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9
Growing the Digital Health
Infrastructure
INTRODUCTION
Drawing on the collective expertise represented in the presentations
and discussions of the first workshop, in the two subsequent workshops
participants focused on four crosscutting priority domains: promoting tech-
nical advances and innovation, knowledge generation and use, engaging
patients and the population, and fostering stewardship and governance.
Encouraged to give due consideration to “out of the box” approaches and
to use examples from health and nonhealth fields to illustrate and test key
needs and opportunities through small group sessions, participants identi-
fied and presented for discussion a number of strategic elements important
to progress in each domain. They are included in Box 9-1 and described in
more detail in the sections below.
Participants called out a number of elements for consideration sur-
rounding the strategic opportunities for technical progress. They included
the need to address health as a complex sociotechnical system and therefore
apply an approach that addresses both characteristics. Discussions noted
the need to focus strategic thinking around the functionalities desired by
such a system, including the ability to produce a complete longitudinal pa-
tient record at the point of care and the ability to use records for research
purposes. Participants cautioned of the importance of taking a parsimoni-
ous approach to systems specifications and suggested one that tolerated the
use of “dirty data” with context maintenance as a starting point. Usability
was discussed as an important strategic consideration, and the need to ad-
dress workflow integration as a crucial component of this consideration.
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BOX 9-1
Strategic Elements
TECHNICAL PROGRESS . . . activities that advance:
• Ultra-large-scale system perspective
• Functionality focus
• System specifications/interoperability
• Workflow and usability
• Security and privacy safeguards
• System innovation
KNOWLEDGE GENERATION AND USE . . . activities that advance:
• Shared learning environment
• Point of decision support and guidance
• Research-ready records for data reuse
• Patient-generated data
• Integration and use of data across sources
• Distributed data repositories
• Sentinel indicators
• Query capacity
• Analytic tools and methods innovation
PATIENT AND POPULATION ENGAGEMENT . . . activities that advance:
• Value proposition and patient confidence
• Shared learning culture
• Patient-clinician outcomes partnerships
• Person-centric, lay-oriented health information access
• Closing the disparity gap
• Continuous evaluation
GOVERNANCE . . . activities that advance:
• The vision
• Guiding principles
• Participant roles and responsibilities
• Process and protocol stewardship
• Implementation phasing
• Continuous evaluation
Attention to the technical aspects of security and privacy concerns were
highlighted as major contributors to the building of trust among system
stakeholders. Finally, the need to drive continuous innovation of technical
approaches through constant testing and refinement and the creation of a
supporting multidisciplinary research ecosystem were suggested.
Discussion of the strategic elements needing attention for the creation
of a robust knowledge generation and use engine for the learning health
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system encompassed issues ranging from cultural changes to the need for
innovative methods development. Workshop participants suggested that a
learning health system would not be possible without patients and clini-
cians buying into a shared learning culture. Consideration of approaches to
facilitate the use of clinical records for research, such as the identification
of core research-related components, was also discussed. Leveraging the full
potential of health information by including sources other than just clini-
cal records—such as patient-generated data and nonmedical health-related
data—was discussed as an important strategic element. Finally, participants
stressed the need to better develop innovative analytical methods to use dis-
tributed data repositories in order to address security and privacy concerns.
Maximally leveraging the digital infrastructure to better engage patients
and the population in health was another principal focus of the discussions.
Conveying the value proposition for stakeholder participation and cre-
ation of a shared learning culture among patients and the population were
prominent themes. Participants discussed using the digital infrastructure to
strengthen patient–clinician outcome partnerships through better patient
portals and increased availability of lay-oriented, user-friendly clinical and
nonmedical health data. Participants highlighted the need to call out the
opportunity presented by a learning health system to aid in the elimination
of health disparities and the role that a digital infrastructure could play to
that end. Finally, the need for constant improvement through evaluation
and innovation was discussed as an important component of an approach
to patient and population engagement.
Explorations of the possible approaches to governance of the digital
infrastructure for the learning health system were approached through the
ultra-large-scale (ULS) lens, and drew from examples outside health care.
