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Page 1: AnnuAl RepoRt - Academie catholique de france · Adam Bosworth Keas, Inc. David R. Brennan AstraZeneca PLC Carolyn M. Clancy, M.D. Agency for Healthcare Resrch & Quality Helen Darling

AnnuAl RepoRt

Page 2: AnnuAl RepoRt - Academie catholique de france · Adam Bosworth Keas, Inc. David R. Brennan AstraZeneca PLC Carolyn M. Clancy, M.D. Agency for Healthcare Resrch & Quality Helen Darling

Authored by Institute of Medicine staff, the text summarizes work and discussions over the past two years by the Roundtable on Evidence-Based Medicine. Content is drawn from publications and discussions of the Roundtable’s meetings and workshops.

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The Roundtable on Evidence-Based Medicine

Learning Healthcare System

Concepts v. 2008

AnnuAl RepoRt

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ii Institute of Medicine

Denis A. Cortese, M.D. (Chair) Mayo Clinic

Adam Bosworth Keas, Inc.

David R. Brennan AstraZeneca PLC

Carolyn M. Clancy, M.D. Agency for Healthcare Resrch & Quality

Helen Darling National Business Group on Health

James A. Guest Consumers Union

George C. Halvorson Kaiser Permanente

Carmen Hooker Odom Milbank Memorial Fund

Michael M.E. Johns, M.D. Emory University

Michael J. Kussman, M.D., M.S. Department of Veterans Affairs

Cato T. Laurencin, M.D., Ph.D. University of Virginia

Stephen P. MacMillan Stryker Corporation

Mark B. McClellan, M.D., Ph.D. The Brookings Institution

Elizabeth G. Nabel, M.D. National Heart, Lung & Blood Institute

Mary D. Naylor, Ph.D., R.N.University of Pennsylvania

Peter NeupertMicrosoft Corporation

Nancy H. Nielsen, M.D., Ph.D. American Medical Association

Jonathan B. Perlin, M.D., Ph.D. HCA, Inc.

Richard Platt, M.D., M.S.Harvard Medical School

John Rother, J.D.AARP

Tim Rothwellsanofi-aventis U.S.

John W. Rowe, M.D.Columbia University

Donald M. Steinwachs, Ph.D.Johns Hopkins University

Andrew L. SternSEIU

I. Steven Udvarhelyi, M.D.Independence Blue Cross

Frances M. ViscoNational Breast Cancer Coalition

Kerry N. WeemsCntrs for Medicare & Medicaid Srvcs

William C. WeldonJohnson & Johnson

Janet Woodcock, M.D.Food & Drug Administration

ROUNDTABLE MEMBERS

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Learning Healthcare System Concepts iii

Peter NeupertMicrosoft Corporation

Nancy H. Nielsen, M.D., Ph.D. American Medical Association

Jonathan B. Perlin, M.D., Ph.D. HCA, Inc.

Richard Platt, M.D., M.S.Harvard Medical School

John Rother, J.D.AARP

Tim Rothwellsanofi-aventis U.S.

John W. Rowe, M.D.Columbia University

Donald M. Steinwachs, Ph.D.Johns Hopkins University

Andrew L. SternSEIU

I. Steven Udvarhelyi, M.D.Independence Blue Cross

Frances M. ViscoNational Breast Cancer Coalition

Kerry N. WeemsCntrs for Medicare & Medicaid Srvcs

William C. WeldonJohnson & Johnson

Janet Woodcock, M.D.Food & Drug Administration

ThE IOM ROUNDTABLE ON EvIDENcE-BASED MEDIcINE

The Institute of Medicine’s Roundtable on Evidence-

Based Medicine was established in 2006, in the face of

growing awareness that care that is important is often not

delivered, and care that is delivered is often not important—

with significant health and economic consequences for

Americans. The Roundtable is composed of leadership from

key sectors—patients, health providers, payers, employers,

manufacturers, health information technology, researchers,

and policy makers—united in their commitment to work

together on innovative approaches to transform the way

evidence on clinical effectiveness is developed and used to

improve health and health care in the United States. It aims

to marshal emerging technology and expertise to create

a learning healthcare system in which each patient care

experience naturally reflects the best available evidence,

and, in turn, adds seamlessly to learning what works best in

different circumstances. Activities of the Roundtable include

public meetings and seminars on key topics, as well as

collaborative joint projects for innovation on central issues.

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iv Institute of Medicine

ROUNDTABLE chARTER AND vISION STATEMENT

The Institute of Medicine’s Roundtable on Evidence-Based Medicine has

been convened to help transform the way evidence on clinical effectiveness is

generated and used to improve health and health care. We seek the development

of a learning healthcare system that is designed to generate and apply the best

evidence for the collaborative healthcare choices of each patient and provider;

to drive the process of discovery as a natural outgrowth of patient care; and to

ensure innovation, quality, safety, and value in health care.

Vision: Our vision is for a healthcare system that draws on the best evidence to

provide the care most appropriate to each patient, emphasizes prevention and

health promotion, delivers the most value, adds to learning throughout the

delivery of care, and leads to improvements in the nation’s health.

Goal: By the year 2020, ninety percent of clinical decisions will be supported

by accurate, timely, and up-to-date clinical information, and will reflect the

best available evidence. We feel that this presents a tangible focus for progress

toward our vision, that Americans ought to expect at least this level of

performance, that it should be feasible with existing resources and emerging

tools, and that measures can be developed to track and stimulate progress.

Context: As unprecedented developments in the diagnosis, treatment, and

long-term management of disease bring Americans closer than ever to the

promise of personalized health care, we are faced with similarly unprecedented

challenges to identify and deliver the care most appropriate for individual

needs and conditions. Care that is important is often not delivered. Care that

is delivered is often not important. In part, this is due to our failure to apply

the evidence we have about the medical care that is most effective—a failure

related to shortfalls in provider knowledge and accountability, inadequate

care coordination and support, lack of insurance, poorly aligned payment

incentives, and misplaced patient expectations. Increasingly, it is also a result

of our limited capacity for timely generation of evidence on the relative

effectiveness, efficiency, and safety of available and emerging interventions.

Improving the value of the return on our healthcare investment is a vital

imperative that will require much greater capacity to evaluate high priority

clinical interventions, stronger links between clinical research and practice,

and reorientation of the incentives to apply new insights. We must quicken

our efforts to position evidence development and application as natural

outgrowths of clinical care—to foster health care that learns.

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Learning Healthcare System Concepts v

Approach: The IOM Roundtable on Evidence-Based Medicine serves as

a forum to facilitate the collaborative assessment and action around issues

central to achieving the vision and goal stated. The challenges are myriad

and include issues that must be addressed to improve evidence development,

evidence application, and the capacity to advance progress on both dimensions.

To address these challenges, as leaders in their fields, Roundtable members

will work with their colleagues to identify the issues not being adequately

addressed, the nature of the barriers and possible solutions, and the priorities

for action, and will marshal the resources of the sectors represented on the

Roundtable to work for sustained public-private cooperation for change.

Activities include collaborative exploration of new and expedited approaches

to assessing the effectiveness of diagnostic and treatment interventions, better

use of the patient care experience to generate evidence on effectiveness,

identification of assessment priorities, and communication strategies to

enhance provider and patient understanding and support for interventions

proven to work best and deliver value in health care.

Core concepts and principles: For the purpose of the Roundtable activities,

we define evidence-based medicine broadly to mean that, to the greatest extent

possible, the decisions that shape the health and health care of Americans—by

patients, providers, payers, and policy makers alike—will be grounded on

a reliable evidence base, will account appropriately for individual variation

in patient needs, and will support the generation of new insights on clinical

effectiveness. Evidence is generally considered to be information from clinical

experience that has met some established test of validity, and the appropriate

standard is determined according to the requirements of the intervention

and clinical circumstance. Processes that involve the development and use of

evidence should be accessible and transparent to all stakeholders.

A common commitment to certain principles and priorities guides the

activities of the Roundtable and its members, including the commitment

to: the right health care for each person; putting the best evidence into

practice; establishing the effectiveness, efficiency, and safety of medical care

delivered; building constant measurement into our healthcare investments;

the establishment of healthcare data as a public good; shared responsibility

distributed equitably across stakeholders, both public and private; collaborative

stakeholder involvement in priority setting; transparency in the execution of

activities and reporting of results; and subjugation of individual, political, or

stakeholder perspectives in favor of the common good.

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vi Institute of Medicine

ThIS SUMMARy

Learning Healthcare System Concepts v. 2008 presents a summary of important touchstones identified during the first two years of the work of the IOM Roundtable on Evidence-Based Medicine. It contains no consensus recommendations, and has been assembled by Roundtable staff from the common themes and discussion summaries of the various meetings, as noted below.

Section 1: background material prepared for the Roundtable website (www.iom.edu/ebm-effectiveness) and from the staff issue overview, Learning What Works Best: The Nation’s Need for Evidence on Comparative Effectiveness in Health Care (2007).

Section 2: figures from the Roundtable workshop, The Learning Healthcare System, July 20-21, 2006; the IOM Annual Meeting, Evidence-Based Medicine and the Changing Nature of Health Care, October 8, 2007; and the Roundtable workshop, Redesigning the Clinical Effectiveness Research Paradigm, December 12-13, 2007.

Section 3: from the Roundtable workshop, The Learning Healthcare System, July 20-21, 2006.

Section 4: from the Roundtable workshop, Leadership Commitments to Improve Value in Health Care, July 23-24, 2007, and the follow-up Roundtable sectoral coordinators meeting, December 3, 2007.

Section 5: from the Roundtable workshop, Judging the Evidence, February 5, 2007.

Section 6: from the Roundtable staff issue overview, Learning What Works Best: The Nation’s Need for Evidence on Comparative Effectiveness in Health Care (2007).

Section 7: from the Roundtable workshop, Redesigning the Clinical Effectiveness Research Paradigm, December 12-13, 2007.

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Learning Healthcare System Concepts vii

Section 8: from the Roundtable workshop, Clinical Data as the Basic Staple of Health Learning, February 28-29, 2008.

Section 9: from the Roundtable workshop, Leadership Commitments to Improve Value in Healthcare, July 23-24, 2007, follow-up Sectoral Coordinators meeting, and the Roundtable Members meeting, September 24, 2007.

Section 10: from the Roundtable workshop, Leadership Commitments to Improve Value in Healthcare, July 23-24, 2007.

