Overview and details of the sessions of this conference. Please select a date or location to show only sessions at that day or location. Please select a single session for detailed view (with abstracts and downloads if available).
Helping the captive audience: advance notice of diagnostic service for hospital inpatients
Nan Liu1, Miao Bai2, Zheng Zhang3
1Boston College; 2University of Connecticut; 3Zhejiang University
Problem: Inpatients wait for hospital diagnostic services, causing chaos. Methodology: We propose "advance notice" scheduling, providing patients with preparation and service time windows. Markov Decision Process optimizes decisions. Numerical study shows significant operational improvement. Managerial implications: Advance notice policy reduces waiting and improves appointment-based services.
Patient sensitivity to emergency department waiting time announcements
Jingqi Wang1, Eric Park2, Huiyin Ouyang2, Sergei Savin3
1Chinese University of Hong Kong Shenzhen; 2University of Hong Kong; 3University of Pennsylvania
Problem: Evaluating an ED delay announcement system in Hong Kong's healthcare. Methodology: Studying 1.3M patient visits, we estimate patient sensitivity to announced waiting times (WT) and factors influencing it. Results show potential improvements in reducing WT and patients leaving without being seen. Implications: Increase patient awareness, reduce WT update window, focus on older population and Kowloon district for promotion.
The impact of hospital and patient characteristics on psychiatry readmissions
Hossein Hejazian1, Beste Kucukyazici2, Javad Nasiry1, Vedat Verter2, Daniel Frank3
We study hospitals' operational characteristics contributing to the re-admission of psychiatry patients. We propose that length of stay (LOS) mediates the effects of hospital characteristics on the risk of readmission. We reveal how patient characteristics moderate these effects. Using a dataset of 15,000 psychiatry patients, we provide evidence on the negative volume-outcome and nonlinear LOS-outcome relationship. Our analysis provides helpful insights for managing the flow of psychiatric patients.