Beginning with a discussion of the need to set a vision as a reference point
for progress, participants explored the need to work toward identifying
a minimal set of guiding principles to meet this vision while allowing for
autonomy and innovation. Participant roles and responsibilities as well as
delineation of the processes and protocols to be managed in support of the
core learning functionalities were also identified as important components
of a strategic plan. Finally, the incorporation of continuous evaluation and
improvement in the approach to governance was also highlighted.
TECHNICAL PROGRESS
A ULS system is complex, constantly growing, and evolving, much
like an organic, biological ecosystem. The digital infrastructure needed to
support the U.S. healthcare system can be classified as a ULS system given
its enormous scale including the numbers of agents, lines of code, and ever-
expanding diverse sources of data; the preponderance of legacy systems that
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must be incorporated; the local nature of health care and the corresponding
requirement that each institution have autonomy; the specific regulatory,
legal, and social requirements that must be met; and the understanding
that it is too complex to be subject to effective central control. Introduced
to the digital health information conversation by colleagues from the com-
puter science field, hallmarks of a ULS system include preservation of local
autonomy through decentralization of data, development, and operational
authority. This allows for local innovation, personalization, and emergent
behaviors without requiring consensus from all nodes. In discussions fo-
cused on developing a set of strategic scenarios for technical progress, the
ULS system approach emerged as an appropriate framework since it would
allow for empowerment through knowledge and control of health and
health information; support a broad diversity of data sources and processes;
support evolution and change; contain minimal, extensible standards; and
leverage past work toward long-term goals.
In discussing the implications and issues surrounding this approach,
participants identified the relevance and appeal of the engineering approach
to health care—systems analyses, design, implementation, and evaluation
plans—inherent to the ULS system perspective. Specifically, they noted the
potential of a collaborative effort between the computer science and health
information technology (HIT) communities to develop a deliberate and
systematic engineering analysis—characterized by iterative testing and de-
velopment of prototypes—to set technical and sociotechnical system goals,
requirements, specifications, and architecture. This could be supported by
a multidisciplinary research community, armed with clarified terminology
for ease of collaboration, and with participation from a wide array of both
private and public stakeholders (computer science, health informatics, law,
policy, ethics, etc.). Similarly, workshop participants stressed the need for
technical policies that support experimentation and innovation and allow
for the progressive adoption and evolution of system requirements, specifi-
cations, and architecture choices.
Participants pointed to a focus on functionalities consistent with ULS
systems, and their application to the digital health system, as a poten-
tial starting point in advancing the ULS approach. Definition of the ULS
principles and characteristics that support learning system functionalities,
including the feedback and feedforward nature of the learning engine, such
as identification strategies, privacy controls, the availability of a complete
longitudinal record at the point of care, inferential capacity, and research-
readiness, were highlighted as critical foundational steps in the development
of this technical enterprise. Noted as similarly important to system func-
tionality was the mechanism for developing and maintaining an approach
to information structure, classification, and storage.
Promoting these targeted functionalities requires advancing parsimoni-
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ous system specifications and interoperability. Discussions centered on the
need to specify the minimum set of standards to allow for partial interop-
erability. A focus on semantic comparability, maintenance of context and
provenance, architectural consistency, and transportability were discussed
as potential starting points. In congruence with the priorities laid out sub-
sequently in the PCAST report (see Appendix E), particular attention was
paid to the use of metadata to facilitate interoperability and information
exchange—including to maintain data context and provenance, authentica-
tion, and privacy. This, in concert with a fast-prototyping component, can
allow for incremental specification and system growth with the opportunity
for functional enhancement, such as refinement of semantic interoperability,
to meet specific requirements depending on use.
Part and parcel with the need to address the technical specifications
of the digital utility for the learning health system is consideration for
how these interface with users. Considerations for workflow integration
were discussed by workshop participants as important to ensure that the
technology is not only innovative and useful but also useable. To date,
this disjuncture between established workflow patterns and an unfamiliar,
often awkward, overlay of HIT tools has proved a substantial barrier to
adoption.
Security and privacy safeguards were an important consideration in all
areas of discussion. Participants often pointed to a lack of trust as being
one of the major impediments to health information exchange. Therefore,
attendance to the technical aspects of these issues was emphasized as a
crucial part of building trust among stakeholders. Discussions and pre-
sentations (see Foster, Chapter 5, and Solomonides, Chapter 8) described
technical approaches such as attribute-based authorization and distributed
identity management, and provided examples of how they could be de-
ployed to address these concerns and achieve a state of secure data liquidity.