Like the dynamic nature of evidence itself, the issues, concepts, and priorities noted in Roundtable activities will continue to evolve, improve, and be revised as indicated—hence the v. 2008 modifier. Source material and related background material may be accessed at the Roundtable’s website: http://www.iom.edu/ebm. These include the following publications, available through the National Academies Press:

• The Learning Healthcare System (2007)• Leadership Commitments to Improve Value in Health

Care: Finding Common Ground (2008—in press)• Redesigning the Clinical Effectiveness Research

Paradigm: Innovation and Practice-Based Approaches (2008—in press)

• Clinical Data as a Basic Staple of Health Learning: Creating and Protecting a Public Good (2008—in press)

Publications planned for 2009 include:

• Engineering a Learning Healthcare System: A Look at the Future (2009—in preparation)

• Learning What Works: Infrastructure and Clinical Priorities for Learning Which Care Is Best (2009—in planning)

• Making Better Choices: Getting the Value We Deserve from Health Care (2009—in planning)

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“We seek the development of a learning healthcare system

that is designed to generate and apply the best evidence

for the collaborative health care choices of each patient

and provider; to drive the process of discovery as a natural

outgrowth of patient care; and to ensure innovation,

quality, safety, and value in health care.”

—Charter, IOM Roundtable on

Evidence-Based Medicine

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LEARNINg hEALThcARE SySTEM cONcEpTS v. 2008

1. Imperative: Patient centered, better results,

better value, and the changing scene

2. context: Some illustrative context

3. Learning: The learning healthcare system

4. value: Advancing the value proposition

5. Evidence: Evidence stewardship in a

learning healthcare system

6. capacity: Expanding the effort to learn

what works

7. Research: Redesigning the clinical effectiveness

research paradigm

8. Data: Creating a clinical data utility for

continuous improvement

10. commitments: Leadership commitments

to better value in health care

9. Expectations: Responsibilities and

expectations for participants

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Learning Healthcare System Concepts �

1 IMpERATIvEPatientcentered,betterresults,bettervalue,andthechangingscene

The United States faces two fundamental healthcare

challenges: (a) meeting the moral obligation to

ensure that everyone is secure in his or her ability to

receive the basic prevention and treatment services needed;

and (b) ensuring that the nation—and each of us—receives

the value we deserve from the healthcare investments we

make. As a nation, we fall shortest on the value proposition.

The immediate and dominant issue of greatest threat to the

health and economic security of Americans is the failure

of our healthcare system to deliver the value that should

be expected from the health care we receive. The IOM

Roundtable on Evidence-Based Medicine is devoted to

accelerating the development of a healthcare system with

an inherent capacity for continuous improvement in the

effectiveness and efficiency of care delivered.

Health care in the United States currently underperforms

on many dimensions. From the global perspective, with per

capita expenditures more than 20 percent higher than any

other country in the world and more than twice the average

expenditure for European countries, the nation ranks well

below at least two dozen others on key health indices such

as infant survival and life expectancy. In part, this is because

people too often do not receive the care they need. One study

found that, where evidence exists, only a little more than half

of recommended services were actually delivered. In part, it

is also because the services people receive are too often not

always the ones necessary or right for them. The intensity of

services for similar conditions—as with procedures for which

discretion is at play, for example, back surgery, hysterectomy,

and bypass surgery—can be many times higher in one place

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� Institute of Medicine

than another, without any difference in outcome or results.

For example, 4.6 lumbar fusions were reported per 1,000

Medicare enrollees annually in Idaho Falls, Idaho, compared

with 0.2 in Bangor, Maine, with no difference in results.

Clearly, more does not by itself equate to better—and the

variation is greater for conditions in which the evidence is

more limited.

One estimate suggested that only about a quarter of the

discrepancy in Medicare spending across regions could be

explained by population illness levels, and if all regional

spending levels matched those of the lowest, Medicare

could see savings of up to $40 billion (1996 dollars) without

compromising health status. This is not just an issue of

waste, but also of potential harm. In To Err is Human, the

IOM Committee on the Quality of Health Care in America

found that each year between 44,000 and 98,000 Americans

die due to medical errors.

It is clear that medical care decision making is already

strained, at both the level of the individual patient and the

level of the population as a whole, by the growing number

of diagnostic and therapeutic options for which evidence is

insufficient to make a clear choice. The strain will worsen

as choices grow, with new pharmaceuticals, medical devices,

diagnostics, biologics, and procedures. A recent review

suggests that half or more of the growth in medical spending

in recent years is attributable to change in technology.

Compounding the complexity is the fact that the world of

health care is about to experience dramatic new insights

on the genetic variation in individual response to different

diagnostic and treatment interventions. The age of

personalized medicine will soon be a reality, if the capacity

can be developed to contend with its insights. Today, the

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Learning Healthcare System Concepts �

IMpER

ATIv

E

average clinical encounter already requires a health provider

to manage more variables than would be considered

reasonable given what is known about the capabilities of the

human mind. With changes in knowledge and options, over

the next decade, that same encounter will require managing

variables perhaps an order of magnitude greater in number.

Engaging ways to address these issues and their implications

has been the focus of the activities of the IOM Roundtable

on Evidence-Based Medicine over the past two years.

Because of the centrality of cross-sector dialog to effective

action on many of these issues, especially important to the

collaborative spirit has been the input of the sector working

groups, which include Roundtable members and beyond.

Summarized here are the products of Roundtable meetings

and sectoral discussions, workshops, commissioned pieces,

and staff issue papers.

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Learning Healthcare System Concepts �

2 cONTEXTSomeillustrativecontext

In the past two years, the IOM Roundtable on Evidence-

Based Medicine has met five times and has sponsored

six large public workshops and meetings and several

smaller meetings on issues central to evidence-driven health

care. Participants in these activities are listed at the back of

this booklet. In the course of the various meetings, many

important points have been made in poignant graphic

format. Presented below are ten representative examples

that illustrate the compelling context of our activities. None

of these tells the whole story; each gives a sense of both

opportunity and challenge.

cONSTANTLy chANgINg MEDIcAL INTERvENTIONS

Molly Coye, IOM Meeting, 8 October 2007. Challenges of increasing diversity, complexity, and cost of interventions.

S-1 new.eps

Challenge = current evidence paradigms

Rapid evolution of technologies

Need for guidance documents for evidence development

Diversity, complexity and cost rather than quantity� Pharmaceuticals biotech drugs � Diagnostics pharmacogenomics and biomarkers� Information technology� Hybrid technologies: devices + pharmaceuticals + information technology � “Follow-on biologics” and biologic equivalency

Ongoing, rapid-cycle innovation

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� Institute of Medicine

InsIghts Into IndIvIdual varIatIon

David Altshuler, IOM Meeting, 8 October 2007. Rapid increases in identification of gene variants for common diseases.

PaucIty of evIdence

Robert Califf, IOM Meeting, 12 December 2007. Less than 20% of AHA/ACC heart disease management recommendations are based on a high level of evidence and over 40% are based on the lowest level of evidence: Level A evidence (multiple populations and risk strata) to Level C (very limited population risk strata). The proportion of recommendations with high evidence levels has not increased over time.

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new S-3.eps

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2000 20101990 2020

Structural Genetics: e.g. SNPs, haplotypes

Functional Genetics: Gene expression

profiles

Proteomics and othereffector molecules

Decisions by Clinical Phenotype

new 2-7.eps

$7,200 to 11,600 (74)6,800 to < 7,200 (45)

6,300 to < 6,800 (55)5,800 to < 6,300 (60)

4,500 to < 5,800 (72)Not Populated

Learning Healthcare System Concepts �

William Stead, IOM Meeting, 8 October 2007. Growth in facts affecting provider decisions versus human cognitive capacity.

consequences for PractIce

Elliot Fisher, IOM Meeting, 8 October 2007. Wide geographic variation in per capita Medicare spending, 2003. [The numbers in parentheses indicate the number of regions in each group.]

con

text

challenges to ProvIders

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new 2-6.eps

1966 1972 1978 1984 1990 1996 2002 2008 2014 2020 2026 2032 2038 2044 2050

Per

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ross

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0

5

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2.5 Percentage Points

Differential of:

1 Percentage PointBeginning in 2025

1 Percentage PointBeginning in 2015

10 Institute of Medicine

consequences for value

Peter Orszag (citing Dartmouth), IOM Meeting, 8 October 2007. Inverse relationship between per capita Medicare spending and hospital quality ranking, 2000-2001.

Peter Orszag, IOM Meeting, 8 October 2007. Scenarios for growth in share of GDP for Medicare and Medicaid spending.

ImPlIcatIons for the economy

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new S-4.eps

THEN• Monitoring• MD exam

• Nurse observations

THEN NOW TOMORROW

NOW• Radiology• EKG

• Labs• Meds• Monitoring

• MD exam• Nurse observations

TOMORROW• Continuous location tracking

• Constant vital signs monitoring• Transcutaneous monitoring of

glucose, ETOH, etc.• Noninvasive testing• Exhaled breath analysis

• Testing to maintain wellness• Increased image utilization• Genomic data

• Proteomics• Personalized pharmacy• Radiology• EKG• Labs

• Meds• Monitoring• MD exam

• Nurse observations

Learning Healthcare System Concepts 11

BRINgINg LEARNINg TO pRAcTIcE

Brent James, IOM Meeting, 20 July 2006. Improvements in diabetes control with systematic clinical program management.

Peter Neupert, IOM Meeting, 8 October 2007. Growth in clinical information and the role for IT in its management.

cON

TEXT

cLINIcAL INfORMATION gROwTh

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12 Institute of Medicine

fORcES IN EvIDENcE-DRIvEN hEALTh cARE

Robert Hayward, IOM Meeting, 8 October 2007. Social and technical elements to address in evidence-driven care.

Integration

Social

Technical

CultureNetworks

Context

EvidenceSynthesis

DisseminationTechnology

SkillsandKnowledge

Collaboration

}{

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Learning Healthcare System Concepts 1�

3 LEARNINgThelearninghealthcaresystem

Contending with the changes in health care clearly

requires doing things differently, as discussed at the

Roundtable’s workshop, The Learning Healthcare

System. The notion of dependence on expensive, time-

consuming, and relatively narrow clinical experiments

as a static and sole source of evidence on the constantly

accelerating flow of diagnostic and treatment challenges,

is unfeasible. Similarly impractical is the prospect of

individual caregivers trying to keep up on their own with

rapidly changing knowledge needs. A learning healthcare

system is needed, in which new insights and evidence are

constantly produced, and value is constantly enhanced, by

real-time learning from the clinical experience and seamless

application of the lessons in the care process.

