Published Nov 2009
Citation
Berger ML, Mamdani M, Atkins D, Johnson ML. Good research practices for comparative effectiveness research: defining, reporting and interpreting nonrandomized studies of treatment effects using secondary data sources: the ISPOR Good Research Practices for Retrospective Database Analysis Task Force Report—part I. Value Health. 2009;12(8):1044-1052.
Abstract
Objectives: Health insurers, physicians, and patients worldwide need
information on the comparative effectiveness and safety of prescription
drugs in routine care. Nonrandomized studies of treatment effects using
secondary databases may supplement the evidence based from randomized
clinical trials and prospective observational studies. Recognizing the challenges
to conducting valid retrospective epidemiologic and health services
research studies, a Task Force was formed to develop a guidance document
on state of the art approaches to frame research questions and report
findings for these studies.
Methods: The Task Force was commissioned and a Chair was selected
by the International Society for Pharmacoeconomics and Outcomes
Research Board of Directors in October 2007. This Report, the first of
three reported in this issue of the journal, addressed issues of framing
the research question and reporting and interpreting findings.
Results: The Task Force Report proposes four primary characteristics—
relevance, specificity, novelty, and feasibility while defining the research
question. Recommendations included: the practice of a priori specification
of the research question; transparency of prespecified analytical plans,
provision of justifications for any subsequent changes in analytical plan,
and reporting the results of prespecified plans as well as results from
significant modifications, structured abstracts to report findings with scientific
neutrality; and reasoned interpretations of findings to help inform
policy decisions.
Conclusions: Comparative effectiveness research in the form of nonrandomized
studies using secondary databases can be designed with rigorous
elements and conducted with sophisticated statistical methods to improve
causal inference of treatment effects. Standardized reporting and careful
interpretation of results can aid policy and decision-making.
Keywords: comparative effectiveness, health policy, nonrandomized
studies, secondary databases.
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Reports
- Good research practices for comparative effectiveness research: analytic methods to improve causal inference from nonrandomized studies of treatment effects using secondary data sources - Task Force Report Part III
- Good research practices for comparative effectiveness research - bias & confounding in the design - Task Force Report Part II
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