- Richard L Tannen, professor of medicine,
- Mark G Weiner, associate professor of medicine,
- Dawei Xie, assistant professor of biostatistics and epidemiology
- 1University of Pennsylvania School of Medicine, 295 John Morgan Building, 36th and Hamilton Walk, Philadelphia, PA 19104, USA
- Correspondence to: R L Tannen
- Accepted 19 October 2008
Objectives To determine whether observational studies that use an electronic medical record database can provide valid results of therapeutic effectiveness and to develop new methods to enhance validity.
Design Data from the UK general practice research database (GPRD) were used to replicate previously performed randomised controlled trials, to the extent that was feasible aside from randomisation.
Studies Six published randomised controlled trials.
Main outcome measure Cardiovascular outcomes analysed by hazard ratios calculated with standard biostatistical methods and a new analytical technique, prior event rate ratio (PERR) adjustment.
Results In nine of 17 outcome comparisons, there were no significant differences between results of randomised controlled trials and database studies analysed using standard biostatistical methods or PERR analysis. In eight comparisons, Cox adjusted hazard ratios in the database differed significantly from the results of the randomised controlled trials, suggesting unmeasured confounding. In seven of these eight, PERR adjusted hazard ratios differed significantly from Cox adjusted hazard ratios, whereas in five they didn’t differ significantly, and in three were more similar to the hazard ratio from the randomised controlled trial, yielding PERR results more similar to the randomised controlled trial than Cox (P<0.05).
Conclusions Although observational studies using databases are subject to unmeasured confounding, our new analytical technique (PERR), applied here to cardiovascular outcomes, worked well to identify and reduce the effects of such confounding. These results suggest that electronic medical record databases can be useful to investigate therapeutic effectiveness.
We gratefully acknowledge the assistance of Xingmei Wang, who assisted with the biostatistical analyses, and James Lewis and Stephen Kimmel for their insightful review of this manuscript.
Contributors: RLT and MHW contributed to conception and design; analysis and interpretation of data; drafting and revision of article; and final approval of published version. CX contributed to design, analysis and interpretation of data, drafting and revision of article, and final approval of published version.
Funding: This work was supported by the National Institutes of Health research grant RO1-HL 073911.
Competing interests: None declared.
Ethical approval: Not required.
Provenance and peer review: Not commissioned; externally peer reviewed.
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