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Reducing abandonment and improving attitudes in emergency departments: Integrating delay announcements into operational transparency to signal service quality
Monika Westphal1, Galit B. Yom-Tov2, Avi Parush2, Anat Rafaeli2
1Ben Gurion University of the Negev, Israel; 2Technion - Israel Institute of Technology, Israel
Emergency Department (ED) clients lack knowledge about the various elements their personal ED journey comprises. In a field study (N=18,903) we provide "Personalized Information about Operations and Time (PIOT)" – (frequently updated) information about the procedures and anticipated wait times for each patient. We show PIOT improves people’s attitudes, and PIO (operational-only information) reduces patients' abandonment. Providing PIOT offers a novel approach to improving healthcare service.
On the Effects of Boarding Patients on Treatment Time in Emergency Departments
Zahra Jalali1, Beste Kucukyazici Verter2, Mehmet Gumus1
1McGill University, Canada; 2Michigan State University, United States of America
In this paper, we study how the boarding patients can affect the treatment time in emergency departments (EDs). First, we conduct an empirical analysis using a dataset from eight EDs and show that the relationship has an inverted U-shape. Next, we recognize two mechanisms behind it: (i)the additional workload on ED physicians, (ii) the hospitalist visits triggered by boarding congestion. Finally, we propose two interventions that can jointly mitigate this impact up to 68% in a tertiary hospital.
A Granular approach to optimal and fair patient placement in hospital emergency departments
1UMass Memorial Hospital, Worcester, MA, USA; 2Babson College, Wellesley, MA, USA; 3Sloan School of Management and Operations Research Center, MIT, Cambridge, MA, USA; 4Operations Research Center, MIT, Cambridge, MA, USA
We introduce a MILP formulation for patient prioritization in the ED that incorporates a breakdown of predicted patient LOS. We propose an SAA based reformulation that can be solved efficiently and provide guarantees on its convergence, stability and sample complexity. A study of 40000 patient visits from a US hospital shows that our solution increases ED throughput by >50% and decreases average waiting time by >75%. Our method displays desirable properties of fairness in patient prioritization.