The IOM report Crossing the Quality Chasm found that if

health care is to meet its central aims to be safe, effective,

patient-centered, timely, efficient, and equitable, several

elements must be central features of the care process:

(1) care based on continuous healing relationships; (2)

customization based on patient needs and values; (3) the

patient as the source of control; (4) shared knowledge and

the free flow of information; (5) evidence-based decision

making; (6) safety as a system property; (7) transparency;

(8) anticipation of needs, (9) continuous decrease in waste,

and (10) cooperation among clinicians.

Achieving health care centered on these principles requires

a transformative learning and change process—one that

takes full advantage of the tools presented with emerging

information technology and builds the continuous

improvement necessary for the effectiveness, efficiency,

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1� Institute of Medicine

and sensitivity inherent in bringing the right care to the

right patient at the right time. Fostering progress toward

this vision, beginning with the basic challenge of knowing

what the right care is for each person, is the aim of the IOM

Roundtable on Evidence-Based Medicine. And, to identify

and explore the necessary foundation stones on which to

build, the Roundtable’s first public meeting focused on the

elements of what it has termed the learning healthcare system.

Noted below are several key features of such a system.

• Continuous improvement in the value delivered.

A learning healthcare system is one that maintains

a constant focus on the health and economic value

returned by care delivered, and continuously improves

in its performance.

• Learning in health care as a partnership enterprise.

Broad culture change is needed to enable the evolution

of the learning environment as a common, partnership

cause of patients, providers, and researchers alike.

The Learning healthcare System• Continuous improvement in the value delivered• Learning in health care as a partnership enterprise• Developing the point of care as the knowledge engine• Full application of information technology• Database linkage and use• Advancing clinical data as a public utility• Building innovative clinical effectiveness research into practice • Patient engagement in the evidence process• Development of a trusted scientific intermediary • Leadership that stems from every quarter

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Learning Healthcare System Concepts 1�

• Developing the point of care as the knowledge engine.

Given the rate at which new interventions are developed,

along with new insights about individual variation in

response to interventions, the point of care must be the

central focus for the continuous learning process.

• Full application of information technology. The rate of

learning—both the application and development of

evidence—will depend on the full and strategic

application of information technology, including

electronic health records central to long-term change.

• Database linkage and use. The emergence of large,

electronically based datasets offer important new

sources for quality improvement and evidence

development. Progress requires fostering interoperable

platforms, linking analyses, establishing networks, and

developing new approaches for ongoing searching of

those databases for patterns and clinical insights.

• Advancing clinical data as a public utility. Meeting the

potential for using new datasets as central sources of

evidence on the effectiveness and efficiency of medical

care, will require recognition of their qualities as a public

good, including assessing issues related to ownership,

availability, and use for real-time clinical insights.

• Building innovative clinical effectiveness research

into practice. Improving the speed and reliability of

evidence development requires fostering development

of a new clinical research paradigm—one that deploys

careful criteria for trial conduct, draws clinical research

more closely to the experience of clinical practice,

advances new study methodologies adapted to the

practice environment, and engages cultural incentives

to foster more rapid learning.

• Patient engagement in the evidence process. Accelera-

ting the potential for better development and application

LEARN

INg

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16 Institute of Medicine

of evidence requires improved communication between

patients and healthcare professionals about the nature

of the evidence base, and the need for partnership in its

development and use.

• Development of a trusted scientific intermediary.

Greater synchrony, consistency, and coordination

in the priority setting, development, interpretation,

and application of clinical evidence requires a trusted

scientific intermediary to broker the perspectives of

different parties.

• Leadership that stems from every quarter. Strong,

visible, and multifaceted leadership from all involved

sectors is necessary to marshal the vision, nurture the

strategy, and motivate the actions necessary to create

the learning healthcare system we need.

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Learning Healthcare System Concepts 1�

4 vALUEAdvancingthevalueproposition

Also established as an early Roundtable priority was

development of a stronger focus on the value we

get from the health care delivered. In fall 2007, the

Roundtable’s Sectoral Strategies working group developed

an initial summary of elements of the value proposition,

described below as touchstones for further exploration and

characterization of the elements of value.

• Value is expressed as what we gain relative to what we

give up—the benefit relative to the cost.

• Value in health care is expressed as the physical health

and sense of well-being achieved relative to the cost.

• High value in health care means getting the right care to

the right patient at the right time for the right price.

• Value from pooled arrangements is expressed as the

aggregate gains relative to the aggregate costs.

• Determining the value proposition for a particular

intervention therefore begins with understanding its

safety, effectiveness, and cost in different populations

and circumstances, relative to alternatives, and its

potential as a source of high-value innovation.

• In assessing value, benefits and costs—often multifaceted

—are objectively characterized and measured.

value in health care value in health care

• The right care• To the right patient• At the right time• For the right price

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1� Institute of Medicine

Each of us seeks value in what we do. At the most basic level,

this means adding to our lives in ways that are meaningful to

us. For any given person, the nature and magnitude of value

gained is personal, and varies by circumstance and what

we must give up for the gain. Meaning may be found in our

abilities, our choices, our relationships, our security, our sense

of well-being, our possessions, our environments, and so on.

Enhancing our status on any relevant dimension may require a

measure of diminished status on another—for example, time,

energy, money. Value is expressed as what we gain relative to

what we give up—the benefit relative to the cost.

The purpose of health care is to enhance physical and mental

health status. Value in health care is expressed as the physical

health and sense of well-being achieved relative to the cost. High

value in health care therefore means getting the right care at the

right time to the right patient for the right price. As with other

issues, value in health care—what is “right” about care, time,

and price—depends on vantage point and circumstance.

Perceived value will vary according to one’s view as a patient,

caregiver, family member, neighbor, community leader,

employer, healthcare manager, innovator, or policy official.

Sometimes the determination of value is complicated by the

fact that a benefit received is the result of a cost shared or

borne elsewhere. This is typical of activities in which there is

advantage or necessity to arrange for pooling of resources to

provide the benefit. Education, police, highways, parks, even

manufacturing and information services, are all examples

of circumstances in which benefits—such as services or

goods—are designed through common processes to make

it possible for groups of people to benefit. In these cases,

the gain is considered from two perspectives: the individual

gain for one person’s investment and the social gain from

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Learning Healthcare System Concepts 1�

the collective investment. Value from pooled arrangements is

expressed as the aggregate gains relative to the aggregate costs.

The challenge of measuring value in any arena lies in

identifying, characterizing, and assessing the nature of the

gains and costs. This is especially complicated in health

care, given the difficulty of measuring inputs and outcomes,

and because payment for health care is primarily organized

through risk-spreading insurance mechanisms. Value must be

understood from both individual and societal or population

perspectives—which may be at substantial variance.

Determining the value proposition for a particular intervention

therefore begins with understanding its safety, effectiveness,

and cost in different populations and circumstances, relative

to alternatives, and its potential as a source of high-value

innovation. From this point, certain interventions can clearly

be assumed to improve the overall value from health care if

properly applied—for example, those that offer substantially

better safety, outcomes, or patient satisfaction with marginal

changes in (economic and other) costs; those that can

offer improvements for conditions that previously had no

alternatives, at costs comparable to the management of other

conditions; those that are cost reducing or otherwise improve

the overall efficiency of health care. Other interventions may

require more detailed analyses, including using metrics

that facilitate comparisons on effectiveness, factoring

patient preferences and innovation potential into the value

calculation, and developing decision rules on balancing value

to individuals with aggregate value to society. Whatever rules

and determinations are made will require constant updating

and refining as new information becomes available on the

targeting, impact, potential, and costs of interventions.

vA

LUE

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20 Institute of Medicine

Rewarding caregivers who deliver high-value care should

be a central goal of incentives embedded in healthcare

financing. Accomplishing this aim will require analytic

tools and capacity beyond what are currently available,

including development of the capacity to study relative

safety and effectiveness; to inform, assess, and integrate

patient preferences; to better characterize and target groups

at particular risk; to understand and balance the various

elements of cost; to fashion the principles needed to ensure

an appropriate balance between an individual’s value

proposition and that of the aggregate for a population; to

systematically track the results of healthcare interventions;

and to identify the system elements most conducive to high-

value health care.

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Learning Healthcare System Concepts 21

5 EvIDENcEEvidencestewardshipinalearninghealthcaresystem

The effectiveness and efficiency of health care begins

with the evidence, the focus of the second Roundtable

workshop, Judging the Evidence. Innovation is the

engine of progress, and evidence is its linchpin. Participants

noted that because the care, integrity, and timeliness with

which medical evidence is produced, interpreted, and applied

is so fundamental to identifying, confirming, and improving

on best practices for different circumstances, it is the shared

responsibility of all stakeholders.

Without—a mutual understanding among all parties

involved—intervention developers, regulators, payers,

healthcare organizations, providers, patients—of the basis

on which evidence will be interpreted and applied, the

generation of new evidence may result in little or no benefit

to patient care. Examples of the issues mentioned included

the notions that payers may lack consistency in their coverage

decisions, regulators may seem arbitrary in their requests,

health product companies may feel that ambiguous

requirements and decision criteria constrain innovation,

caregivers may be uncertain about the appropriate

intervention, and patients may feel confused about what’s

best for them. All of these dynamics impede progress,

efficiency, and the results that should be expected from our

healthcare delivery system.

Achieving a learning healthcare system requires robust

capacity to generate and apply new insights based upon

clarity and confidence in the principles that serve as a

foundation and guide to the generation and use of the

evidence. Participants in the Roundtable’s sectoral strategies

collaboration offer the following set of core principles to

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22 Institute of Medicine

guide stewardship of evidence in a learning healthcare

system. Individuals and institutions involved in developing

or applying evidence on the effectiveness of a healthcare

diagnostic or treatment product, procedure, or service are

expected to follow these principles in their work.

• Independent and trusted source. Conclusions and

recommendations based on the evidence must derive

from a trusted organization of proven independence in

the conduct of evidence assessment and validation.

• Evaluated by established standards. Each diagnostic

or treatment product, procedure, or service used in

health care must be supported by evidence of safety

and effectiveness produced through established and

validated standards and processes. If circumstances

preclude customary assessment, the intervention must

be supported by ample documentation of biologic and

clinical plausibility.

• Collaborative and consultative review. Strategies

and activities to assess the evidence for a particular

intervention, and apply the results in advancing the

principles for Interpretation and Use of clinical Evidence

principles for Interpretation and Use of clinical Evidence

• Independent and trusted source • Evaluated by established standards • Collaborative and consultative review • Transparent decision processes • Appropriately applied • Patient-focused choices• Effective communication and comprehension• Value driven • Accountability and assessment• Continuous learning

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Learning Healthcare System Concepts 2�

most effective health care, should be collaborative,

consultative, and supportive of the most efficient use of

limited resources.

