"Make the Implicit Explicit": Measuring Perceptions of Gender Bias and Creating a Gender Bias Curriculum for Internal Medicine Residents.

BACKGROUND: Gender bias in clinical training has been well established; however, little is known about how perceptions differ between men and women. Furthermore, few curricular options have been developed to discuss gender bias. OBJECTIVE: To measure the prevalence of gender bias, examine qualitative differences between men and women, and create a gender bias curriculum for internal medicine residents. METHODS: We surveyed 114 residents (response rate of 53.5%) to identify the prevalence and types of gender bias experienced in training. We compared estimates between genders and organized qualitative results into shared themes. We then developed a curriculum to promote and normalize discussions of gender bias. RESULTS: Among surveyed residents, 61% reported personal experiences of gender bias during training, with 98% of women and 19% of men reporting experiences when stratified by gender. We identified two domains in which gender bias manifested: role misidentification and a difficult working environment. Residents identified action items that led to the development of a gender bias curriculum. The curriculum includes didactic conferences and training sessions, a microaggression response toolkit, dinners for men and women residents, participation in a WhatsApp support group, and participation in academic projects related to gender bias in training. CONCLUSION: We confirmed a wide prevalence of gender bias and developed a scalable curriculum for gender bias training. Future work should explore the long-term impacts of these interventions.

Remote Patient Monitoring Program for Hospital Discharged COVID-19 Patients.

OBJECTIVE: We deployed a Remote Patient Monitoring (RPM) program to monitor patients with coronavirus disease 2019 (COVID-19) upon hospital discharge. We describe the patient characteristics, program characteristics, and clinical outcomes of patients in our RPM program. METHODS: We enrolled COVID-19 patients being discharged home from the hospital. Enrolled patients had an app, and were provided with a pulse oximeter and thermometer. Patients self-reported symptoms, O2 saturation, and temperature daily. Abnormal symptoms or vital signs were flagged and assessed by a pool of nurses. Descriptive statistics were used to describe patient and program characteristics. A mixed-effects logistic regression model was used to determine the odds of a combined endpoint of emergency department (ED) or hospital readmission. RESULTS: A total of 295 patients were referred for RPM from five participating hospitals, and 225 patients were enrolled. A majority of enrolled patients (66%) completed the monitoring period without triggering an abnormal alert. Enrollment was associated with a decreased odds of ED or hospital readmission (adjusted odds ratio: 0.54; 95% confidence interval: 0.3-0.97; p = 0.039). Referral without enrollment was not associated with a reduced odds of ED or hospital readmission. CONCLUSION: RPM for COVID-19 provides a mechanism to monitor patients in their home environment and reduce hospital utilization. Our work suggests that RPM reduces readmissions for patients with COVID-19 and provides scalable remote monitoring capabilities upon hospital discharge. RPM for postdischarge patients with COVID-19 was associated with a decreased risk of readmission to the ED or hospital, and provided a scalable mechanism to monitor patients in their home environment.