Optimization of Patient Flow in Urgent Care Centers Using a Digital Tool for Recording Patient Symptoms and History: Simulation Study (Preprint)
Preprint
- 10 December 2020
- preprint
- Published by JMIR Publications Inc. in JMIR Preprints
Abstract
BACKGROUND Crowding can negatively affect patient and staff experience, and consequently the performance of health care facilities. Crowding can potentially be eased through streamlining and the reduction of duplication in patient history-taking through the use of a digital symptom-taking app. OBJECTIVE We simulated the introduction of a digital symptom-taking app on patient flow. We hypothesized that waiting times and crowding in an urgent care center (UCC) could be reduced, and that this would be more efficient than simply adding more staff. METHODS A discrete-event approach was used to simulate patient flow in a UCC during a 4-hour time frame. The baseline scenario was a small UCC with 2 triage nurses, 2 doctors, 1 treatment/examination nurse, and 1 discharge administrator in service. We simulated 33 scenarios with different staff numbers or different potential time savings through the app. We explored average queue length, waiting time, idle time, and staff utilization for each scenario. RESULTS Discrete-event simulation showed that even a few minutes saved through patient app-based self-history recording during triage could result in significantly increased efficiency. A modest estimated time saving per patient of 2.5 minutes decreased the average patient wait time for triage by 26.17%, whereas a time saving of 5 minutes led to a 54.88% reduction in patient wait times. Alternatively, adding an additional triage nurse was less efficient, as the additional staff were only required at the busiest times. CONCLUSIONS Small time savings in the history-taking process have potential to result in substantial reductions in total patient waiting time for triage nurses, with likely effects of reduced patient anxiety, staff anxiety, and improved patient care. Patient self-history recording could be carried out at home or in the waiting room via a check-in kiosk or a portable tablet computer. This formative simulation study has potential to impact service provision and approaches to digitalization at scale.Keywords
All Related Versions
- Published version: JMIR Formative Research, 5 (5), e26402.
This publication has 34 references indexed in Scilit:
- Improving emergency department patient-doctor conversation through an artificial intelligence symptom taking tool: an action-oriented design pilot studymedRxiv, 2020
- Patients’ Utilization and Perception of an Artificial Intelligence–Based Symptom Assessment and Advice Technology in a British Primary Care Waiting Room: Exploratory Pilot Study (Preprint)JMIR Preprints, 2020
- Patient motives behind low-acuity visits to the emergency department in Germany: a qualitative study comparing urban and rural sitesBMJ Open, 2016
- ‘The time it takes…’ How doctors spend their time admitting a patient during the acute medical takeClinical Medicine, 2016
- Dynamic patient grouping and prioritization: a new approach to emergency department flow improvementHealth Care Management Science, 2014
- Patient flow modelling and performance analysis of healthcare delivery processes in hospitals: A review and reflectionsComputers & Industrial Engineering, 2014
- Emergency department crowdingEmergency Medicine Journal, 2012
- International Perspectives on Emergency Department CrowdingAcademic Emergency Medicine, 2011
- Emergency department crowding and risk of preventable medical errorsInternal and Emergency Medicine, 2011
- Modeling and Simulation of Patient Flow in Hospitals for Resource UtilizationSNE Simulation Notes Europe, 2010