The number of studies using clinical registries or claims-based sources has exploded over the past decade. For the American College of Surgeons National Surgical Quality Improvement Program (NSQIP) alone, the annual number of publications increased 10-fold from 68 in 2010 to 805 in 2019. The reasons for this growth are clear: these sources are easily accessible, can be imported into statistical programs within minutes, and offer opportunities to answer a diverse breadth of questions. The limitations are also well known: because the data are observational, they may be prone to bias from selection or confounding. However, in the absence of randomized data, clinicians often rely on database research to develop guidelines, make patient care decisions, and shape health care policy. With increased use of database research, greater caution must be exercised in terms of how it is performed and documented.
Surgical database research is here to stay, and its use will only increase. Decisions made from the time the data set is imported to the final regression model can impact the validity of the findings. A system that questions these steps will pay off with replicable, valid data that are more likely to be accurate and beneficial when informing clinical practice.
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