts (such as the CDC Assessment Initiative). These efforts, if 

adequately supported, can meet multiple needs, avoid creation of numerous separate data 

systems for individual data needs, and serve as “magnets” for further integration and 

standardization.

Guiding Principle 8. Timely production of valid and reliable health 

statistics.

GP recommendation 8.1: Data set development – timeliness 

benchmarks

The national HSPB should develop model standards and benchmarks for timeliness, 

and individual data systems should adhere to standards for timeliness of release of data 

and standards for release of regularly scheduled reports. Timeliness standards should 

mandate release of data and reports no later than within one year of the conclusion of the 

data year.69

GP recommendation 8.2: Research agenda – maximizing timeliness 

of data release

A research agenda should be developed and funded to develop data collection, collation, 

analysis, and dissemination methods and technologies that will maximize the timeliness 

of release of regularly scheduled reports from ongoing data collection systems.

Guiding Principle 9. Appropriate access to and ease of use of health 

statistics.

GP recommendation 9.1: Data access – Web-based access to data

The massive capacity of the World Wide Web should be exploited to provide more ready 

access to health statistics through:

• An integrated agenda for the further improvement, expansion, and dissemination 

of Web-based systems that provide access to national, state, and local data on the 

population’s health and influences on the population’s health. These systems

should be designed for users of differing levels of statistical sophistication and

should be built so they can be searched by health topic and not solely by data 

set.70

69Prior recommendations and related models: Office of Management and Budget, “Guidelines for Ensuring 

and Maximizing the Quality, Objectivity, Utility, and Integrity of Information Disseminated by Federal Agencies,” 

Federal Register, 24 September 2001 and 1 October 2001.

70Prior recommendations and related models: 

a) Friedman, D., et al, “Accessing public health information through interactive systems: lessons learned 

and future directions,” Public Health Reports, 2001;116:132-147.

b) Recommendation 2.2.1, improving the use and delivery of public health information–information 

delivery and access, source: Australian Institute of Health and Welfare and the National Public Health 

Information Working Group, National Public Health Information Development Plan, Australian Institute of 

Health and Welfare, Canberra, 1999, page v.

NCVHS Recommendations
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Shaping a Health Statistics Vision for the 21st Century

• A World Wide Web health statistics locater portal for data on the population’s 

health and influences on the population’s health, together with a Web-based metadata directory containing essential information for each set of data, including 

descriptions of samples, data collection modes, statistical methods, periodicity, 

questions or items, and caveats about use.71

GP recommendation 9.2: Research agenda – research data centers

An expanded program of Research Data Centers should be developed to provide Centerapproved population health researchers pursuing approved research projects with 

controlled access to potentially identifiable individual-level data on the population’s 

health and influences on the population’s health at designated sites, building on models 

developed by the Census Bureau and NCHS.

GP recommendation 9.3: Data access – best practices

Mechanisms should be developed to disseminate throughout the health statistics 

enterprise examples of best practices, new methods, and new technologies for 

maximizing appropriate access to and ease of use of health statistics.72

Guiding Principle 10. Continuous evaluation of the scientific 

integrity, accuracy, and timeliness of health statistics and of the 

ability of the health statistics enterprise to fulfill its mission.

Recommendations GP 1.1 through 1.6 also address this principle.

GP recommendation 10.1: Evaluation – examples of health statistics 

uses

The HSPB, and the Planning Boards of each state, should systematically compile 

feedback on the practical applications of health statistics to policy, research, and public 

health practice in order to develop a more complete picture of the usefulness of statistics 

and the ability of the health statistics enterprise to meet needs. This information should 

be published and disseminated to providers of data, policymakers, and the public. The 

information can help encourage participation in health statistics systems, make clear the 

benefits of these systems in debates over resources and privacy, and highlight innovative 

uses of data that might be replicated elsewhere.

71Prior recommendations and related models: Spar, E., letter to NCVHS, 5 October 2001.

72Prior recommendations and related models: Upshaw, V., NCVHS public hearing testimony on: “21st Century 

Vision for Health Statistics,” Research Triangle Park, 20 November 2000, Available from: 

http://www.ncvhs.hhs.gov/001120tr.htm [accessed 1 September 2002].

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Shaping a Health Statistics Vision for the 21st Century

73National Research Council, Martin, M., Straf, M., and Citro, C., ed., Principles and Practices for a Federal 

Statistics Agency, 2nd edition, National Academy Press, Washington, DC, 2001.

74Prior recommendations and related models: 

a) National Committee on Vital and Health Statistics, Classifying and Reporting Functional Status, July 

2001.

b) “Vision” discussion group, Albuquerque, 1 March 2000, Available from: 

http://www.ncvhs.hhs.gov/hsvision/Albuquerque.pdf [accessed 1 September 2002].

c) National Committee on Vital and Health Statistics, Expert Discussion Group, Developing A 21st Century 

Vision for Health Statistics, Washington, D.C., March and May 1999.

GP recommendation 10.2: Evaluation – NCHS adherence to NAS 

guidelines

The NCHS Board of Scientific Counselors (Recommendation GP 1.2) should periodically 

conduct a formal evaluation of the extent to which NCHS adheres to the attributes of 

a Federal statistical agency, as outlined by the Committee on National Statistics of the 

National Academy of Sciences.73

Recommendations for moving toward the adoption of 

the overarching conceptual framework

CF recommendation 1: Data set development – measurement of 

health

The health statistics enterprise, under the leadership of the national HSPB, should 

examine ongoing data collection systems in order to assess the extent to which functional 

status and well-being, including mental health, are being measured. Based upon that 

assessment, measures of functional status and well-being should be incorporated as 

identified to fill gaps. As needed, research should be conducted on what the most 

appropriate measures would be and how to operationalize them.74

CF recommendation 2: Data set development – data sets for 

community analyses

A manual and a “tool kit” of data sets for use in community-level analyses should 

be prepared for use by staff of state and Federal agencies with health statistics 

responsibilities. The tool kit should emphasize data sets that provide information on 

contextual variables and community-level attributes.

