National Healthcare Quality and Disparities Report
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AHRQ Research Studies
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Research Studies is a compilation of published research articles funded by AHRQ or authored by AHRQ researchers.
Results
26 to 48 of 48 Research Studies DisplayedYano EM, Resnick A, Gluck M
AHRQ Author: Kwon H, Mistry KB
Accelerating learning healthcare system development through embedded research: career trajectories, training needs, and strategies for managing and supporting embedded researchers.
Health systems and organizations seeking to achieve learning healthcare system principles are increasingly relying on embedded research teams to optimize delivery of evidence-based, high-quality care that improves patient and staff experience alike. In February 2018, 115 attendees from multiple agencies, institutions and professional societies participated in a conference to accelerate development of learning healthcare systems through embedded research. This paper describes the process.
AHRQ-authored.
Citation: Yano EM, Resnick A, Gluck M .
Accelerating learning healthcare system development through embedded research: career trajectories, training needs, and strategies for managing and supporting embedded researchers.
Healthc 2021 Jun;8(Suppl 1):100479. doi: 10.1016/j.hjdsi.2020.100479..
Keywords: Learning Health Systems, Health Systems, Health Services Research (HSR)
Harrison MI, Shortell SM
AHRQ Author: Harrison MI
Multi-level analysis of the learning health system: Integrating contributions from research on organizations and implementation.
The authors have developed a comprehensive, multilevel framework to inform learning health systems (LHSs) research and practice in order to enhance both research on LHSs and practical steps toward their development. Drawing on the Consolidated Framework for Implementation Research, the social-ecological framework, and the organizational change framework, their new framework can help investigators and practitioners broadly scan and then investigate forces influencing improvement and learning and may point to otherwise unnoticed interactions among influential factors.
AHRQ-authored.
Citation: Harrison MI, Shortell SM .
Multi-level analysis of the learning health system: Integrating contributions from research on organizations and implementation.
Learn Health Syst 2021 Apr;5(2):e10226. doi: 10.1002/lrh2.10226..
Keywords: Learning Health Systems, Health Systems, Implementation, Organizational Change
Graves JA, Nshuti L, Everson J
Breadth and exclusivity of hospital and physician networks in US insurance markets.
The goal of this study was to quantify network breadth and overlap among primary care physician (PCP), cardiology, and general acute care hospital networks for employer-based (large group and small group), individually purchased (marketplace), Medicare Advantage (MA), and Medicaid managed care (MMC) plans. The main outcomes measured were percentage of in-network physicians and/or hospitals within a 60-minute drive from a hypothetical patient in a given zip code (breadth), and the number of physicians and/or hospitals within each network that overlapped with other insurers' networks, expressed as a percentage of the total possible number of shared connections (exclusivity). Networks were categorized by network breadth size and analyzed by insurance type, state, and insurance, physician, and/or hospital market concentration level, as measured by the Hirschman-Herfindahl index. Markets with concentrated primary care and insurance markets had the broadest and least exclusive primary care networks among large-group commercial plans. Markets with the least concentration had the narrowest and most exclusive networks. Rising levels of insurer and market concentration were associated with broader and less exclusive healthcare networks. The authors suggest that this means that patients could switch to a lower-cost, narrow network plan without losing-in-network coverage to their PCP.
AHRQ-funded; HS025976; HS026395.
Citation: Graves JA, Nshuti L, Everson J .
Breadth and exclusivity of hospital and physician networks in US insurance markets.
JAMA Netw Open 2020 Dec;3(12):e2029419. doi: 10.1001/jamanetworkopen.2020.29419..
Keywords: Health Insurance, Learning Health Systems, Health Systems, Primary Care, Hospitals, Healthcare Delivery
Hernandez AV, Roman YM, White CM
Developing criteria and associated instructions for consistent and useful quality improvement study data extraction for health systems.
