Mercaldo, Nathaniel D.

Objective: To characterize the current state of mental health within the surgical workforce in the United States. Background: Mental illness and suicide is a growing concern in the medical community; however, the current state is largely unknown. Methods: Cross-sectional survey of the academic surgery community assessing mental health, medical error, and suicidal ideation. The odds of suicidal ideation adjusting for sex, prior mental health diagnosis, and validated scales screening for depression, anxiety, post-traumatic stress disorder (PTSD), and alcohol use disorder were assessed. Results: Of 622 participating medical students, trainees, and surgeons (estimated response rate=11.4%–14.0%), 26.1% (141/539) reported a previous mental health diagnosis. In all, 15.9% (83/523) of respondents screened positive for current depression, 18.4% (98/533) for anxiety, 11.0% (56/510) for alcohol use disorder, and 17.3% (36/208) for PTSD. Medical error was associated with depression (30.7% vs. 13.3%, P<0.001), anxiety (31.6% vs. 16.2%, P=0.001), PTSD (12.8% vs. 5.6%, P=0.018), and hazardous alcohol consumption (18.7% vs. 9.7%, P=0.022). Overall, 13.2% (73/551) of respondents reported suicidal ideation in the past year and 9.6% (51/533) in the past 2 weeks. On adjusted analysis, a previous history of a mental health disorder (aOR: 1.97, 95% CI: 1.04–3.65, P=0.033) and screening positive for depression (aOR: 4.30, 95% CI: 2.21–8.29, P<0.001) or PTSD (aOR: 3.93, 95% CI: 1.61–9.44, P=0.002) were associated with increased odds of suicidal ideation over the past 12 months. Conclusions: Nearly 1 in 7 respondents reported suicidal ideation in the past year. Mental illness and suicidal ideation are significant problems among the surgical workforce in the United States.

Abstract Objective We describe a stratified sampling design that combines electronic health records (EHRs) and United States Census (USC) data to construct the sampling frame and an algorithm to enrich the sample with individuals belonging to rarer strata. Materials and Methods This design was developed for a multi-site survey that sought to examine patient concerns about and barriers to participating in research studies, especially among under-studied populations (eg, minorities, low educational attainment). We defined sampling strata by cross-tabulating several socio-demographic variables obtained from EHR and augmented with census-block-level USC data. We oversampled rarer and historically underrepresented subpopulations. Results The sampling strategy, which included USC-supplemented EHR data, led to a far more diverse sample than would have been expected under random sampling (eg, 3-, 8-, 7-, and 12-fold increase in African Americans, Asians, Hispanics and those with less than a high school degree, respectively). We observed that our EHR data tended to misclassify minority races more often than majority races, and that non-majority races, Latino ethnicity, younger adult age, lower education, and urban/suburban living were each associated with lower response rates to the mailed surveys. Discussion We observed substantial enrichment from rarer subpopulations. The magnitude of the enrichment depends on the accuracy of the variables that define the sampling strata and the overall response rate. Conclusion EHR and USC data may be used to define sampling strata that in turn may be used to enrich the final study sample. This design may be of particular interest for studies of rarer and understudied populations.