CF recommendation 3: Data set development – portraits of 

influences on the population’s health throughout the life cycle

Priority should be placed by state and Federal agencies on the development of portraits 

of the population’s health throughout the life cycle. Data sets to provide such portraits 

should only be constructed after the development of privacy impact statements as called 

for in GP recommendation 3.1. The constructed data sets should be built and operated 

with safeguards such as those recommended in the U.S. General Accounting Office’s 

report on Record Linkage and Privacy: Issues in Creating New Federal Research and 

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Shaping a Health Statistics Vision for the 21st Century

Statistical Information.75 Constructed data sets may link: administrative health data 

sets longitudinally on a person basis; data on births, deaths, marriages, and divorces, 

longitudinally on a person and family basis; multiple surveillance data sets longitudinally 

on a person basis; survey data sets longitudinally on a person, family, and household 

basis; and data collected through multiple modes (such as surveys, administrative health 

data collection systems, surveillance systems, and vital records) combined into single 

data sets longitudinally on a person basis.76

To complement constructed longitudinal data sets, state and Federal agencies 

should place greater priority on developing and implementing person-based, longitudinal 

surveys to better understand the various influences on the population’s health throughout 

the life cycle.77 An example of this type of survey is the congressionally mandated 

National Children’s Study, a multi-agency Federal effort being coordinated by the 

National Institute for Child Health and Human Development of the National Institutes of 

Health. This study will examine the effects of environmental influences on the health and 

development of more than 100,00 children, following them from before birth until age 

21.78

CF recommendation 4: Data access – regularly released health 

statistics reports

Regularly released health statistics reports should be enhanced to reflect an overarching 

conceptual framework of influences on the population’s health:

• Models of community and multilevel analyses including both individual-level 

75United States General Accounting Office, Record Linkage and Privacy: Issues in Creating New Federal 

Research and Statistical Information, Washington, D.C, April 2001, GAO-01-126SP.

76Prior recommendations and related models:

a) Canadian Institute for Health Information, Health Information Roadmap: Responding to Needs, 

Canadian Institute for Health Information, Ottawa, 1999, pp. 8-9.

b) Fielding, J., NCVHS public hearing testimony on: “21st Century Vision for Health Statistics,” San 

Francisco, 30 October 2000, Available from: http://www.ncvhs.hhs.gov/001030tr.htm [accessed 1 

September 2002].

c) “Vision” discussion group, New Orleans, 22 March 2000, Available from: 

http://www.ncvhs.hhs.gov/hsvision/NewOrleans1.pdf [accessed 1 September 2002]

77Prior recommendations and related models: Recommendation for comprehensive national longitudinal 

health study, source: National Research Council, Kalsbeek, W. and Perrin, E., “Some new directions,” Toward 

a Health Statistics System for the 21st Century: Summary of a Workshop, Perrin, E., Kalsbeek, W., and Scanlan, 

T., ed., National Academy Press, Washington, D.C., 2001, pp. 64-66.

78The National Children’s Study, Available from: http://nationalchildrensstudy.gov/ [accessed 1 September 

2002].

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and community-level data should be developed for regularly released health 

statistics reports.79

• Analyses at multiple geopolitical and population levels (e.g., state, county, 

community) should be incorporated into regularly released health statistics 

reports.80

• Relationships between the population’s health and influences on the population’s 

health should be explored in regularly released health statistics reports.81

• Areal linkage of health data to the geographic, demographic, and environmental

data that are publicly available from various state and Federal agencies should be 

included in regularly released health statistics reports; e.g., health data can be 

linked to the data from the Environmental Protection Agency, Census Bureau, 

and U.S. Geological Survey that are included in LandViewV.82

CF recommendation 5: Training – population health

National organizations should provide intensive teaching/learning sessions focusing on 

concepts related to the population’s health and influences on the population’s health at 

professional meetings attended by staff of state and Federal agencies with health statistics 

responsibilities, such as meetings of the National Association for Public Health Statistics 

and Information Systems, the National Association of Health Data Organizations, and the 

Association of Maternal and Child Health Programs.

79Prior recommendations and related models:

a) Diez-Roux, A., “Bringing context back into epidemiology: variables and fallacies in multilevel analysis,” 

Am J of Public Health. 1998;88:216-222.

b) Susser, M., “Does risk factor epidemiology put epidemiology at risk? Peering into the future,” 

J Epidemiology and Community Health. 1998;58:608-611.

c) Susser, M. and Susser, E., “Choosing a future for epidemiology: II. From black box to Chinese boxes 

and eco-epidemiology,” Am J Public Health. 1996;86:674-677.

d) McKinlay, J. and Marceau, L., “To boldly go . . .” Am J Public Health. 2000;25-33.

80Prior recommendations and related models: McMichael, A., “Persons, populations, and planets,” 

Epidemiology, Volume 6, Number, 6, November 1995, pp. 633-635.

