Categorizing Care Delays and Their Impact on Hospital Length of Stay.

Abstract

Unnecessary care delays of hospitalized patients increase the risk of hospital-related complications and drive up health care costs. While health systems focus on reducing the length of stay of hospitalized patients, not many studies looked at specific causes of the care delays that prolong length of stay. In this study, we sought to systematically identify and categorize the various care delays that contribute to prolonged length of stay on a hospital medicine service. We conducted a retrospective observational study looking at all inpatient encounters to the hospitalist service (N=6633) for the fiscal year 2021. Observation status, COVID-19 positive, and other services' discharged patients were excluded (N=2849) leaving 3784 eligible encounters. The resulting 5% stratified random sample accounted for 190 encounters accounting for a total of 1152 patient-days. Using a standardized data extraction tool, a day-by-day review of the sample encounters was performed for all care delays. These care delays were categorized into specific groups (System, Discharge, Provider, Patient/Family, or Consultant related) and subgroups based on predetermined criteria. The stratified sample was found to be comparable to the total patient population, with no statistically significant differences in key demographic and clinical metrics. About 30% of all patient-days had a care delay; 33% of these delays were attributable to system delays internal to the hospital such as waiting for imaging/procedures; 28% of delays were due to discharge barriers, driven overwhelmingly by a lack of available post-acute care beds, and about 20% of delays were attributable to the provider. Our study systematically looked at care delays that led to prolonged hospital length of stay. Most of these care delays were caused by either wait times for procedures and imaging studies or by a lack of post-acute care bed availability. Hospitals and health systems can use this approach to better determine which systemic changes are likely to be the most effective at reducing length of stay.