This paper describes AHRQ’s efforts to collate and assess quality improvement studies to support learning health systems (LHS). The authors identified quality improvement studies and evaluated the consistency of data extraction from two experienced independent reviewers at three time points: baseline, first revision, and final revision. Six investigators looked at the data extracted by the independent reviewers and determined the extent of similarity on a scale of 0 to 10. Two LHS participants were then asked to assess the relative value of their criteria. The consistency of extraction improved from a mean 1.17 score at baseline to 6.07 at first revision, and 6.81 at the final revision. There was not a significant improvement from the first to final revision. However, the LHS participants rated the value of these ratings a 9 and a 6, demonstrating that there is value in developing criteria.
AHRQ-funded; 290201500012I.
Citation: Hernandez AV, Roman YM, White CM .
Developing criteria and associated instructions for consistent and useful quality improvement study data extraction for health systems.
J Gen Intern Med 2020 Nov;35(Suppl 2):802-07. doi: 10.1007/s11606-020-06098-1..
Keywords: Quality Improvement, Quality of Care, Learning Health Systems, Health Systems, Health Services Research (HSR), Research Methodologies
Lin JS, Murad MH, Leas B
A narrative review and proposed framework for using health system data with systematic reviews to support decision-making.
This paper addresses when and how the use of health system data might make systematic reviews more useful to decisionmakers. The authors have developed a framework to guide the use of health system data alongside systematic reviews based on a narrative review of the literature and empirical experience. They recommend future methodological work on how best to handle internal and external validity concerns of health system data in the context of systematically reviewed data and work on developing infrastructure to do this type of work.
AHRQ-funded; 290201500007I; 29032001T05; 290201500005I; 290201500009I.
Citation: Lin JS, Murad MH, Leas B .
A narrative review and proposed framework for using health system data with systematic reviews to support decision-making.
J Gen Intern Med 2020 Jun;35(6):1830-35. doi: 10.1007/s11606-020-05783-5..
Keywords: Learning Health Systems, Health Systems, Evidence-Based Practice, Data, Shared Decision Making
Richesson RL, Bray BE, Dymek C
AHRQ Author: Dymek C
Summary of second annual MCBK public meeting: mobilizing computable biomedical knowledge-a movement to accelerate translation of knowledge into action.
The Mobilizing Computable Biomedical Knowledge (MCBK) community formed in 2016. This report summarizes the main outputs of the Second Annual MCBK public meeting, which was held at the National Institutes of Health on July 18-19, 2019 and brought together over 150 participants from various domains to frame and address important dimensions for mobilizing CBK.
AHRQ-authored.
Citation: Richesson RL, Bray BE, Dymek C .
Summary of second annual MCBK public meeting: mobilizing computable biomedical knowledge-a movement to accelerate translation of knowledge into action.
Learn Health Syst 2020 Apr;4(2):e10222. doi: 10.1002/lrh2.10222..
Keywords: Implementation, Evidence-Based Practice, Learning Health Systems
Guise JM, Reid E, Fiordalisi CV
AHRQ Author: Borsky A, Chang S
AHRQ series on improving translation of evidence: progress and promise in supporting learning health systems.
The authors discuss the articles in the AHRQ EPC series published in this journal over the past six months. They state that satisfaction, care, and costs would all improve if health care delivery were as efficient and effective as possible given current knowledge. They conclude that millions of health decisions must be made by clinicians, patients, and health care systems, and they believe better decisions will be made with evidence.
AHRQ-authored; AHRQ-funded; 290201700003C.
Citation: Guise JM, Reid E, Fiordalisi CV .
AHRQ series on improving translation of evidence: progress and promise in supporting learning health systems.
Jt Comm J Qual Patient Saf 2020 Jan;46(1):51-52. doi: 10.1016/j.jcjq.2019.10.008..
Keywords: Implementation, Evidence-Based Practice, Learning Health Systems, Health Systems, Healthcare Delivery, Shared Decision Making
Borsky AE, Savitz LA, Bindman AB
AHRQ Author: Borsky AE
AHRQ series on improving translation of evidence: perceived value of translational products by the AHRQ EPC Learning Health Systems Panel.