81Prior recommendations and related models:

a) National Research Council. New Horizons in Health: An Integrative Approach. Burton H. Singer and 

Carol D. Ryff, Editors. Board on Behavioral, Cognitive, and Sensory Sciences. Washington, D.C.: National 

Academy Press, 2001.

b) Office of Behavioral and Social Sciences Research, National Institute of Health, “Report of a conference 

held on June 27-28 2000,” Toward Higher Levels of Analysis: Progress and Promise in Research on 

Social and Cultural Dimensions of Health, Available from: http://obssr.od.nih.gov/Conf_Wkshp/higherlevel/ 

[accessed 7 January 2002].

c) Canadian Institute for Health Information, Health Information Roadmap: Responding to Needs, 

Canadian Institute for Health Information, Ottawa, 1999, pp. 10-11.

d) Health Canada, The Population Health Template: Key Elements and Actions That Define A Population 

Health Approach, July 2001 draft.

e) Frohlich, K. and Potvin, L., “Collective lifestyles as the target for health promotion,” Can J Public Health.

1999;90:S11-S13.

82LandView is a desktop mapping system that incorporates database extracts from the Environmental 

Protection Agency, the U.S. Census Bureau, and the U.S. Geological Survey. See Landview, Available from: 

http://landview.census.gov [accessed 1 September 2002].

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CF recommendation 6: Research agenda–causal relationships

The Federal government should support research into how health statistics can be used 

more effectively to understand the causal relationships between 1) specific influences on 

health and functionality and well-being in general and 2) specific high priority diseases 

(such as lung cancer, breast cancer, childhood asthma, depression) in particular.

NCVHS Recommendations
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Shaping a Health Statistics Vision for the 21st Century

Summary of recommendations

Recommendations on data access 

• Use the World Wide Web to Improve access to national, state, and local data on 

the population’s health and influences on the population’s health. [GP 9.1]

• Disseminate throughout the health statistics enterprise the best methods for 

maximizing appropriate access to and ease of use of health statistics. [GP 9.3]

• Enhance regularly released health statistics reports to reflect an overarching 

conceptual framework of influences on the population’s health. [CF 4]

Recommendations on data set development

• Develop systems to actively monitor the population’s health and potential 

influences on the population’s health in order to identify emerging problems. [GP 

4.1]

• Develop mechanisms to rapidly modify the samples, data collection strategies, 

and data collection instruments of ongoing data collection systems in response to 

emerging issues. [GP 4.2]

• Geocode all ongoing data sets that feed the health statistics enterprise to the 

census block group level. [GP 6.2]

• Develop and validate topic-specific question modules for population-based

surveys to support state and local agencies’ development of small-area health 

statistics. [GP 6.3]

• Identify duplicative data collection efforts and eliminate redundancy. [GP 7.1]

• Support and fund efforts within individual states to integrate or better coordinate, 

as appropriate, discrete data systems. [GP 7.2]

• Support and fund ongoing multi-purpose data collection systems and data 

integration efforts. [GP 7.3]

• Develop and adopt benchmarks for timeliness of release of data and reports 

derived from those data. [GP 8.1]

• Assure that appropriate measures of functional status and well-being are included 

in ongoing systems that are a part of the health statistics enterprise. [CF 1]

• Prepare and provide to staff of state and Federal agencies with health statistics 

responsibilities a manual and a “tool kit” of data sets for use in community-level 

analyses. [CF 2]

• Develop person-based, longitudinal data sets and surveys in order to develop 

portraits of influences on the population’s health throughout the life cycle. [CF 3]

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Recommendations on data standards 

• Harmonize the CDC public health conceptual data model with the overarching 

conceptual framework for the health statistics enterprise in order to facilitate the 

development of standards. [GP 5.1]

• Adopt or, if necessary, develop standards for data elements commonly used in 

all methods of data collection, for electronically transmitting data, for presenting 

and disseminating data, and for providing electronic access to data. [GP 5.2]

• Provide guidance for implementing and auditing the use of standards by the 

health statistics enterprise. [GP 5.3]

• Contribute to the national standards setting process. [GP 5.4]

Recommendations on enterprise structure 

• Assign overall responsibility for health statistics leadership within DHHS to 

a reconstituted National Center for Health Statistics, supported by a strong Board 

of Scientific Counselors. [GP 1.1]

• Establish a national Health Statistics Planning Board with overall responsibility 

for planning and agenda setting for health statistics in the United States. [GP 1.2]

• Assign overall responsibility for health statistics planning and coordination 

activities within each state’s government to a single state agency. Establish a

Health Statistics Planning Board in each state with overall responsibility for 

planning and agenda setting for health statistics within the state. [GP 1.3]

Recommendations on evaluation 

• Compile feedback on the practical applications of health statistics to policy,

research, and public health practice and disseminate these findings to providers of 

data, policymakers, and the public. [GP 10.1]

• Conduct periodic evaluations of NCHS’ adherence to the National Academy of 

Sciences’ attributes of a Federal statistical agency. [GP 10.2]

Recommendations on privacy policy 

• Develop a code of fair information practices for the health statistics enterprise. 