Additionally, innovations around data security and privacy in alternative
environments such as hosted, web-based systems were suggested in order
to build capacity.
Finally, the need for continuous innovation was a recurring theme in
technical discussions. Participants suggested strategies such as creating a
test-bed network for assessment of innovative system functionalities, the
use of challenge problems to test ULS system issues and opportunities, and
the cultivation of interdisciplinary research initiatives among academic,
industry, and government stakeholders.
KNOWLEDGE GENERATION AND USE
Discussions of the generation and use of knowledge fell into three
areas: the availability and capture of reliable data, the tools to analyze the
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data, and seamless feedback of knowledge to the system. Research, quality
improvement initiatives, and public health surveillance efforts are all ex-
amples of uses and drivers for these learning-associated processes.
A necessary precondition for successful progress on any of these
dimensions is a shared learning environment. Technical advances and
innovative research methods make it possible to bring clinical research
and clinical practice much closer together. However, it was noted that
the ability to take advantage of that opportunity depends on a health-
care culture in which both patients and clinicians are compelled by the
prospects of clinical data to improve understanding, care delivery, and
outcomes as well as provide reliable, just-in-time information to assist
decision making. For these reasons, participants highlighted the need for
a learning environment that is supported, shared, and nurtured by both
patients and clinicians.
Several tools and approaches currently exist to provide point-of-
decision support and guidance. In the face of the number of interacting
factors, competing priorities, and an ever-growing set of diagnostic and
therapeutic options, “best practice” can only be a theoretical notion with-
out the ability to bring the best available information to the decision pro-
cess. On the other hand, it was noted that reminders and decision prompts
not successfully engineered into natural workflow patterns will be little
more than ignored distractions. Consequently, approaches are needed to
better marshal reliable clinical information and guidelines in time, form,
and content that is seamlessly accessed and used by clinicians and patients.
Participants identified a number of needs to be addressed in order
for the digital health infrastructure to reach its full potential as a source
of real-time clinical research insights. For example, clinical research ac-
tivities require enlisting clinician support and involvement in research-
ready clinical records on both quality and content dimensions for reuse in
knowledge generation. The identification of a limited set of standardized
core research-related components as basic elements across vendors and
systems was one suggestion to facilitate individual and cooperative clinical
research activities as well as sentinel event surveillance. Concerns over the
reliability and heterogeneity of data in clinical records were underscored
as an important rate-limiting factor for both quality of care and clinical
research activities, again highlighting the importance of the mechanisms
for information structure, classification, and storage. This is particularly
important for repurposing data collected for other uses, such as Food
and Drug Administration (FDA) clinical trial–associated data, in order to
maximally leverage efforts and investments already in place.
Discussions on the increased utility of clinical records for research
went hand in hand with those on the need to take advantage of informa-
tion from patients and other sources. Patient-generated data can provide
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a level of context that is impossible to capture through more traditional
data collection methods. Initiatives to better develop, test, and improve the
capture and use of these data so that they can be used to support research,
quality improvement, public reporting, and patient care were suggested as
priorities.
Similarly, efforts to promote the integration and use of data across
various sources—clinical, public health, commercial—were emphasized as
central to effectively leveraging the full range of information for progress
in improving efforts aimed at populations as well as individuals. Included
in this, and considered with a longer term vision, were growing informa-
tion sources outside of “mainstream” health care, such as online forums
and communities. In order for such proposals to be successful, it was noted
that protocols must be developed to build interoperability as a natural and
seamless element of data sources.
Storage and aggregation of data for the purpose of analysis and knowl-
edge generation have been problematic given the security and privacy issues
they entail. Discussions of current and ongoing efforts in the creation of
distributed data repositories, such as those being used in FDA’s Sentinel
Initiative and the HMO Research Network, suggest a promising approach.
Coordination between these ongoing efforts, additional support and incen-
tives for their use for clinical research activities, and the support of coor-
dinated intervention-specific patient registries were discussed as potential
approaches moving forward. Prospects for the use of scalable, distributed,
hosted, storage solutions—such as those used by Amazon—were also noted
as promising future directions. These discussions, however, were often
punctuated with caution around privacy and security, components that
participants felt needed further exploration and development.
