The Agency for Healthcare Research and Quality (AHRQ) provides many valuable evidence-based resources and tools for patients, providers, policymakers, researchers, systematic reviewers, guideline developers, and many other healthcare stakeholders. These offerings are spread across over ~20 different websites with different structures, content types, and purposes. This can make it difficult for potential users to appreciate that AHRQ has resources useful to address their needs, find these resources, and integrate them into their workflows and information systems. These challenges are dramatically amplified from the user perspective given the myriad other public and private resources to meet their information and support needs. As a result, critical healthcare decisions and actions are often not informed by the important evidence, guidance, and tools that are available. Such problematic information and resource flow is a major contributor (1) (2) (3) to suboptimal performance in healthcare quality, cost, safety, patient satisfaction, and provider well-being (see Urgent Challenge: Put Evidence into Practice More Effectively). AHRQ established the AHRQ evidence-based Care Transformation Support (ACTS) initiative in late 2018 to propose a Roadmap to make its evidence-based tools and resources—along with those from many other public and private sources—easy to find and apply by healthcare stakeholders who need them. To ensure that any eventual AHRQ efforts to implement the Roadmap leverage and support related efforts by others, the ACTS project team engaged a broad Stakeholder Community. Several workgroups were formed during 2019 to provide input and establish foundations for the Roadmap. During 2020, three AHRQ-funded pilot efforts were initiated with the Stakeholder Community to explore key Roadmap components. The Stakeholder Community grew steadily throughout 2019 and 2020, reaching nearly 300 members by the end of 2020. The ACTS Roadmap is a 10-year plan to produce a robust digital healthcare knowledge ecosystem anchored by an AHRQ Digital Knowledge Platform (DKP). This Roadmap requires a substantial Federal investment to seed critical activities, which will then inspire and be amplified by complimentary private-sector investment. This knowledge ecosystem will make evidence, guidance, tools, and resources from AHRQ—and other public and private sources—more FAIR (i.e., findable, accessible, interoperable, reusable); computable; and useful. The goal is to have the knowledge ecosystem broadly support learning health systems (LHSs) and realization of the Quintuple Aim. In addition to these benefits, it is estimated that billions of public and private-sector dollars could be saved annually (4) (5) (6) by reducing waste in healthcare delivery and redundancies and inefficiencies in resource development (see Value Proposition & ROI). To help ensure that Roadmap execution delivers near-term value toward this goal, initial proposed execution efforts focus on addressing <span style="color: #262626"><strong>four clinical targets</strong></span> for which improved performance is a high priority:<ac:structured-macro ac:name="anchor" ac:schema-version="1" ac:macro-id="9020b3d2-ef3c-4f47-931f-e2a23cb14c74"><ac:parameter ac:name="">Targets</ac:parameter></ac:structured-macro> <span style="color: #262626"><strong>1) COVID19/pandemic response;</strong></span> <span style="color: #262626"><strong>2) preventive care;</strong></span> <span style="color: #262626"><strong>3) hypertension control; and 4) pain management</strong></span> <span style="color: #262626"><strong>/</strong></span> <span style="color: #262626"><strong>opioid use</strong></span>. Additional targets will be added as execution progresses, and efforts to improve the knowledge ecosystem function for all these targets will be designed to scale to many other targets via efforts that unfold synergistically and in parallel with those specifically addressed by this Roadmap. As depicted in Figure 1. Summary of Deliverables by Phase, the Roadmap is divided into four phases: <span style="color: #262626"><strong>Concept Demonstrations (2021–2024), Pilots (2024–2027), Scaling (2027–2030), and LHS (2031)</strong></span>. Each phase includes tasks organized around five critical activities: <span style="color: #262626"><strong>Create/Use Governance & Collaboration;</strong></span> <span style="color: #262626"><strong>Enhance/Leverage Infrastructure;</strong></span> <span style="color: #262626"><strong>Enhance/Develop Living, Computable Guidance; Enhance</strong></span> <span style="color: #262626"><strong>Guidance Implementation and Assessment; and Evaluate/Plan Roadmap Execution</strong></span>. Together, the tasks are designed to improve the <span style="color: #262626"><strong>entire</strong></span> knowledge ecosystem cycle (i.e., from evidence to guidance to action to data and back to evidence). Initial AHRQ-funded pilots to address Roadmap activities that enhance this cycle are currently underway as this Roadmap is being reviewed by AHRQ and many other