• Transparent decision processes. Each decision to

propose, introduce, use, and pay for a diagnostic or

treatment product, procedure, or service, must be open,

documented, and transparent as to the data on which

the decision is based and the criteria applied in judging

the evidence.

• Appropriately applied. Each report, conclusion,

recommendation, and implementation plan must

stipulate accurately and effectively the population to

which the evidence applies, and those using the evidence

must account for the stipulations.

• Patient-focused choices. Decisions on diagnostic or

treatment approaches must take into consideration

not only the appropriateness of the evidence to the

patient, but also patient preferences reasonable to the

circumstances.

• Effective communication and comprehension. Every

application of a diagnostic or treatment product,

procedure, or service must include the most effective

communication possible between patient and caregiver

on the issue, options, choices, and evidence.

• Value driven. Because high-value care means using

the evidence to get the right care at the right time to

the right patient for the right price, each care decision

should be undertaken with transparency as to value,

including price and evidence of effectiveness.

• Accountability and assessment. Accountabilty,

performance assessment, and reporting should be a

core feature in the design strategy for every point of

service in a healthcare system.

EvID

ENcE

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2� Institute of Medicine

• Continuous learning. Learning is a continuous and

natural feature of each patient and caregiver healthcare

experience, and evidence development should be an

integral aspect of the delivery of care, not just an activity

performed elsewhere by others.

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Learning Healthcare System Concepts 2�

6 cApAcITyExpandingtheefforttolearnwhatworks

Achieving the value we should expect from the health

care we receive depends on how much we know about

the relative effectiveness of various interventions. In

2007, Learning What Works Best was developed for the IOM

Roundtable Working Group on Sustainable Capacity as an

overview of some of the primary issues and strategies for

stronger evidence development. A critical hallmark of the past

half century of progress in medicine has been the development

of many alternatives for diagnosing and treating many of the

illnesses and injuries that occur among Americans. Yet, of

the nation’s more than $2 trillion annual health expenditure,

less than 0.1 percent is invested in assessing the comparative

effectiveness of available interventions, and, of this, the

funds specifically appropriated by Congress for comparative

effectiveness research are just a small fraction. The result is

that far too little is known about the relative advantages and

disadvantages of different diagnostic and treatment options.

A 1994 Congressional Office of Technology Assessment

report noted that longstanding estimates suggest only about

10-20 percent of medical procedures have been formally

evaluated for safety and efficacy. Today, with expanded

medical options and low capacity for assessment, the gap is

likely larger.

Concern about the limited evidence on which to base

reasonable decisions in health care has prompted a number

of proposals on ways to improve the process. Elements of the

concern focus both on the need for substantially expanded

capacity to conduct the necessary research, and on the need

for better and more consistent priority setting, standards,

methods, and coordination of the work that is done. Several

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26 Institute of Medicine

COMPARAtIvE EFFECtIvENESS RESEARCH ENtERPRISE MODElS

ACtIvIty FEDERAl INDEPENDENt BOARD HyBRID

Reference model NIH or AHRQ Federal Reserve Board NAS (IOM/TRB)

Priority setting Agency*/HHS Board Governing Board/Staff Governing Board/

ISO**

Budget allocation

Agency/HHS Board Governing Board/Staff Governing

Board/ISO

Study selection Agency Governing Board/Staff ISO

Design/methods Agency Agencies/

IOM-NAS Agencies/ISO

Agency designation Agency Governing Board/Staff Governing

Board/ISO

Studymanagement Agency Agencies Agencies

Study conduct Agency/field Agencies/Field Agencies/Field

Study certification Agency Governing Board/Staff ISO

Study conclusions Agency Governing Board/Staff ISO

Dissemination Agency Governing Board/Staff ISO

Advantages Builds on current Independent Independent

Builds on current

Disadvantages Politically vulnerable No established credibility Other missions

of ISO

Linked to one agency Duplicate capacity

* Some proposals suggest creating an agency-associated but privately operated FFRDC (Federally Funded Research and Development Center) to give the work quasi-insulated status.**ISO: Independent Scientific Organization (e.g., Institute of Medicine, on the model of the NAS Transportation Research Board)

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Learning Healthcare System Concepts 2�

proposals have offered different approaches to creating

and managing a stepped-up program of comparative

effectiveness research. In Learning What Works Best, the

primary models were summarized, and the principal current

options can be grouped into three categories, as in the table

at left—one placing primary responsibility in a federal health

agency, one placing it primarily in an independent entity

outside any cabinet department, and a hybrid version using

a federal agency and an established independent scientific

organization.

More recently (2008), the IOM Committee on the

Identification and Evaluation of Highly Effective Clinical

Services, expressed concern over what it characterized as the

fragmented approach and inconsistent standards used in

assessing even the limited research base that exists, and called

for the establishment by the Secretary of Health and Human

Services of a dedicated advisory and program capacity for

the conduct of systematic reviews of the evidence.

Various groups looking at related issues have identified

similar touchstone principles to help guide policy choices

among the various possible approaches to creating a national

entity and capacity to steward and advance comparative

effectiveness research. Core elements include:

• Scientific credibility—ability to gain the trust and

confidence of the public, the scientific community, and

the other stakeholders involved.

• Political independence—well insulated from the

political processes that interests from all perspectives

will seek to leverage.

• Stakeholder neutrality—ability to engage with

all stakeholders—patients, providers, employers,

manufacturers, and insurers—in an independent,

even-handed fashion.

COMPARAtIvE EFFECtIvENESS RESEARCH ENtERPRISE MODElS

ACtIvIty FEDERAl INDEPENDENt BOARD HyBRID

Reference model NIH or AHRQ Federal Reserve Board NAS (IOM/TRB)

Priority setting Agency*/HHS Board Governing Board/Staff Governing Board/

ISO**

Budget allocation

Agency/HHS Board Governing Board/Staff Governing

Board/ISO

Study selection Agency Governing Board/Staff ISO

Design/methods Agency Agencies/

IOM-NAS Agencies/ISO

Agency designation Agency Governing Board/Staff Governing

Board/ISO

Studymanagement Agency Agencies Agencies

Study conduct Agency/field Agencies/Field Agencies/Field

Study certification Agency Governing Board/Staff ISO

Study conclusions Agency Governing Board/Staff ISO

Dissemination Agency Governing Board/Staff ISO

Advantages Builds on current Independent Independent

Builds on current

Disadvantages Politically vulnerable No established credibility Other missions

of ISO

Linked to one agency Duplicate capacity

cApA

cITy

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2� Institute of Medicine

• Participatory governance—opportunity for relevant

stakeholders to engage, as appropriate, in priority

setting and agenda setting, while safeguarding the

scientific integrity.

• Investigator integrity—management and conduct

of the research processes, and the determination and

validation of research results completely insulated from

outside influence.

• Agenda flexibility—decision and program processes

with the flexibility to respond quickly to emerging

issues and changing circumstances.

• Infrastructure efficiency—use where possible existing

capacity for the establishment of scientific standards

and for the management and conduct of studies.

• Transparency of processes and results—open access to

the data on which determinations are based and clarity

as to the processes and tools used in their evaluation.

Groups examining the need for the expanded research

activity have estimated increased annual funding needs

for such research ranging from several hundred million

to several billion dollars yearly. Although these may seem

startlingly large amounts, in the context of the $2 trillion

spent on health care, and the potential efficiencies that

might be gained, if only 1 percent (well below the R&D

levels targeted in most industries) of the nation’s healthcare

bill were devoted to understanding the effectiveness of the

care purchased, the total would come to approximately $20

billion annually.

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Learning Healthcare System Concepts 2�

7 RESEARchRedesigningtheclinicaleffectivenessresearchparadigm

Information demand is colliding with shortages of

money and time to effect fundamental improvements

in the way evidence is produced on the effectiveness of

diagnosis and treatment interventions. This was the focus

of the Roundtable’s workshop Redesigning the Clinical

Effectiveness Research Paradigm. With the historic advantages

of the randomized controlled trial blunted by time, cost, and

focus, innovative study designs and mathematics, applied to

routine administrative and clinical data are combining to

forge clinical effectiveness research integral to patient care.

Redesigning the clinical Effectiveness Research paradigm

• Address current limitations in applicability of research results• Counter inefficiencies in timeliness, costs, and volume• Define a more strategic use to the clinical experimental model• Provide stimulus to new research designs, tools, and analytics• Encourage innovation in clinical effectiveness research conduct• Promote effectiveness research as a routine part of practice• Improve access and use of clinical data as a knowledge resource• Foster the transformational research potential of information technology• Engage patients as full partners in the learning culture• Build toward continuous learning in all aspects of care

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�0 Institute of Medicine

Presenters ranging from clinicians to computer scientists

discussed issues related to certain core, recurrent themes.

• Address current limitations in applicability of research

results. Because clinical conditions and interventions

may be complex, lengthy, and vary in circumstances,

there are different implications for the evidence needed,

the study designs, and the ways lessons are applied: the

internal and external validity challenge. In particular,

given our aging population, often people have multiple

conditions—comorbidities—yet study designs generally

focus on people with just one condition, limiting

their applicability. While our assessment of candidate

interventions is primarily through studies early in

product development, the opportunity for discovery

extends throughout the life cycle of an intervention—

development, approval, coverage, and the full period of

implementation.

• Counter inefficiencies in timeliness, costs, and volume.

Much of current clinical effectiveness research has

inherent limits and inefficiencies related to time,

cost, and volume. Small studies may have insufficient

reliability or follow-up. Large experimental studies may

be expensive and lengthy, but have limited applicability

to practice circumstances. Studies sponsored by product

manufacturers have to overcome perceived conflicts and

may not be fully used. Each incremental unit of research

time and money may bring greater confidence, but also

carries greater opportunity costs. There is a strong need

for more systematic approaches to better defining how,

when, for whom, and in what setting an intervention is

best used.

• Define a more strategic use of the clinical experimental

model. Just as there are limits and challenges to

observational data, there are limits to the use of

experimental data. Challenges related to the scope of

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Learning Healthcare System Concepts �1

inferences possible, to discrepancies in the ability to

detect near-term vs. long-term events, to the timeliness

of our insights and our ability to keep pace with

changes in technology and procedures, all must be

managed. Part of the strategy challenge is choosing the

right tool at the right time. For the future of clinical

effectiveness research, the important issues relate not

to whether randomized experimental studies are better

than observational studies, or vice versa, but to what’s

right for the circumstances, and how the capacity can

be systematically improved.

