Learning What Works Infrastructure Required for Comparative Effectiveness Research: Workshop Summary (2011) / Chapter Skim
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4 The Talent Required
4 The Talent Required
Pages 191-240
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, Don E Detmer (American Medical Informatics Association)
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Hersh, M.D., Oregon Health and Science University; Timothy S Carey, M.D., M.P.H., University of North Carolina; Thomas Ricketts, Ph.D., University of North Carolina; Mark Helfand, M.D., M.P.H., Oregon Health and Science University; Nicole Floyd, M.P.H., Oregon Health and Science University; Richard N
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committee on "knowing what works in health care" emphasizes the central role of comparative effectiveness reviews as a critical linkage between evidencebased medicine (EBM) and practice guidelines, coverage decision making, clinical practice, and health policy (IOM, 2008)
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(Helfand et al., 2005) , which perform comparative effectiveness reviews -- that is, syntheses of existing research on the effectiveness, comparative effectiveness, and comparative harms of different healthcare interventions (Slutsky et al., 2010)
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While this heterogeneity is probably appropriate to the status of CER as an emerging field of study and effort, it also makes planning for its workforce needs challenging. Investigators and staff in CER come from many backgrounds, including clinical medicine, clinical epidemiology, biomedical informatics, biostatistics, and health policy.
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As illustrated in Figure 4-1, information and knowledge originate from clinical trials and other clinical research studies, particularly studies using registries, EHRs, practice network data, and pharmacoepidemiologic studies. This information is synthesized in comparative effectiveness reviews and technology assessments, sometimes including meta-analyses, decision analyses, or economic analyses, which inform the development of evidence-based clinical guidelines and decisions about coverage.
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Clinical Epidemiology/Pharamcoepidemiology/ Biomedical Informatics Evidence-Based Medicine Electronic Clinical Data Clinical Other Clinical Information - Electronic Health Record Data into Data Warehouses Trials Studies Needs - Clinical Decision Support - Public Health Informatics Systematic Reviews Data Mining and Analysis - Prioritization - Validation Methods Development Health Services Research Clinical - Outcomes Research Guidelines Guideline - Decision Science Development Development - Economics - Benefits Design and - Coverage Decisions Implementation - Formulary Decisions Guideline Communications Implementation Dissemination - Translation for Clinicians - Translation for Patients/Consumers FIGURE 4-1 Key activity domains for comparative effectiveness research. Workforce development will be critical to support the many primary functions within each of these domains as well as to foster the cross-domain interactions and activities identified (e.g., methods development, identifying information needs)
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It can be difficult to determine from such trials -- and from the systematic reviews that aggregate them -- what the "best" treatments are. In contrast, effectiveness trials, such as practical clinical trials, compare treatments in a head-to-head manner in settings that can be applied to real-world clinical practice.
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. These reviews follow the explicit principles of systematic reviews, but they are more comprehensive and multidisciplinary, requiring a wider range of expertise.
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Individual comparative effectiveness reviews are usually conducted by project teams led by a project principal investigator under the oversight of a center director. The center director must have exceptional, in-depth disciplinary knowledge and skills in the underlying core disciplines of clinical epidemiology, clinical medicine, and medical decision making.
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to develop an analytic framework and key questions addressing uncertainties that underlie controversy or variation in practice; they should have a broad view of eligible evidence, one that has recognized that the kinds of evidence included in a review depends on the kinds of questions asked and on what kinds of evidence are available to answer them; and they should understand that while systematic reviews do not in themselves dictate decisions, they can play a valuable role in helping decision makers clarify what is known as well as unknown about the issues surrounding important decisions and, in that way, affect both policy and clinical practice (Helfand, 2005)
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have noted that systematic reviews published in the medical literature have a half-life of about 5.5 years, with about 23 percent requiring updating within 2 years of publication (Shojania et al., 2007)
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Programs in Canada and Sweden provide these as well. Current training programs are probably adequate to absorb a moderate increase in demand for systematic reviews, but significant expansion of systematic reviews will require more capacity, which will inevitably lead to competition with other clinical research needs.
