Introduction
Early in the COVID-19 epidemic, many gloomy images emerged of what might be ahead. In one, hospitals would be overrun by more COVID-19 patients than they could treat. Models developed at the Institute for Health Metrics and Evaluation provided numbers that supported the image. For the most part, overrun hospitals did not happen. Things turned out better because America’s hospitals did better than the IHME model thought they could.
Hospital productivity has proved to be greater than anticipated in the IHME model. Productivity determines how many patients hospitals can serve. Productivity reflects how many beds a hospital has and how many days each patient stays in a bed. The most common pattern in hospitals, patients who are discharged alive and do not require time in an intensive care unit (ICU), provide an example. Length of stay for that group has been a third shorter than assumed in the IHME model.
The data required to tell the adaptability story in detail is not yet available. Only a qualitative assessment is possible at this point. Hospitals adapted in ways not anticipated in the IHME model. For example, they delayed elective surgical procedures, freeing up beds. The story will become more detailed as data about hospital admissions and the clinical course of COVID-19 patients becomes available.