This paper discusses the outcomes of an evaluation of translational products for clinicians and healthcare providers by an EPC (Evidence-based Practice Center) Learning Health Systems Panel convened by AHRQ. The panel, led by two national leaders and composed of key stakeholders evaluated different translational products for learning health systems and also discussed challenges in adopting evidence-based practices. They evaluated a number of different products, and decided that the one- and three-page summaries, the MAGICapp and Tableau for interactive data visualization, and clinical encounter and health system decision aids were the most useful products. As a result of their findings, the EPC Program is further developing the one- and three-page summaries and MAGICapp and Tableau data visualization products.
AHRQ-authored; AHRQ-funded; 233201500014I.
Citation: Borsky AE, Savitz LA, Bindman AB .
AHRQ series on improving translation of evidence: perceived value of translational products by the AHRQ EPC Learning Health Systems Panel.
Jt Comm J Qual Patient Saf 2019 Nov;45(11):772-78. doi: 10.1016/j.jcjq.2019.08.002..
Keywords: Implementation, Evidence-Based Practice, Patient-Centered Outcomes Research, Learning Health Systems
White CM, Coleman CI, Jackman K
AHRQ series on improving translation of evidence: linking evidence reports and performance measures to help learning health systems use new information for improvement.
This paper analyzed ways to enhance usability of AHRQ’s Evidence-based Practice Center (EPC) reports. The reports are often lengthy and difficult for users to navigate. A quality measure index was created to allow health systems to more efficiently access relevant information. A test was created where two tables were embedded in an EPC report. The first identified quality measures covered by the report descriptively. The second contained page numbers in the executive summary which hyperlinked to those pages with the quality measures. An exercise with two health system-targeted scenarios was then created. The participants were timed how long it took to find answers to scenario questions and gave feedback. It was found that it took 63.4% less time to find quality measure information with the hyperlinked indexing tables than without. The participants felt that the tables were easy to use and more user friendly to health systems.
Jt Comm J Qual Patient Saf 2019 Oct;45(10):706-10. doi: 10.1016/j.jcjq.2019.05.002.
Citation: White CM, Coleman CI, Jackman K .
AHRQ series on improving translation of evidence: linking evidence reports and performance measures to help learning health systems use new information for improvement.
Jt Comm J Qual Patient Saf 2019 Oct;45(10):706-10. doi: 10.1016/j.jcjq.2019.05.002..
Keywords: Implementation, Evidence-Based Practice, Health Systems, Learning Health Systems, Patient-Centered Outcomes Research, Provider Performance, Quality Measures, Quality Improvement, Quality of Care
Fiordalisi C, Borsky A, Chang S
AHRQ EPC series on improving translation of evidence into practice for the learning health system: introduction.
This article introduces a special series of articles summarizing the AHRQ EPC program’s work to improve translation of high-quality evidence into practice. The authors summarize each of the nine EPC pilot projects and characterize the chosen approach to improve uptake of EPC review findings. They anticipate that the articles in this series will inform health systems about how others have tried to improve the translation of evidence into practice and use this information to inform their own efforts to bridge the evidence-to-practice gap going forward.
AHRQ-authored; AHRQ-funded; 290201700003C.
Citation: Fiordalisi C, Borsky A, Chang S .
AHRQ EPC series on improving translation of evidence into practice for the learning health system: introduction.
Jt Comm J Qual Patient Saf 2019 Aug;45(8):558-65. doi: 10.1016/j.jcjq.2019.05.006..
Keywords: Evidence-Based Practice, Learning Health Systems, Implementation, Quality Improvement, Quality of Care
Borsky AE, Flores EJ, Berliner E
AHRQ Author: Borsky AE, Berliner E, Chang C, Chang SM
Next steps in improving healthcare value: AHRQ Evidence-based Practice Center Program-applying the knowledge to practice to data cycle to strengthen the value of patient care.
