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1
Introduction
Health and health care are going digital. As multiple intersecting plat-
forms evolve to form a novel operational foundation for health and health
care—the nation’s digital health utility—the stage is set for fundamental
and unprecedented transformation. Most changes will occur virtually out
of sight, and the pace and profile of the transformation will be determined
by stewardship that fosters alignment of technology, science, and culture
in support of a continuously learning health system. In the context of
growing concerns about the quality and costs of care, the nation’s health
and economic security are interdependently linked to the success of that
stewardship.
Progress in computational science, information technology, and bio-
medical and health research methods have made it possible to foresee the
emergence of a learning health system that enables both the seamless and
efficient delivery of best care practices and the real-time generation and ap-
plication of new knowledge. Increases in the complexity and costs of care
compel such a system. With rapid advances in approaches to diagnosis and
treatment, and new genetics insights into individual variation, clinicians
and patients must sort through exponentially increasing numbers of issues
with each clinical decision. At the same time, healthcare costs are draining
the purchasing power of consumers and handicapping the competitiveness
of U.S. businesses, yet health outcomes are falling far short of the possible.
Against this backdrop of opportunity and urgency, the Institute of
Medicine (IOM) of the National Academies, sponsored by the Office of
the National Coordinator for Health Information Technology (ONC), con-
vened a series of expert meetings to explore strategies for accelerating the
53
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54 ENGINEERING A LEARNING HEALTHCARE SYSTEM
development of the digital infrastructure for the learning health system.
Major elements of those discussions are summarized in this publication,
Digital Infrastructure for the Learning Health System: The Foundation for
Continuous Improvement in Health and Health Care.
THE LEARNING HEALTH SYSTEM
In 2001, the IOM report Crossing the Quality Chasm called national
attention to untenable deficiencies in health care, noting that every patient
should expect care that is safe, effective, patient-centered, timely, efficient,
and equitable (IOM, 2001). Based on the determination that health care is
a complex adaptive system—one in which progress on its central purpose
is shaped by tenets that are few, simple, and basic—the report identified
several rules to guide health care. In particular, these rules underscore the
importance of issues related to the locus of decisions, patient perspectives,
evidence, transparency, and waste reduction. The report envisioned, in ef-
fect, engaging patients, providers, and policy makers alike to ensure that
every healthcare decision is guided by timely, accurate, and comprehensive
health information provided in real time to ensure constantly improving
delivery of the right care to the right person for the right price.
The release of the IOM Chasm report stimulated broad activities re-
lated to clinical quality improvement and the effectiveness of health care,
including the creation by the IOM of the Roundtable on Value & Science-
Driven Health Care. Begun in 2006 as the IOM Roundtable on Evidence-
Based Medicine, it has explored ways to improve the evidence base for
medical decisions and sought the development of a learning health system
“designed to generate and apply the best evidence for collaborative health
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.” From its inception, the Roundtable has con-
ducted The Learning Health System Series of public meetings in an effort
to outline components of the conceptual foundation of the learning health
system. Since 2006 the IOM has conducted 15 workshops in the Learning
Health System Series, with 10 reports published and in production:
• T
he Learning Healthcare System
• Leadership Commitments to Improve Value in Health Care: Find-
ing Common Ground
• E
vidence-Based Medicine and the Changing Nature of Health Care
• R
edesigning the Clinical Effectiveness Research Paradigm: Innova-
tion and Practice-Based Approaches
• C
linical Data as the Basic Staple of Healthcare Learning: Creating
and Protecting a Public Good
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55
INTRODUCTION
• E
ngineering a Learning Healthcare System: A Look at the Future
• L
earning What Works: Infrastructure Required for Comparative
Effectiveness Research
• V
alue in Health Care: Accounting for Cost, Quality, Safety, Out-
comes, and Innovation
• T
he Healthcare Imperative: Lowering Costs and Improving Outcomes
• P
atients Charting the Course: Citizen Engagement and the Learn-
ing Health System
As the most recent contribution to this series, this publication considers
what has been variously described as the system’s nerve center, its circula-
tion system, or the engine to drive the progress envisioned in the Learning
Health System Series: the digital infrastructure.
As it has been laid out by the work of the Roundtable, in a learning
health system patients and providers will have access to timely, accurate,
and comprehensive health information that can be used to deliver services
effectively and efficiently. Characteristics of such a system are noted in
Box 1-1 and in matrix form in Appendix A.