Finally, considerable attention was paid to the development of methods,
tools, and query capacity for the generation of knowledge needed to sustain
a digital learning health system. In line with the ULS system architecture
approach, and the creation and support of distributed data repositories, the
development of capacity for national, distributed query-based research—
including the ability to identify and track sentinel events and indicators—
was identified as a strategic priority. To support this, and the continuing
development and innovation around other analytical approaches, the im-
portance of collaborative interdisciplinary networks of researchers was
underscored. This was discussed not only for cooperative studies, but for
cooperative engagement of issues such as strategies on consistent identifiers
for patients, the use of modeling and simulation for knowledge generation,
evaluation of approaches for the use of diverse data types and varying data
quality, and development of methods for the use of information from mo-
bile consumer devices and patient-generated data.
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PATIENT AND POPULATION ENGAGEMENT
Discussions on the roles of patients and the public in growing the digi-
tal infrastructure for the learning health system were anchored strongly in
the concept of reengineering the care culture to ensure the centrality of the
individual patient in the care process—a concept underscored in the Quality
Chasm report (IOM, 2001) that remains elusive. Signs of change are only
beginning to appear as appreciation increases for the use of web-based in-
formation and the clinical and outcome advantages of a patient who is bet-
ter informed and more involved. Often referenced in the discussions was the
need for the establishment of a “new norm” around engaging patients and
the population in health—both theirs and that of the population—through
the use of the digital infrastructure. Basic to this “re-norming” is a deep-
ened appreciation by patients and the general population for the personal
and public benefits that are likely to occur, as well as a strong measure of
confidence in the security of the system.
The value proposition must be apparent to the stakeholders. Commu-
nication of the value of a digital health infrastructure in the improvement
of care coordination, quality, and, ultimately, the health of the population
at large, was identified in workshop discussions as a fundamental priority.
Furthermore, participants pointed out that, in order to be successful, the
value proposition should be approached in the context of transparent con-
versations about privacy, security, and other impeding concerns. The use
of case studies and quantitative assessments of the contribution of HIT to
improved patient experiences and outcomes was discussed as a potential
starting point.
A common theme across several workshop discussions was the value
in fostering a shared learning culture among system stakeholders—in par-
ticular, a culture that recognizes the unique contributions that patients and
the general population can make to the learning system as collaborators,
not subjects. Activities that foster patient involvement in and support
of knowledge generation, including illustrating the importance of patient
preference information to improving care, were discussed as potential ap-
proaches to this issue.
Following the theme of “renorming” participation of patients and
the population in health improvement, and building on the framework
established by previous Institute of Medicine work in this area, discussions
of the opportunity for strengthening patient–clinician outcome partner-
ships through the digital infrastructure were discussed. The development
of templates and protocols that support the use of HIT to engage patients
in decision making as well as tools for more effective provider–patient
communication were proposed. An important element in this respect is
providing patients with secure access to and control of their health infor-
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mation. This includes further development of patient portals, building on
technologies already widely accepted by consumers, and supporting efforts
for increased information liquidity and control such as the Veterans Health
Administration/Centers for Medicare & Medicaid Services Blue Button
initiative.
In concert with these efforts, participants discussed the need to increase
the availability and access to lay-oriented, user-friendly clinical and non-
medical health information. Investing in templates for form and content of
information for the lay consumer, as well as gathering patient-derived data
for care and delivery improvement were suggested as areas of focus. Indeed,
the “new norm” was discussed as involving a focus on improving patients’
health, not just health care, by emphasizing health maintenance as a lifelong
process that includes a patient’s actions and decisions outside of the clinical
care setting. To this end, participants proposed providing individuals with
useful information concerning their clinical encounters and the relevant
state of evidence, as well as giving them more responsibility for utilizing
this information in their own decision making.
HIT provides an opportunity for engaging populations not historically
well served by the traditional healthcare community. For this reason, the
potential of the digital health utility in the elimination of health disparities
was discussed as a strategic priority for further attention and action. The
impact of facilitating patient and population contribution to, and control
of, their health information has the potential to address disparities in un-
derserved populations.
