@article{89963de9d0014ffd8a92d3989d0736f5,
title = "Reporting to Improve Reproducibility and Facilitate Validity Assessment for Healthcare Database Studies V1.0",
abstract = "Purpose: Defining a study population and creating an analytic dataset from longitudinal healthcare databases involves many decisions. Our objective was to catalogue scientific decisions underpinning study execution that should be reported to facilitate replication and enable assessment of validity of studies conducted in large healthcare databases. Methods: We reviewed key investigator decisions required to operate a sample of macros and software tools designed to create and analyze analytic cohorts from longitudinal streams of healthcare data. A panel of academic, regulatory, and industry experts in healthcare database analytics discussed and added to this list. Conclusion: Evidence generated from large healthcare encounter and reimbursement databases is increasingly being sought by decision-makers. Varied terminology is used around the world for the same concepts. Agreeing on terminology and which parameters from a large catalogue are the most essential to report for replicable research would improve transparency and facilitate assessment of validity. At a minimum, reporting for a database study should provide clarity regarding operational definitions for key temporal anchors and their relation to each other when creating the analytic dataset, accompanied by an attrition table and a design diagram. A substantial improvement in reproducibility, rigor and confidence in real world evidence generated from healthcare databases could be achieved with greater transparency about operational study parameters used to create analytic datasets from longitudinal healthcare databases.",
keywords = "healthcare databases, longitudinal data, methods, pharmacoepidemiology, replication, reproducibility, Transparency",
author = "Wang, {Shirley V.} and Sebastian Schneeweiss and Berger, {Marc L.} and Jeffrey Brown and {de Vries}, Frank and Douglas, {Ian J.} and Gagne, {Joshua J.} and Rosa Gini and Olaf Klungel and Mullins, {C. Daniel} and Nguyen, {Michael D.} and Rassen, {Jeremy A.} and Liam Smeeth and Miriam Sturkenboom",
note = "Funding Information: Stakeholders involved in healthcare are increasingly interested in evaluating additional streams of evidence beyond randomized clinical trials and are turning their attention toward real‐world evidence from large healthcare database studies. This interest has led to groundbreaking infrastructure and software to scale up capacity to generate database evidence from public and private stakeholders. The United States FDA's Sentinel System is one example of a large scale effort to create an open source analytic infrastructure. Supported by FDA to achieve its public health surveillance mission, the tools and infrastructure are also available to the research community through Reagan Udall Foundation's IMEDS system. Sentinel has committed itself to transparency through online posting of study protocols, final reports, and study specifications, including temporal anchors, how data are processed into a common data model, and study design details. Similarly, the Canadian government, the European Medicines Agency (EMA) and several countries in Asia have developed consortia to facilitate transparent evidence generation from healthcare databases, including the Canadian Network for Observational Drug Effect Studies (CNODES),8 Innovative Medicines Initiative (IMI), ENCePP70 and others.9 Funding Information: Pharmaceuticals and Medical Devices Agency Gr{\"u}nenthal GmbH Head of Global Epidemiology, Boehringer Ingelheim GmbH Instituto Nacional de Cancer AstraZeneca Boston Scientific Grimsdyke House Eli Lilly Karolinska Institute Novartis Institute of Bio pharmaceutical Science, College of Medicine, National Cheng Kung University Bristol‐Myers Squibb RTI Health Solutions Optum London School of Hygiene and Tropical Medicine MIE Resources University of Utah, Pharmacotherapy Outcomes Research Center Teva Pharmaceuticals Nestle Health Science Roche, Pharmaceuticals Division Bayer Novartis University of Maryland, School of Pharmacy Takeda University of New South Wales Australia School of Pharmacy and Medical Sciences, University of South Australia Publisher Copyright: {\textcopyright} 2017 The Authors. Pharmacoepidemiology & Drug Safety Published by John Wiley & Sons Ltd.",
year = "2017",
month = sep,
day = "1",
doi = "10.1002/pds.4295",
language = "English",
volume = "26",
pages = "1018--1032",
journal = "Pharmacoepidemiology and Drug Safety",
issn = "1053-8569",
publisher = "John Wiley & Sons Inc.",
number = "9",
}