Because information technology serves as the functional engine for
the continuous learning system, this ONC-commissioned exploration was
broadly conceived to consider the issues and strategies required for the
emergence of a digital infrastructure that allows data collected during
activities in various settings—clinical, research, and public health—to be
integrated, analyzed, and broadly applied (“collect once, use for multiple
purposes”) to inform and improve clinical care decisions, promote patient
education and self-management, design public health strategies, and sup-
port research and knowledge development efforts in a timely manner.
THE DIGITAL HEALTH INFRASTRUCTURE
The digital infrastructure for the learning health system will not solely
be the result of features designed and built de novo; there is a growing
body of existing initiatives and resources actively in play at multiple levels.
These include expanding adoption of technologies such as electronic health
records (EHRs), personal health records (PHRs), telehealth, health informa-
tion portals, electronic monitoring devices, mobile health applications, and
advances in molecular diagnostics. Also in play are collections of health
information, such as biobanks, and health information databases main-
tained by large health systems, private insurers, and regulatory agencies.
Each adds important capacity for clinical care, clinical and health services
research, public health surveillance and intervention, patient education and
self-management, and safety and cost monitoring.
Still, these capacities are relatively early in their development and as
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56 ENGINEERING A LEARNING HEALTHCARE SYSTEM
BOX 1-1
Learning Health System Characteristics
Culture: participatory, team-based, transparent, improving
Design and processes: patient-anchored and tested
Patients and public: fully and actively engaged
Decisions: informed, facilitated, shared, and coordinated
Care: starting with the best practice, every time
Outcomes and costs: transparent and constantly assessed
Knowledge: ongoing, seamless product of services and research
Digital technology: the engine for continuous improvement
Health information: a reliable, secure, and reusable resource
The Data utility: data stewarded and used for the common good
Trust fabric: strong, protected, and actively nurtured
Leadership: multi-focal, networked, and dynamic
SOURCE: Adapted from The Learning Healthcare System (IOM, 2007).
they continue to unfold, progress toward a digital health infrastructure
depends on continuous improvement. Challenges include the fact that as
of 2009, only about 12% of hospitals and 6% of clinician offices had an
EHR in place (DesRoches et al., 2008; Jha et al., 2010) and only about 1
in 14 Americans had electronic access to any patient-oriented version of
their health record (CHCF, 2010). On the other hand, since 2000, the num-
ber of Americans who have access to the Internet has jumped from 46%
to 74%, and the number of American adults who have looked online for
health information has jumped from 25% to 61% (Fox, 2010), suggesting a
change in the way people access health information. Wireless technology is
quickening the pace of change. With 6 in 10 American adults using wireless
capability with a laptop or mobile device (Smith, 2010), mobile applica-
tions are rapidly developing for remote site access to health information,
as well as diagnostic and even treatment services.
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57
INTRODUCTION
The striking progress in the capacity and influence of information tech-
nology on society over the past three decades is a blended product of inter-
related initiatives arising from within the commercial, independent, and
public sectors. Leaps in the speed and power of information processing, the
efficiency of the operations, the development of the Internet and World Wide
Web, and its use to facilitate near-universally available real-time access to
information have spawned a new economy and new vehicles for progress.
Health information vendors, large and small, have emerged to meet the
growing demand for capacity to manage the retrieval, storage, and delivery
of information for agencies, institutions, professionals, and individuals in
virtually every aspect of health and health care. The range of newly digi-
talized services—and the growth of vendors to provide them—is startling.
Through technologies developed by companies such as Google, Microsoft,
and Yahoo, the rapidly expanding amounts of health-related information
available on the Internet have become increasingly easy to access and query.
The amount of web-based health information accessed daily by individuals
and clinicians, and the frequency with which they turn to the Internet for
this information, is already transforming the care process.
Care Management Resources
Beyond publicly available digital resources, a vast array of specialized
care management products have emerged to support a broad range of ac-
tivities. A wide array of companies have emerged to support the various
facets of clinical recordkeeping and information management needed to
support clinical processes. Many of these, such as individual patient chart-
ing, are served through EHRs. Vendors include EPIC, Cerner, Greenway
Medical, General Electric, and Allscripts, as well as newer companies that
provide web-based services such as Practice Fusion. Most of these are
comprehensive EHR products that integrate support of administrative pro-
cesses such as scheduling, billing, claims processing, payment, and even
supply and equipment inventory maintenance. Other products supporting
health information management are PHRs—records maintained by indi-
vidual consumers—that provide patients a format for contributing and
managing their health information electronically. Microsoft HealthVault
and Google Health are two of the leading efforts in this area, as well as
Dossia, an employer-led, open source effort. Prescribing is another compo-
nent of the clinical care continuum moving to the digital platform. Led by
companies such as Surescripts—with an expansive network and increasing
capabilities—e-prescribing is, in many ways, leading the way in current
health information exchange.