The importance of a component of continuous evaluation and improve-
ment in efforts for patient and population engagement in the digital health
learning system was again emphasized. Areas of focus that were highlighted
include ongoing assessment of patient preferences for use in tailoring of
health plans, innovative approaches to confidentiality and privacy issues,
and assessments of opportunities to use contemporary sociotechnical ap-
proaches (e.g., social networking and smart phones) for patient and popu-
lation engagement.
GOVERNANCE
Discussions of governance strategies for the digital infrastructure for
the learning health system focused on facilitating activities to advance some
very basic components and principles of the ULS digital health informa-
tion system. Participants often struggled with the question “what are we
proposing to govern?” and certainly the health information system as it
exists now does not easily fit into most established governance models. On
the other hand, upon applying the ULS lens to this issue, and consider-
ing innovative governance approaches in cases outside of health (such as
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VISA and the Smart GRID, see Appendix B for more information), certain
governance-related strategic elements emerged. Participants often pointed
to the example of the Internet Engineering Task Force as one example of
a governance approach that, while created under different circumstances,
reflects many of the same governing principles.
Of principal concern is the issue of the vision. As a means of establish-
ing a reference point for progress, workshop participants articulated the
need for work to establish a shared vision of the digital health utility for
the learning health system. Prospective components noted for this vision
include expectations, guiding principles, modus operandi, and an apprecia-
tion for the global perspective. Considerations of the differences between
a structure that governs versus one that provides guidance were included
in these discussions.
Participants noted that a governance model in line with the ULS ap-
proach would be one that identified and depended on a minimal set of
guiding principles with which all stakeholders must comport, maximizing
local autonomy over all other decisions. Tolerance of change and adapt-
ability were additional characteristics that participants felt were impor-
tant to incorporate. Exploring the most decentralized level at which these
standards might be delegated and focusing standards on major functional
requirements were proposed as starting points. Additionally, the importance
of tailoring the governance approach to the local situation and needs was
emphasized. A focus on the ability to use an inclusive (both/and) rather
than a deterministic (either/or) approach was discussed as a foundational
principle that encapsulated this thinking. A related issue discussed was
the broader context of the governance enterprise. Participants discussed
the need to include societal values such as trust, privacy, and fairness; fair
information practices such as transparency and data collection and use limi-
tations; goals of the health sector to improve quality of care and enhance
clinical knowledge; technical concepts such as innovation; and economic
aspects such as promoting efficiency and reducing costs.
Possible participant roles and responsibilities in the governance struc-
ture were identified as an important early step, and different approaches
were considered. These included broad participation by all stakeholders,
which was pointed out to be logistically very difficult; very narrow partici-
pation, which participants felt was unlikely to be successful; or a hybrid
model, that incorporated both broad and narrow participation depending
on the needs at that particular level. Some participants noted that multiple
layers of governance were likely to be required to address concerns at the
appropriate level whether local, regional, national, or international.
Several approaches to the establishment of a governance model were
considered and discussed by workshop participants. Leveraging lessons
through collaborative discussions among ongoing efforts—at both the na-
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tional and local levels—and establishing a working group to begin collect-
ing initial input were suggested as starting points. To enhance the efficiency
of deliberative efforts, participants suggested coordinating these activities,
potentially through the Office of the National Coordinator for Health In-
formation Technology’s Health IT Policy Committee’s Governance Working
Group; building upon and aligning existing policies, such as Health Insur-
ance Portability and Accountability Act, agency regulations, and informed
consent processes to encourage learning health system activities; and nur-
turing the interfaces with the international community.
A potential responsibility discussed for the governance structure was
the stewardship of processes and protocols associated with learning health
system functionalities. Participants noted that developing processes for pro-
posing, reviewing, and validating protocols on key elements including data
gathering, security, and use is an integral part of this approach. Ongoing
stewardship responsibilities for the governing entity will involve monitor-
ing and maintaining protocols, managing variability across participants,
and devising an approach to provide incentives to stakeholders to conform
to stated goals and principles. A related element discussed as a governance
challenge was that of implementation phasing, or sequencing protocol
development activities so that barriers to progress in an entrepreneurial
environment are not presented by premature initiation of activity bound-
ing exercises.
