Comparative Effectiveness Topics from a Large, Integrated Delivery System

Danforth, Kim N.; Patnode, Carrie D.; Kapka, Tanya; Butler, Melissa G.; Collins, Bernadette; Compton-Phillips, Amy; Baxter, Raymond J.; Weissberg, Jed; McGlynn, Elizabeth A.; Whitlock, Evelyn P

doi:10.7812/tpp/13-036

Cited by 5 publications

(6 citation statements)

References 3 publications

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“…Given the reputations of the organizations invited to attend the meeting, these findings reflect the viewpoints of aspirational early adopters. However, they are concordant with previous findings (Alexander et al, 2007;Cosgrove et al, 2013;Danforth et al, 2013), and they provide valuable insights about meaningful incentives and operational enablers for integrating knowledge generation into care. With respect to the aim in drawing knowledge generation as a more integral component of medical practice, conclusions from this sample include general enthusiasm for the opportunity that data networks offer to learn from ongoing clinical work, especially as it offers a return on the immense investments systems have made in health information technology balanced against concerns that the pace of research is "out of sync" with demands of health care systems and a sense that topics of interest to researchers do not map well with needs of systems to improve access, improve quality and reduce rising costs.…”

Section: Observations and Follow-upsupporting

confidence: 89%

“…Research conducted in and with health care systems is not business as usual. Previous commentators have noted different priorities between health systems and most research studies (Alexander et al, 2007;Cosgrove et al, 2013;Danforth et al, 2013). But what do health care executives think of the value and challenges of integrating effectiveness research knowledge generation about what works best for whom as a core element of continuous care system improvement (see Box 1)?…”

Section: Introductionmentioning

confidence: 99%

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Integrating Research into Health Care Systems: Executives' Views

Johnson¹,

Großmann²,

Anau³

et al. 2015

NAM Perspectives

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BOX 1 Definition Used in Survey A continuous learning healthcare system is one where knowledge is derived from practice and used to drive the cycle of continuous improvement. Knowledge generation can include data analysis for process and quality improvement as well as a range of research activities, for example:  An observational study using data from different organizations to compare stroke rates among patients treated with either dabigatran or warfarin therapy for atrial fibrillation  A cluster randomized trial where hospitals are randomized to either routine care or chlorhexidine bathing and nasal decolonization to assess if this reduces hospital-associated infections.

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Section: Observations and Follow-upsupporting

confidence: 89%

Section: Introductionmentioning

confidence: 99%

Integrating Research into Health Care Systems: Executives' Views

Johnson¹,

Großmann²,

Anau³

et al. 2015

NAM Perspectives

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“…The themes discussed above reflect practical operational challenges that are likely experienced by other health systems and are consistent with Johnson et al’s leadership surveys 20 and other work in this area. 6 – 8 , 16 – 18 Our findings suggest first that clinical and operational leaders tend to adopt a very pragmatic approach to learning, especially to the evaluation of “learning activities,” such that although they recognize the value of rigorous evaluation, that value is often trumped by the operational imperative to execute operational objectives efficiently (Theme 7). This is in contrast to research leaders who have different objectives and incentives.…”

Section: Discussionmentioning

confidence: 96%

“… 3 – 8 Senior leadership support and operational-research partnerships have been identified as key components of successful LHS activity, 9 – 15 yet little has been published to provide guidance on important operational issues and strategies for systemwide learning and operationalization of the LHS model. 16 – 18 A recent survey of leaders and managers from organizations involved in patient-centered network programs funded by the Patient-Centered Outcomes Research Institute (PCORI) recognized that research had a beneficial role to play in care delivery, but discussed a number of challenges with integrating research into clinical practice. 19 While learning is contextual, i.e., is highly influenced by the organizational and individual characteristics in which it occurs, leaders across health care systems could benefit from a greater understanding of the challenges and opportunities surrounding learning from their peers.…”

Section: Introductionmentioning

confidence: 99%

Leadership Perspectives on Operationalizing the Learning Health Care System in an Integrated Delivery System