organizations for possible actions. The ACTS project team has received letters from<ac:structured-macro ac:name="anchor" ac:schema-version="1" ac:macro-id="7f7bc46f-40c9-426a-84c3-27e26f553b60"><ac:parameter ac:name="">StakeholderOrgCount</ac:parameter></ac:structured-macro> <span style="color: #262626"><strong>33 stakeholder organizations</strong></span> (1 Federal agency; 8 care delivery organizations \[CDOs\]; 8 professional societies, accrediting bodies, and institutes; 7 health IT vendors and initiatives; 7 clinical evidence/guidance organizations; and 1 patient advocate) expressing support for the ACTS Future Vision and interest in cultivating synergies between their efforts and Roadmap-recommended approaches to broadly realizing that future vision (Appendix G, ACTS Support Letters). More letters are forthcoming. <ac:structured-macro ac:name="anchor" ac:schema-version="1" ac:macro-id="ef410f20-020f-4aaa-8abe-9cd05aa69041"><ac:parameter ac:name="">_Ref62738851</ac:parameter></ac:structured-macro><span style="color: #262626">Figure 1. Summary of Deliverables by Phase</span> Roadmap Execution Steering Committee (RESC), Coordinating Center (CC). See Appendix H, Acronyms & Abbreviations for definitions. !worddav7afd01d8d11c01cb05efe08cd2076811.png|height=465,width=705! \\
Healthcare outcomes in the United States are far from optimal. Patients' care experiences are often frustrating and fragmented—lacking clear care plans, plagued by slow or missing communication and unclear or unshared priorities, and fraught with challenges to access critically needed information and tools. Patients often are not fully engaged in reconciling their care goals with those of their clinicians to achieve important results. Furthermore, the United States has the poorest healthcare outcomes among 11 high-income countries, even though it spends the most (7). According to the Centers for Medicare and Medicaid Services (CMS), the United States spent 17.7% of its 2019 Gross Domestic Product (GDP) on healthcare—and costs are rising (8). A 2019 peer review of literature from 2012 to 2019 estimated approximately 30% of healthcare spending could be considered waste, resulting in a staggering total annual waste estimate of $760 billion to $935 billion and a potential $191 billion to $286 billion in savings from interventions that address waste, including in the following domains pertinent to this Roadmap (4):
Despite the high expenditures, many are still uninsured or underinsured and substantial health disparities by race, ethnicity, and socioeconomic status exist (9). It can take over a decade for research-supported interventions to become standard care (10), and one New England Journal of Medicine study found that adults receive only half the care that is recommended (11). Preventable harm (e.g., medication errors) causes up to 1,000 deaths per day (12), and that does not include errors of omission. Approximately $210 billion/year is wasted on unnecessary services, while another $130 billion/year is spent on inefficient services and $55 billion is lost to missed prevention opportunities (13).
Clinicians are also burning out. Poor information flow also contributes to clinician burnout that costs billions every year (14) and further degrades care quality. A 2017 panel on physician burnout called it "a public health crisis" and described the pressure on doctors to meet quality measures without the resources or support to meet those demands (15). The 2019 novel coronavirus (COVID19) has exacerbated this problem (16). While high burnout is associated with lower quality care, the magnitude and clinical significance is still unclear (17) (18) (19). One contributor to burnout could be lack of resources needed to work more efficiently and effectively. Some estimate that physician decisions influence more than 80 percent of healthcare costs (20) (21), so efficiently supporting these decisions should be a priority. Valuable evidence-based resources, knowledge, and tools curated by AHRQ and others to guide decisions and actions to address these problems do exist, but they are underused. This may be due to potential users not being aware that these resources already exist, having poor access to them, or having difficulty integrating them within their workflow and underlying health IT systems.
Figure 2. High-Cost, Suboptimal U.S. Healthcare (12) (13) (14) (20) (11) (15)
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A common theme underlying these problems is suboptimal support for healthcare decisions and actions with helpful, evidence-based guidance and tools. Effective support requires a robust flow of essential information, tools, and resources around the LHS cycle, but as shown in Figure 3. Current Barriers to an Effective LHS Cycle this flow isn't happening well. This is due in part to myriad, fragmented, uncoordinated pathways whereby these assets are created and deployed (e.g., across patients, care teams, resource developers, insurance providers, hospitals, clinics, public health organizations, researchers, and many other users).