EHRs, PHRs, and their associated functions represent a wealth of
potential in the support of clinical decisions and as sources of information
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58 ENGINEERING A LEARNING HEALTHCARE SYSTEM
for research, surveillance, public health reporting, and patient–clinician
communication. This is accomplished through portals for more regular, di-
rect communication between patients and their providers; clinical research
protocol processes; postmarket product monitoring; safety and hazard
exposure monitoring; disease and intervention registries; and data aggre-
gation, analysis, and modeling. Increased use of digital technology also
includes remote examination and diagnosis through telehealth technologies,
such as those used by the military and in rural locations. Furthermore, the
use of monitoring sensors to follow patients remotely and collect informa-
tion in real time is growing in use, especially among the chronically ill.
Several organizations are actively involved in employing these technologies
at their full potential, and some of these are highlighted in the case studies
presented in Appendix B and discussed below.
Healthcare Delivery Organizations
Various large academic health centers and healthcare delivery
organizations—Veterans Health Administration (VHA), Kaiser Perman-
ente (see summary in Box 1-2, and the full written description in Appendix
B), Geisinger Health System, Vanderbilt, MD Anderson, Palo Alto Medical
Foundation, Group Health Cooperative, several Harvard facilities, Chil-
dren’s Hospital of Philadelphia, Virginia Mason, and the Mayo Clinic,
to name a few—have invested substantially in the creation of advanced
digital resources for administrative, patient care, and research functions.
For example, the VHA established one of the first EHR systems, Veterans
Health Information Systems and Technology Architecture (VISTA), and
has been a pioneer in its use of health information technology (HIT) for
quality improvement. More recently, VHA launched the ‘My HealtheVet’
program, a PHR system that allows veterans to track their clinical visits,
tests, and prescriptions, while also having access to relevant health informa-
tion and patient support communities. Other important HIT applications
employed by these organizations include: clinical decision support tech-
nologies integrated within their EHR systems and data mining for adverse
event surveillance and identification of populations at risk or in need of
directed follow-up. Nonetheless, the diversity and limited compatibility of
the products, coupled with the lack of economic incentives for their use,
has, to date, restrained the uptake, application, and functional utility of
these capacities across the broader system.
Independent Sector
A number of public, private, and independent sector initiatives have
emerged to accelerate stakeholder action on various dimensions important
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59
INTRODUCTION
BOX 1-2
Case: Kaiser Permanente
In 2003, Kaiser Permanente (KP) launched a $4 billion health information
system called KP HealthConnect that links its facilities and clinicians throughout
their delivery system and represents the largest civilian installation of electronic
health records (EHRs) in the United States. The EHR at the heart of KP Health-
Connect provides a reliably accessible longitudinal record of member encounters
across clinical settings including laboratory, medication, and imaging data; as well
as supporting
• lectronic prescribing and test ordering (computerized physician-order
E
entry) with standard order sets to promote evidence-based care
• opulation and patient-panel management tools such as disease regis-
P
tries to track patients with chronic conditions
• ecision support tools such as medication-safety alerts, preventive-care
D
reminders, and online clinical guidelines
• lectronic referrals that directly schedule patient appointments with spe-
E
cialty care physicians
• ersonal health records providing patients with the ability to view their
P
personal clinical information including lab results, plus linkage with phar-
macy, physician scheduling, and secure and confidential e-mail messag-
ing with clinicians.
• erformance monitoring and reporting capabilities
P
• atient registration and billing functions
P
Physician leaders report that access to the EHR in the exam room is helping
to promote compliance with evidence-based guidelines and treatment protocols,
eliminate duplicate tests, and enable physicians to handle multiple complaints
more efficiently within one visit. Ongoing evaluation by Kaiser indicates that pa-
tient satisfaction with outpatient physician encounters has increased and that the
combination of computerized physician-order entry, medication bar coding, and
electronic documentation tools is helping to reduce medication administration
errors in hospital care.
Overall, Kaiser’s experience suggests that use of the EHR and online portal
to support care management and new modes of patient encounters is having
positive effects on utilization of services and patient engagement. For example,
three-quarters or more of online users surveyed agreed that the portal enables
them to manage their health care effectively and that it makes interacting with the
healthcare team more convenient.
to progress. To supplement the relatively limited pre-2009 public invest-
ments, independent sector leadership has come from foundations such as
the Markle Foundation, the Robert Wood Johnson Foundation (RWJF),
and the California HealthCare Foundation (CHCF). For example, the
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60 ENGINEERING A LEARNING HEALTHCARE SYSTEM
Markle Foundation has played a leading role in facilitating conversations
in the areas of privacy and security in order to ensure that the patient is the
ultimate beneficiary of a digitally–supported learning health system. Their
Common Framework for sharing and protecting health information has
been fundamental in identifying principles and approaches for safe health
information exchange. Among many other activities, RWJF has led the
way in stimulating innovation in PHRs through its Project HealthDesign,
and CHCF has funded a number of projects to explore the use of HIT to
improve the care of patients with chronic conditions.