This paper discusses AHRQ’s Evidence-based Practice Center (EPC) Program which has been in existence for over 20 years. The EPC program and its objectives are described. The three phases of the Learning Healthcare System cycle is described. A sample topic (hospital medicine Clostridium difficile colitis prevention and treatment) is used to describe the process and results of the effectiveness of the EPC program.
AHRQ-authored.
Citation: Borsky AE, Flores EJ, Berliner E .
Next steps in improving healthcare value: AHRQ Evidence-based Practice Center Program-applying the knowledge to practice to data cycle to strengthen the value of patient care.
J Hosp Med 2019 May;14(5):311-14. doi: 10.12788/jhm.3157..
Keywords: Evidence-Based Practice, Learning Health Systems, Implementation
Adler-Milstein J, Nong P, Friedman CP
AHRQ Author: Adler-Milstein J
Preparing healthcare delivery organizations for managing computable knowledge.
This article describes results of an AHRQ-funded conference where a group of experts from a range of fields examined the current state of knowledge management in healthcare delivery organizations. Conference presentations and discussions were recorded and analyzed by the authors in order to identify foundational concepts. The concepts identified are: the current state of knowledge management in healthcare delivery organizations is reliant upon an outdated biomedical library model, and only a small number of organizations have developed management approaches to push knowledge in computable form to frontline decisions; Learning Health Systems create a need for scalable computable knowledge management approaches; the ability to represent data science discoveries in computable form that are findable, accessible, interoperable, and reusable is fundamental to spreading knowledge at scale.
AHRQ-funded; HS025316.
Citation: Adler-Milstein J, Nong P, Friedman CP .
Preparing healthcare delivery organizations for managing computable knowledge.
Learn Health Syst 2019 Apr;3(2):e10070. doi: 10.1002/lrh2.10070..
Keywords: Healthcare Delivery, Learning Health Systems, Organizational Change, Health Systems
Guise JM, Savitz LA, Friedman CP
Mind the gap: putting evidence into practice in the era of learning health systems.
This paper discusses two main mechanisms to close the evidence-to-practice gap: (1) integrating Learning Health System (LHS) results with existing systematic review evidence and (2) providing this combined evidence in a standardized, computable data format.
AHRQ-funded; 29020120004C.
Citation: Guise JM, Savitz LA, Friedman CP .
Mind the gap: putting evidence into practice in the era of learning health systems.
J Gen Intern Med 2018 Dec;33(12):2237-39. doi: 10.1007/s11606-018-4633-1..
Keywords: Evidence-Based Practice, Healthcare Delivery, Learning Health Systems, Implementation
Davis MM, Lindberg P, Cross S
Aligning systems science and community-based participatory research: a case example of the Community Health Advocacy and Research Alliance (CHARA).
In this article, the investigators explored opportunities to utilize concepts from systems science to understand the development, evolution, and sustainability of 1 community-based participatory research partnership: The Community Health Advocacy and Research Alliance (CHARA). Their goal was to highlight CHARA as a case for applying the complementary approaches of CBPR and systems science to (1) improve academic/community partnership functioning and sustainability, (2) ensure that research addresses the priorities and needs of end users, and (3) support more timely application of scientific discoveries into routine practice.
AHRQ-funded; HS022981.
Citation: Davis MM, Lindberg P, Cross S .
Aligning systems science and community-based participatory research: a case example of the Community Health Advocacy and Research Alliance (CHARA).
J Clin Transl Sci 2018 Oct;2(5):280-88. doi: 10.1017/cts.2018.334..
Keywords: Learning Health Systems, Research Methodologies
Harrison MI, Grantham S
AHRQ Author: Harrison MI
Learning from implementation setbacks: identifying and responding to contextual challenges.
