Redesigning the Clinical Effectiveness Research Paradigm Innovation and Practice-Based Approaches: Workshop Summary (2010) / Chapter Skim
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6 Aligning Policy with Research Opportunities
6 Aligning Policy with Research Opportunities
Pages 323-362
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has released a report that assesses the impact of the Health Insurance Portability and Accountability Act (HIPAA) Privacy Rule on the conduct of health research and provides recommendations for ensuring the efficient conduct of research while maintaining or strengthening the privacy protections of personally 2
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Focused on course-of-care data, Greg Pawlson of the National Committee for Quality Assurance describes a major opportunity to use these clinical data for "rapid learning." By capturing the experience of each patient and clinician in a structured and quantifiable manner, EHR systems have great potential to help transform our capacity to develop information that can be used as important evidence in making clinical decisions. Policy interventions will play a crucial role in improving the development of and access to databases that are suitable for clinical effectiveness research.
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. For the purposes of this paper, we will include clinical effectiveness, health services, and other related research using large clinical databases as within the scope and definition of rapid learning.
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that Health Insurance Portability and Accountability Act (HIPAA) regulations be reviewed, modified, and delimited to remove the major barriers imposed on research and rapid learning that pose NO direct risk for patients; and (5)
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While there are some efforts that are at least tangentially related to rapid learning, such as the Practice Research Network funded by the AHRQ, Aligning Forces for Quality funded by the Robert Wood Johnson Foundation, or various RHIOs and HIEs, most efforts are very underfunded and none that we are aware of directly address issues of rapid learning. Also related to research, there continues to be a large chasm between clinical practice and even health services research.
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However, it would seem that the risks to patients from data that have already been collected to monitor and assist in their own care are both quantitatively and qualitatively different from primary data collection for research purposes. Finally, there have been several incidents in which projects that have been centered on quality improvement (which is in many ways very analogous to rapid learning)
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Pediatric cancer care may provide a useful example, as virtually all of the treatment provided in pediatric oncology is recorded and applied to registries or active clinical trials, which then informs the optional future care for children ongoing treatment. To address the lack of standardization of data elements in EMRs, and to appropriately harness this resource for comparative or clinical effectiveness research or for rapid learning, researchers must be actively involved in the many discussions and organizations that are working to set standards for EMRs.
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In conclusion, this appears to be a critical moment in the development of EMRs and EHRs, which have the potential to provide complete, real-world data to inform clinical practices, help to develop needed clinical effectiveness information, improve the systematic quality of care, and produce a rapid, evidence-based method of continuous practice improvement. Unless the substantial barriers to progress are addressed quickly and collectively, the United States may well fall far behind in yet another critical aspect of health care.
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Regulatory, stakeholder, payer, and patient demands for increased data requirements, transparency, access, and value represent formidable issues in the areas of benefit–risk assessment, ongoing safety assessment, and comparative effectiveness. Several important initiatives are under way to address these challenges; however, significant opportunities remain that are amenable to research and policy remediation, including clinical trial and pharmacovigilance methodologies, data standards and access, as well as the perpetual challenge of education focused on translating evidence into behaviors.
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. Active comparators are being increasingly incorporated into clinical registration studies and post-approval clinical trials, in part, to demonstrate incremental value.
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and other groups and is the subject of a growing professional discipline around demonstration of absolute and relative clinical effectiveness. There also are some efforts underway to have more structured approaches to benefit–risk assessment.
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, and the teaching of evidence-based decision making, but there is much work to be done. The medical education system may not adequately address needs in basic pharmacology and clinical pharmacology let alone clinical effectiveness.
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Because this information will not be derived from traditional randomized clinical trials, support will be needed for infrastructure, data aggregation, and analysis, and for improving the relevant statistical methods. Given the slow movement in Congress on comparative effectiveness, for the short term, a priority should be to enhance the healthcare system's capacity to generate data as a routine part of care and to use these data to learn what works in practice.