[GP 3.1]

• Develop guidance on the application of the HIPAA Standards for Privacy of 

Individually Identifiable Health Information to health statistics. [GP 3.2]

• Develop model state and Federal privacy, confidentiality, and security statutes for 

government-sponsored health statistics. [GP 3.3]

• Develop a toolbox of privacy, confidentiality, and security best practices for use 

throughout the health statistics enterprise. [GP 3.4]

NCVHS Recommendations
68

Shaping a Health Statistics Vision for the 21st Century

Recommendations on a research agenda 

• Develop and fund a research agenda for the study of methods and technologies to

enhance the privacy, confidentiality, and security of health statistics. [GP 3.6]

• Develop and fund a research agenda to explore new data collection strategies that 

can rapidly and flexibly provide data on emerging influences on the population’s

health; assess the validity and reliability of items used in key ongoing data 

collection systems; and estimate any loss in accuracy from early publication of 

provisional, incomplete data from ongoing data collection systems. [GP 4.3]

• Develop methods to validly and reliably estimate important indicators of the 

health, and of the influences on the health, of state and local populations. [GP 6.1]

• Develop and implement methods and technologies that will maximize the 

timeliness of release from ongoing data collection systems of regularly scheduled 

reports. [GP 8.2]

• Provide controlled access to potentially identifiable individual-level data on the 

population’s health and influences on the population’s health. Such access would 

be provided, at designated sites, to researchers pursuing approved projects. [GP 

9.2]

• Support research into how health statistics can be used more effectively 

to understand the causal relationships between specific influences on health and 

functionality and well-being in general and specific high priority diseases. [CF 6]

Recommendations on training 

• Expanded graduate, in-service, and continuous training opportunities should be

developed and offered in focusing on all elements of the health statistics 

enterprise. [GP 1.4]

• Develop a model training agenda and training materials for use throughout the

health statistics enterprise focusing on fair information practices, privacy, 

confidentiality, and security. [GP 3.5]

• Provide training about concepts related to the population’s health and influences 

on the population’s health at professional meetings attended by staff of state and 

Federal agencies with health statistics responsibilities. [CF 5]

NCVHS Recommendations
69

Shaping a Health Statistics Vision for the 21st Century

Glossary

Aggregate measures are those community attributes that are derivable from the attributes 

of individual members of the community, such as the infant mortality rate. Aggregate 

measures can represent average behaviors or attributes as well as the distribution of 

behaviors or attributes.

Collective lifestyles are “not just the behaviors that people engage in, but rather the 

relationship between people’s social conditions and their behaviours. . . the idea of 

collective lifestyles proposes that this relationship between social conditions and 

behaviour is a collective experience, and therefore, may have similar influences on those 

who partake in this experience.”83

A community is “a unit, generally geographically defined, which is the locus of basic 

political and social responsibility and in which everyday social interactions involving all 

or most of the spectrum of life activities of the people within it takes place.”84

Cultural context is the interrelated “body of customary beliefs, social forms, and 

material traits constituting a distinct complex of tradition” of a community.

85 The cultural 

context includes, but is not limited to, norms, values, racism, and sexism.

A norm is “an ideal standard binding upon the members of a group and serving to 

guide, control, or regulate proper and acceptable behavior”86

A value is “something (as a principle, quality, or entity) intrinsically valuable of 

desirable.”87

Sexism is “interpersonal and institutional practices whereby members of dominant 

gender groups (typically men) accrue privileges by subordinating other gender groups 

(typically women) and justify these practices via ideologies of innate superiority, 

difference, or deviance.”88

Racism is interpersonal and institutional practices whereby members of one racial 

group accrue privileges by subordinating other racial groups and justify these practices 

via ideologies of innate superiority, difference, or deviance.89

83Frohlich, K. and Potvin L., “Collective lifestyles as the target for health promotion,” Can J Public Health.

1999;90: S13.

84Starfield, B., “Basic concepts in population health and health care,” J Epidemiology and Community Health.

2001;55(7):452.

85Webster’s Third International Dictionary of the English Language, Unabridged, Springfield, Massachusetts: 

Merriam-Webster Inc., Publishers, 1993, “culture,” definition 5b, p. 552.

86Webster’s Third International Dictionary of the English Language, op cit., “norm,” definition 3, p. 1540.

87Webster’s Third International Dictionary of the English Language, op cit., “value,” definition 8, p. 2530.

88Krieger, N., “A glossary for social epidemiology,” J Epidemiology and Community Health, 2001;55(10):694.

89Adapted from Krieger, N., “A glossary for social epidemiology,” J Epidemiology and Community Health. 2001:

55(10):694.

Glossary
70

Shaping a Health Statistics Vision for the 21st Century

Ecological measures are those community attributes that are not derivable from the 

attributes of individual members of the community (e.g., public policies or environmental 

attributes).

Health services can be characterized through structure, process, access, and use.

Structure refers to those “aspects of the design of health services that influence the 

way in which services are delivered. These include the numbers and types of personnel 

and staff; the way in which these personnel are organized to do their work; the nature 

and extent of the facility and equipment; the range of services offered; systems of 

management and amenities; accessibility; mode of financing; the way in which the 

eligible population is determined and enumerated; and the mechanisms of governance and 

administrative decision making.”90

Processes of health services care are “aspects of the behavior or performance of the 

health care system or health facility and the nature of participation on the part of people 

it serves. These consist of two parts: behaviors of the professionals and participation 

of the people who relate to the system or facility. Behaviors of professionals include 

the spectrum of clinical care involving problem (or needs) recognition, the diagnostic 

process, the recommendation of treatment or management, and appropriate follow up. 

Participation of people who relate to the system includes utilization, understanding of 

recommendations, satisfaction with services rendered, and participation in decisions 

concerning strategies for management.”90

Utilization is defined as the “experience of people as to their receipt of health care 

services of different types.”90

Access is defined as “the perceptions and experiences of people as to their ease 

in reaching health services or health facilities in terms of location, time, and ease of 

approach.”90

Accessibility is defined as “aspects of the structure of health services or health 

facilities that enhance the ability of people to reach a health care practitioner, in terms of 

location, time, and ease of approach.”90

Health statistics are numerical data that characterize the health of a population and the 

influences and actions that affect the health of a population.