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To sum up the areas considered so far, analysis of the relevant data in the areas of clinical epidemiology, clinical research, pharmacoepidemiology, and EBM show that the workforce required is likely to be substantial, not available solely based on those who are currently trained, and dependent on the amount of systematic reviews, clinical trials, and other work related to CER that policy makers and others believe must be funded. Furthermore, for all categories of workers, and especially physicians, CER will find itself in a competition both for various types of clinical researchers and also for clinical practitioners, for which there is already a looming shortage (Dall et al., 2006)
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data mining, text mining, and other forms of knowledge discov ery (e.g., tools that help streamline the production of systematic reviews) (Cohen et al., 2006)
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. "Advanced" HIT is generally assumed to be stage 4, which includes computerized physician order entry (CPOE)
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This has led to the 10×10 ("ten by ten") program of the American Medical Informatics Association, which aims to provide a detailed introduction in BMI to 10,000 individuals by the year 2010 (Hersh and Williamson, 2007)
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informatics research applications, including comparative effectiveness research (CER) Data warehouse manager Oversees development IT, CS, or MIS of research data warehouse Web designer Designs Web front IT, CS, or MIS end for data access systems Web engineer Deploys Web back IT, CS, or MIS end for data access systems Research applications Develops CER and other IT, CS, or MIS programmer applications Database administrator Administers research IT, CS, or MIS data warehouse Project manager Manages CER and other IT, CS, or MIS projects Biomedical Informatics Chief medical information Oversees clinical BMI officer IT applications, including research data warehouse Physician leads Provide leadership in BMI, formally or informally implementation and use of electronic health records Medical informatics Oversees data mining BMI researcher activities for CER Medical informatics Oversees information BMI researcher needs assessment for CER Research analyst Works with medical Variety informatics researchers to collect data and carry out analysis with medical informatics researchers
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To create evidence-based guidelines, knowledge must be distilled from the scientific literature and combined with expert judgment. Authors typically work from evidence tables, meta-analyses, and systematic reviews to summarize the facts that are known about a topic.
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Expertise in clinical care comes most often from clinical training and experience. Expertise in judging evidence may come from coursework in epidemiology and study design.
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There will, however, be some particular challenges to health services researchers as they become involved in CER studies.
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There is a substantial overlap between the core competencies in Table 4-3 and the skills needed to conduct CER, including a knowledge of study designs, the ability to develop conceptual models, responsible conduct of research, secondary data methods, study design, implementation of protocols, clear scientific communication, and collaboration with stakeholders. HSR is recognized in universities and research institutes as a pathway for development of advanced inquiry.
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Application of HSR foundational Health, financing of health care, organization knowledge to health policy problems of health care, health policy, access and use, quality of care, health informatics, literature review Pose innovative HSR questions Scientific method and theory, literature review, proposal development Interventional and observational study Study design, survey research, qualitative designs research Primary data collection methods Health informatics, survey research, qualitative research, data acquisition and quality control Secondary data acquisition methods Health informatics, HSR data sources, data acquisition and quality control Conceptual models and operational Scientific method and theory, measurement measures and variables Implementation of research protocols Health informatics, survey research, qualitative research, data acquisition and quality control Responsible conduct of research Research ethics Multidisciplinary teamwork Teamwork Data analysis Advanced HSR analytic methods, economic evaluation and decision sciences Scientific communication Proposal development, dissemination Stakeholder collaboration and Health policy, dissemination knowledge translation SOURCE: Data derived from Forrest et al., 2005, 2009. but that the field is currently very labile.
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, their families and caregivers, clinicians, healthcare administrators, governmental policy makers, and employers. Evidence translation is the process of extracting key messages from evidence summaries (systematic reviews or technology assessments)
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The multidisciplinary team required to perform evidence translation and dissemination includes a variety of individuals who have different skills and who commonly have diverse educational backgrounds. While some individuals may play more than one role (e.g., a clinician with skills in clinical research methodologies)
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Trialists and systematic reviewers must, for example, work with domain experts to determine the key aspects of their research questions to be studied. Likewise,
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2. What quantity of CER systematic reviews will need to be performed?
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While the number of personnel required for systematic reviews is relatively well understood, the requirements for the other categories of clinical trials and pharmacoepidemiological analyses are much less clear. Beyond clinical epidemiology, the picture becomes even less certain.
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Likewise, who will fund the development of clinical practice guidelines? For studies derived from the secondary use of clinical data, which medical centers and health systems will be required to participate, and how will they be funded?
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Particularly for the workforce required, and for the components within it (such as clinical epidemiology, BMI, and HSR) , research should be undertaken to identify not only the skills required now, but also how the workforce will be best organized in the future for maximum efficiency, best-quality output, and the anticipated expansion.
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Funding this research requires approximately $8 million to $10 million in incremental spending per year and the support of Ministry of Health staff, as well as of hospital and university investigators with a wide variety of expertise, including epidemiologists, biostatisticians, physicians, health economists, health policy experts, and health services researchers. The direct and explicit link between the decision makers and the CER entities facilitates research timeliness and helps ensure a clear focus on generating information that is carefully designed to satisfy the needs of decision makers.