Figure 3. Current Barriers to an Effective LHS Cycle
In this broken supply chain, data, knowledge, information—and access to them—are siloed in disparate systems that are not interoperable. This problem is pervasive throughout the entire healthcare system, leading to inefficiencies, lost time and productivity, and undesirable outcomes. For example, healthcare organizations often experience difficulties to:
More specifically, there are significant missed opportunities at critical junctures along the LHS cycle. Data reflecting care results are frequently not used well to improve the evidence base because it is typically difficult and expensive to gather, incomplete, and/or inaccurate. This limited data scope yields evidence that does not address many important questions. Further, the evidence is often inconsistent and not in a standardized format, making it difficult to process into readily updatable knowledge, tools, and resources that support care delivery and transformation. The many support offerings that already exist are difficult to locate and apply. They often do not fit smoothly into workflow and can require major investments to acquire and deploy in health IT systems. The poor interoperability and flow from data to evidence to guidance to tools that support critical decisions and actions and back to data about care results is depicted in Figure 4. Current Healthcare Information Flow). This current state is a major driver for the preventable problems with care and patient outcomes, unnecessarily high expenditures, suboptimal patient experience, and overburdened clinicians noted above. <ac:structured-macro ac:name="anchor" ac:schema-version="1" ac:macro-id="01e10289-94ec-4617-85cd-cf5955f280a6"><ac:parameter ac:name="">_Ref60735279</ac:parameter></ac:structured-macro><span style="color: #262626">Figure 4.<ac:structured-macro ac:name="anchor" ac:schema-version="1" ac:macro-id="e3da25cd-dbe7-4523-8eac-f4f993a91e67"><ac:parameter ac:name="">_Ref56414265</ac:parameter></ac:structured-macro></span> <span style="color: #262626">Current Healthcare Information Flow</span> !worddav3e459d814a2972a4d0ded15a3f8c09aa.png|height=409,width=384! These challenges led healthcare leaders to establish the <span style="color: #262626"><strong>Quintuple Aim</strong></span> (22) (23)—a goal where the healthcare system simultaneously enhances patient experience, improves population health, reduces costs, and improves clinician experience. Health information technology (IT) is widely considered a key enabler to improve information flow and achieve the Quintuple Aim. While there have been major investments in health IT (including artificial intelligence \[AI\] and cloud computing infrastructure), substantial standards efforts, and regulations around _data_ interoperability, there remains a chasm between the kind of transformation achieved in other industries and that seen in healthcare (2). There is growing consensus that health IT-enabled care transformation delivered through an LHS, both at the enterprise and national levels, supported by evidence and knowledge interoperability that complements data interoperability, is the solution to these deficiencies (24). There have been major efforts over decades to address these problems, and this ACTS Roadmap builds on these efforts, a sampling of which includes:
Full realization of LHSs and the Quintuple Aim in follow-up to these important initaitives have been impeded by forces such as:
This ACTS Roadmap deliverable builds on prior work and leverages more robust and widely adopted critical standards (e.g., Fast Healthcare Interoperability Resources \[FHIR\], more ubiquitous and sophisticated health IT (developed with greater attention to user-centered design), increased interest in value-based care and LHSs, and greater attention to stakeholder-driven approaches to accelerate transformation. These developments should substantially accelerate progress toward the Quintuple Aim beyond what these prior initiatives achieved. This Roadmap focuses on the problems and solutions that AHRQ and other knowledge ecosystem stakeholders can directly address by replacing the broken cycle, shown in Figure 3. Current Barriers to an Effective LHS Cycle and Figure 4. Current Healthcare Information Flow with an effective LHS cycle, shown in Figure 5. The LHS Cycle. In this effective LHS cycle, public health, care delivery, and quality improvement (QI) actions produce data about results, which is processed into evidence about effective actions, which is in turn processed into knowledge, tools, and resources that inform subsequent action—in a continuous cycle—to achieve the Quintuple Aim. Producing an effective LHS cycle requires that information flows seamlessly around that cycle. The environment in which people use processes and technology to address this flow in ways that deliver desired outcomes we call the "knowledge ecosystem."