• Provide stimulus to new research designs, tools, and

analytics. An exciting part of the advancement process

has been the development of new tools and resources

that may quicken the pace of our learning and add

real value by helping to better target, tailor, and refine

approaches. Use of innovative research designs, statistical

techniques, genomic information, and probability and

other models may accelerate the timeliness and level of

research insights. Some interesting approaches using

modeling for virtual intervention studies may hold

prospects for revolutionary change in certain clinical

outcomes research.

• Encourage innovation in clinical effectiveness research

conduct. The kinds of “safe harbor” opportunities

that exist in various fields for developing and testing

innovative methodologies for addressing complex

problems are rarely found in clinical research. Initiative

is needed for the research community to challenge and

assess its approaches—a sort of meta-experimental

strategy—including those related to analyzing large data

sets, in order to learn about the purposes best served by

different approaches.

• Promote effectiveness research as a routine part

of practice. Taking full advantage of each clinical

experience is the theoretical goal of a learning healthcare

RESEA

Rch

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�2 Institute of Medicine

system. But for the theory to move closer to the practice,

tools and incentives are needed for the caregiver to

participate. One starting point is anchoring the focus

of clinical effectiveness research planning and priority

setting at the point of service—the patient-provider

interface—as the source of attention, guidance, and

involvement in defining the key questions to engage.

The work with patient registries by many specialty

groups is an indication of the promise in this respect,

but additional emphasis on using practice settings

to evaluate interventions is necessary, especially in

anticipation of the access and use of the technology that

opens new evaluation possibilities.

• Improve access and use of clinical data as a knowledge

resource. With the development of bigger and more

numerous clinical datasets, the potential exists for larger

scale data mining and analysis to develop and explore

new insights into the effectiveness and optimal use of

interventions. Taking advantage of these prospects

requires improvements in data-sharing arrangements

and platform compatibilities, addressing issues related

to real and perceived barriers from interpretation of

privacy and patient protection rules, enhanced access

for secondary analysis to federally sponsored clinical

data (e.g., Medicare, Part D pharmaceutical, clinical

trials), the necessary expertise, and stronger capacity to

use clinical data for postmarket surveillance.

• Foster the transformational research potential of

information technology. Broad application and linkage

of electronic health records holds the potential to

foster movement toward real-time clinical effectiveness

research that can generate vastly enhanced insights into

the performance of interventions, caregivers, institutions,

and systems—and how they vary by patient needs

and circumstances. Capturing that potential requires

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Learning Healthcare System Concepts ��

working to better understand and foster the progress

possible, through full application of electronic health

records, development and application of standards that

facilitate interoperability, development of new search

strategies for data mining, and investment of patients

and caregivers as key supporters in learning.

• Engage patients as full partners in the learning culture.

With the impact of the information age growing daily,

access to up-to-date information by both caregiver and

patient changes the state of play in several ways. The

patient sometimes has greater time and motivation to

access relevant information than the caregiver, and a

sharing partnership is to the advantage of both. Taking

full advantage of clinical records, even with blinded

information, requires a strong level of understanding

and support for the work and its importance to

improving the quality of health care. This support may

be the most important element in the development of

the learning enterprise. In addition, the more patients

understand and communicate with their caregivers

about the evolving nature of evidence, the less disruptive

will be the frequency and amplitude of public response

to research results that find themselves prematurely,

or without appropriate interpretative guidance, in the

headlines and short-term consciousness of Americans.

• Build toward continuous learning in all aspects

of care. This foundational principle of a learning

healthcare system will depend on system and culture

change in each element of the care process with the

potential to promote interest, activity, and involvement

in the knowledge and evidence development process,

from health professions education to care delivery and

payment.

RESEA

Rch

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�� Institute of Medicine

The multifaceted, practice-oriented approach to clinical

effectiveness research discussed at the workshop is

represented in this figure as a continuum in which evidence

is continuously produced by a blend of experimental studies

with patient assignment (clinical trials); modeling, statistical,

and observational studies without patient assignment; and

monitored clinical experience. The ratio of the various

approaches varies with the nature of the intervention, as

does the weight given to the available studies. This enhanced

flexibility and range of research resources is facilitated by the

development of innovative design and analytic tools, and by

the growing potential of electronic health records to allow

much broader structure access to the results of the clinical

experience.

EvIDENcE DEvELOpMENT IN ThE LEARNINg hEALThcARE SySTEM

Recorded clinical outcomes

Models and nonexperimental studies

Experimental studies

Market EntrySafety & Efficacy Safety & Effectiveness

Contribution to Body of Evidence

Periodic Systematic Reviews of the Evidence

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Learning Healthcare System Concepts ��

8 DATACreatingaclinicaldatautilityforcontinuousimprovement

The quality, availability, and utility of the evidence to

guide healthcare decisions depend entirely on the

quality, availability, and utility of the data and analysis

to produce the evidence. Important information about the

results of different diagnostic and treatment interventions is

collected in multiple forms by many institutions for different

reasons and audiences—providers, patients, insurers,

manufacturers, health researchers, and public agencies.

Medical care data represent a vital resource for improving

insight and action for more effective treatment. With the

increasing potential of technical capacity for aggregation

and sharing of data while ensuring confidentiality, the

prospects are at hand for powerful and unprecedented

tools to determine the circumstances under which medical

interventions work best, and for whom. Although there

are various challenges to the use of such data—coding

discrepancies, platform incompatibilities, patient protection

tools—practical approaches can be developed for most. The

most significant challenge may be the barrier to data access

and the restrictions in treating clinical outcome data as a

proprietary commodity.

In February 2008, the IOM workshop Clinical Data as the

Basic Staple of Health Learning: Creating and Protecting a

Public Good was convened to facilitate the identification and

exploration of issues and strategies to engage in advancing

the access and use of clinical data for new knowledge and

health improvement. In addition to underscoring the paucity

of translational insights emerging from the vast and growing

body of clinical data, workshop participants discussed the

range of relevant technical, economic, legal, and policy

issues. Several common themes were referenced as priorities

in points made throughout the meeting.

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�6 Institute of Medicine

Advancing the clinical Data Utility

• Develop and foster the basic principles of clinical data

stewardship. The starting point for expanded access

and use of clinical data for knowledge development is

agreement on some of the fundamental notions to guide

the activities for all individuals and organizations with

responsibility for managing clinical data. Consensus on

approaches to such issues as data structure, standards,

reporting requirements, quality assurance, timeliness,

de-identification or security measures, access and use

procedures all will determine the pace and nature of

evidence development.

• Provide incentives for real-time use of clinical data in

evidence development. Current barriers to the real-time

use of clinical data for new knowledge—ranging from

regulatory and commercial issues to cost and quality

issues—require a dedicated program of activities,

• Develop and foster the basic principles of clinical data stewardship

• Provide incentives for real-time use of clinical data in evidence development

• Guarantee transparency to the patient when data are applied for research

• Correct the market failure for expanding electronic health records

• Center patients in the learning process through personal records and portals

• Foster coordinated EHR user organization evidence development work

• Develop the business case for expanded data sharing in a distributed network

• Ensure that publicly funded data are used for the public benefit.• Foster initiatives on broader semantic strategies for data mining.• Engage and inform the public in evidence development

strategies

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Learning Healthcare System Concepts ��

incentives, and strategies that will improve the methods

and approaches, their testing and demonstration,

the cooperative decision making on priorities and

programs, and the collective approach to regulatory

barriers.

• Guarantee transparency to the patient when data are

applied for research. Patient acceptance is key to use of

clinical data for knowledge development, and patient

engagement and control are key to the acceptance.

Clarity to individual patients on the structure, risks, and

benefits of access to data for knowledge development

is important. Confidence and accountability may be

enhanced through notification and audit transparent to

patients when and by whom their information has been

accessed for knowledge development.

• Correct the market failure for expanding electronic

health records. Currently, market incentives are

inadequate to the necessary expansion of use of

electronic health records. Demand by providers or

patients is not sufficient to counter the expense to small

organizations, competing platforms and asynchronous

reporting requirements work against their utility for

broad quality and outcome determinations, and even

the larger payers—apart from government—do not

possess the critical mass necessary to drive broader

scale applicability and complementarity. It will likely

take a deeper, more directed and coordinated strategy

involving Medicare leadership to foster the necessary

changes.

• Center patients in the learning process through

personal records and portals. Patient demand could

be strategically instrumental in spreading the progress

of the availability of electronic health records for

improving patient care and knowledge development.

Such demand will depend upon much greater patient

DA

TA

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�� Institute of Medicine

access to, comfort level with, and regular use of

programs that allow either the maintenance of personal

electronic health records or access through a dedicated

portal to their provider-maintained electronic medical

record. As developing consumer-oriented products give

patients and consumers more active roles in managing

personal clinical information, they may demonstrate

value in the speed and ease of personal access to the

information, better accommodate patient preference

in care, and foster a partnership spirit conducive to the

broader EHR application.

• Foster coordinated EHR user organization evidence

development work. A vehicle to enhance collaboration

among larger EHR users of different vendors may

accelerate the emergence of more standardized

agreements and approaches to integrating and sharing

data across multiple platforms, common query

strategies, virtual data warehousing rules and strategies,

relational standards, and engagement of ways to reduce

misperceptions on regulatory compliance issues.

• Develop the business case for expanded data sharing

in a distributed network. Demonstrate the prospect for

cost savings or avoidance from facilitated feedback to

providers on quality and outcomes; quick, continuous

improvement information; and improved management,

coordination, and assessment of patient care.

• Ensure that publicly funded data are used for the public

benefit. Federal and state funds that support medical

care, as well as support insights into medical care

through clinical research grant funding, are the source

of substantial clinical data that are not yet effectively

applied to the generation of new knowledge.

• Foster initiatives on broader semantic strategies for

data mining. Platform incompatibilities for clinical

data clearly represent substantial rate-limiting factors

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Learning Healthcare System Concepts ��

in the spread of electronic health records and their use

for knowledge development. Yet there may be strategies

using alternative semantic approaches for mining

clinical data for health insights, and which warrant

dedicated cooperative efforts to develop and apply

them.

• Engage and inform the public in evidence development

strategies. There is a need to generate a base of support

for and shared emphasis on developing a healthcare

ecosystem in which all stakeholders play a contributory

role. Ultimately, the public will determine the broad

acceptance and applicability of clinical data for

knowledge development, underscoring the importance

of keeping the public closely involved and informed on

all relevant activities to use clinical data to generate new

knowledge.