In the spirit of a continuously improving learning health system, a pro-
cess for continuous evaluation and improvement of the governance entity
and approach was emphasized as important. Areas highlighted included
establishing an approach to ongoing assessment of progress and problems,
systematic assessment of value realization for recognition and promotion of
successful practices, and the support of research on governance and orches-
tration of the ULS digital health utility in the United States and globally.
COMMON THEMES AND PRINCIPLES
Several common themes recurred throughout the rich and varied dis-
cussion. These themes, included in Box 9-2 and summarized below, were
reflected in discussions of each of the four focus areas (technical progress,
knowledge generation and use, patient and population engagement, and
governance), as well as the discussions around various strategic elements.
They ranged from issues related to the culture and environment for learning
to the centrality of the patient and the importance of flexibility and trust.
Build a shared learning environment. HIT provides an opportunity
•
to change the current environment in which health decisions are
made to one of shared input and active participation from patients,
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BOX 9-2
Common Themes and Principles
• Build a shared learning environment
• Engage health and health care, population, and patient
• Leverage existing programs and policies
• Embed services and research in a continuous learning loop
• Anchor in an ultra-large-scale systems approach
• Emphasize decentralization and specifications parsimony
• Keep use barriers low and complexity incremental
• Foster a socio-technical perspective, focused on the population
• Weave a strong and secure trust fabric among stakeholders
• Provide continuous evaluation and improvement
caregivers, and the population at large. Approaches discussed to
developing this shared learning environment include the direct in-
volvement and support of patient and population roles in the gen-
eration of knowledge through the incorporation of user-generated
data, understanding the benefits of information use in patient care
and population health improvement, and improving patient ac-
cess to health information to allow for a more active role in care
decisions.
Engage health and health care, population, and patient. Many par-
•
ticipants reiterated that in order to improve health outcomes for the
nation, thinking must extend beyond clinical encounters, and even
beyond the individual patient, to the population as a whole. This
shift of scope brought into clearer focus several issues discussed,
including the opportunity to use HIT and its associated information
to build a concept of health that is about more than medical care
and draws on seamless interface with information from nonmedical
health-related sources to generate knowledge that allows for a more
inclusive view of population health improvement.
Leverage existing programs and policies. A foundational assump-
•
tion during the discussions was the advantage provided by building
on, and accelerating, the substantial recent progress, both nation-
ally and internationally, with an emphasis on the importance of
fostering coordination among these efforts to capture efficiencies
and prevent unnecessary duplication and waste going forward. Par-
ticipants often noted that recent policies and legislation have laid
a foundation for this work, and that the resulting investments and
progress can be leveraged to move toward long-term system goals.
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Embed services and research in a continuous learning loop. Meet-
•
ing participants often underscored that a digital infrastructure that
supports both the generation and use of knowledge cannot be ef-
fective unless it is integrated seamlessly within the processes from
which it draws and is meant to support care delivery, research,
quality improvement, and population health monitoring. Ease of
use for health system stakeholders, attention to the effects on work-
flow, and the delivery of useful decision support at point of care
were often mentioned in discussions.
Anchor in an ultra-large-scale systems approach. One of the most
•
prominent features of the discussions was the notion that the health
system is a complex, sociotechnical ecosystem, and therefore ne-
cessitates a unique conceptual approach. Grounding this approach
to coordination and integration of the digital infrastructure for
the learning health system in the principles of a ULS systems ap-
proach was suggested by several workshop participants from the
computer science community (see Box 9-3). The term “ultra-large-
scale system” refers to the existence of a virtual system that has
bearing on a social purpose—for example, improving health and
health care—and in which a few key elements, such as interchange
representation, may be standardized, but whose many participants
have diverse and even conflicting goals, so adaptability is key. Insti-
tutions retain flexibility for innovation in their choices, and evolu-
tionary functional change can be shaped by architectural precepts,
incentives, and compliance assessment, but not by centralized con-
trol. ULS functionality is therefore facilitated by protocols that
allow maximum practical flexibility for participants. Incorporating
decentralization of data, development, and operational authority
and control, this approach fosters local innovation, personaliza-
tion, and emergent behaviors. Participants felt that this approach
was well suited to the complex adaptive characteristics of the
health system, and that it could serve as an anchoring framework
for approaching both the social and technical components of the
overall infrastructure.
