Analyzing discharge strategies during acute care: a discrete-event simulation study.
We developed a discrete-event simulation model of patient pathway through an acute care hospital that comprises an ED and several inpatient units. The effects of discharge timing on ED waiting and boarding times, ambulance diversions, leave without treatment, and readmissions were explicitly modeled. We then analyzed the impact of 1 static and 2 proactive discharge strategies on these system outcomes.



Our analysis indicated that although the 2 proactive discharge strategies significantly reduced ED waiting and boarding times, and several other measures, compared with the static strategy (P < 0.01), the number of readmissions increased substantially. Further analysis indicated that these findings are sensitive to changes in patient arrival rate and conditions for ambulance diversion.



Determining the appropriate time to discharge patients not only can affect individual patients' health outcomes, but also can affect various aspects of the hospital. The study improves our understanding of how individual inpatient discharge decisions can be objectively viewed in terms of their impact on other operations, such as ED crowding and readmission, in an acute care hospital.
Department of Biomedical, Industrial and Human Factors Engineering, Wright State University, Dayton, OH (EC, PJP).
Elizabeth A
EA
Crawford
Department of Biomedical, Industrial and Human Factors Engineering, Wright State University, Dayton, OH (EC, PJP).
Pratik J
PJ
Parikh
Weldon School of Biomedical Engineering, Purdue University, West Lafayette, IN (NK)
Nan
N
Kong
Department of Internal Medicine, Universityof Cincinnati and Renal Section, Cincinnati VA Medical Center, Cincinnati, OH (CVT)
Charuhas V
CV
Thakar
D000208:Acute Disease; D006801:Humans; D008962:Models, Theoretical; D010351:Patient Discharge
ED crowding; acute care; discrete-event simulation; inpatient discharge