DA

TA

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Learning Healthcare System Concepts �1

9 EXpEcTATIONSResponsibilitiesandexpectationsforparticipants

A continuously learning and improving healthcare

system requires the active engagement of all its

participants, conveying certain expectations for

the roles of each. Growing out of the Roundtable’s Sectoral

Strategies Working Group discussion of core principles for

evidence interpretation and use (see section 5), following is a

summary of suggestions on the expectations for the roles of

each individual and institution involved in the development,

interpretation, and use of the evidence underpinning each

product, procedure, or service in healthcare diagnosis and

treatment.

• Caregivers and health care organizations. For

each healthcare decision, draw where possible on

the assessment and recommendation of a trusted

independent source; know the strength of the evidence

and the attendant risks of relevant clinical options;

know what the evidence says about the appropriateness

of various options for the circumstance at hand; explain

the nature and strength of the evidence to the patient,

and the relative merits of alternatives; seek and consider

patient preferences reasonable to the circumstances; be

mindful of the cost to the patient and to the healthcare

system of alternative interventions; have a strong

scientific rationale if recommending an intervention

insufficiently supported by available evidence specific to

the condition; know the services provided by all medical

caregivers to the patient; and participate in formal

evaluations, including systemwide interventions, to

address gaps in knowledge about the care they provide.

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�2 Institute of Medicine

• Patients (or designees). Each patient, or their designee,

should expect the information they need, and in turn,

should be expected to ask questions, express concerns,

and discuss healthcare preferences; achieve a reasonable

understanding of the rationale for a recommended

healthcare intervention, how it applies to the circum-

stance, the nature and strength of the supporting

evidence, and the nature of risk or uncertainty; agree to

close monitoring and documentation when opting for

an intervention in need of additional evidence of

effectiveness; and commit to following through on the

care agreed upon. Patients should also make clear to

their caregivers their expectation that information

about their care and its outcomes should be used to

assess the usefulness of the treatment they receive,

including participation in systemwide intervention

evaluation.

• Healthcare product companies. For each new healthcare

product or service, scrupulously follow established

standards in the development and testing processes;

provide full and transparent documentation of the

testing, safety, and effectiveness of the intervention; if

circumstances preclude customary assessment, offer

full documentation of biologic and clinical plausibility;

meet both the letter and the spirit of requirements in

place to ensure and promote the appropriate use of any

healthcare product or service; represent the products

or services to patients and clinicians in a manner

consistent with the level and findings of the evidence

on benefits and risks; and work with users to arrange

effective tracking and reporting, appropriate to the

nature of the intervention, on the results of its use in

the patient population.

• Researchers. In the design, execution, and reporting

of each study on the effectiveness of a healthcare

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Learning Healthcare System Concepts ��

intervention, design a study protocol that reflects,

to the extent practical, the circumstances in which

an intervention is expected to be used; specify

methodological limits, trade-offs in study design, and

possible biases in play; ensure and describe participant

consent, safety, and privacy, including compliance with

all related requirements; describe fully the data and

analytic criteria for their assessment; reveal decision

rules used in drawing conclusions, and, as possible

with appropriate safeguards, make data available as

a resource to others; report results in a form that is

objective and faithful to the data, identifies the nature

of any uncertainties, and allows for accurate translation

and communication.

• Systematic assessors and communicators of evidence.

In formulating each healthcare finding or guidance on

choice of interventions to manage a particular condition,

describe fully and accurately the targeted condition

(nature, impact, course); the proposed diagnostic or

treatment intervention (nature, mode of application,

level of invasiveness, possible side-effects); the nature

of the candidate population (characteristics, size); the

likely follow-on events anticipated from use of the

intervention (other diagnosis or treatments triggered,

duration of impact, longer-term consequences); the

nature and effectiveness of available alternatives; the

studies reviewed (cite, type, duration, size, outcomes,

quality, limitations) and reasons for studies excluded;

the extent to which the studies, individually and as

a body, reflect generally accepted principles for the

production and reporting of evidence; the metrics used

in determining the strength of the evidence; and how

analytic components determined guidance (strength

and quality of the evidence, seriousness of the condition,

effectiveness and consequences of the intervention, and

EXpEcTA

TION

S

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�� Institute of Medicine

available alternatives to the intervention). Descriptions

should also include the sources of support for the

work, the consideration of relevant information from

major stakeholders, the clinical and methodological

experts in the assessment activity, and the nature of the

consultative and review processes. Recommendations

should offer clear, succinct, and informative context

for conversations between patients and caregivers;

characterize uncertainties and risks (from condition

or intervention) in terms meaningful for informed

decision making; and underscore issues to clarify as

evidence evolves.

• Regulators. In determining the conditions for allowing

use of a diagnostic or treatment intervention for a

particular condition, maintain evidence standards

that give priority to safeguarding the public and

that provide incentives for the growth of insights on

safety and effectiveness; employ decision rules and

processes that are transparent; be explicit about the

review requirements at the outset and apply them

consistently across interventions of similar potential

impact and risk; ensure that review requirements and

processes yield reliable information on the proposed

intervention’s likely advantages relative to available

alternatives; take into account the anticipated life cycle

for an intervention, so that information gathered in the

premarket period for regulatory approval is structured

to support decision making for delivery and payment

as well; foster innovative approaches to the review of

interventions whose elements are sufficiently similar

to existing interventions as to provide an informative

experience base; tailor the review processes, as

appropriate, for expedited handling of interventions

with the potential for a breakthrough health impact or

significant cost savings; place a premium on monitoring

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Learning Healthcare System Concepts ��

protocols for interventions slated for expedited phased

introduction; provide consistent follow-up on post-

approval monitoring requirements; engage in regular

communication efforts with providers and the public

to place into context and improve understanding about

the nature of risks and benefits, the evolving nature of

evidence, and the importance of wide involvement in

the learning process.

• Payers and purchasers. Organizations responsible for

assessing a body of evidence to determine the allowable

payments for healthcare diagnostic or treatment

products, procedures, or services for a particular

condition are expected to encourage continuous

improvement in value delivered; draw where possible

on the assessments and recommendations of trusted

independent sources; ensure appropriate balance of

participants with clinical and methodological skills; be

explicit about the methods and results of analyses on the

safety and effectiveness of the healthcare intervention;

be explicit about cost analyses, and the role of cost-

effectiveness determinations in the decision process;

describe the participants in the work, the process, and

the decision criteria; consider having cost estimates

validated independently by an entity without economic

incentives. EXpEcTA

TION

S

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Learning Healthcare System Concepts ��

10 cOMMITMENTSLeadershipcommitmentstoimprovevalueinhealthcare

As a stakeholder leadership forum, the IOM Round-

table on Evidence-Based Medicine provides a venue

not only to highlight and discuss key issues of common

interest, but also to engage in collaborative efforts that reach

out within and across sectors. In 2007, led by Roundtable

representatives, participants from the different stakeholder

communities—providers, patients and consumers, employers

and employees, healthcare organizations, insurers, healthcare

product companies, regulators, information technology

developers, and evaluators—formed working groups to

review the opportunities for each sector to foster progress,

as well as to identify priorities for cross-sector collaboration.

The products of these sectoral working groups were then

discussed at a July 2007 multisector IOM Roundtable

workshop, Leadership Commitments to Improve Value in

Healthcare: Finding Common Ground, and published as part

of the workshop proceedings. Broad common themes of

the discussions included the importance of: building trust

and collaboration among participants; fostering agreement

on what constitutes value in health care; improving public

acceptability of the concepts and terms related to evidence-

based medicine; making the public and policy case for a

stronger focus on evidence identifying the priority evidence

development analyses needed; working to improve the level,

quality, and efficiency of evicence; clarifying and promoting

transparency in health care and related decision processes;

establishing common principles for evidence interpretation

and use; improving engagement of the full life cycle in the

assessment of health interventions; focusing on front-line

providers as change agents; fostering development of a

neutral and trusted intermediary for evidence development;

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�� Institute of Medicine

establishing the capacity and incentives for better evidence

development; and accelerating the advances in health

information technology.

Pegging off these general themes, sectoral participants

identified the following projects as priorities for collaborative

work under Roundtable auspices.

• Development of a priority assessment inventory.

Termed a “national problem list” by meeting participants,

this is a multisector collaborative effort to develop

criteria and a list of the diagnostic and treatment

interventions that might be viewed as particularly

important for the development of comparative

effectiveness studies. The list will serve as a means of

illustrating and prompting discussion on the key

evidence gaps and on the design, support, and execution

of the studies needed.

• Pursue agreement on the value proposition. Identify

key concepts and elements to be considered in assessing

and characterizing value from health care, setting the

stage for discussions on approaches to assessing those

elements and applying to add perspective and inform

decision making (see section 4). An IOM workshop,

Making Better Choices: Getting the Value We Deserve

from Health Care, is scheduled for November 2008.

• Identify common principles for evidence interpretation

and use. Identify the core principles underpinning

activities in interpretation and use of evidence, as

background for discussion of the implications and

of the ways the principles might be applied in the

development of a framework adaptive to different

circumstances related either to the evidence base or the

condition of interest (see section 5).

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Learning Healthcare System Concepts ��

• Foster cooperative data sharing. Several issues are

important in this regard: platform compatibilities,

standards, economic incentives and disincentives, the

regulatory and privacy environment. HIPAA issues are

being addressed by an IOM Committee expected to

issue its report and recommendations in 2008, including

those related to the use of clinical data for knowledge

development. The Roundtable’s February 2008 meeting,

Clinical Data as the Basic Staple of Healthcare Learning:

Creating and Protecting a Public Good, addressed a

number of the other issues related to sound data

stewardship (see section 8). And collaborative work has

been sponsored by the Roundtable on mining electronic

health records for postmarket surveillance and clinical

safety and effectiveness insights.

• Pursue a public communication initiative on evidence-

based medicine. Use the Roundtable membership’s

collective communication expertise to explore

improving terminology and advancing public awareness

on the nature and importance of evidence in medical

care, the key needs, and the centrality of patient and

provider communication around the state of

the evolving evidence for individual treatment

choices. The Roundtable’s Evidence Communication

Collaborative has a working group actively working on

a communication initiative proposal.

• Support progress on a trusted intermediary for

evidence promotion. The Roundtable’s Sustainable

Capacity working group oversaw the development of

a comprehensive Issue Brief, framing the issues and

options under discussion related to enhancement of the

national capacity to develop, evaluate, organize, validate,

and disseminate information on the comparative

effectiveness of health interventions (see section 6).

Technical assistance and related information is provided

cOM

MITM

ENTS

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�0 Institute of Medicine

on an ongoing basis to the various policy discussions of

the issue.