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Nevertheless, provincial governments still pay for the majority of healthcare costs, and the recent surge in the development of promising but often unproven medical technologies has placed added pressure on both public payers (i.e., provincial ministries of health) and providers (i.e., hospitals)
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Following a brief overview of the workforce and funding requirements, it discusses potential lessons for policy makers in the United States. Developing a Comparative Effectiveness Capacity for Nondrug Medical Technologies Establishing an Agenda and Making Policy Recommendations As has happened in most jurisdictions, nondrug healthcare interventions have historically rapidly diffused into the Ontario healthcare system, even in the absence of definitive clinical evidence of benefit.
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22 LEARNING WHAT WORKS BOX 4-2 Comparative Effectiveness Entities for Drug Evaluation At the national level, new drugs undergo a systematic review (via what is called the Common Drug Review process) by the Canadian Agency for Drugs and Technologies in Health.
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NOTE: GRADE = Grading Recommendations Assesment, Development, and Evalu ation Working Group; MAS = Medical Advisory Secretariat; MOHLTC = Ministry of Health and Long Term Care; OHTAC = Ontario Health Technology Assessment Committee; PATH = Program for the Assessment of Technologies in Health; THETA = Toronto Health Economic and Technology Assessment Collaboration. Figure 4-2, editable SOURCE: Whicher, D
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OHTAC has determined that a multifaceted approach to public engagement is preferable to programs that conduct field evaluations to generate an evidence base for important high-demand health technologies. There are several programs in Ontario, all of which are independent and largely government funded, with the capacity to carry out field evaluations for promising technologies.
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Appropriate study design is discussed by these independent entities in collaboration with experts knowledgeable about the health technology under investigation. While field evaluations are being conducted, the Ontario Health Insurance Plan covers physician costs for the medical technologies used for patients participating in the study as long as a technology is already insured (Goeree and Levin, 2006; Levin et al., 2007)
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22 LEARNING WHAT WORKS BOX 4-3 Comparative Effectiveness Study Comparing Drug-Eluting Stents to Bare Metal Stents for Treatment of Coronary Artery Disease In 2002, the Medical Advisory Secretariat completed a gray literature based health technology assessment on the clinical effectiveness of drug-eluting stents (DESs) compared to bare-metal stents (BMSs)
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ICES faculty are able to link large data sets to monitor patterns of use for various drugs and medical technologies as well as patterns in quality of care (Center for Global eHealth Innovation University Health Network, n.d.)
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Workforce Analysis for Comparative Effectiveness Network in Ontario Personnel The activities described above require staff from a variety of backgrounds, including health policy experts, health economists, clinical epidemiologists, biostatisticians, health services researchers, human factors analysts, and engineers, as well as physicians, nurses, hospital representatives, and information specialists. In addition, the success of this network is dependent on the willingness of university faculty and clinical experts to assist in the development of study designs and the collection of necessary data.
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. Provincial Government Funding for Field Evaluations Currently, the Ministry of Health spends CA$8 million to CA$10 million a year on field evaluations for high-demand, emerging medical technologies.
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This close and ongoing contact between the Ministry of Health, OHTAC, MAS, and the various programs that conduct field evaluations and economic analyses ensures that studies are responsive to the questions of importance to policy makers and potential purchasers. In Ontario, studies are designed collaboratively with input from government officials, hospital representatives, physicians, health economists, and health services researchers.
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Create Partnerships Between Universities and Programs Responsible for Conducting Field Evaluations The Ontario technology assessment network relies on partnerships between programs conducting field evaluations and various universities, such as the University of Toronto (THETA) and McMaster University (PATH)
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Methodology Implications for the United States Draw on Existing Capacities to Support Comparative Effectiveness Research Government funding for CER in Ontario is relatively small because MAS, PATH, and THETA are able to make use of existing capacities within the province, such as ICES and university researchers and clinicians, to help support their projects. Once these programs receive requests from OHTAC, they are able to launch studies fairly quickly and efficiently, which is critical given the rapid evolution of high-demand, emerging medical technologies.
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Decision makers in Ontario rely on information from a number of sources, including systematic reviews, cost-effectiveness modeling, and (if necessary) field evaluations.
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Clinical Trials 3:496-502. Center for Global eHealth Innovation University Health Network.
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Journal of Clinical Epidemiology 59:1040-1048.
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2005. Clinical epidemiology: How to do clinical practice research, 3rd ed.
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2007. How quickly do systematic reviews go out of date?
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2003. Practical clinical trials -- Increasing the value of clinical research for decision making in clinical and health policy.
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