Functionally, the knowledge ecosystem enables the LHS cycle, which we also refer to as the "knowledge ecosystem cycle."
Figure 5. The LHS Cycle
The CDS 5 Rights Framework (29), is a widely cited approach for putting evidence, guidance, and tools into practice better—that is, for optimizing the _guidance to action_ portion of the knowledge ecosystem cycle. The framework, recommended by CMS as a health IT / QI best practice (30), asserts that optimizing a particular healthcare process or outcome requires getting the information (e.g., evidence-based and actionable) to the right people (e.g., care teams and patients) in the right formats (e.g., registry reports, documentation tools, data display, care plans) through the right channels (e.g., electronic health record \[EHR\], personal health record \[PHR\], smartphones, smart home devices) at the right times (e.g., during a key decision or action). This framework can be extended to cover the _entire_ LHS cycle by broadening each of the five dimensions to include _all_ the pertinent who, what, when, where, how options.
Figure 6. The Decision/Action Support (DAS) 5-Rights-Supported LHS Cycle illustrates how the LHS virtuous cycle requires addressing well each of those five dimensions throughout all activities in the cycle.
Figure 6. The Decision/Action Support (DAS) 5-Rights-Supported LHS Cycle
Figure 7. LHS Functions That the Knowledge Ecosystem Supports illustrates additional details about processes performed around the knowledge ecosystem cycle. Each of these processes is an opportunity to put the DAS 5 Rights Framework into action to make them efficient and well-coordinated to achieve a virtuous LHS cycle.
Figure 7. LHS Functions That the Knowledge Ecosystem Supports
AHRQ produces many valuable, evidence-informed resources to support care delivery and transformation and LHSs. However, many who could significantly benefit from these resources aren't aware they exist, have difficulty finding or accessing them, or are challenged to incorporate them into information systems and workflow. To promote broader value from these carefully curated resources, AHRQ launched the ACTS Initiative (31) in late 2018 to develop a roadmap for how to improve access to and use of resources that AHRQ and others provide. That is, to chart a path for how the Agency could better realize its mission (32) (33) by creating an AHRQ DKP that makes its resources more FAIR (34), computable, and useful, and, most importantly, does this in a manner synergistic with other public and private efforts to likewise mobilize computable biomedical information into an integrated knowledge ecosystem that supports LHSs, the DAS 5 Rights, and the Quintuple Aim in ways that help achieve respective organizational missions.
See Figure 8. Sampling of Non-AHRQ Initiatives Addressing the Knowledge Ecosystem With Which Roadmap Execution Coordinates and Appendix A, Interplay With a Sampling of Other Strategic Plans, Priorities & Initiatives for examples of these other important and inter-related activities.
Figure 8. Sampling of Non-AHRQ Initiatives Addressing the Knowledge Ecosystem With Which Roadmap Execution Coordinates
[N] indicates not a Federal initiative. See Appendix H, Acronyms & Abbreviations for definitions.
The current knowledge ecosystem does not support aspiring LHSs (e.g., CDOs seeking to create the virtuous LHS cycle depicted in Figure 5. The LHS Cycle) well and contributes significantly to slow progress toward the Quintuple Aim. The elements (e.g., information and tools) that comprise each LHS cycle component (i.e., data, evidence, guidance, and action) are poorly integrated and don't optimally meet knowledge ecosystem stakeholder needs—as depicted in Figure 4. Current Healthcare Information Flow. Each component isn't optimally driven by the preceding component or used to efficiently drive the following component. These silos and misalignments—which often require extensive manual, error-prone work to get information and tools to flow around the cycle—are major impediments to creating the virtuous LHS cycle. Addressing these impediments is a grand challenge.
Few, if any, organizations that control all the ecosystem cycle components (e.g., large, integrated delivery networks that have extensive research and guidance processing capabilities) have created the high-functioning, well-integrated knowledge ecosystem illustrated in Figure 7. LHS Functions That the Knowledge Ecosystem Supports. Creating a ubiquitous, high-functioning LHS cycle will require that DKPs from individual organizations better meet ecosystem needs and interoperate with each other better.