• Identify the potential from best practices in the use of

evidence. It is important to assess and underscore the

best practices in evidence development and application,

including consideration of ongoing methods of

identifying and disseminating those best practices. A

working group is underway to characterize the potential

returns from implementing certain established best

practices.

• Enlist front-line healthcare providers more effectively.

Charge the sectoral working group on providers with

proposing approaches to convening a coalition of

provider groups, perhaps under Roundtable auspices,

to consider sustained, coordinated work on health

professions education, testing, credentialing, and

practice setting tools and structure to improve focus,

accessibility, use, and generation by providers of the

best evidence. A Roundtable collaborative of providers

is being formed to engage this issue.

Each of these activities is now underway, or in the planning

stage, as collaborative ventures of Roundtable members and

other sectoral participants recruited to the process.

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Learning Healthcare System Concepts �1

LOOkINg fORwARD

Previewed throughout this Annual Report are various

activities on the emerging Roundtable agenda: workshops

on key issues and concepts of central interest and concern to

Roundtable members; and collaboratives for which a neutral

venue is advantageous to facilitate information sharing

and cooperative initiative to improve the development and

application of evidence for clinical decision making.

2008 Workshops

• Clinical Data as a Basic Staple of Health Learning.

Creating and Protecting a Public Good. To assess the

potential of emerging data capacity to serve as a

compass for continuous improvement in health care,

and to explore some of the technical, economic, social,

and legal challenges to improving the access and use of

clinical data for evidence development.

• Engineering a Learning Healthcare System: A Look at

the Future. To consider, in a collaboration between the

National Academy of Engineering and the Institute of

Medicine, how to harness the tools and experience of

systems engineering and operations research to improve

the efficiency, quality, and outcomes in health care.

• Learning What Works: Infrastructure and Clinical

Priorities for Learning Which Care Is Best. To engage and

characterize the nature and magnitude of infrastructure

improvements to meet the need for better and more

timely evidence for sound clinical decision making.

• Making Better Choices: Getting the Value We Deserve

from Health Care. To conduct an examination of the

needs and approaches to a better understanding and

measurement of value in health care, and its potential

role in guiding healthcare decisions.

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�2 Institute of Medicine

2008 Innovation Collaboratives

• Evidence Communication Innovation Collaborative: To

engage participants from multiple sectors in developing

and implementing a communications strategy that

helps foster better dialogue between patients and

providers on the nature, importance, and appropriate

use of clinical evidence to inform and improve health

care choices.

• Best Practices Innovation Collaborative: To bring together

representatives of health professional organizations

for discussion and cooperative action to identify and

improve implementation of best practices in evidence

development and application, including work to assess

the health and economic returns.

• Electronic Health Record User Innovation Collaborative:

To provide a venue for healthcare delivery organizations

using electronic health records to identify common

issues and interests, and to explore collaborative projects

that can facilitate their contributions to advance evident

development and application—and the frontiers of the

learning healthcare system.

• Effectiveness Research Innovation Collaborative: To

engage leaders of the research community—from

public, private, and academic sectors—in work to

improve research methods, identify priorities, and

stimulate activity in comparative effectiveness research

that can generate insights on which interventions work

best for whom, under which circumstances.

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Learning Healthcare System Concepts ��

ROUNDTABLE cONTRIBUTORSListed here are individuals who have served as members,

sponsors, advisors, planning committee members, authors,

presenters, formal respondents, or reviewers for Roundtable

activities referenced in this update. We thank them for their

valuable contributions, as well as all others who have attended

and participated in Roundtable-sponsored meetings.

Madhulika Agarwal, Dept VA

John Agos, sanofi-aventis

Rakesh Agrawal, Microsoft

Kate Ahlport, Burroughs Wellcome

Chuck Alston, Manning Selvage & Lee

Stuart Altman, Brandeis University

Steve Altschuler, Chldrns Hosp Phil

David Altshuler, Mass Gen Hospital

Pat Anderson, Stryker

David Atkins, Dept VA

Wade Aubry, Hlth Technology Center

Jerry Avorn, Brighm Wmn’s Hosp

Peter Bach, CMS

Mara Baer, Blue Cross Blue Shield

Bruce Bagley, Amer Assn Fam Phys

Susan Bales, Frameworks Institute

Andy Barbash, Apractis Sol, LLC

Michael Barbouche, Univ Wisc

Annette Bar-Cohen, Nt Brst Ca Coaltn

Jack Bates, VHA

Ray Baxter, Kaiser Permanente

Rachel Behrman, FDA

Karen Bell, CMS

Abdul Bengali, Mayo Clinic

Mark Benton, NC HHS

Marc Berger, Merck & Co., Inc.

Donald Berry, MD Anderson Cncr Ctr

Donald Berwick, Inst Hlthcr Imprvmt

David Blumenthal, Mass Gen Hosp

Ashley Boam, FDA

Carmella Bocchino, AHIP

Kenneth Boff, GA Inst Tech

Marilyn Sue Bogner, Ins Std Hum Err

Queta Bond, Burroughs Wellcome

Catherine Bonuccelli, AstraZeneca

William Bornstein, Emory University

Adam Bosworth, Google, Inc.

Marc Boutin, National Health Council

Jeff Brady, AHRQ

David Brailer, Hlth Evolution Partners

Miles Braun, FDA

David Brennan, AstraZeneca

Jennifer Bright, Mental Hlth America

Sarah Bronko, IOM

Sarah Jane Brown, IOM

Lynda Bryant-Comstock, GSK

Rebecca Burkholder, Natl Cnsmrs Lg

Helen Burstin, Natl Quality Forum

Sam Butler, Epic Systems Corporation

Kathleen Buto, Johnson & Johnson

Robert Califf, Duke Univ Med Ctr

Bruce Nedrow Calonge, CO Pub Hlth

Tanisha Carino, Avalere Health, LLC

Gunnar Carlsson, Stanford University

Kristin Carman, Amer Inst for Res

Margaret Cary, Dept VA

Samantha Chao, IOM

Michael Chase, Kaiser Permanente

Michael Chernew, Harvard Med Schl

Michaele Christian, NCI / NIH

Carolyn Clancy, AHRQ

David Classen, First Consulting Group

Gina Clemons, Dept VA

Amanda Cline, IOM

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�� Institute of Medicine

Simon Cohn, Kaiser Permanente

Dale Compton, Purdue University

Paul Conlon, Trinity Health

James Cooper, US House of Reps

Denis Cortese, Mayo Clinic

Peter Covitz, National Cancer Institute

Molly Coye, Health Technology Center

Robert Crane, Kaiser Permanente

William Crown, i3 Innovus

Francesca Cunningham, Dept VA

Gerald Dal Pan, FDA

Helen Darling, Natl Bus Grp on Hlth

Terry Davis, LA State Univ

Nancy Derr, FDA

Don Detmer, AMIA

Amy Deutschendorf, Johns Hop Hosp

Carol Diamond, Markle Foundation

Louis Diamond, Thomson Hlthcr, Inc

Kay Dickersin, Johns Hop Univ

Efrem Dlugacz, Johnson & Johnson

Steve Downs, RWJF

Benjamin Druss, Emory University

Joyce Dubow, AARP

Elizabeth DuPre, Amer Entrprs Inst

Mary Durham, Kaiser Permanente

Carl Dvorak, Epic Systems Corp

David Eddy, Kaiser Permanente

Dee Edington, University of Michigan

Earnest Edwards, formerly Alcoa

Jonathan Einbinder, Prtnrs HlthCr

Alexander Eremia, MedStar Hlth, Inc.

Lynn Etheredge, George Wash Univ

Judy Faulkner, Epic Systems Corp

Nancy Featherstone, AstraZeneca

Mark Fendrick, University of Michigan

Jorge Ferrer, Dept VA

Harvey Fineberg, IOM

Brian Firth, Johnson & Johnson

Elliott Fisher, Dartmouth University

Patricia Flatley Brennan, Univ Wisc

Lee Fleisher, Univ Penn

David Flum, University of Washington

Christopher Forrest, Epic Sys Crp

Joseph Francis, Dept VA

Kathleen Frisbee, Dept VA

Steven Galson, FDA

Robert Galvin, General Electric

Alan Garber, Stanford University

Geoff Garin, Hart Research Associates

Annetine Gelijns, Columbia University

Kim Gilchrist, AstraZeneca LP

Michael Gillam, Microsoft

Marge Ginsburg, Sacrmto Hlthcr Dec

Ron Goetzel, Thomson Hlthcr, Inc

Veronica Goff, Natl Bus Grp on Hlth

Marthe Gold, City College NY

Janlori Goldmann, Columbia Univ

Don Goldmann, Inst Hthcr Imprvmt

David Goldstein, Duke University

Elizabeth Goldstein, CMA

Steven Goodman, Johns Hop Univ

Gail Graham, Dept VA

Sheldon Greenfield, Univ CA, Irvine

Edward Greissing, sanofi-aventis

Thomas Gross, FDA

Jeffrey Grossman, Univ Wisc

Jerome Grossman, Harvard University

Jessie Gruman, Cntr Advncmnt Hlth

James Guest, Consumers Union

Gordon Guyatt, McMaster University

Cecily Hall, Microsoft

George Halvorson, Kaiser Permanente

Bruce Hamory, Geisinger Hlth Sys

Martin Harris, Cleveland Clinic

Tracy Harris, IOM

Winifred Hayes, Hayes, Inc.

Crystal Hayling, Blue Shield CA Fndtn

Anthony Hayward, NIH

Robert Hayward, University of Ottawa

Mark Helfand, OR Hlth & Sci Univ

David Helms, AcademyHealth

Carolina Hinestrosa, Nt Brst Ca Cltn

Louis Hochheiser, Humana, Inc.

Peter Honig, Merck & Co., Inc.

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Learning Healthcare System Concepts ��

Carmen Hooker Odom, Mlbnk Mmrl

Julianne Howell, CMS

Courtney Hudson, EmergingMed

Kathy Hudson, Johns Hop Univ

John Iglehart, Health Affairs

Karen Ignagni, AHIP

Belinda Ireland, BJC Healthcare

Telba Irony, FDA

George Isham, HealthPartners, Inc.