As a result of the increased activity in the area, a number of facilitative
stakeholder groups have emerged. A portion of these have taken the shape
of capacity-building resources such as the Health Information Exchanges,
which serve to work with clinicians and institutions to facilitate the ex-
change of health information between systems, often within a defined geo-
graphic area. Other groups include the Clinical Data Interchange Standards
Consortium (CDISC) an organization involved in developing standards to
enable aggregation of health information across datasets and methodologies
to support its use for research, and Integrating the Healthcare Enterprise
(IHE), which promotes coordinated use of established standards to improve
health information interoperability. An example of the coordinative poten-
tial of these groups is found in the development of integration profiles by
IHE and CDISC to support the use of EHRs for clinical research, quality
and public health, and the testing and demonstration of these profiles by
several vendors including Cerner, Allscripts, Greenway Medical, and GE
Healthcare. Additionally, there are a number of organizations working to
promote the use of information and information technology to improve
health and health care. Notable among them are the eHealth Initiative,
the National eHealth Collaborative, and the Healthcare Information and
Management Systems Society. Finally, on the professional advancement
dimension, the American Medical Informatics Association has emerged
as a growing resource for the contributions of biomedical and health in-
formaticians working in activities to organize, manage, analyze, and use
information in health care.
Examples from Outside Health Care
The developing potential presents opportunities and challenges for
stewardship. Issues related to interoperability, governance, engagement
of patients and the general population, and privacy and security concerns
resulting from the collection and use of health information will need to be
better addressed for successful progress toward a learning health system.
Given these challenges, workshop proceedings included the consideration
of a number of different cases studies of innovative approaches from both
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INTRODUCTION
within and outside the healthcare space to inform participants’ consider-
ations of the challenges ahead. These case studies are included in their en-
tirety in Appendix B and summarized in boxes in several places throughout
this introductory chapter. Two of those cases drawn from outside health
care were VISA and Consumer Energy.
VISA was introduced as an example of an innovative approach to the
governance of a highly decentralized network of service providers. Through
the leadership of Dee Hock, a system based on a minimal set of core stan-
dards that maximized peripheral autonomy was created. The principles of
this approach—which include maximizing human ingenuity, shared clarity
on the purpose and principles of the group, pushing all possible operations
to the periphery, and fostering and tolerating evolution—were specifically
highlighted as important for consideration.
Consumer Energy’s work in the Smart Grid Initiative was used to il-
lustrate a systematic approach to implementation of a complex systems
development project of nationwide scale. This approach, based on the
ultra-large-scale (ULS) system principles, includes applying an engineering
approach to accommodate and network a wide variety of legacy nodes
while allowing for continuous expansion and evolution without the use of
a comprehensive internal design or rigid standardization. The Smart Grid
case is summarized in Box 1-3 and the full written description is included
in Appendix B.
Regardless of the model, a key rationale for workshop discussions was
the reality that effective and efficient progress in the growth and develop-
ment of our national and global digital health infrastructure requires active
cooperation, collaboration, and role delineation among many organiza-
tions, companies, and agencies—private and public—at the cutting edge of
using HIT for improving health and health care.
Federal and State Governments
At the national level, stewardship of the digital health infrastructure
has fallen primarily to the federal government. ONC was created in 2004
in the U.S. Department of Health and Human Services (HHS) to stimulate
progress in the field by providing leadership, policy coordination, stra-
tegic planning, and infrastructure development for the adoption of HIT.