Returning to AHRQ as an example, this Agency provides many high-value tools and resources that together support each step in the knowledge ecosystem cycle (see Figure 9. How AHRQ Supports Key Tasks in the Knowledge Ecosystem Cycle, and more details about each offering and enhancement plans in Appendix F. AHRQ Offerings & the Knowledge Ecosystem Cycle). These offerings—like those from most other sources—are produced and disseminated to address different goals and constraints that programs responsible for them have, rather than to optimize overall ecosystem function. As a result, producing these offerings typically requires extensive manual processing of information from the previous knowledge ecosystem cycle step as noted above. Likewise, offerings are typically disseminated in formats that require further manual processing before they can be applied to support decisions and actions in the following ecosystem cycle step.
Putting evidence related to preventive care into practice—for which AHRQ provides important support—is a case example. Consider challenges on the resource production side. When AHRQ Evidence-based Practice Centers (EPCs) create systematic reviews, extensive manual processing of data from individual studies (some of which AHRQ funds) is required. When the AHRQ-supported U.S. Preventive Services Task Force (USPSTF) creates preventive care guidelines, manual processing of data in systematic reviews is required. When CDS interventions to support preventive care are created (e.g., using AHRQ's CDS Connect Authoring tool), extensive manual processing of data in guidance statements is required, and so on around the cycle.
Similar challenges arise for those consuming resources from AHRQ and others. For example, consider a sampling of user perspectives and their needs related to screening for colorectal cancer—a major preventable cause of morbidity and mortality:
AHRQ has valuable information to address all these needs, but it is challenging for users to get this information efficiently and effectively using available tools, such as the search and browse features on search.ahrq.gov (35). This is because the resource collection wasn't developed to address an enterprise portal "one-stop shop" use case and individual resources haven't had components tagged at a detailed level regarding their content and application to enable users to identify and retrieve just the elements that are applicable to their specific need.
Problems for users with these important needs are greatly compounded due to the countless sources besides AHRQ that could be considered for help. There are many people, process, and technology hurdles to overcome in addressing these challenges. For example, achieving agreement on standards-based tags that enable users to identify and access valuable, evidence-based answers and resources suited to their need from the many available sources, and having those resources be more computable to minimize manual data reentry.
The widespread siloed approach to resource development and dissemination around the ecosystem cycle contributes to the current state where, patients, care teams and other healthcare knowledge ecosystem participants—despite countless offerings from a myriad of different sources—often don't have the evidence-based support they need to help make critical decisions and take appropriate actions to achieve their health, care, policy, and other goals.
Organizations that provide tools and resources need next-generation DKPs that enable them to process inputs and produce outputs that are more FAIR and computable. Such DKPs will make product development more efficient by reducing the time to find and access building blocks used to create the products and making it easier to combine the building blocks efficiently to create value-added offerings. DKPs can likewise help ensure that these products are widely used and enhance workflow, processes, and outcomes. For example, DKPs could apply and use standards-based tags to indicate details of what evidence, guidance, care results, and other key ecosystem cycle data are about. User interfaces (UIs) to these DKPs can then support seamless data flow from one ecosystem cycle step to the next through UIs that leverage the data tagging to help users (people and systems) find and apply information and tools that are highly responsive to specific needs.
Figure 9. How AHRQ Supports Key Tasks in the Knowledge Ecosystem Cycle See Appendix H, Acronyms & Abbreviations for definitions.
Figure 10. AHRQ DKP
An AHRQ DKP (see Figure 10. AHRQ DKP) would make AHRQ offerings around the ecosystem cycle more FAIR, computable, and useful. AHRQ offerings that populate these gears are spread across over 20 different websites, each with different purposes, structures, and content types. This makes it difficult for those who can benefit from one of the offerings to know that AHRQ has it, to find it, and to understand and apply it within their information systems and workflows—in the context of related content and tools from other sources. An AHRQ DKP would provide a more user- and need-focused platform to serve users better by providing just what's needed—when, where, and how it would be most helpful.
AHRQ tools and resources—and websites and other channels used to disseminate them—have been developed and enhanced independently in response to pressing healthcare needs that align with AHRQ's mission (32). Healthcare delivery—and the knowledge ecosystem that supports it—have evolved dramatically in the years (and, in many cases, decades) since these offerings were first created, particularly due to the increasing focus on value-based care and LHSs and the powerful opportunities provided by rapidly evolving health IT. The time is ripe for AHRQ to comprehensively reexamine in an integrated way how it supports the knowledge ecosystem cycle along with others and how an AHRQ DKP integrated seamlessly with platforms from others could address pressing healthcare needs more efficiently and effectively to better fulfillment AHRQ's mission. These same issues and opportunities exist for essentially all other public and private organizations that provide tools and resources supporting the knowledge ecosystem cycle.