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Much can be learned about drug risks and benefits from observational studies of large population datasets; for questions that require randomization or other statistical approaches, these databases also have great potential to help design targeted trials or postmarket clinical studies. Perhaps eventually with more efficient generation of information on risks and benefits, costly postmarket clinical trials can be efficiently used to augment the routine postmarket surveillance system.
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scanning. A second type of coverage with evidence development involves providing needed support for clinical trials.
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Information is needed not just on whether a patient gets a treatment or not, but what kind of interventions work in terms of payment reforms, formulary reforms, care management programs, or that other interventions that affect medical practices and populations can influence how a population of patients is being treated. These kinds of incremental differences in medical practice are very difficult to analyze through traditional randomized clinical trials; but, putting in place better infrastructure for collecting data and developing evidence longitudinally over time, on actual treatments that populations of patients are
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Practical, less-burdensome policies for secondary data that protect patient confidentiality, expansion of Medicare claims files to incorporate new types and sources of data, and facilitated, lower cost access to private-sector secondary clinical data for publicly funded studies need to be developed and implemented. Concerning evidence-based comparative effectiveness, if our ultimate objective is to answer clinically relevant questions, most researchers are likely in agreement that while RCTs are necessary, they are not in and of themselves sufficient to answer all of our questions.
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The most significant problems in clinical effectiveness research are not that we employ poor methodology, but rather that we fail to ask the right questions. Working backwards from a problem, one needs to structure the decision and get the information we need to identify the gaps in data needs.
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There is an order of magnitude difference between potential harm to a patient if one is looking and exploring data that has no identifying information to that patient, versus exposing someone to an active treatment; yet, most IRBs do not seem to make that distinction. It would be extremely useful to have HIPAA guidance for private data clarified and to extend federal data-use agreements regarding secondary data to institutions.
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We need to facilitate lower cost access to privatesector secondary clinical data for publicly funded studies. We need to increase public–private partnerships (e.g., the Interagency Registry for Mechanically Assisted Circulatory Support -- INTERMACS)
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For clinical trials, there should be a policy for funding some of these methods concurrently to see what these methods would have shown compared to what the trial is going to show. Broad experimentation with quasi-experimental and practical RCTs is also needed.
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, is an international collaboration focused on critical path research from translation to clinical development. The ITN conducts scientific review, clinical trials planning and implementation, tolerance assays, data analysis, and identification of biomarkers, as well as provides scientific support in informatics, trial management, and communications.
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1% 0% 25 30 35 40 45 50 55 60 65 70 75 80 85 90 Age FIGURE 6-1 Changing demographics from 1980 to 2006 in age of medical school Figure 6-1.eps faculty and principal investigators (PIs) of NIH research project grants (RPGs)
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These programs span research career development opportunities for investigators who have made a commitment to focus on patient-oriented research through the 3 See http://books.nap.edu/catalog/11249.html. 4 See www.nap.edu/booksearch.php?
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Each applicant academic health center creates an individualized home for clinical and translational science, challenging some traditional approaches to link clinical trial design, implementation, and regulation with biostatistics, informatics, ethics, training, and community. These new entities serve as platforms for healthcare organizations, industry, and government to synergize their efforts to shepherd biomedical discoveries to clinical applications.
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If "translational research" involves moving basic discoveries from concept to clinical evaluation, the critical path involves drug development via "proof of principle" studies, including clinical trials, assay development, and evaluation tools. The ITN aggregates more than 75 clinicians, investigators, and government officials to provide the infrastructure to review and develop grant proposals, fund clinical trials and assay development, and provide infrastructure required to test the applicability of basic discovery to human disease.
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To address this gap, the Immune Tolerance Institute (ITI) was forged to support academic–industrial collaboration to leverage discoveries into marketable therapeutics.