Since 2009, with the enactment of the Health Information Technology
for Economic and Clinical Health Act (HITECH) as part of the American
Recovery and Reinvestment Act, the federal government leadership profile
has become especially prominent. The principal goals of HITECH are to
build approval for HIT adoption and meaningful use; increase patient and
provider participation in electronic health information exchange; educate
the public about the uses of personal health information and privacy and
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62 ENGINEERING A LEARNING HEALTHCARE SYSTEM
BOX 1-3
Case: The Smart Grid
The Smart Grid is a long-term, complex systems development project using
an engineering approach to accommodate a wide variety of legacy nodes that are
organic—constantly growing and evolving, much like a biological system. This con-
tinuous evolution allows the Smart Grid’s architecture to preserve and encourage
the capacity of each node to innovate locally and deal with complexity in a way
that suits local and grid needs. As conceived, the Smart Grid will
• Enable active participation by consumers
• Accommodate all generation and storage options
• Enable new products, services, and markets
• Provide power equality for the digital economy
• Optimize asset utilization and operate efficiently
• Anticipate and respond to system disturbances (self-heal)
• Operate resiliently against attack and natural disaster
Because there is no need for consensus among the nodes on how they
should operate within local boundaries, the Smart Grid development methodology
is not based on comprehensive internal design and operating standards for each
node on the Grid to follow. Instead, the approach accommodates highly diverse
nodes connecting to the Smart Grid using open data translation protocols that
standardize information management, rather than using the internal workings of
each node. The Grid becomes a communications bus to which each node must
be able to write, and from which each node must be able to read. This architecture
preserves capacities for local operating autonomy and innovation throughout the
Smart Grid. It also manages a standardized communications capacity among
complex, and otherwise noninteroperable, legacy nodes on the Grid. These fea-
tures are all characteristics of ultra-large-scale software-intensive systems.
security protections available to them; and use a comprehensive, integrated
approach to successfully communicate about privacy, security, and mean-
ingful use to target audiences. Meeting these goals has come with the com-
mitment of unprecedented resources administered through the leadership of
ONC. Implementation of HITECH by ONC has been done with the aid of
two federal advisory committees made up of representatives from across all
HIT stakeholder areas, the HIT Policy Committee and the HIT Standards
Committee. The committees have guided ONC’s work on meaningful use,
certification and adoption, information exchange, strategic planning, pri-
vacy and security, and enrollment.
Under HITECH, ONC was granted $2 billion to facilitate the adop-
tion and meaningful use of HIT. In addition, an estimated $27 billion was
designated for the Centers for Medicare & Medicaid Services (CMS) to be
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INTRODUCTION
distributed as incentive payments for physicians and hospitals to become
meaningful users of HIT. Designed as a set of staged requirements to qualify
for CMS incentive payments, the first-stage elements of “meaningful use”
were released by CMS on July 13, 2010. These established a core set of
requirements for eligible professionals and hospitals, as well as a menu of
additional choices, from which five are to be chosen. The stage 1 meaning-
ful use target elements are listed in summary fashion in Box 1-4, and details
are contained in Appendix D. The subsequent stages of meaningful use are
currently under development and are presented in Chapter 10, along with
an indication of related issues flagged in workshop discussions.
In addition to the meaningful use requirements, ONC has funded a series
of grant programs through HITECH such as the Beacon Community grants
(aimed at demonstrating community-wide digital infrastructure capacity and
use for health improvement) and the Strategic Health Information Technol-
ogy Advanced Research Projects Program (aimed at fostering the capture of
technological advances to improve system performance). At the broader level,
ONC is pursuing a series of initiatives to foster health information exchange
among stakeholders under the Nationwide Health Information Network.
Several additional HHS agencies have activities important to the de-
velopment of the digital infrastructure for the learning health system. CMS
has had primary responsibility for establishing rules for meaningful use
and requirements for uniform condition identifiers central to healthcare
payment and research. Additionally, the passage of the Affordable Care
Act (ACA) created the $10 billion Center for Medicare and Medicaid
Innovation (CMMI). CMMI will test innovative payment and program
service delivery methods, many of which will rely on robust information
technology systems.
Within the National Institutes of Health (NIH), the National Library
of Medicine (NLM) serves as the central coordinating body for clinical
terminology standards. In addition, NLM also supports a number of HIT
system development tools—in areas such as language and knowledge pro-
cessing—and offers grant programs in HIT education and training. The
NIH Clinical and Translational Science Awards Program provides funding
for a consortium of organizations to facilitate collaborative research and
speed the adoption of clinical research results in the clinic including sup-
porting the development and use of innovative technologies by individual
grantee organizations. Additionally, the National Cancer Institute has a
number of initiatives that serve as key contributors to building the capacity
to derive scientific discovery from patient care. Among these are the Enter-
prise Vocabulary Services which provide controlled terminology and ontol-
ogy services for use by researchers, and the cancer Biomedical Informatics
Grid (caBIG®) which is designed to improve care and accelerate scientific
discoveries by enabling the collection and analysis of large amounts of
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64 ENGINEERING A LEARNING HEALTHCARE SYSTEM
BOX 1-4
Meaningful Use Requirement Categories
Core structured personal data (age, sex, ethnicity, smoking status)
Core list of active problems and diagnoses
Core structured clinical data (vital signs, meds, [labs])
Outpatient medications electronically prescribed
Automated medication safeguard/reconciliation
Clinical decision support
Care coordination support/interoperability
Visit-specific information to patients
Automated patient reminders
e-Record patient access (copy or patient portal)
Embedded measures for clinical quality reporting
Security safeguards
Examples of optional elements:
Advance directives for ages >65
Condition-specific data retrieval capacity
Public health reporting (reportable conditions)
SOURCE: Adapted from Blumenthal and Tavenner (2010). See Appendix D for details.
biological and clinical information (see Box 1-5 and Appendix B for addi-
tional information).
