Earlier medically ready for discharge date entry associated with lower unnecessary bed days.

BACKGROUND: Discharge planning plays a critical role in managing patient hospital length of stay. We report on the implementation of a program in a large hospital system where health care providers were requested to estimate and record the Medically-Ready-for-Discharge Date (MRDD) in the electronic health record (EHR) for hospitalized patients to facilitate efficient hospital stays. A new metric for discharge delays, unnecessary bed days (UBD), was tracked as the difference between actual discharge date and MRDD. The objective was to evaluate the association between MRDD timing and UBD. A secondary aim was to evaluate other factors associated with UBD. METHODS: Discharges for 112,930 patient visits from 4 hospitals were considered within the period 01-January-2021/31-July-2022. Detailed subgroup analysis was conducted for 33,771 Medicine and Pediatric patients. Descriptive statistics were used to report MRDD utilization and other patient population characteristics. Multivariable regression models and tree-based machine learning methods were used to control for medical, demographic and operational characteristics to estimate factors associated with UBD. RESULTS: The longer the delay in entering the MRDD forecast after admission, the greater the UBD. The longer the time between the first MRDD entry time stamp and the last MRDD value, the lower the UBD. Disposition, level of care, insurance, and day of week were significant for predicting UBD. CONCLUSIONS: A statistically significant decrease in UBD was associated with earlier entry of the MRDD forecast. Decreasing UBD can allow for improved patient throughput in capacity-constrained hospitals. Our findings of the observed consequences of implemented policies and of quantifying the impact on UBD can help other hospitals assess the appropriate scope for implementing similar initiatives.