The health statistics enterprise consists of the infrastructure and the activities or 

processes necessary to produce health statistics. This includes the organizations and 

individuals responsible for collecting data that become health statistics; aggregating and 

compiling those data into health statistics; analyzing and translating health statistics; and 

evaluating the health statistics enterprise in order to improve it.91

90Starfield, B., “Basic concepts in population health and health care,” J Epidemiology and Community Health. 

2001;55(7): 452.

91See also the definition and explanation of the health statistics enterprise on page 5.

Glossary
71

Shaping a Health Statistics Vision for the 21st Century

Political context is determined by public policy, political culture, and political 

enfranchisement and participation.

Public policy is “a guide to action at any level of government to change what would 

otherwise occur, a decision about amounts and allocations of resources: the overall 

amount is a statement of commitment to certain areas of concern; the distribution of 

the amount shows the priorities of decision making. Policy sets priorities and guides 

resource allocation.”92

Political culture is the “integrated pattern of human behavior [relating to politics 

and political participation] that includes thought, speech, action, and artifacts and 

depends upon [hu]man’s capacity for learning and transmitting knowledge to succeeding 

generations”93

Political enfranchisement and participation refers to is the extent to which 

population subgroups are allowed to and do engage in politics.

The population’s health is “not merely the sum of the health of individuals; it 

also entails consideration of the nature of the distribution of health throughout the 

population.”94 Population health has three components: well-being, functional status, and 

disease.

Well-being is “the extent to which an individual or group is able, on the one 

hand, to realize aspirations and satisfy needs and, on the other hand, to cope with the 

interpersonal, social, biological and physical environments.”94

Functional status is the “ability to engage in the activities of daily living and social 

life activities.”94

Disease is medically defined illness, either clinically or subclinically manifested.

92Milio, N., “Glossary: healthy public policy,” J Epidemiology and Community Health. 2001;55(9): 622.

93Webster’s New Collegiate Dictionary, Springfield, Massachusetts: G & C Merriam Company, publisher, 1981, 

“culture,” definition 5a, p. 274

94Starfield, B., “Basic concepts in population health and health care,” J Epidemiology and Community Health. 

2001;55(7): 453.

Glossary
7

2

Shaping a Health Statistics Vision for the 21st Century

Table 1

Table 1. Influences on the health of populations, typical approaches for gathering information on these influences, and systems that gather this information in the United States at the national, state, and local levels95

Influences on health Typical approaches

Examples of systems:

national level

Examples of systems:

state level

Examples of systems:

local level

ContextNatural environmentClimate and weather

(atmosphere)

Weather monitoring stations;satellite data

National Oceanographic and

Atmospheric Administration andNational Weather Service data files;

private companies

National Oceanographic andAtmospheric Administrationand National Weather Service

data files; private companies

National Oceanographic and

Atmospheric Administrationand National Weather Servicedata files; private companies;

local television and radio

stations

Air quality; water quality;

environmental contaminants

Environmental monitoringsystems; sentinel surveys and

special studies of vectors

Environmental Protection Agency:

Aerometric Information Retrieval

System and STORET

State environmentalprotection departments; state

Air Quality Control Boards;state health departments

Local water districts; local

sewer districts; local

sanitation departments; local

air quality monitoring

programs; local health

departments

Geology; topography;vegetative cover; and water

resources

Land surveys; satelliteimages; aerial photographs

U.S. Geological Survey; U.S.

Department of Agriculture; U.S.Environmental Protection Agency

State geology departments;

state agriculture departments;

state environmental protection

departments

Local water districts; local

land use planning programs

Animal vectors (biosphere) Field surveys State health departments;

state agriculture departments

Local health departments;local animal control programs

95Sources:

a) Pearce, N., ‘‘Information resources in the United States,’’ Oxford Textbook of Public Health, Vol. 2, Detels, R., Holland, W., McEwen, J., and Omenn, G., editors, Oxford University Press,

New York, 1997, pp. 435–450;

b) U.S. Department of Health and Human Services. Tracking healthy people 2010, DHHS, Washington, D.C., 2000;

c) Health and Human Services, Part C: Major Data Sources for Healthy People 2010, available from: http://www.health.gov/healthypeople/Document/html/tracking/THP_PartC.htm

[accessed 1 September 2002];

d) Parrish, R., and McDonnell, S., ‘‘Sources of health-related information,’’ Principles and practice of public health surveillance, Teutsch, S., and Churchill, E., ed.,. Oxford University Press,

New York, 2000, pp. 49–54;

e) National Research Council, Institute of Medicine, Integrating Federal statistics on children: report of a workshop. NAS Press, 1995.
73

Shaping a Health Statistics Vision for the 21st Century Table 1. Influences on the health of populations, typical approaches for gathering information on these influences, and systems that gather this information in the United States at the national, state, and local levels95 (continued) Influences on health Typical approaches Examples of systems: national level Examples of systems: state level Examples of systems: local level Cultural context Norms & and values General Social Survey Racism General Social Survey Sexism Competition or cooperation Political context

Public policies & and laws

(social, economic, health,

environment)

Compilations and indexes Thomas—U.S. Congress on the

Internet

National Conference of State

Legislatures

Political culture General Social Survey

Differential politicalenfranchisement orparticipation

Community resourcesBiological characteristicsPopulation (number,geographic distribution)

Census and periodic

population surveys

Decennial census; Current

Population Survey

Decennial census; state vital

statistics system;