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0 Transforming Critical Path Science Current Structure/ Challenges ITI Strengths Opportunities • Economies of scale Consor tium-driven/ Decentralized • Centralized resources and expertise • Streamlined processes (SOPs) • Higher quality, more reproducible data • Enhanced business service Single investigator studies / • High throughput, highly standardized • More effective data integratio n Lack robustness technologies ma ximizes interpetive power • Scalabilit y, reproducibilit y • Qualit y assurance and control Manual processing of patient samples/ • Centralized processing • Reproducibilit y/standardizatio n Inef ficiencies • Sample tracking system • Qualit y control • Data visualization • Cost effectiveness • Customer service • Better data management Limited business development resources/ • Dedicated, focused business • More effective intellectual proper ty Hampers product development development and intellectual development proper ty infrastructure • Productive collaborations, i.e., public –private, industry–academic partnerships • Ef ficient product development • Enhanced translation to patient benefit FIGURE 6-3 ITI strengths and opportunities to transform critical path science.
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Highly Standardized Assays / Product Bioinformatics Data Analysis / Development Assay Research and Biomarker Development • Fee for service • Validation of disease Development Discover y • Clinical trials and therapy markers • Application to monitoring • Basic discoveries • Statistical analyses • Partner to set up human studies that drive new • Disease staging • Potential disease validation studies • Drug /disease assay development • GLP, CLIA and therapy specific • Out-licensing of specific compliance markers diagnostic /biomarker • Bioinformatics products plat form ITN ITN /ITI ITI/ ITN ITI /ITN ITI FIGURE 6-4 Collaborative workflow for ITI/ITN immune biomarker discovery and development. Figure 6-4.eps landscape
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2 REDESIGNING THE CLINICAL EFFECTIVENESS RESEARCH PARADIGM Leveraged discoveries Marketable therapeutics FIGURE 6-5 ITI: At the intersection of academia and industry. Together the ITN and ITI couple6clinicalstrials and discovery research Figure -5.ep bitmap image with milestone-oriented industry standards for quality control, standard operating procedures, with validated production methodologies.
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thanks its funders, The Pew Charitable Trusts and the National Human Genome Research Institute, for making possible its public engagement work. Gail Geller, David Kaufman, Lisa LeRoy, Juli Murphy, and Joan Scott each played invaluable roles in its focus groups.
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This model has driven communication of science and technology for so long despite its very obvious shortcoming: Neither public support for research nor scientific literacy has increased notably in all of that time. In fact, asymmetric communications practices have cultivated a public wary and mistrustful of the scientific enterprise (Millstone and van Zwanenberg, 2000)
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. As a consequence, research-performing institutions increasingly are turning to public engagement and public consultation approaches to enlist public support (Bauer et al., 2007)
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. In terms of the translation of human genetics from research to clinical practice, public engagement can be undertaken at a number of points along the discovery pipeline (Figure 6-6)
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Rather, public engagement if it exists at all is clustered almost exclusively around health outcomes, principally comprising such items as information, advertising, and health campaigns. The next level upstream from simply informing is to consult, to obtain meaningful feedback from the public, and then to collaborate, to a point where the public is involved in issue identification, framing, prioritization, and agenda setting for research.
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. Accordingly, the GPPC entered into a cooperative agreement with the National Human Genome Research Institute at the NIH to learn what the public knows and thinks about large-scale genetic databases and to pilot test engagement strategies; as part of this effort we are conducting interviews, surveys, focus groups, and town hall meetings.
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They asked us to talk first about the project with veterans. This quote from a veteran shows again the value of symmetric communication: "The fact that they have people sitting around talking about this in advance of even starting to 16 Unpublished data, Genetics and Public Policy Center.
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Mutual satisfaction requires that researchers be open to reasonable changes requested of them, just as effective -- and ethical -- public engagement programs in science should signal a willingness to incorporate public input in science policy, regulatory programs, or research design. REFERENCES Bauer, M., N
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2002. The Immune Tolerance Network: A new paradigm for developing tolerance-inducing therapies.
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