Anil Jain, Cleveland Clinic

Brent James, Intrmtn Health Care, Inc

Michael Johns, Emory University

Roger Johns, Johns Hop Schl Med

Michael Johnson, Kaiser Permanente

Peter Juhn, Johnson & Johnson

Douglas Kamerow, RTI International

Jim Karkanias, Microsoft

Sam Karp, CA Hlthcre Fndtn

Stephen Katz, NIAMSD / NIH

Rae-Ellen Kavey, NHLBI / NIH

Marcia Kean, Feinstein Kean Hlthcr

Edward Kelley, AHRQ

Brian Kelly, Accenture

Jeffrey Kelman, CMS

Ann Kempski, Srvc Emp Int Union

Helen Kim, Kosan Biosciences

Joe Kimura, Hrvrd Vngrd /Atrius Hlth

Darrell Kirch, AAMC

Margaret Kirk, Y-ME Ntl Brst Ca Org

Kenneth Kizer, Medsphere

Jim Knutson, Aircraft Gear Corp

Isaac Kohane, Harvard Medical School

Mary Jane Koren, Commonwlth Fund

Ron Krall, GlaxoSmithKline

Barry Kramer, NIH

Missy Krasner, Google, Inc.

Alan Krensky, NIH

Phillip Kroth, Univ New Mexico

Joel Kupersmith, Dept VA

Michael Kussman, Dept VA

Pierre La Chance, Kaiser Permanente

Jeanne Lambrew, George Wash Univ

Carol Lannon, Cincinn Chldrn’s Hosp

Eric Larson, Group Hlth Coop

Richard Larson, Mass Inst Technol

Tara Larson, NC HHS

Michael Lauer, NHLBI / NIH

Cato Laurencin, University of Virginia

William Lawrence, NC HHS

Arthur Levin, CMS

Jeffrey Levin-Scherz, Hrvrd Vanguard

John Lewin, Amer Collge, Cardiology

Louise Liang, Kaiser Permanente

Richard Lilford, Univ Birmngham, UK

Keith Lind, AARP

Chris Lisi, The Glover Park Group

Kathleen Lohr, RTI International

Douglas Lowery-North, Emory Univ

Bryan Luce, United BioSource Corp

Michael Mack, CSANT

Stephen MacMillan, Stryker

Brian Maloney, AstraZeneca

Benjamin Mann, DARPA

Teri Manolio, NHLBI / NIH

JoAnn Manson, Harvard Med Schl

Janet Marchibroda, eHealth Initiative

William Marder, Thomson Hlthcr, Inc

Norman Marks, FDA

Elliott Maxwell, Johns Hop Univ

Mark McClellan, Brookings Institution

Clem McDonald, NLM / NIH

Walter McDonald, Cncl Med Sp Soc

Robert McDonough, Aetna

Terry McGeeney, TransforMED

Barbara McNeil, Harvard Med School

David Meltzer, University of Chicago

Richard Menschel, Charina Endw Fnd

Kate Meyers, Kaiser Permanente

Karen Milgate, CMS

JoAnn Minor, FDA

Deb Mizeur, U.S. House of Reps

Tara Montgomery, Consmr Rpts Hlth

Alan Morris, University of Utah

Ralph Muller, UPenn Health System

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�6 Institute of Medicine

Mary O’Neil Mundinger, Columbia U

William Munier, AHRQ

Michael Mustille, Permanente Fedrtn

Elizabeth Nabel, NHLBI / NIH

John Nance, ABC / Phoenix Partners

Mary Naylor, UPenn Schl Nursng

John Neiderhuber, NCI / NIH

Garry Neil, Johnson & Johnson

Eugene Nelson, Drtmth-Htchk Md Cr

Chalapathy Neti, IBM

Peter Neupert, Microsoft

Nicole Newburg-Rinn, Consultant

Len Nichols, New Amer Foundation

Nancy Nielsen, Amer Med Assn

Sharon-Lise Normand, Harvard Med

Leslie Norwalk, CMS

Samuel Nussbaum, Wellpoint, Inc.

Susan Odenthal, Johnson & Johnson

Peggy O’Kane, Ntl Comm Qual Assrn

Elizabeth Olmstead Teisberg, UVA

Alexander Ommaya, Dept VA

Paul O’Neill, Value Capture LLC

Peter Orszag, Congrssnl Budget Office

Eduardo Ortiz, NHLBI / NIH

James Ostell, NLM / NIH

J. Marc Overhage, Regenstrief

Douglas Owens, Stanford University

Andy Page, IOM

Cynthia Palmer, AHRQ

Rachel Passman, IOM

Margie Patlak, Consultant

Avinash Patwardhan, URAC

Steven Paul, Eli Lilly and Company

Ronald Paulus, Geisinger Hlth Sys

Greg Pawlson, NCQA

Lisa Payne-Simon, Blue Shld CA Fnd

Cindy Pearson, Ntl Wmn’s Hlth Ntwk

Steven Pearson, NIH

Gerald Peden, Ind Blue Cross

Steve Pelletier, Pelletier Editorial

Jonathan Perlin, HCA, Inc.

Eric Peterson, Duke Univ Med Schl

Diana Petitti, U So CA Schl Med

Robert Phillips, Robert Graham Cntr

Steve Phurrough, CMS

Richard Platt, Hrvrd Plgm Hlth Care

Michael Porter, Harvard Bus School

Eva Powell, Natl Part Wmn & Fmlies

David Pryor, Ascension Health

Barbra Rabson, MA Hlth Qual Prtnrs

Eric Racine, sanofi-aventis

Gurvaneet Randhawa, AHRQ

Kimberly Rask, Emory University

Sir Michael Rawlins, NICE, UK

Wayne Ray, Vanderbilt University

Rita Redberg, UCSF

Proctor Reid, Natl Acad Engineering

Alison Rein, AcademyHealth

Vicky Rideout, Kaiser Fam Fndtn

Mark Roberts, U Pttsbrgh Med Clg

Alan Rosenberg, Wellpoint, Inc.

Wayne Rosenkrans, AstraZeneca

Murray Ross, Kaiser Permanente

John Rother, AARP

Tim Rothwell, sanofi-aventis

William Rouse, GA Inst Tech

John Rowe, Columbia University

A. John Rush, UT Sthwstrn Med Cntr

Leonard Sacks, FDA

Khaled Saleh, University of Virginia

Judith Salerno, IOM

Lewis Sandy, United HealthCare

Sebastian Schneeweiss, Harvard Med

Deborah Schwab, Blue Shld CA Fndtn

Sanford Schwartz, Univ Pennsylvania

Nina Schwenk, Mayo Clinic

Joe Selby, Kaiser Permanente

Leopold Selker, Evnstn Nthwst Hlthcr

Donna Shalala, University of Miami

Gail Shearer, Consumers Union

Paul Shekelle, Rand

Kristina Shulkin, IOM

Jeffrey Shuren, FDA

Susan Shurin, NHLBI /NIH

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Learning Healthcare System Concepts ��

Denise Simons-Morton, NHLBI /NIH

Eve Slater, Pfizer, Inc.

Jean Slutsky, AHRQ

Karen Smith, AstraZeneca

Mark Smith, CA Hlthcr Fndtn

Peter Smith, Duke Univ Med Schl

Thomas Smith, Evnstn Nthwst Hlthcr

Steven Solomon, CDC

Harold Sorenson, UCSD

Steve Soumerai, Harv Med/Harv Pil

Steven Spear, Mass Inst Technology

Stephen P. Spielberg, Dartmouth Coll

Judy Staffa, FDA

William Stead, Vanderbilt University

Donald Steinwachs, Jns Hop Pub Hlth

Andrew Stern, Service Emp Intl Union

Eugene Steuerle, Urban Institute

Mark Stewart, Amer Collg Cardiol

Walter Stewart, Geisinger Hlth Sys

Susanne Stoiber, IOM

Barry Straube, CMS

Nancy Sung, Burroughs Wellcome

Stephen Swensen, Mayo Clinic

Gary Teal, Emory University

Robert Temple, FDA

Jeff Tenner, IBM

Nicolas Terry, St Louis U Schl of Law

Steve Teutsch, Merck & Co., Inc.

James Tien, Univ Miami

Laura Tollen, Kaiser Permanente

David Tollerud, IOM

Sean Tunis, Ctr Med Tech Policy

I. Steven Udvarhelyi, Ind Blue Cross

Steve Vinter, Google, Inc.

Frances Visco, Natl Br Ca Coaltn

Steven Waldren, Amer Acad Fam Phys

Alexander Walker, Harvard University

Elizabeth Walker, Amer Entrprs Inst

Paul Wallace, Kaiser Permanente

Phil Wang, NIMH / NIH

Kerry Weems, CMS

Kenneth Weine, Consumers Union

James Weinstein, Drmth-Hthk Md Ctr

Harlan Weisman, Johnson & Johnson

Kevin Weiss, Northwstrn Med Schl

Jed Weissberg, Kaiser Permanente

Lynda Welage, University of Michigan

William Weldon, Johnson & Johnson

Alan Westin, Privacy Consltng Grp

Ben Wheatley, IOM

John Wilbanks, Science Commons

Marcy Wilder, Hogan & Hartson LLP

Gail Wilensky, Project HOPE

Mark Williams, Emory University

Thomas Winkel, Stryker

Janet Woodcock, FDA

Steve Woolf, VA Cmmnwlth Univ

Jill Yegian, CA Hlthcr Fndtn

Jason Zielonka, Ortho-McNl Janssen

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�� Institute of Medicine

Sponsors of the IOM Roundtable on Evidence-Based Medicine

Agency for Healthcare Research and Quality

America’s Health Insurance Plans

AstraZeneca

Blue Shield of California Foundation

Burroughs Wellcome Fund

California HealthCare Foundation

Centers for Medicare and Medicaid Services

Charina Endowment Fund

Commonwealth Fund

Food and Drug Administration

Johnson & Johnson

Gordon and Betty Moore Foundation

National Heart, Lung and Blood Institute

sanofi-aventis

Stryker

Department of Veterans Affairs

Roundtable Staff

Katharine W. Bothner, Administrative Assistant

W. Alexander Goolsby, M.S.P.H., Program Officer

J. Michael McGinnis, M.D., M.P.P., Senior Scholar & Executive Director

LeighAnne M. Olsen, Ph.D., Program Officer

Daniel F. O’Neill, M.B.A., Research Associate

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Related IOM Reports To Err is Human, 2000 Crossing the Quality Chasm, 2001 Small Clinical Trials: Issues and Challenges, 2001 Medical Innovation in the Changing Healthcare Marketplace: Conference Summary , 2002 Priority Areas for National Action: Transforming Health Care Quality, 2003 Knowing What Works in Health Care: A Roadmap for the Nation, 2008 The Institute of Medicine serves as adviser to the nation to improve health. Established in 1970 under the charter of the National Academy of Sciences, the IOM provides independent, objective, evidence-based advice to policymakers, health professionals, the private sector, and the public. The mission of the IOM embraces the health of people everywhere.

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