The AHRQ DKP is a relatively small but important component of the global digital healthcare knowledge ecosystem depicted in Figure 11. Digital Healthcare Knowledge Ecosystem, which illustrates seamless, interoperable information flow among DKPs that comprise public and private marketplaces. This information flow is more efficient and easier to maintain than the current state (see Figure 4. Current Healthcare Information Flow) because the information can be reused without extensive manual processing; thus, it meets user needs and supports desired healthcare outcomes better. The seamless information flow is supported by a common reference architecture, which includes interoperability enablers such as standards for expressing and exchanging information, including tags for identifying what individual pieces of information and tooling are about, where they came from, how they have been validated, and how they can be used. This flow requires coordination and cooperation among organizations participating in the knowledge ecosystem through a public–private partnership (PPP) (36) (37) (38), which supports knowledge ecosystem-related governance, establishes information exchange standards, sets priorities, and takes other joint steps to help ensure that stakeholders' individual and shared goals are achieved.
Development and execution of this Roadmap aligns with AHRQ's role in achieving the Patient-Centered Outcomes Research Trust Fund's (PCORTF) goals (39). That is, to support patient-centered outcomes research dissemination (40) through evidence synthesis, translation and communication, and implementation. The actions outlined in this Roadmap will ensure that AHRQ resources become more synergistic with other resources supporting each knowledge ecosystem/LHS component and that these components interoperate more smoothly to achieve LHS goals more efficiently and effectively.
Figure 11. Digital Healthcare Knowledge Ecosystem
Revisiting the colorectal cancer screening example in the Needed: Better DKPs section illustrates how an AHRQ DKP within an interoperable digital healthcare knowledge ecosystem that supports a virtuous LHS cycle can help address the waste, harm, inefficiencies, and missed opportunities in the current system. Appendix B, Future Vision also contains an extensive discussion of a consensus future vision enabled by an effective digital healthcare knowledge ecosystem related to colorectal cancer screening and other preventive care examples. This ACTS Roadmap outlines how to realize this future vision in ways that leverage assets and efforts from AHRQ (as outlined in Appendix F, AHRQ Offerings & the Knowledge Ecosystem Cycle) and many other initiatives (e.g., as outlined in Appendix A, Interplay With a Sampling of Other Strategic Plans, Priorities & Initiatives).
Results from, and citations to, research funded by AHRQ and others are tagged using standardized, computable codes that enable information of greatest interest (e.g., about patient intervention, comparison, outcome \[PICO\] (41) dimensions) to be retrieved (e.g., via search, browse, or application programming interface \[API\]) and used in computable format to address a particular task such as answering a question, performing a systematic review, or enhancing a QI effort. Assets from AHRQ and other selected sources can be accessed in a user-focused manner from the AHRQ DKP's Insights Engine, as depicted in Figure 9. How AHRQ Supports Key Tasks in the Knowledge Ecosystem Cycle, including planned enhancements via the Center for Evidence and Practice Improvement (CEPI) Evidence Discovery & Retrieval (CEDAR) project (42). These functions build on the ACTS Computability Requirements Pilot for Tool 1: creating, storing, and accessing computable study results. See Appendix E, AHRQ-Funded ACTS Pilots.
EPCs and other users can subscribe to be automatically notified when new research on the topic is produced and this information can flow seamlessly into tools for creating systematic reviews such as Systematic Review Data Repository Plus (SRDR+) (43) and others. Users apply these tools to process computable study information into living systematic reviews that likewise consist of computable and interoperable components. This enables reuse of this information for systematic review updating, guideline development and updating, answering clinical questions, and other purposes. Assets from AHRQ and other selected sources can be accessed in a user-focused manner from the AHRQ DKP's Insights Engine, as depicted in Figure 9. How AHRQ Supports Key Tasks in the Knowledge Ecosystem Cycle, including planned enhancements via CEDAR (42), SRDR+, and Effective Health Care (EPC) website (44). These functions build on the ACTS Computability Requirements Pilot for Tool 2: creating, storing, and accessing computable systematic review results. See Appendix E, AHRQ-Funded ACTS Pilots.
