Predicting the Future: Using Simulation Modeling to Forecast Patient Flow on General Medicine Units
| Autor: | Joseph A. Heim, Lindsey Hall, Alan W. Dow, Shin Ping Tu, Heather Masters, Vimal Mishra, Ralph R. Clark |
|---|---|
| Rok vydání: | 2018 |
| Předmět: |
Male
Leadership and Management education MEDLINE Assessment and Diagnosis Efficiency Organizational InformationSystems_GENERAL 03 medical and health sciences Patient Admission 0302 clinical medicine 030225 pediatrics Internal Medicine Humans Medicine Computer Simulation Operations management 030212 general & internal medicine Discrete event simulation Complex adaptive system Care Planning Patient Care Team business.industry Unintended consequences Health Policy Simulation modeling General Medicine Hospitals Patient Discharge Workflow Hospitalists Time and Motion Studies Key (cryptography) Female Fundamentals and skills Construct (philosophy) business Forecasting |
| Zdroj: | Journal of Hospital Medicine. 14:9-15 |
| ISSN: | 1553-5606 1553-5592 |
| DOI: | 10.12788/jhm.3081 |
| Popis: | Background Hospitals are complex adaptive systems within which multiple components such as patients, practitioners, facilities, and technology interact. A careful approach to optimization of this complex system is needed because any change can result in unexpected deleterious effects. One such approach is discrete event simulation, in which what-if scenarios allow researchers to predict the impact of a proposed change on the system. However, studies illustrating the application of simulation in optimization of general internal medicine (GIM) team inpatient operations are lacking. Methods Administrative data about admissions and discharges, data from a time-motion study, and expert opinion on workflow were used to construct the simulation model. Then, the impact of four changes: aligning medical teams with nursing units, adding a hospitalist team, adding a nursing unit, and adding both a nursing unit and hospitalist team with higher admission volume were modeled on key hospital operational metrics. Results Aligning medical teams with nursing units improved team metrics for aligned teams but shifted patients to unaligned teams. Adding a hospitalist team had little benefit, but adding a nursing unit improved system metrics. Both adding a hospitalist team and a nursing unit would be required to maintain operational metrics with increased patient volume. Conclusion Using simulation modeling, we provided data on the implications of four possible strategic changes on GIM inpatient units, providers, and patient throughput. Such analyses may be a worthwhile investment to study strategic decisions and make better choices with fewer unintended consequences. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|
Plný text