The Learning Healthcare System Workshop Summary (2007) / Chapter Skim
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3 Narrowing the Research-Practice Divide—Systems Considerations
3 Narrowing the Research-Practice Divide—Systems Considerations
Pages 151-184
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From page 151... ...
Improved performance and patient care were fostered by a system designed to collect data to track inputs and outcomes and provide feedback on performance -- elements that also created a useful research tool that has led to incremental improvements in quality along with discovery and large advancements in care at the practice level. The experience at Intermountain identifies some of the organizational and cultural changes needed, but a key was the utilization of electronic health records (EHRs)
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FEEDBACK LOOPS TO ExPEDITE STUDy TIMELINESS AND RELEVANCE Brent James, M.D., M.Stat. Intermountain Healthcare Quality improvement was introduced to health care in the late 1980s.
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. The Intermountain strategy depended heavily upon a new "shared baselines" approach to care delivery, that evolved during early quality improvement projects as a mechanism to functionally implement evidence-based medicine (James 2002)
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Finally, we applied two important criteria for which we could not find metrics: we used expert judgment to identify underserved subpopulations, and to balance our rollout across all elements of the Intermountain care delivery system.
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On careful examination, the administrative data contained gaping holes relative to clinical care delivery. They were organized for facilities management, not patient management.
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From page 156... ...
. Physician leaders are required to be in active practice within their Clinical Program; to have the respect of their professional peers; and to complete formal training in clinical quality improvement methods through Intermountain's internal clinical QI training programs (the Advanced Training Program in Clinical Practice Improvement)
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From page 157... ...
The majority of Development Team members are drawn from front-line physicians and clinical staff, geographically balanced across the Intermountain system, who have immediate hands-experience with the clinical care under discussion (technically, "fundamental knowledge")
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A finished CPM is formally deployed into clinical practice by the governing Guidance Council, through its regional physician/nurse leader dyads. At that point, the Development Team's role changes.
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; relate it to clinical workflow; show delivery teams how to track patient results through the outcomes data system; tie the CPM to decision support tools built into the electronic medical record; and link it to a full set of educational materials, for patients and for care delivery professionals. Chronic disease Knowledge Experts also run the specialty clinics that support front-line care delivery teams.
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A third report tracks progress on quality improvement goals, and links them to financial incentives. Finally, a separate summary report goes to the team's Clinical Program medical director.
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for all key clinical care delivery processes. In such a setting, all care changes get tested.
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. That led to a randomized controlled trial to identify best antibiotic choices for outpatient management of CAP (Level 1 evidence)
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It holds massive potential to deliver "best care" to patients, while generating evidence to find the next step in "best care." ELECTRONIC HEALTH RECORDS AND EVIDENCE-BASED PRACTICE Walter F Stewart, Ph.D., M.P.H., and Nira R
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Patients seen in clinical practice tend to be considerably more diverse and more clinically complex than patients enrolled in clinical trials. This gap between existing evidence and the needs of clinical practice does not mean that we should change how RCTs are done.
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In the paper-based world of most clinical practices, clinicians will always be constrained by a "pony-express" model of bringing knowledge to practice. That is, with very limited time, clinicians must choose a few things to learn from time to time and hope that they use what they learn effectively when needed.
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From page 166... ...
This process is qualitatively different from what occurs in R&D, where, as we have noted, the intention of research is to create value. Despite the challenges, adoption of an R&D model for healthcare delivery is not practical, given the constraints of a paper-based world.
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From page 167... ...
Namely, it is almost not worth considering the expansive development and adoption of clinical data standards, expansive use of human independent interactions (e.g., algorithmic ordering of routine preventive health interventions) , real-time monitoring of data, detailed feedback on patient management performance, sophisticated means of clinical decision support, and timely creation of evidence, to mention a few.
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rapid protocols designed to conduct clinical trials as a routine part of care delivery in the
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For example, one such method may include research on how longitudinal EHR data can be used to replicate the results of prior randomized clinical trials. Such an evaluation might include imposing the same patient inclusion and exclusion criteria, duration of "observation," and other design features used in pivotal trials.
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. The future of CDS is in developing real-time processes that directly influence clinical care decisions at exactly the right time (i.e., sensing when it is appropriate to present decision options)
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Coverage decisions are particularly sensitive to a narrowing of the research-practice divide, and this discussion focuses on how evidence standards currently operate in coverage decisions for both diagnostic and therapeutic technologies. Quicker, practice-based research opportunities inherent to a learning healthcare system may affect evidence standards in an unanticipated manner.
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From page 172... ...
Part of the difficulty is the lack of appropriate studies, but for procedures and devices the lack of evidence is related to the fluid nature of technology development and our evidence base. For example, devices are often rapidly upgraded and improved, and the procedures and practitioner competency with those procedures evolve over time.
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From page 173... ...
Decision makers in private health plans have to wrestle with this problem constantly while trying to establish a consistent and transparent approach to evidence. So what happens to the evidence bar when we move toward a learning healthcare system?
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Ultimately CED may be used to support studies whose results will enhance the strength of evidence to meet existing standards, certainly part of the vision of CED -- but might it also lead to a shift to a lower initial standard of evidence for coverage decisions? As we know when CED policy became known to industry, many groups approached CMS with not "promising" but perhaps even "poor" evidence, asking for coverage in return for the establishment of a registry from which we will all "learn." Resolving these issues is an active area of policy discussion -- with individuals at CMS and elsewhere still very early on the learning curve -- and is vital to improving approaches as we develop and advance our vision of a learning healthcare system.
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NARROWING THE RESEARCH-PRACTICE DIVIDE Pharma / Device "My job is innovation that helps people .
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FDA approval does not necessarily equate to insurance coverage. Payers, most often CMS and health insurance companies, make coverage decisions.
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Evidence development can proceed through submission of data to a registry or through practical clinical trials, and the end point is a definitive decision on coverage. This novel approach addresses three issues simultaneously: by covering the service, those patients most in need have access; by developing information on a large population, future tailoring of coverage to just those subpopulations who truly benefit can mitigate overuse; and by paying for the service, the manufacturer collects revenue immediately and gets a more definitive answer on coverage sooner -- a potential mechanism for accelerating innovation.
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THE LEARNING HEALTHCARE SYSTEM resonance imaging are focused at and destroy the fibroids (Fennessy and Tempany 2005)
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NARROWING THE RESEARCH-PRACTICE DIVIDE Progress to Date and Major Challenges The initiative has progressed more slowly than originally planned, but data collection is set to begin before the end of 2006. The number and intensity of challenges has exceeded the expectations of the principals, and addressing them has frankly required more time and resources than anyone had predicted.
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0 THE LEARNING HEALTHCARE SYSTEM is clearly described and there is a business case to offer them (e.g., that controlled accumulation of evidence could better tailor and limit future use of the innovation) , then uptake may be satisfactory.
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1995. Bridges between health care research evi dence and clinical practice.
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2002. Quality improvement opportunities in health care.
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NARROWING THE RESEARCH-PRACTICE DIVIDE Williamson, J, P Goldschmidt, and I Jillson.
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