Psek

Davis

Gerrity

et al. 2016

eGEMs

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Introduction:Healthcare leaders need operational strategies that support organizational learning for continued improvement and value generation. The learning health system (LHS) model may provide leaders with such strategies; however, little is known about leaders’ perspectives on the value and application of system-wide operationalization of the LHS model. The objective of this project was to solicit and analyze senior health system leaders’ perspectives on the LHS and learning activities in an integrated delivery system.Methods:A series of interviews were conducted with 41 system leaders from a broad range of clinical and administrative areas across an integrated delivery system. Leaders’ responses were categorized into themes.Findings:Ten major themes emerged from our conversations with leaders. While leaders generally expressed support for the concept of the LHS and enhanced system-wide learning, their concerns and suggestions for operationalization where strongly aligned with their functional area and strategic goals.Discussion:Our findings suggests that leaders tend to adopt a very pragmatic approach to learning. Leaders expressed a dichotomy between the operational imperative to execute operational objectives efficiently and the need for rigorous evaluation. Alignment of learning activities with system-wide strategic and operational priorities is important to gain leadership support and resources. Practical approaches to addressing opportunities and challenges identified in the themes are discussed.Conclusion:Continuous learning is an ongoing, multi-disciplinary function of a health care delivery system. Findings from this and other research may be used to inform and prioritize system-wide learning objectives and strategies which support reliable, high value care delivery.

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“…Information from EHRs needed to be aggregated into clinical data repositories [21][22][23][24], registries [5,6] and data warehouses to support clinical investigation. New tools were also developed to assist clinicians with the task of query [21,[25][26][27][28][29][30].…”

mentioning

confidence: 99%

Reuse Of Clinical Data

Safran¹

2014

Yearb Med Inform

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SummaryObjectives: To provide an overview of the benefits of clinical data collected as a by-product of the care process, the potential problems with large aggregations of these data, the policy frameworks that have been formulated, and the major challenges in the coming years. Methods: This report summarizes some of the major observations from AMIA and IMIA conferences held on this admittedly broad topic from 2006 through 2013. This report also includes many unsupported opinions of the author. Results: The benefits of aggregating larger and larger sets of routinely collected clinical data are well documented and of great societal benefit. These large data sets will probably never answer all possible clinical questions for methodological reasons. Non-traditional sources of health data that are patient-sources will pose new data science challenges. Conclusions: If we ever hope to have tools that can rapidly provide evidence for daily practice of medicine we need a science of health data perhaps modeled after the science of astronomy. As a byproduct of a patient's care, vast quantities of information are stored in electronic databases. The primary reason for collecting this information is to support the care of the patient during an encounter or subsequent encounters. For the purpose of this review, all other uses of a particular patient's data not for that patient's care will be considered reuse. The reuse of patient data for quality assurance and clinical research is not new, but in the context of "big data", has new importance both for the prospect of refining the "evidence" that we base medical decisions upon as well as the potential for gaining new insights in the era of personalized medicine. This review will highlight some of the benefits of reuse, the potential problems with large clinical databases, the policy frameworks that have been formulated, and the major challenges in the coming years. KeywordsThe volume and availability of health data has increased primarily for two reasons -the mandated adoption of data exchange standards and the variety of types and sources of data. The stimulus to adopt information technology in healthcare is driven by the belief that it can help control costs as well as improve the safety of care. Demonstrating the improvement in the quality or safety of care is much easier than proving that health information technology saves money. For instance, while automation in the clinical laboratories has improved efficiency, in our hospital we have re-purposed personnel to perform other tasks. In the United States, these drivers are embodied in the HITECH act of 2009 that provides incentives for hospitals and physicians to adopt electronic health records (EHRs) that are interoperable. The trends are similar worldwide.In three decades (1983 to 2013), the data storage needs of our hospital has increased by about six orders of magnitude -from two gigabytes to approximately two petabytes of data. Although our hospital has merged with another hospital and our EHR now captures all clinical ...

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Comparative Effectiveness Topics from a Large, Integrated Delivery System

Cited by 5 publications

References 3 publications

Integrating Research into Health Care Systems: Executives' Views

Integrating Research into Health Care Systems: Executives' Views

Leadership Perspectives on Operationalizing the Learning Health Care System in an Integrated Delivery System

Reuse Of Clinical Data

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