Benefits and pitfalls of pooling datasets from comparable observational studies: combining US and Dutch nursing home studies

Author:

van der Steen JT1,Kruse RL2,Szafara KL3,Mehr DR2,van der Wal G4,Ribbe MW5,D'Agostino RB6

Affiliation:

1. Department of Nursing Home Medicine, EMGO Institute, VU University Medical Center, Amsterdam; Department of Public and Occupational Health, EMGO Institute, VU University Medical Center, Amsterdam

2. Department of Family and Community Medicine, University of Missouri, Columbia, Missouri

3. Department of Internal Medicine, Institute of Gerontology, University of Michigan Medical School, Ann Arbor, Michigan

4. Department of Public and Occupational Health, EMGO Institute, VU University Medical Center, Amsterdam; Netherlands Health Care Inspectorate, The Hague

5. Department of Nursing Home Medicine, EMGO Institute, VU University Medical Center, Amsterdam

6. Mathematics and Statistics Department, Boston University, Boston, Massachusetts

Abstract

Different research groups sometimes carry out comparable studies. Combining the data can make it possible to address additional research questions, particularly for small observational studies such as those frequently seen in palliative care research. We present a systematic approach to pool individual subject data from observational studies that addresses differences in research design, illustrating the approach with two prospective observational studies on treatment and outcomes of lower respiratory tract infection in US and Dutch nursing home residents. Benefits of pooling individual subject data include enhanced statistical power, the ability to compare outcomes and validate models across sites or settings, and opportunities to develop new measures. In our pooled dataset, we were able to evaluate treatments and end-of-life decisions for comparable patients across settings, which suggested opportunities to improve care. In addition, greater variation in participants and treatments in the combined dataset allowed for subgroup analyses and interaction hypotheses, but required more complex analytic methods. Pitfalls included the large amount of time required for equating study procedures and variables and the need for additional funding.

Publisher

SAGE Publications

Subject

Anesthesiology and Pain Medicine,General Medicine

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