Medical Care

Skip Navigation LinksHome > June 2010 - Volume 48 - Issue 6 > Privacy-Maintaining Propensity Score-Based Pooling of Multip...
Medical Care:
doi: 10.1097/MLR.0b013e3181d59541
Comparative Effectiveness

Privacy-Maintaining Propensity Score-Based Pooling of Multiple Databases Applied to a Study of Biologics

Rassen, Jeremy A. ScD*; Solomon, Daniel H. MD, MPH*†; Curtis, Jeffrey R. MD, MPH‡; Herrinton, Lisa PhD§; Schneeweiss, Sebastian MD, ScD*

Collapse Box


Introduction: A large study on the safety of biologics required pooling of data from multiple data sources, but while extensive confounder adjustment was necessary, private, individual-level covariate information could not be shared.

Objectives: To describe the methods of pooling data that investigators considered, and to detail the strengths and limitations of the chosen method: a propensity score (PS)-based approach that allowed for full multivariate adjustment without compromising patient privacy.

Research Design: The project had a central data coordinating center responsible for collection and analysis of data. Private data could not be transmitted to the data coordinating center. Investigators assessed 4 methods for pooled analyses: full covariate sharing, cell-aggregated sharing, meta-analysis, and the PS-based method. We evaluated each method for protection of private information, analytic integrity and flexibility, and ability to meet the study's operational and statistical needs.

Results: Analysis of 4 example datasets yielded substantially similar estimates if data were pooled with a PS versus individual covariates (0%–3% difference in point estimates). Several practical challenges arose. (1) PSs are best suited for dichotomous exposures but 6 or more exposure categories were desired; we chose a series of exposure contrasts with a common referent group. (2) Subgroup analyses had to be specified a priori. (3) Time-varying exposures and confounders required appropriate analytic handling including re-estimation of PSs. (4) Detection of heterogeneity among centers was necessary.

Conclusions: The PS-based pooling method offered strong protection of patient privacy and a reasonable balance between analytic integrity and flexibility of study execution. We would recommend its use in other studies that require pooling of databases, multivariate adjustment, and privacy protection.

© 2010 Lippincott Williams & Wilkins, Inc.


Article Tools


Article Level Metrics

Search for Similar Articles
You may search for similar articles that contain these same keywords or you may modify the keyword list to augment your search.