Decennial census

Population (age and sex

distribution)

Census and periodic

population surveys

Decennial census; Current

Population Survey

Decennial census; state vital

statistics system;

Decennial census

Biological composition (e.g.,

genetic endowment, immune

status)

Health care records; health

examination surveys (e.g.,

hypertension, immune status);

Human genome project; research

studies; outbreak investigations;

National Health and Nutrition

Examination Survey

Fertility and natality (rate,

geographic and demographicdistribution, and temporal

trends)

Vital registration; health care

records; periodic population

or health care provider

surveys; periodic surveys of

abortion providers

National Vital Statistics System;

CDC Abortion Surveillance System;National Survey of Family Growth;

Alan Guttmacher Institute

State vital statistics system;

National Vital StatisticsSystem; CDC AbortionSurveillance System

State vital statistics systems;

National Vital Statistics

System

Table 1
7

4

Shaping a Health Statistics Vision for the 21st Century

Influences on health Typical approaches

Examples of systems:

national level

Examples of systems:

state level

Examples of systems:

local level

Built environmentLand use (deforestation,

farming)

Land surveys; satelliteimages; aerial photographs;

population surveys

U.S. Department of Agriculture;

Decennial census;

State agriculture departments

Urbanization (type, location,

and extent); and housing

Department of Housing and Urban

Development

Decennial census Local land use planning

programs

Workplaces U.S. population surveys;

business and employer

surveys; workplace regulatory

inspections

Bureau of Labor Statistics;

Occupational Safety and Health

Administration; Mine Safety and

Health Administration; CensusBureau

Current Population Survey;

County Business Patterns;Census of Industrial Sectors;

Census of Agriculture; statelabor departments

SchoolsTransportation infrastructure Land surveys; satellite

images; aerial photographs

U.S. Department of Transportation State transportation

departments

Local road and highway

departments

Communication infrastructure

(access to health information)

Population surveys;government agencies

regulatory activities; and

mandated reporting by private

organizations

Federal CommunicationsCommission; Census Bureau;

private telecommunicationcompanies

Private telecommunicationcompanies

Private telecommunicationcompanies

SocialSocial supportSocial influenceSocial cohesionEducation (literacy)

Table 1. Influences on the health of populations, typical approaches for gathering information on these influences, and systems that gather this information in the United States at the national, state, and local levels95 (continued)

Table 1
75

Shaping a Health Statistics Vision for the 21st Century Influences on health Typical approaches Examples of systems: national level Examples of systems: state level Examples of systems: local level Economic Economic development and equity (e.g., income distribution, employment, access to material resources) Population surveys; national financial records; World Bank; Department of Commerce; Department of Labor, Bureau of Labor Statistics; State economic development departments of economic development Local Chamber of Commerce Work environment Population surveys; business and employer surveys;

workplace regulatoryinspections

Bureau of Labor Statistics;

Occupational Safety and Health

Administration; Mine Safety and

Health Administration; CensusBureau; National Council on

Compensation; National Agricultural

Workers Survey

Current Population Survey;

County Business Patterns;Census of Industrial Sectors;

Census of Agriculture; statelabor departments

Population health programs

Air quality; water supply and

quality; waste disposal

Environmental laws and

regulations; data collection

specific programs during

environmental doing cleanup;

mandated reporting of

locations of major sources of

pollution; research studies of

pollutants and their effects;environmental monitoringsystems; sentinel surveys and

special studies of vectors

Environmental Protection Agency:Aerometric Information RetrievalSystem and STORET

State environmentalprotection departments;state air quality control

boards; state health

departments

Local water district; local

sewer district; local sanitation

department; local air quality

monitoring programs; local

health departments

Table 1. Influences on the health of populations, typical approaches for gathering information on these influences, and systems that gather this information in the United States at the national, state, and local levels95 (continued)

Table 1
7

6

Shaping a Health Statistics Vision for the 21st Century

Influences on health Typical approaches

Examples of systems:

national level

Examples of systems:

state level

Examples of systems:

local level

Personal health practices

Prevalence; geographic and

demographic distribution

Populations surveys (e.g.,

behaviors, activities);observations of behavior;

health examination surveys

(e.g., body fat, nutritional

status); qualitative research;

behavioral risk factor surveys;

exit surveys; focus groups

National Health Interview Survey;

Youth Risk Behavior Survey;

National Household Survey on Drug

Abuse; Monitoring the Future Study;

1999 National Worksite Health

Promotion Survey; Mothers’ Survey,

Abbott Laboratories, Inc., Ross

Products Division

State departments of health;

state departments ofeducation; state Behavioral

Risk Factor Surveys; Youth

Risk Behavior Survey; School

Health Policies and Programs

Study; State TobaccoActivities Tracking andEvaluation System

Youth Risk Behavior Survey

Table 1. Influences on the health of populations, typical approaches for gathering information on these influences, and systems that gather this information in the United States at the national, state, and local levels95 (continued)

Table 1
77

Shaping a Health Statistics Vision for the 21st Century Influences on health Typical approaches Examples of systems: national level Examples of systems: state level Examples of systems: local level Health services Providing effective health care (Number and types of persons individuals and facilities; geographic distribution; type of care given; number of people that can be served; utilization of health care) Government health reports; licensure of health professionals; surveys of health facilities and health care providers; populations surveys; studies of health care quality and access to care; accreditation and

licensing of health care

providers and facilities;

reporting systems from

professional associations;

census of local health

departments; reportingsystems from for physicians

who treat end-stage renal

disease

National Health Care Survey;