Emphasize decentralization and specifications parsimony. In line
•
with the complex adaptive qualities of the health system outlined
in the Quality Chasm (IOM, 2001) report and reiterated during the
workshops, both the social and technical components of the digital
health infrastructure require a framework that allows for tailoring
to specific needs, local innovation, and evolvability. In this respect,
the commonly repeated refrain was a call for the principle of parsi-
mony and minimizing centralization that might constitute a barrier
to entry: specify only the minimal set of standards or requirements
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BOX 9-3
Ultra-Large-Scale (ULS) System Characteristics
The ULS approach can be best described by a set of characteristics that tend
to arise as a result of the scale of the system (in this case health and health care)
rather than a prescriptive set of required components. Previous work on the ULS
concept has identified the following key characteristics of ULS systems:
Decentralization: The scale of ULS systems means that they will necessarily be
decentralized in a variety of ways—decentralized data, development, evolution,
and operational control.
Inherently conflicting, unknowable, and diverse requirements: ULS systems
will be developed and used by a wide variety of stakeholders with unavoidably
different, conflicting, complex, and changing needs.
Continuous evolution and deployment: There will be an increasing need to in-
tegrate new capabilities into a ULS system while it is operating. New and different
capabilities will be deployed, and unused capabilities will be dropped; the system
will be evolving not in phases, but continuously.
Heterogeneous, inconsistent, and changing elements: A ULS system will not
be constructed from uniform parts: there will be some misfits, especially as the
system is extended and repaired.
Erosion of the people/system boundary: People will not just be users of a
ULS system; they will be elements of the system, affecting its overall emergent
behavior.
Normal failures: Software and hardware failures will be the norm rather than
the exception.
New paradigms for acquisition and policy: The acquisition of a ULS system
will be simultaneous with the operation of the system and require new methods
for control.
SOURCE: Northrop et al. (2006).
necessary for key functional utility, and push the maximum amount
of control to the periphery. This approach is in line with strategies
such as those suggested in the PCAST report for use of metadata
for wrapping individual information packets to facilitate interoper-
ability and health information exchange, in which a primary focus
would be on development of the metadata standards.
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237
GROWING THE DIGITAL HEALTH INFRASTRUCTURE
Keep use barriers low and complexity incremental. Similarly, in-
•
centives for broad participation in the digital infrastructure by all
stakeholders was discussed as a crucial factor to its success. The
proposal to keep the barriers for use of the infrastructure, such as
deployment and operational complexity, low was articulated by
workshop participants in order to allow for maximum participa-
tion at a baseline level, and allow for incremental complexity and
sophistication where possible or necessary.
Foster a sociotechnical perspective, focused on the population.
•
From the outset of the discussions, participants pointed out that the
major barriers to technical progress often lie in social and cultural
domains. Acknowledging and engaging this fact was described as
being crucial to success, with discussions centering on an approach
that reorients future efforts to engage the patient more directly in
the collection and use of information in a way that is most useful
to them.
Weave a strong trust fabric among stakeholders. Security and
•
privacy concerns represent a strong threat to participation in, and
therefore the success of, the sociotechnical ecosystem. Accordingly,
they must be dealt with from both the social and technical per-
spectives. Participants emphasized the need for systems security to
comply with all current requirements and regulations and retain an
ability to evolve to meet future needs. In addition, continued hon-
est communication to the public and other involved stakeholders
about risks and benefits will be crucial to building a foundation of
trust.
Provide continuous evaluation and improvement. A learning sys-
•
tem is one that assesses its own performance against a set of goals
and uses the results of that evaluation to change future behaviors.
Workshop participants articulated the importance that all compo-
nents of a digital infrastructure must themselves function as learn-
ing systems.
REFERENCES
IOM (Institute of Medicine). 2001. Crossing the quality chasm: A new health system for the
21st century. Washington, DC: National Academy Press.
Northrop, L., P. H. Feiler, B. Pollak, and D. Pipitone. 2006. Ultra-large-scale systems: The
software challenge of the future. Pittsburgh, PA: Software Engineering Institute, Carnegie
Mellon University.
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