Through its National Resource Center for Health IT and initiatives on
patient registries, the Agency for Healthcare Research and Quality (AHRQ)
supports a number of programs to advance the digital utility for healthcare
quality and safety. Currently these programs are focused on the areas of
support for HIT program management, guidance, assessment, and plan-
ning; HIT technical assistance, content development, and program-related
projects and studies; HIT dissemination, communication, and marketing;
and HIT portal infrastructure management and website design and usability
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INTRODUCTION
BOX 1-5
Case: The National Cancer Institute’s caBIG® Initiative
The National Cancer Institute of the National Institutes of Health has devel-
oped an informatics program designed to improve patient care and accelerate
scientific discoveries by enabling the collection and analysis of large amounts of
biological and clinical information and facilitating connectivity and collaboration
among biomedical researchers and organizations. More than 700 different orga-
nizations are actively engaged in caBIG®, including basic and clinical researchers,
consumers, physicians, advocates, software architects and developers, bioinfor-
matics specialists and executives from academe, medical centers, government,
and commercial software, pharmaceutical, and biotechnology companies from the
United States and in 15+ countries around the globe.
At the heart of the caBIG® program is caGrid, a model-driven, service-
oriented architecture that provides standards-based core “services,” tools, and
interfaces so the community can connect to share data and analyses efficiently
and securely. More than 120 organizations are connected to caGrid. In partnership
with the American Society of Clincal Oncology, caBIG® is developing specifica-
tions and services to support oncology-extended EHRs that are being deployed
in community practice and hospital settings. caBIG® tools and technology are
also being used by researchers working on cardiovascular health, arthritis, and
AIDS. In addition, pilot projects have successfully connected caGrid to other net-
works, including the Nationwide Health Information Network, the CardioVascular
Research Grid, and the computational network TeraGrid.
support. AHRQ also supports the National Guideline Clearinghouse which
provides healthcare institutions, providers, and researchers access to objec-
tive, detailed information on clinical practice guidelines.
At the Food and Drug Administration (FDA), the Sentinel Initiative (see
Box 1-6 and Appendix B) has been designed to build and implement a na-
tional electronic system for postmarket surveillance of approved drugs and
other medical products. A smaller working pilot of the Sentinel system has
been developed, under contract from the FDA, by Harvard Pilgrim Health
Care to test epidemiological and statistical methodologies on distributed
data sources.
As the federal focal point for programs in public health, the Centers
for Disease Control and Prevention have supported several major HIT-
anchored programs including the surveillance programs BioSense, EPI-X,
and the National Healthcare Safety Network. The Health Resources and
Services Administration, as the primary federal agency for improving access
to healthcare services for the uninsured, isolated, or medically vulnerable,
supports a portfolio of HIT programs aimed at improving care access and
coordination for underserved populations and those in rural areas.
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66 ENGINEERING A LEARNING HEALTHCARE SYSTEM
BOX 1-6
Case: The FDA’s Sentinel Initiative
In 2008, the Department of Health and Human Services and the Food
and Drug Administration (FDA) announced the launch of FDA’s Sentinel Initia-
tive, a long-term program designed to build and implement a national electronic
s
ystem—the Sentinel System—for monitoring the safety of FDA-approved drugs
and other medical products. Data partners in the Sentinel System will include
organizations such as academic medical centers, healthcare systems, and health
insurance companies. As currently envisioned, participating data partners will
access, maintain, and protect their respective data, functioning as part of a “dis-
tributed system.”
In a related pilot activity, FDA is working with Harvard Pilgrim Health Care,
Inc. to develop a smaller working version of the future Sentinel System, dubbed
“Mini-Sentinel.” Through this pilot, FDA will learn more about some of the barriers
and challenges, both internal and external, to establishing a Sentinel System for
medical product safety monitoring. The Mini-Sentinel Coordinating Center (MSCC)
represents a consortium of more than 20 collaborating institutions, working with
participating data partners to use a common data model as the basis for their ap-
proach. Data partners transform their data into a standardized format, based upon
which the MSCC will write a single analytical software program for a given safety
question and provide it to each of the data partners. Each partner will conduct
analyses behind its existing, secure firewall, and send only summary results to
the MSCC for aggregation and further evaluation.
