How Many Hospital Beds?

Linda V. Green

INQUIRY The Journal of Health Care Organization Provision and Financing · 2002 · 204 citations · 26 references

DOIFull text

Open access

Concepts

TL;DR

Hospital bed capacity decisions have historically relied on average occupancy levels, with the prevailing view that the nation has excess beds based on a 25‑year‑old 85% occupancy target. The study uses New York state data and queueing analysis to estimate bed unavailability in ICUs and obstetrics units. The authors apply queueing models with patient delay standards to identify units lacking capacity, requiring collection and analysis of operational data on bed demand, usage, and delays. The analysis shows that up to 40 % of obstetrics units and 90 % of ICUs lack sufficient capacity, a stark contrast to estimates based on average occupancy, and suggests that capacity planning should rely on timely bed‑placement standards rather than occupancy targets.

Abstract

For many years, average bed occupancy level has been the primary measure that has guided hospital bed capacity decisions at both policy and managerial levels. Even now, the common wisdom that there is an excess of beds nationally has been based on a federal target of 85% occupancy that was developed about 25 years ago. This paper examines data from New York state and uses queueing analysis to estimate bed unavailability in intensive care units (ICUs) and obstetrics units. Using various patient delay standards, units that appear to have insufficient capacity are identified. The results indicate that as many as 40% of all obstetrics units and 90% of ICUs have insufficient capacity to provide an appropriate bed when needed. This contrasts sharply with what would be deduced using standard average occupancy targets. Furthermore, given the model's assumptions, these estimates are likely to be conservative. These findings illustrate that if service quality is deemed important, hospitals need to plan capacity based on standards that reflect the ability to place patients in appropriate beds in a timely fashion rather than on target occupancy levels. Doing so will require the collection and analysis of operational data-such as demands for and use of beds, and patient delays--which generally are not available.

References

26