The authors addressed organizational learning about implementation context during setbacks to primary care redesign in an ambulatory system. They found that redesigned teams were not implemented as widely or rapidly as anticipated and did not deliver hoped-for gains in operational metrics; however, team redesign was leading to improvements in chronic care and prevention and eased provider burden. Redesign and system leaders engaged in more thorough organizational learning. Their responses to challenges helped to strengthen the redesign's prospects, improved the delivery system's position in its labor market, and helped the system prepare to meet emerging requirements for value-based care and population health.
AHRQ-authored; AHRQ-funded; 2902010000341.
Citation: Harrison MI, Grantham S .
Learning from implementation setbacks: identifying and responding to contextual challenges.
Learn Health Syst 2018 Oct;2(4):e10068. doi: 10.1002/lrh2.10068..
Keywords: Organizational Change, Learning Health Systems, Health Systems, Primary Care: Models of Care, Primary Care, Ambulatory Care and Surgery, Implementation
Forrest CB, Chesley FD, Tregear ML
AHRQ Author: Chesley FD, Mistry KB
Development of the learning health system researcher core competencies.
The purpose of this study was to develop core competencies for learning health system (LHS) researchers to guide the development of training programs. The investigators found that the iterative development process yielded seven competency domains: (1) systems science; (2) research questions and standards of scientific evidence; (3) research methods; (4) informatics; (5) ethics of research and implementation in health systems; (6) improvement and implementation science; and (7) engagement, leadership, and research management.
AHRQ-authored; AHRQ-funded; 290201200017I.
Citation: Forrest CB, Chesley FD, Tregear ML .
Development of the learning health system researcher core competencies.
Health Serv Res 2018 Aug;53(4):2615-32. doi: 10.1111/1475-6773.12751..
Keywords: Education: Continuing Medical Education, Learning Health Systems, Training
Moffatt-Bruce S, Huerta T, Gaughan A
IDEA4PS: the development of a research-oriented learning healthcare system.
In this paper, the authors present the approach of one academic medical center in becoming a research-oriented Learning Healthcare System (ro-LHS). By reframing the role of research in improving outcomes, the organization was able to move beyond its focus on quality improvement to foster a culture in which feedback informs practice and research drives improvement.
AHRQ-funded; HS024091.
Citation: Moffatt-Bruce S, Huerta T, Gaughan A .
IDEA4PS: the development of a research-oriented learning healthcare system.
Am J Med Qual 2018 Jul;33(4):420-25. doi: 10.1177/1062860617751044..
Keywords: Health Services Research (HSR), Learning Health Systems, Outcomes, Quality Improvement
Mullins CD, Wingate LT, Edwards HA
Transitioning from learning healthcare systems to learning health care communities.
The learning healthcare system (LHS) model framework has three core, foundational components. These include an infrastructure for health-related data capture, care improvement targets and a supportive policy environment. This paper discusses transitioning from learning healthcare systems to learning healthcare communities.
AHRQ-funded; HS022135.
Citation: Mullins CD, Wingate LT, Edwards HA .
Transitioning from learning healthcare systems to learning health care communities.
J Comp Eff Res 2018 Jun;7(6):603-14. doi: 10.2217/cer-2017-0105..
Keywords: Community-Based Practice, Healthcare Delivery, Learning Health Systems, Patient-Centered Healthcare
Kamal AH, Kirkland KB, Meier DE
A person-centered, registry-based learning health system for palliative care: a path to coproducing better outcomes, experience, value, and science.
In this paper, the authors discuss measurement of the impact of palliative care, which is critical for determining what works for which patients in what settings, to learn, improve care, and ensure access to high value care for people with serious illness. The authors described an approach to codesigning and implementing a palliative care registry that functions as a learning health system, by combining patient and family inputs and clinical data to support person-centered care, quality improvement, accountability, transparency, and scientific research.
AHRQ-funded; HS023681.
Citation: Kamal AH, Kirkland KB, Meier DE .
A person-centered, registry-based learning health system for palliative care: a path to coproducing better outcomes, experience, value, and science.