As this pilot is being implemented, a governance structure is being devel-
oped to ensure that the activity encourages broad collaboration within appropri-
ate guidelines for the conduct of public health surveillance activities. In order to
accomplish that, the MSCC is developing a Statement of Principles and Policies
that will include descriptions of the organizational structure and policies related
to communication, privacy, confidentiality, data usage, conflicts of interest, and
intellectual property.
Efforts to promote the development, implementation, and widespread
adoption of HIT also build on a wide array of digital learning leadership
efforts by other federal agencies. In particular, important contributions stem
from responsibilities and activities of the VHA and the Department of De-
fense (DOD). The Telemedicine and Advanced Technology Research Center
is a joint program between DOD and the VHA to promote research and
applications in health informatics, telemedicine, and mobile health moni-
toring systems. Additionally, the DOD and VHA are working together to
create a Virtual Lifetime Electronic Record to allow for seamless availability
of healthcare, benefits, and services information for service members from
enlistment to death. Additional efforts include defining a plan for HIT in
the Federal Communications Commission’s National Broadband Plan, and
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INTRODUCTION
the National Science Foundation’s Smart Health and Wellbeing initiative.
Because of the deep and broad set of capabilities and initiatives collectively
sponsored by federal agencies, their coordination and interface with private
sector activities offer a vital strategic opportunity to accelerate the learning
health system’s development.
Testament to the compelling priority of the prospects, in December
2010 the President’s Council of Advisors on Science and Technology
(PCAST) issued its report, Realizing the Full Potential of Health Informa-
tion Technology to Improve Healthcare for Americans: The Path Forward
(PCAST, 2010). The PCAST report examines the opportunities and needs
for the use of HIT to improve healthcare quality and reduce cost, as well
as the activities and alignments of current federal programs with relevant
responsibilities. It sets out a series of recommendations intended to facilitate
private, entrepreneurial initiatives through governmental action to speed
development of a “universal exchange language” for health information,
the application of which would maximize the ability to use existing and
developing electronic record systems. Specifically, it recommends action by
the federal government—especially ONC and CMS—accelerate the iden-
tification of standards required for health information exchange using
metadata-tagged data elements, map various existing semantic taxonomies
onto the tagged elements, develop incentives for product use of tagged ele-
ments; foster use of metadata for security and safety protocols, bring federal
program capacity and policy leverage to bear in implementing and guiding
the efforts, and develop metrics to assess progress. The PCAST recommen-
dations are included in Appendix E.
ABOUT THE DIGITAL INFRASTRUCTURE MEETINGS
As indicated by the title of this report, the primary intent of the meet-
ings was to identify and explore strategic opportunities for accelerating the
evolution of a digital infrastructure necessary to support and drive con-
tinuous assessment, learning, and improvement in health and health care.
Three meetings were held in the summer and fall of 2010, bringing together
researchers, computer scientists, privacy experts, clinicians, healthcare ad-
ministrators, HIT professionals, representatives of patient advocacy groups,
healthcare policy makers, and other stakeholders.
A planning committee,1 composed of leading authorities on various
aspects of the digital health learning process, established the main objectives
for the workshop series. The series began by fostering a shared understand-
1 Institute of Medicine planning committees are solely responsible for organizing the
workshop, identifying topics, and choosing speakers. The responsibility for the published
workshop summary rests with the workshop rapporteurs and the institution.
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68 ENGINEERING A LEARNING HEALTHCARE SYSTEM
ing of the vision for the digital infrastructure for continuous learning and
quality-driven health and healthcare programs by building on the existing
foundations of HIT. Following the establishment of a vision, participants
explored the current capacity, approaches, incentives, and policies and
identified key technological, organizational, policy, and implementation
priorities for the development of the digital infrastructure. Finally, partici-
pants considered strategy elements and priorities for accelerating progress
on building a more seamless learning enterprise that will improve the health
and health care of Americans.
Several contextual considerations informed the Committee’s develop-
ment of the agenda. These included rapid developments in information
technology that promise to facilitate exponentially the potential of health
data for knowledge generation and care improvement—these developments
include federated and distributed research approaches that allow data to
remain local while enabling querying and virtual pooling across systems,
as well as ongoing innovation in search technologies with the potential to
accelerate use of available data from multiple sources for new insights.
