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Privacy-preserving Analytic Methods for Multisite Comparative Effectiveness and Patient-centered Outcomes Research

Bibliographic Data

ID9103602
AuthorsSengwee Toh (0000-0002-5160-0810, Harvard University, corresponding author), Susan Shetterly (0000-0001-8208-8576, Kaiser Permanente), J David Powers (0000-0003-2779-3402, Kaiser Permanente), David Arterburn (0000-0002-5208-8492, Kaiser Permanente Washington Health Research Institute)
Year2014
Volume52
Issue7
Pages664-668
Publication date2014-07-01
Peer ReviewedYes
Open AccessNo
TypeARTICLE
VenueMedical Care (JOURNAL)
Journal identifiersISSN: 0025-7079 • E-ISSN: 1537-1948
PublisherOvid Technologies (Wolters Kluwer Health) (PUBLISHER)
DOI10.1097/mlr.0000000000000147
PMID24926715
OpenAlexW2323128682
LanguageEN
References cited5

BACKGROUND: For privacy and practical reasons, it is sometimes necessary to minimize sharing of individual-level information in multisite studies. However, individual-level information is often needed to perform more rigorous statistical analysis. OBJECTIVES: To compare empirically 3 analytic methods for multisite studies that only require sharing of summary-level information to perform statistical analysis that have traditionally required access to detailed individual-level data from each site. RESEARCH DESIGN, SUBJECTS, AND MEASURES: We analyzed data from a 7-site study of bariatric surgery outcomes within the Scalable Partnering Network. We compared the long-term risk of rehospitalization between adjustable gastric banding and Roux-en-y gastric bypass procedures using a stratified analysis of propensity score (PS)-defined strata, a case-centered analysis of risk set data, and a meta-analysis of site-specific effect estimates. Their results were compared with the result from a pooled individual-level data analysis. RESULTS: The study included 1327 events (18.1%) among 7342 patients. The adjusted hazard ratio was 0.71 (95% CI, 0.59, 0.84) comparing adjustable gastric banding with Roux-en-y gastric bypass in the individual-level data analysis. The corresponding effect estimate was 0.70 (0.59, 0.83) in the PS-stratified analysis, 0.71 (0.59, 0.84) in the case-centered analysis, and 0.71 (0.60, 0.84) in both the fixed-effect and random-effects meta-analysis. CONCLUSIONS: In this empirical study, PS-stratified analysis, case-centered analysis, and meta-analysis produced results that are identical or highly comparable with the result from a pooled individual-level data analysis. These methods have the potential to be viable analytic alternatives when sharing of individual-level information is not feasible or not preferred in multisite studies

Comparative effectiveness research · Data mining · Meta-analysis · Random effects model · Statistical analysis · Statistics · Advanced Causal Inference Techniques · Bariatric Surgery and Outcomes · Computer Science · Genetic Associations and Epidemiology · Internal Medicine · Mathematics · Medicine

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