The Use of a Comparability Scoring System in Reporting Observational Studies
The traditional statistical analyses with adjustment for confounders in observational studies assume that there is perfect similarity in the already-provided medical management between the comparison groups. However, variations in medical management frequently exist because of differences in circumstances of health care. We propose that to minimize the selection bias of observational studies, the degree of similarity or dissimilarity of the comparison groups regarding the circumstances of health care should be considered. Circumstances of health care include the geographic setting, health care setting, type of health care providers, and likelihood in having confounding introduced by differences in the medical management between comparison groups. We propose a comparability scoring system of circumstances of care and provide examples of the application of this system, using recent literature to assess comparability among study groups. In our examples, the presupposed statistical associations disappeared once the analyses accounted for the differences in circumstances of care. Authors of submitted manuscripts using an observational study design may consider incorporating our scoring system or an equivalent in their methods and in reporting of the results. The comparability score should be factored during statistical analysis so that the appropriate analysis can correct for differences in circumstances of care. The use of a comparability scoring system can provide important insights for reviewers and readers that will improve the interpretation of this type of research study.
Published In/Presented At
Vintzileos, A., Ananth, C., & Smulian, J. (2014). The use of a comparability scoring system in reporting observational studies. American Journal Of Obstetrics And Gynecology, 210(2), 112-116. doi:10.1016/j.ajog.2013.09.002
Medical Specialties | Medicine and Health Sciences | Obstetrics and Gynecology | Physical Sciences and Mathematics | Statistics and Probability
Department of Obstetrics and Gynecology, Department of Obstetrics and Gynecology Faculty