American Hospital AssociationAnnual Survey of Hospitals;

American Medical AssociationPhysician Masterfile; Healthcare

Cost and Utilization Project; National

Medical Expenditure Survey; Joint

Commission on the Accreditation of

Health Care Organizations; Clinical

Preventive Services Guidelines;

National Immunization Survey;

National Profile of Local Health

Departments; U.S. Renal Data

System; American Association ofColleges of Osteopathic Medicine

reports on osteopathic medical

education; American Association ofColleges of Pharmacy enrollment

report; American Dental Associationsurveys of dental educational

institutions; Annual Census of

Hospitals; Association of AmericanMedical Colleges reports on

enrollment; Association of Schoolsand Colleges of Optometry data on

enrollment; Association of Schoolsof Public Health data on schools of

public health; National Health

Maintenance Organization Census;National League of Nursing annual

survey of schools of nursing

National ImmunizationSurvey

National Profile of Local

Health Departments;U.S. Renal Data System

Table 1. Influences on the health of populations, typical approaches for gathering information on these influences, and systems that gather this information in the United States at the national, state, and local levels95 (continued)

Table 1
78

Shaping a Health Statistics Vision for the 21st Century

Influences on health Typical approaches

Examples of systems:

national level

Examples of systems:

state level

Examples of systems:

local level

Population healthDiseaseMortality (number, geographic

and demographic distribution,

temporal trends, causes); and

life expectancy

Vital registration; health care

records; periodic population

or health care provider

surveys; ‘‘verbal autopsy’’

National

Vital Statistics System;

Bureau of Labor Statistics; National

Institute of Occupational Safety and

Health

State vital statistics systems;

state medical examiners and

coroners; Census of Fatal

Occupational Injuries

Local (county) medical

examiners and coroners

Morbidity (number, nature

and severity, geographic and

demographic distribution,temporal trends, causes)

General: registers of visits to

health care facilities96;

electronic health carerecords; administrative or

financial data derived from

health care records (e.g.,

insurance claims, data

collected by payers from

health care providers in order

to process payment for

providing health care, and

reports required bygovernment or regulatory

agencies); populationsurveys;Hospitalizations: hospitalrecords; hospital discharge

surveys;

General: databases maintained by

managed care organizations;

MEDSTAT research databases andother commercial health-care data

sets; national Medicaid data files;

Medicare data files

Hospitalizations: National Hospital

Discharge Survey; national Medicaid

data files; Healthcare Cost and

Utilization Project; MedicalExpenditure Panel Survey

Ambulatory: National AmbulatoryMedical Care Survey and National

Hospital Ambulatory Medical CareSurvey (NCHS);HIV/AIDS Surveillance System;

General: databasesmaintained by managed care

organizations; MEDSTATresearch databases and other

commercial health-care data

sets; state Medicaid data

files; Medicare data files

Hospitalizations: statehospital discharge surveys;

state Medicaid data files;

Healthcare Cost andUtilization Project; Medical

Expenditure Panel Survey

General: databases

maintained by Managed Care

Organizations; MEDSTATresearch databases and other

commercial health-care datasets; state Medicaid data

files; Medicare data files

Hospitalizations: statehospital discharge surveys;state Medicaid data files;

Healthcare Cost andUtilization Project; MedicalExpenditure Panel Survey

96Type of health care facility visited is often used as a surrogate for severity.

Table 1. Influences on the health of populations, typical approaches for gathering information on these influences, and systems that gather this information in the United States at the national, state, and local levels95 (continued)

Table 1
79

Shaping a Health Statistics Vision for the 21st Century Table 1. Influences on the health of populations, typical approaches for gathering information on these influences, and systems that gather this information in the United States at the national, state, and local levels95 (continued) Influences on health Typical approaches Examples of systems: national level Examples of systems: state level Examples of systems: local level Morbidity Specific diseases: disease notifications; reporting of sentinel disease by health-care providers; required reporting of epidemic diseases (‘‘disease notifications’’); registries of patients with specific diseases kept by health care providers or facilities, or

health agencies; surveys of

employers (occupationalinjury and illness records;

laboratory reporting

Specific diseases: National

Notifiable Disease SurveillanceSystem; Drug Abuse Warning

Network; National Electronic Injury

Surveillance; Annual Survey of

Occupational Injuries and

Illnesses;National AgriculturalWorkers Survey

Ambulatory:Specific diseases: NationalNotifiable DiseaseSurveillance System; state

notifiable disease programs;state cancer registries; state

birth defects registries; Drug

Abuse Warning Network;National Electronic InjurySurveillance

Ambulatory:Specific diseases: state

notifiable disease programs;state cancer registries; state

birth defects registries; Drug

Abuse Warning Network;National Electronic Injury

Surveillance

Function

Population surveys(self-reported health status)

National Health Interview Survey;

