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Med Care. 2014 Jul;52(7):664-8. doi: 10.1097/MLR.0000000000000147.

Privacy-preserving analytic methods for multisite comparative effectiveness and patient-centered outcomes research.

Author information

1
*Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute, Boston, MA †Institute for Health Research, Kaiser Permanente Colorado, Denver, CO ‡Group Health Research Institute, Seattle, WA.

Abstract

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.

PMID:
24926715
DOI:
10.1097/MLR.0000000000000147
[Indexed for MEDLINE]

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