USPSTF and other users can subscribe to be automatically notified when new or updated systematic reviews on the topic are produced and this information can flow seamlessly into tools for creating computable guidance. Users apply these tools to process computable systematic reviews and other evidence and information into living guidelines that likewise consist of computable and interoperable components. This enables reuse of this information for CDS and eCQM development and updating, answering clinical questions, and other purposes. Assets from AHRQ and other selected sources can be accessed in a user-focused manner from the AHRQ DKP's Insights Engine, as depicted in Figure 9. How AHRQ Supports Key Tasks in the Knowledge Ecosystem Cycle, including planned enhancements via CEDAR (42). These functions build on the ACTS Computability Requirements Pilot for Tool 3: creating, storing, and accessing computable rationale for guidance and for Tool 4: identifying, storing, and accessing terminology for computable recommendation definition. See Appendix E, AHRQ-Funded ACTS Pilots. Explorations into a possible next-generation version of the National Guideline Clearinghouse (NGC) (45) could leverage computable information from the research, review, and guidance steps outlined above to make updating guidance in a possible, enhanced, NGC more efficient and timely.
Those who create and maintain CDS interventions (such as order sets, documentation tools, dashboards, patient-driven care plans using tools like the CDS Connect Authoring Tool (46) and others), eCQMs, and QI tools (such as those provided by the Center for Quality Improvement and Patient Safety \[CQuIPS\] (47)) can subscribe to be automatically notified when new or updated guidance on the topic is produced. This computable guidance information can flow seamlessly into these tools, which are used to create and maintain _living_ CDS interventions, eCQMs, and QI tools that likewise consist of computable, interoperable, and reusable components (48). Assets from AHRQ and other selected sources can be accessed in a user-focused manner from the AHRQ DKP's Insights Engine, as depicted in Figure 9. How AHRQ Supports Key Tasks in the Knowledge Ecosystem Cycle, including planned enhancements via CEDAR (42), and to other relevant websites that provide AHRQ tools. These functions build on the ACTS Virginia Commonwealth University (VCU)-led Patient-driven Care Plan Tool Refinement and Implementation Pilot. See Appendix E, AHRQ-Funded ACTS Pilots and plannedInsert link to Appendix F. AHRQ Offerings? enhancements to CDS Connect Authoring Tool functionality.
Authoring tools that produce the output from the step above—as well as the resulting tools that are produced—are accessible via the marketplaces depicted in Figure 11. Digital Healthcare Knowledge Ecosystem. Tools produced by AHRQ, other Federal agencies, and other organizations that want to freely disseminate their offerings, flow seamlessly into the open, free, public-sector marketplace. Vendors and other private-sector organizations have parallel commercial marketplaces, and all tools in all marketplaces are seamlessly interoperable due to the common reference architecture and governance mechanisms established by the PPP. These functions build on the current and planned CDS Connect Repository functions and sustainability efforts (49) as well as corresponding efforts around marketplaces as outlined in Figure 8. Sampling of Non-AHRQ Initiatives Addressing the Knowledge Ecosystem With Which Roadmap Execution Coordinates and Appendix A, Interplay With a Sampling of Other Strategic Plans, Priorities & Initiatives.
Computable evidence, guidance, and tools from AHRQ (e.g., from the CEPI and CQuIPS) and other public and private sources can be readily identified, selected based on user needs, and integrated into information systems that are used to support patients, care teams, QI teams and others involved in care delivery and QI. When critical information changes, users are notified, and associated tools are readily updated. Playbooks, courses, and other materials foster the dynamic workforce learning required to integrate and apply evolving information and tools in practice. The information and tools are highly responsive to user needs for effectively supporting important decisions, workflows, and actions. These functions are supported by the AHRQ DKP, other DKPs and public and private marketplaces.
The preceding steps ensure that the CDS 5 Rights (29) are realized for the clinical target (i.e., the right information is delivered to the right people in the right formats through the right channels at the right times). These functions are supported by the AHRQ DKP and other DKPs. The AHRQ–National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK) Project (50) to develop eCare plans as IT-enabled tools that support seamless care coordination, communication, and collaboration among care team members will be leveraged as one key mechanism for addressing the CDS 5 Rights in ways that put evidence into practice.
