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      A questionnaire to assess the relevance and credibility of observational studies to inform health care decision making: an ISPOR-AMCP-NPC Good Practice Task Force report.

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          Abstract

          Evidence-based health care decisions are best informed by comparisons of all relevant interventions used to treat conditions in specific patient populations. Observational studies are being performed to help fill evidence gaps. Widespread adoption of evidence from observational studies, however, has been limited because of various factors, including the lack of consensus regarding accepted principles for their evaluation and interpretation. Two task forces were formed to develop questionnaires to assist decision makers in evaluating observational studies, with one Task Force addressing retrospective research and the other Task Force addressing prospective research. The intent was to promote a structured approach to reduce the potential for subjective interpretation of evidence and drive consistency in decision making. Separately developed questionnaires were combined into a single questionnaire consisting of 33 items. These were divided into two domains: relevance and credibility. Relevance addresses the extent to which findings, if accurate, apply to the setting of interest to the decision maker. Credibility addresses the extent to which the study findings accurately answer the study question. The questionnaire provides a guide for assessing the degree of confidence that should be placed from observational studies and promotes awareness of the subtleties involved in evaluating those.

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          Author and article information

          Journal
          Value Health
          Value in health : the journal of the International Society for Pharmacoeconomics and Outcomes Research
          1524-4733
          1098-3015
          Mar 2014
          : 17
          : 2
          Affiliations
          [1 ] Real World Data and Analytics, Pfizer, New York, NY, USA.
          [2 ] Division of Pharmaceutical Evaluation and Policy, Little Rock, AR, USA. Electronic address: bmartin@uams.edu.
          [3 ] Institute of Health Economics, Edmonton, AB, Canada; Department of Epidemiology and Community Medicine, University of Ottawa, Ottawa, ON, Canada; University for Health Sciences, Medical Informatics and Technology, Tirol, Austria.
          [4 ] Comprehensive Health Insights, Humana, Inc., Cincinnati, OH, USA.
          [5 ] OmedaRx, Portland, OR, USA.
          [6 ] Blue Shield of California, Woodland Hills, CA, USA.
          [7 ] Healthcare Quality, Optimer Pharmaceuticals, Inc., Jersey City, NJ, USA.
          [8 ] University of Maryland, School of Pharmacy, Pharmaceutical Health Services Research, Baltimore, MD, USA.
          [9 ] HEOR, Novartis Pharmaceuticals Corporation, East Hanover, NJ, USA.
          [10 ] OptumLabs, Cambridge, MA, USA.
          Article
          S1098-3015(14)00009-6 NIHMS636381
          10.1016/j.jval.2013.12.011
          4217656
          24636373
          3d79405c-ad62-4c76-9659-7f7997ea380a
          Copyright © 2014 International Society for Pharmacoeconomics and Outcomes Research (ISPOR). Published by Elsevier Inc. All rights reserved.
          History

          bias,checklist,comparative effectiveness research,confounding,consensus,credibility,decision making,prospective observational study,quality,questionnaire,relevance,retrospective observational study,validity

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