Development and Validation of a Machine Learning-Based Decision Support Tool for Residency Applicant Screening and Review.

Purpose: Residency programs face overwhelming numbers of residency applications, limiting holistic review. Artificial intelligence techniques have been proposed to address this challenge but have not been created. Here, a multidisciplinary team sought to develop and validate a machine learning (ML)-based decision support tool (DST) for residency applicant screening and review.

Warm Handoffs: a Novel Strategy to Improve End-of-Rotation Care Transitions.

Background: Hospitalized medical patients undergoing transition of care by house staff teams at the end of a ward rotation are associated with an increased risk of mortality, yet best practices surrounding this transition are lacking.

Aim: To assess the impact of a warm handoff protocol for end-of-rotation care transitions.

Setting: A large, university-based internal medicine residency using three different training sites.