J Palliat Med 2018 Mar;21(S2):S61-s67. doi: 10.1089/jpm.2017.0354..
Keywords: Palliative Care, Patient-Centered Healthcare, Patient-Centered Outcomes Research, Outcomes, Learning Health Systems, Registries, Patient and Family Engagement
Nix M, McNamara P, Genevro J
AHRQ Author: Nix M, McNamara P, Genevro J, Vargas N, Mistry K, Fournier A, Shofer M, Lomotan E, Miller T, Ricciardi R, Bierman AS
Learning collaboratives: Insights and a new taxonomy from AHRQ's two decades of experience.
The authors examined AHRQ's experience with learning collaboratives to characterize their attributes, identify factors that might contribute to their success or failure, and assess the challenges they encountered. Building on the literature and insights from AHRQ's experience, they propose a taxonomy that can offer guidance to decision makers and funders about the factors they should consider in developing collaboratives.
AHRQ-authored.
Citation: Nix M, McNamara P, Genevro J .
Learning collaboratives: Insights and a new taxonomy from AHRQ's two decades of experience.
Health Aff 2018 Feb;37(2):205-12. doi: 10.1377/hlthaff.2017.1144.
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Keywords: Learning Health Systems, Health Systems, Quality Improvement, Quality of Care, Healthcare Delivery
Franklin P, Chenok K, Lavalee D
Framework to guide the collection and use of patient-reported outcome measures in the learning healthcare system.
Web-based collection of patient-reported outcome measures (PROMs) in clinical practice is expanding rapidly as electronic health records include web portals for patients to report standardized assessments of their symptoms. As the value of PROMs in patient care expands, a framework to guide the implementation planning, collection, and use of PROs to serve multiple goals and stakeholders is needed. In this study, researchers identified diverse clinical, quality, and research settings where PROMs have been successfully integrated into care and routinely collected and analyzed drivers of successful implementation.
AHRQ-funded; HS022789.
Citation: Franklin P, Chenok K, Lavalee D .
Framework to guide the collection and use of patient-reported outcome measures in the learning healthcare system.
eGEMS 2017 Sep 4;5(1):17. doi: 10.5334/egems.227..
Keywords: Learning Health Systems, Health Systems, Electronic Health Records (EHRs), Health Information Technology (HIT), Web-Based, Patient-Centered Healthcare
Ramsey LB, Mizuno T, Vinks AA
Learning health systems as facilitators of precision medicine.
To illustrate the concept of the Learning Health System, the authors of this paper describe the example of the ImproveCareNow Network and use a network case study to illustrate how the concept of precision medicine can be achieved through a Learning Health System in a real-world clinical environment.
AHRQ-funded; HS020024; HS016957.
Citation: Ramsey LB, Mizuno T, Vinks AA .
Learning health systems as facilitators of precision medicine.
Clin Pharmacol Ther 2017 Mar;101(3):359-67. doi: 10.1002/cpt.594..
Keywords: Learning Health Systems, Research Methodologies
Nembhard IM, Morrow CT, Bradley EH
Implementing role-changing versus time-changing innovations in health care: differences in helpfulness of staff improvement teams, management, and network for learning.
This paper examined the hypothesis that the degree to which access to groups that can alter organizational learning depends on innovation type. Team representativeness and network membership were positively associated with implementing role-changing practices; while senior management engagement was positively associated with implementing time-changing practices. The authors concluded that these findings advance implementation science by explaining mixed results across past studies, that the nature of change for workers alters potential facilitators' effects on implementation.
AHRQ-funded; HS018987.
Citation: Nembhard IM, Morrow CT, Bradley EH .
Implementing role-changing versus time-changing innovations in health care: differences in helpfulness of staff improvement teams, management, and network for learning.
Med Care Res Rev 2015 Dec;72(6):707-35. doi: 10.1177/1077558715592315.
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Keywords: Healthcare Delivery, Quality Improvement, Organizational Change, Teams, Quality of Care, Learning Health Systems, Implementation