Data from EHRs, systems that manage patient-generated health data (PGHD), and other sources that characterize care processes and results related to the clinical target are produced and managed using the same reference architecture that supports developing and disseminating standards-based, computable evidence, guidance, and tools in earlier ecosystem cycle steps. This enables more immediate and efficient use of process and outcomes data to drive QI and public health efforts, support feedback and reflection for workforce learning, and close the ecosystem cycle by providing new evidence for further care delivery enhancements. These functions are supported by extensive efforts to make patient data more FAIR (e.g., see Figure 8. Sampling of Non-AHRQ Initiatives Addressing the Knowledge Ecosystem With Which Roadmap Execution Coordinates and Appendix A, Interplay With a Sampling of Other Strategic Plans, Priorities & Initiatives). They will also be supported by AHRQ's Insight Platform (51), which provides publicly available data and analytic tools to support evidence-based answers to questions about healthcare system performance and improvement opportunities. In turn, the knowledge ecosystem will support enhancements to how these AHRQ offerings that detail healthcare performance are produced and disseminated. These enhancements will be driven by greater computability of the information they contain, which enables more seamless data input from sources (e.g., EHRs) and more seamless and user-needs-focused delivery of targeted information.
Creating LHSs at organization, national, and international scales is increasingly viewed as a core strategy to optimize healthcare delivery and achieve the Quintuple Aim (57) (58). Computable knowledge is a key enabler for these LHSs (3). By illustrating how health IT that supports the interoperable flow of computable knowledge around the knowledge ecosystem and LHS cycle, Figures 5–11 and 13 reflect key future vision elements for broadly realizing LHSs. In this future vision, resources needed to support key decisions and actions throughout the knowledge ecosystem cycle are FAIR (59) (see Figure 14. Characteristics of FAIR Resources), computable, useful, and widely used to great benefit.
Enhanced information flow in the knowledge ecosystem and LHS cycle should produce continuously improving public health, and care quality and outcomes. Evidence is effectively translated into resources that are widely and successfully used to guide actions, which generate useful data that inform more robust evidence in a virtuous learning cycle (see What a Digital Knowledge Ecosystem Will Enhance). Stakeholders in each area of the cycle must have clear economic incentives naturally guiding local policies and behaviors toward this model. We refer to this overall cycle as a national LHS cycle when it encompasses efforts across an entire country. An ultimate Roadmap goal is data, evidence, knowledge, guidance, and tools that are computable and interoperable across national, geographic, policy, and other boundaries in ways that enable the virtuous cycle to encompass everyone, everywhere. The COVID19 pandemic reinforces the need for such a global learning and improvement cycle.
Individual CDOs can likewise become LHSs by supporting helpful evidence-based information and tools use in practice by care teams, quality teams and patients (e.g., through evidence-based, integrated care plans); systematically examining results from their care delivery and QI efforts; and using these results to enhance care and QI efforts continuously. We refer to this CDO-specific work as the organizational LHS cycle. CDOs and entities that support them typically refer to these activities as QI, continuous QI (CQI), or care transformation.
The ACTS Future Vision Workgroup described in detail desirable workflows and information flows that could occur in LHSs supported by a high-functioning knowledge ecosystem (Appendix B, Future Vision). Four knowledge ecosystem perspectives were selected for this visioning work:
Figure 15. Future Vision for a Virtuous LHS Cycle includes a one-sentence future vision overview for each of these perspectives, encapsulating many pages of detailed descriptions presented in the future vision appendix.
Other future vision perspectives not addressed by the Future Vision Workgroup are also essential for driving a knowledge ecosystem that delivers LHSs. For example, defining desirable specifics for the data-to-evidence portion of the LHS cycle as depicted in Figure 15. Future Vision for a Virtuous LHS Cycle. The Roadmap is designed to support stakeholders in defining and addressing a consensus future vision for these key ecosystem components in ways that leverage and advance related initiatives to collect and analyze data to generate new evidence (60) (61) (62) (63) and for related LHS cycle activities. The LHS cycle—and the outcomes it should deliver such as the Quintuple Aim—will only be as successful as permitted by the least effective cycle component, so careful attention must be paid to all components.
Figure 14. Characteristics of FAIR Resources Adapted from (347) and (59)
Figure 15. Future Vision for a Virtuous LHS Cycle