Open AccessImproving Early Discharges With an Electronic Health Record Discharge Optimization Tool
Author(s) -
Michael Perry,
Charlie Macias,
Juan D. Chaparro,
Allison C Heacock,
Kenneth W. Jackson,
Ryan Bode
Publication year - 2020
Publication title -
pediatric quality and safety
Language(s) - English
Resource type - Journals
ISSN - 2472-0054
DOI - 10.1097/pq9.0000000000000301
Subject(s) - medicine , workflow , noon , quality management , discharge planning , multidisciplinary team , multidisciplinary approach , electronic health record , hospital discharge , health care , medical emergency , emergency medicine , nursing , service (business) , intensive care medicine , computer science , database , business , social science , physics , astronomy , sociology , economic growth , economics , marketing
Delays in hospital discharge can negatively impact patient care, bed availability, and patient satisfaction. There are limited studies examining how the electronic health record (EHR) can be used to improve discharge timeliness. This study aimed to implement an EHR discharge optimization tool (DOT) successfully and achieve a discharge before noon (DBN) percentage of 25%. Methods: We conducted a single-center quality improvement study of patients discharged from 3 pediatric hospital medicine teaching service teams at a quaternary care academic children’s hospital. The multidisciplinary team created a DOT centrally embedded within the care team standard workflow to communicate anticipated time until discharge. The primary outcome was the monthly percentage of patients discharged before noon. Secondary outcomes included provider utilization of the DOT, tool accuracy, and patient length of stay. Balancing measures were 7- and 30-day readmission rates. Results: The DBN percentage increased from 16.4% to an average of 19.3% over the 13-month intervention period ( P = 0.0005). DOT utilization was measured at 87.2%, and the overall accuracy of predicting time until discharge was 75.6% ( P < 0.0001). Median length of stay declined from 1.75 to 1.68 days ( P = 0.0033), and there was no negative impact on 7- or 30-day readmission rates. Conclusion: This initiative demonstrated that a highly utilized and accurate discharge tool could be created in the EHR to assist medical care teams with improving DBN percentage on busy, academic teaching services.