National Health and Nutrition

Examination Survey; National Crime

Victimization Survey

State Behavioral Risk Factor

Surveys; State and Local

Area Integrated TelephoneSurvey

State and Local AreaIntegrated Telephone Survey

Well-bein

(continued)

g

Table 1
8

0

Shaping a Health Statistics Vision for the 21st Century

Step in Cycle

Examples of programs and

activities: national level

Examples of programs and

activities: state level

Examples of programs and

activities: local level

Define data needs Legislation and Congressional support organizations

(e.g., Congressional Research Service, General

Accounting Office, Congressional Budget Office);administration policy priorities; Federal agency policy

and regulatory agendas; Operational and research

needs of program managers of Federal program

operations; advisory bodies (e.g., National Committee on

Vital and Health Statistics); findings of review and study

panels (e.g., National Academy of Sciences and Institute

of Medicine); reports of commissions; scientific literature

State legislatures; executive

agency policies; managers of

state program operations;advisory bodies operational and

research needs of program

managers

County and city councils; local

executive agency policies;managers of local program

operations; Turning Point

grantees

Specify necessary data

attributes

Centers and programs within CDC, including the

National Center for Health Statistics; Agency for

Healthcare Quality and Research; other Federal

statistical agencies; other HHS components

State Centers for Health

Statistics; state epidemiologists;

state chronic disease

epidemiologists; Robert WoodJohnson Foundation-fundedState Health Access Data

Assistance Center; Urban

Institute-Assessing NewFederalism

Identify appropriate data

sources

FedStats, a gateway to statistics from Federal

agencies97

State Centers for Health

Statistics; state epidemiologists;

state chronic disease

epidemiologists

Collect, aggregate, and

compile data

Multiple centers and programs within CDC, including the

National Center for Health Statistics; Agency for

Healthcare Quality and Research; other Federal

statistical agencies; other HHS components; foundationsupported entities organizations such as the Center for

Studying Health Systems Change

State Centers for Health

Statistics; state epidemiologists;

state chronic disease

epidemiologists

97www.fedstats.gov/

Table 2. Programs and activities that contribute to the Health Statistics Cycle in the United States at the national, state, and local levels.

Table 2
81

Shaping a Health Statistics Vision for the 21st Century Table 2. Programs and activities that contribute to the Health Statistics Cycle in the United States at the national, state, and local levels. (continued)

98www.fedstats.gov/

Step in Cycle

Examples of programs and

activities: national level

Examples of programs and

activities: state level

Examples of programs and

activities: local level

Analyze and interpret data Centers and programs within CDC, including the

National Center for Health Statistics; Agency for

Healthcare Quality and Research; other Federal

statistical agencies; other HHS components; foundationsupported organizations such as the Center for Studying

Health Systems Change

State Centers for Health

Statistics; state epidemiologists;

state chronic disease

epidemiologists

Communicate and translatefindings [statistics]

FedStats, a gateway to statistics from Federal

agencies98

State Centers for Health

Statistics; state epidemiologists;

state chronic disease

epidemiologists; state health

department Web sites (e.g.,

Missouri’s MICA, Massachusetts’

MassCHIP)

County and other local health

department Web sites

Evaluate extent to whichneeds are met

DHHS Data Council; Committee on National Statistics,

National Academy of Sciences; NCVHS

Integrating statistics DHHS Data Council; NCVHS; standards development

organizations; CDC’s NEDSS program; Public Health

Standards Data Consortium

Table 2
82

Shaping a Health Statistics Vision for the 21st Century

Appendix 

Appendix: National Committee on Vital 

and Health Statistics, 2002 Membership

(note: Members of the Workgroup on Health Statistics for the 21st Century are noted in 

bold text.

John R. Lumpkin, M.D., M.P.H., Chair

Director

Illinois Dept. of Public Health

Springfield, Illinois 

Brady A. Augustine, M.S.

Corporate Director for Special Projects

Senior Biostatistician and Medical Economist

Gambro Healthcare USA, Inc.

Fort Lauderdale, Florida

Jeffrey S. Blair, M.B.A.

Vice President

Medical Records Institute

Albuquerque, New Mexico

Simon P. Cohn, M.D., M.P.H.

National Director for Health Information Policy

Kaiser Permanente Medical Care Program

Oakland, California 

Kathryn L. Coltin, M.P.H.

Director, External Quality and 

 Data Initiatives

Harvard Pilgrim Health Care

Wellesley, Massachusets

John W. Danaher, M.D.

Litchfield, Connecticut 

Daniel Friedman, Ph.D. (Workgroup Chair)

Assistant Commissioner

Bureau of Health Statistics, 

 Research and Evaluation

Massachusetts Department of Public Health

Boston, Massachusetts 
83

Shaping a Health Statistics Vision for the 21st Century

Richard K. Harding, M.D.

Professor of Clinical Psychiatry 

 and Pediatrics

Vice Chairman, Clinical Services

Neuropsychiatry & Behavioral Science

University of South Carolina

Columbia, South Carolina 

Eugene J. Lengerich, V.M.D.

Penn State University

Hershey, Pennsylvania

Vickie M. Mays, Ph.D., M.P.H.

Department of Psychology

University of California, Los Angeles

Los Angeles, California

Clement Joseph McDonald, M.D.

Distinguished Professor of Medicine

Indiana University School of Medicine

Director

Regenstrief Institute

Indianapolis, Indiana 

Paul Newacheck, Dr. P.H.

Professor of Health Policy and Pediatrics

Institute of Health Policy Studies

School of Medicine

University of California, San Francisco

San Francisco, California 

Mark A. Rothstein, J.D.

Herbert F. Boehl Chair of Law and Medicine

Director, Institute for Bioethics, Health Policy

 and Law

University of Louisville School of Medicine

Louisville, Kentucky 

Edward H. Shortliffe, Ph.D., M.D.

Department of Medical Informatics 

Columbia University

New York, New York 

Appendix 
84

Shaping a Health Statistics Vision for the 21st Century

Barbara Starfield, M.D., M.P.H.

Distinguished University Professor

 and Professor of Health Policy and Pediatrics

School of Hygiene/Public Health

The Johns Hopkins University

Baltimore, Maryland 

Kepa Zubeldia, M.D.

President

Claredi

Kaysville, Utah 

Appendix