Accordingly, considerations included developing standards that will fa-
cilitate distributed access to large datasets for comparative effectiveness
research, biomarker validation, disease modeling, and improving research
processes. This technological promise, coupled with policy initiatives like
HITECH and the ACA that encourage the digital capture and storage of
health data, provide starting points, incentives, and guidance, while encour-
aging innovation. Additionally, the committee considered the coevolving re-
quirement for governance policies that foster strengthening the data utility
as a core resource to advance the common good; in particular by cultivating
the trust fabric among stakeholders and accelerating collaborative prog-
ress. Hand in hand with these were practical considerations including the
increasing appreciation of the need to limit the burden of health data collec-
tion to the issues most important to patient care and knowledge generation.
The three workshops in the series progressed from a broad explora-
tion of the state of play and various stakeholder perspectives on a learning
health system, to a more specific identification of strategic approaches to
components of the challenge, and concluded with detailed discussions of
strategic elements, stakeholder responsibilities, and key crosscutting chal-
lenges. To maximize the identification and sharing of perspectives, expert
presentations were followed by open discussion among participants and
separate small group discussion sessions were incorporated in all of the
workshops.
The first workshop, “Opportunities, Challenges, Priorities,” consid-
ered the overall vision of the digital infrastructure for the learning health
system as well as some of the prominent issues and opportunities related
to technical progress, ensuring commitment to population and patient
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INTRODUCTION
needs, development of the necessary trust fabric, stewardship and gover-
nance, and the implications of a global character of the health data trust.
These presentations are captured in the speaker-authored manuscripts in
Chapters 2 through 8. The second meeting, “The System After Next,”
went deeper into three cross cutting areas identified during the first work-
shop: engaging the patient and population, promoting technical advances,
and fostering stewardship and governance structures. The third and final
meeting of the series, “Strategy Scenarios,” reviewed the common themes
and information from the previous workshops and extended into deeper
consideration of strategy elements, opportunities, responsibilities, and next
steps for progress on four key focus areas: technical progress, knowledge
generation and use, patient and population engagement, and governance.
An integrated summary of the discussions during the second and third meet-
ings is captured in Chapters 9 and 10.
Collectively, the discussions captured in this publication represent un-
precedented promise for innovation and progress in health and health care.
Yet, the discussions also underscored that without successful efforts to cre-
ate the conditions necessary for seamless interoperability, to build the pro-
tocols for enhanced access and use of available information for knowledge
generation, and to nurture a culture of engagement and support on behalf
of the sort of information utility possible, the potential will go unmet. By
thoroughly and candidly engaging in discussions on the vision, the current
state of the system, the key priorities for future work, and the strategic
elements for accelerating progress, participants have set in motion perspec-
tives that can quicken the progress in building the digital infrastructure
required for the continuously learning health system necessary to ensure
better health for all.
REFERENCES
Blumenthal, D., and M. Tavenner. 2010. The “meaningful use” regulation for electronic health
records. New England Journal of Medicine 363(6):501-504.
CHCF (California HealthCare Foundation). 2010. New national survey finds personal health
records motivate consumers to improve their health. http://www.chcf.org/media/press-
releases/2010/new-national-survey-finds-personal-health-records-motivate-consumers-to-
improve-their-health#ixzz12kT8FU00 (accessed October 18, 2010).
DesRoches, C. M., E. G. Campbell, S. R. Rao, K. Donelan, T. G. Ferris, A. Jha, R. Kaushal,
D. E. Levy, S. Rosenbaum, A. E. Shields, and D. Blumenthal. 2008. Electronic health
records in ambulatory care—a national survey of physicians. New England Journal of
Medicine 359(1):50-60.
Fox, S. 2010. E-patients, cyberchondriacs, and why we should stop calling names. http://
www.pewinternet.org/Commentary/2010/August/Epatients-Cyberchondriacs.aspx (ac-
cessed October 19, 2010).
IOM (Institute of Medicine). 2001. Crossing the quality chasm: A new health system for the
21st century. Washington, DC: National Academy Press.
OCR for page 70
70 ENGINEERING A LEARNING HEALTHCARE SYSTEM
———. 2007. The learning healthcare system: Workshop summary. Washington, DC: The
National Academies Press.
Jha, A. K., C. M. DesRoches, P. D. Kralovec, and M. S. Joshi. 2010. A progress report on
electronic health records in U.S. hospitals. Health Affairs (Millwood) 29(10):1951-1957.
Smith, A. 2010. Mobile access 2010. http://www.pewinternet.org/Reports/2010/Mobile-
Access-2010.aspx (accessed October 19, 2010).
