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Review
. 2020 Apr;107(4):834-842.
doi: 10.1002/cpt.1754. Epub 2020 Jan 24.

Analytic and Data Sharing Options in Real-World Multidatabase Studies of Comparative Effectiveness and Safety of Medical Products

Sengwee Toh  1
Affiliations
Review

Analytic and Data Sharing Options in Real-World Multidatabase Studies of Comparative Effectiveness and Safety of Medical Products

Sengwee Toh. Clin Pharmacol Ther. 2020 Apr.

Abstract

A wide range of analytic and data sharing options are available in nonexperimental multidatabase studies designed to assess the real-world benefits and risks of medical products. Researchers often consider six scientific domains when choosing among these options-study design, exposure type, outcome type, covariate summarization technique, covariate adjustment method, and data sharing approach. This article reviews available analytic and data sharing options and discusses key scientific and practical considerations when choosing among these options in multidatabase studies of comparative effectiveness and safety of medical products. The scientific considerations must be balanced against what the data-contributing sites are able or willing to share. While pooling of person-level data sets remains the most familiar and analytically flexible approach, newer analytic and data sharing approaches that share less granular summary-level information may be equally valid and preferred in some multidatabase studies, especially when sharing of person-level data is challenging or infeasible.

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Conflict of interest statement

Conflict of interest: The authors declared no competing interests for this work.

Figures

Figure 1.
Figure 1.
The organizational structure of a typical multi-database study of comparative effectiveness and safety of medical products. Panel A shows a multi-database study in which the data-contributing sites each shares a person-level dataset with the analysis center. In a typical person-level dataset, each row represents an observation of a patient and each column represents a variable. Panel B shows a multi-database study in which the data-contributing sites each shares a summary-level dataset with the analysis center. The information included in the summary-level dataset varies by the analytic and data sharing option used. See Tables S1–S7 for some examples of person-level and summary-level datasets.
Figure 2.
Figure 2.
Six scientific domains of analytic and data sharing considerations in real-world multi-database studies of comparative effectiveness and safety of medical products.
Figure 3.
Figure 3.
Trade-off between analytic flexibility and privacy protection, by analytic and data sharing option. Analytic flexibility is broadly defined by the ability to perform pre-specified and post hoc analyses and the complexity of these analyses.
Figure 4.
Figure 4.
The amount of data processing and statistical analysis done at the data-contributing site versus the analysis center, by analytic and data sharing option
Figure 4.
Figure 4.
The amount of data processing and statistical analysis done at the data-contributing site versus the analysis center, by analytic and data sharing option
See this image and copyright information in PMC

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