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Assessing risk of bias and confounding in observational studies of interventions or exposures : further development of the RTI item bank / investigators, Meera Viswanathan, Nancy D Berkman, Donna M Dryden, Lisa Hartling.

Author/creator Viswanathan, Meera author.
Format Electronic and Book
Publication Info Rockville (MD) : Agency for Healthcare Research and Quality (US), 2013.
Description1 online resource (1 PDF file (various pagings)) : illustrations.
Supplemental Content Direct link to resource
Subject(s)
Other author/creatorBerkman, Nancy D., editor.
Other author/creatorDryden, Donna M., editor.
Other author/creatorHartling, Lisa, editor.
Other author/creatorUnited States. Agency for Healthcare Research and Quality, issuing body.
Other author/creatorRTI International-University of North Carolina Evidence-based Practice Center, author.
Other author/creatorUniversity of Alberta Evidence-based Practice Center, author.
Series Methods research report
Methods research report. ^A1330188
Summary OBJECTIVES: To develop a framework for the assessment of the risk of bias and confounding against causality from a body of observational evidence, and to refine a tool to aid in identifying risk of bias, confounding, and precision in individual studies. METHODS: In conjunction with a Working Group, we sought to develop an overarching approach to assess the effect of confounding across the body of observational study evidence and within individual studies. We sought feedback from Working Group members on critical sources of bias most common to each observational study design type. We then refined and reduced the set of "core" questions that would most likely be necessary for evaluating risk of bias and confounding concerns for each design and refined the instructions provided to users to improve clarity and usefulness. RESULTS: We developed a framework that identifies additional steps necessary to evaluate the validity of causal claims in observational studies of benefits and harms from interventions. With the help of the Working Group, we narrowed the list of RTI Item Bank questions for evaluating risk of bias and precision from 29 to 16. Working Group members also provided their opinion of the most important questions for assessing risk of bias for four common observational study design types. CONCLUSIONS: Attributing causality to interventions from such evidence requires prespecification of anticipated sources of confounding prior to the review, followed by appraisal of potential confounders at three levels: outcomes, studies, and the body of evidence. We propose a substantial expansion in the critical appraisal of confounding when systematic reviews include observational studies for evaluation of benefits or harms of interventions. Questions about burden, reliability, and validity remain to be answered. Consensus around specific items necessary for evaluating risk of bias for different types of observational study designs does not yet exist.
General noteTitle from PDF title page.
General note"August 2013."
Bibliography noteIncludes bibliographical references.
Funding informationPrepared for: Agency for Healthcare Research and Quality, U.S. Department of Health and Human Services, 540 Gaither Road, Rockville, MD 20850; www.ahrq.gov Contract No. 290-2007-10056-I. Prepared by: RTI International-University of North Carolina at Chapel Hill Evidence-based Practice Center, Research Triangle Park, NC, University of Alberta Evidence-based Practice Center, Edmonton, Canada
Source of descriptionVersion viewed January 23, 2014.

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