Annals of internal medicine
-
Major depressive disorder is a common mental health condition that affects an estimated 16.2 million adults and 3.1 million adolescents in the United States. Yet, a lack of uniformity remains in measurements and monitoring for depression both in clinical practice and in research settings. This project aimed to develop a minimum set of standardized outcome measures relevant to both patients and clinicians that can be collected in depression registries and clinical practice. ⋯ The panel identified 10 broadly relevant measures and harmonized definitions for these measures through in-person and virtual meetings. The harmonized measures represent a minimum set of outcomes that are relevant to clinicians and patients and appropriate for use in depression research and clinical practice. Routine and consistent collection of these measures in registries and other systems would support creation of a national research infrastructure to efficiently address new questions, improve patient management and outcomes, and facilitate care coordination.
-
Hahnemann University Hospital provided care for Philadelphians starting in 1848, but its recent history has been riddled with financial turmoil that culminated in its rapid closure in summer 2019. As the hospital shuttered its doors to patients, it also orphaned 583 medical trainees. ⋯ In a firsthand account of the situation that developed in Philadelphia and reached academic institutions across the country, the authors reflect on lessons learned that may help leaders at other institutions mitigate the inevitable difficulties that arise when academic hospitals close. These lessons pertain to handling panic and administrative burdens in the aftermath of closure, the importance of well-defined processes, a clear understanding of GME funding, and strategies for placement of trainees that minimize disruption of their education.
-
Electronic health record (EHR) systems can be configured to deliver novel EHR interventions that influence clinical decision making and to support efficient randomized controlled trials (RCTs) designed to evaluate the effectiveness, safety, and costs of those interventions. In designing RCTs of EHR interventions, one should carefully consider the unit of randomization (for example, patient, encounter, clinician, or clinical unit), balancing concerns about contamination of an intervention across randomization units within clusters (for example, patients within clinical units) against the superior control of measured and unmeasured confounders that comes with randomizing a larger number of units. One should also consider whether the key computational assessment components of the EHR intervention, such as a predictive algorithm used to target a subgroup for decision support, should occur before randomization (so that only 1 subgroup is randomized) or after randomization (including all subgroups). ⋯ Trials of EHR interventions should be reviewed by an institutional review board, but may not require patient-level informed consent when the interventions being tested can be considered minimal risk or quality improvement, and when clinical decision making is supported, rather than controlled, by an EHR intervention. Data and safety monitoring for RCTs of EHR interventions should be conducted to guide institutional pragmatic decision making about implementation and ensure that continuing randomization remains justified. Reporting should follow the CONSORT (Consolidated Standards of Reporting Trials) Statement, with extensions for pragmatic trials and cluster RCTs when applicable, and should include detailed materials to enhance reproducibility.