title: 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.
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.
authors.affiliation: Real World Data and Analytics, Pfizer, New York, NY, USA.
authors.forename: Marc L
authors.initials: ML
authors.lastname: Berger
authors.affiliation: Division of Pharmaceutical Evaluation and Policy, Little Rock, AR, USA. Electronic address: bmartin@uams.edu.
authors.forename: Bradley C
authors.initials: BC
authors.lastname: Martin
authors.affiliation: 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.
authors.forename: Don
authors.initials: D
authors.lastname: Husereau
authors.affiliation: Comprehensive Health Insights, Humana, Inc., Cincinnati, OH, USA.
authors.forename: Karen
authors.initials: K
authors.lastname: Worley
authors.affiliation: OmedaRx, Portland, OR, USA.
authors.forename: J Daniel
authors.initials: JD
authors.lastname: Allen
authors.affiliation: Blue Shield of California, Woodland Hills, CA, USA.
authors.forename: Winnie
authors.initials: W
authors.lastname: Yang
authors.affiliation: Healthcare Quality, Optimer Pharmaceuticals, Inc., Jersey City, NJ, USA.
authors.forename: Nicole C
authors.initials: NC
authors.lastname: Quon
authors.affiliation: University of Maryland, School of Pharmacy, Pharmaceutical Health Services Research, Baltimore, MD, USA.
authors.forename: C Daniel
authors.initials: CD
authors.lastname: Mullins
authors.affiliation: HEOR, Novartis Pharmaceuticals Corporation, East Hanover, NJ, USA.
authors.forename: Kristijan H
authors.initials: KH
authors.lastname: Kahler
authors.affiliation: OptumLabs, Cambridge, MA, USA.
authors.forename: William
authors.initials: W
authors.lastname: Crown
mesh_terms: D026683:Advisory Committees; D003657:Decision Making; D003695:Delivery of Health Care / Q000379:methods; D019317:Evidence-Based Medicine; D006801:Humans; D038622:Internationality; D064887:Observational Studies as Topic / Q000379:methods / Q000592:standards*; D012107:Research Design / Q000592:standards; D011795:Surveys and Questionnaires
keywords: bias; checklist; comparative effectiveness research; confounding; consensus; credibility; decision making; prospective observational study; quality; questionnaire; relevance; retrospective observational study; validity