As health care institutions near the peak of the COVID-19 pandemic, they are grappling with how to proactively and ethically distribute scarce health care resources to treat the sick. The news is rife ...

The pandemic put a spotlight on the challenges that health systems face when deciding how to allocate scarce resources during a time of crisis. To better understand differing opinions on this issue, ...

Researchers argue that, in some situations where machine-learning models are used to allocate scarce resources or opportunities, randomizing decisions in a structured way may lead to fairer outcomes.

Physician trauma is on the rise. Much has been written about the burnout, anxiety, and emotional and physical exhaustion that clinicians (and other front-line health care workers) experience when ...

The COVID-19 pandemic will continue to demand more resources than the US medical system has to supply, likely requiring explicit rationing of ventilators, critical and intensive care beds, and ...

Editor's note: Find the latest COVID-19 news and guidance in Medscape's Coronavirus Resource Center. During surges in COVID-19 infections, the lack of regional, statewide, and national data has made ...

Among the many failures in America’s early COVID-19 disaster response, unprepared federal authorities mismanaged the allocation of emergency medical equipment as the pandemic mushroomed. Decisions by ...

Open-Label, Multicenter, Randomized, Biomarker-Integrated Umbrella Trial for Second-Line Treatment of Advanced Gastric Cancer: K-Umbrella Gastric Cancer Study Resource shortages in oncology and ...

CAMBRIDGE, MA – Organizations are increasingly utilizing machine-learning models to allocate scarce resources or opportunities. For instance, such models can help companies screen resumes to choose ...