Improving the Efficiency of an Emergency Department Based on Activity-Relationship Diagram and Radio Frequency Identification Technology

Emergency department crowding has been one of the main issues in the health system in Taiwan. Previous studies have usually targeted the process improvement of patient treatment flow due to the difficulty of collecting Emergency Department (ED) staff data. In this study, we have proposed a hybrid model with Discrete Event Simulation, radio frequency identification applications, and activity-relationship diagrams to simulate the nurse movement flows and identify the relationship between different treatment sections. We used the results to formulate four facility layouts. Through comparing four scenarios, the simulation results indicated that 2.2 km of traveling distance or 140 min of traveling time reduction per nurse could be achieved from the best scenario.

[1]  Scott Levin,et al.  Discrete Event Simulation for Healthcare Organizations: A Tool for Decision Making , 2013, Journal of healthcare management / American College of Healthcare Executives.

[2]  Alexander Komashie,et al.  Modeling emergency departments using discrete event simulation techniques , 2005, Proceedings of the Winter Simulation Conference, 2005..

[3]  D. Eitel,et al.  Improving service quality by understanding emergency department flow: a White Paper and position statement prepared for the American Academy of Emergency Medicine. , 2010, The Journal of emergency medicine.

[4]  Yeonsook Heo,et al.  Unit-Related Factors That Affect Nursing Time with Patients: Spatial Analysis of the Time and Motion Study , 2009, HERD.

[5]  Wang-Chuan Juang,et al.  Emergency department overcrowding: Quality improvement in a Taiwan Medical Center. , 2019, Journal of the Formosan Medical Association = Taiwan yi zhi.

[6]  Donald R. Jones,et al.  Contained nomadic information environments: Technology, organization, and environment influences on adoption of hospital RFID patient tracking , 2014, Inf. Manag..

[7]  Todd G Nick,et al.  Estimating the degree of emergency department overcrowding in academic medical centers: results of the National ED Overcrowding Study (NEDOCS). , 2004, Academic emergency medicine : official journal of the Society for Academic Emergency Medicine.

[8]  Debajyoti Pati,et al.  Estimating Design Impact on Waste Reduction: Examining Decentralized Nursing , 2012, The Journal of nursing administration.

[9]  Gilles Reinhardt,et al.  Analysis of factors influencing length of stay in the emergency department. , 2003, CJEM.

[10]  Moutaz Haddara,et al.  RFID Applications and Adoptions in Healthcare: A Review on Patient Safety , 2018, Procedia Computer Science.

[11]  D. Aronsky,et al.  Systematic review of emergency department crowding: causes, effects, and solutions. , 2008, Annals of emergency medicine.

[12]  C. Gadbois,et al.  Hospital design and the temporal and spatial organization of nursing activity , 1992 .

[13]  K. Ronald Laughery,et al.  Advanced uses for micro saint simulation software , 1997, WSC '98.

[14]  A. Hendrich,et al.  Effects of acuity-adaptable rooms on flow of patients and delivery of care. , 2004, American journal of critical care : an official publication, American Association of Critical-Care Nurses.

[15]  Yeonsook Heo,et al.  A Modeling Approach for Estimating the Impact of Spatial Configuration on Nurses' Movement , 2009 .

[16]  R. Vogel,et al.  Emergency department use by nursing home residents. , 1998, Annals of emergency medicine.

[17]  S. M. Wang,et al.  ED overcrowding in Taiwan: facts and strategies. , 1999, The American journal of emergency medicine.

[18]  L. Burgio,et al.  A descriptive analysis of nursing staff behaviors in a teaching nursing home: differences among NAs, LPNs, and RNs. , 1990, The Gerontologist.

[19]  Sima Ajami,et al.  Radio Frequency Identification (RFID) technology and patient safety , 2013, Journal of research in medical sciences : the official journal of Isfahan University of Medical Sciences.

[20]  Brian H Rowe,et al.  Emergency department overcrowding and access block. , 2013, CJEM.

[21]  Alkin Yurtkuran,et al.  Simulation based decision-making for hospital pharmacy management , 2008, 2008 Winter Simulation Conference.

[22]  P. Sprivulis,et al.  Access block causes emergency department overcrowding and ambulance diversion in Perth, Western Australia , 2005, Emergency Medicine Journal.

[23]  Edmund Jones,et al.  Discrete Event Simulation for Decision Modeling in Health Care: Lessons from Abdominal Aortic Aneurysm Screening , 2018, Medical decision making : an international journal of the Society for Medical Decision Making.

[24]  J. Twanmoh,et al.  When overcrowding paralyzes an emergency department. , 2006, Managed care.

[25]  Eylül Damla Gönül-Sezer,et al.  A Review on Discrete-event Simulation and System Dynamics Studies for Healthcare Problems , 2015, SIMULTECH.

[26]  R. Tappen,et al.  Nursing staff time allocation in long-term care: a work sampling study. , 1997, The Journal of nursing administration.

[27]  Jesse M Pines,et al.  What we have learned from a decade of ED crowding research. , 2015, Academic emergency medicine : official journal of the Society for Academic Emergency Medicine.

[28]  Mehdi Amini,et al.  Simulation Modeling and Analysis: A Collateral Application and Exposition of RFID Technology , 2007 .

[29]  Effie Lai-Chong Law,et al.  In and Out of the Hospital: The Hidden Interface of High Fidelity Research Via RFID , 2007, INTERACT.

[30]  Jeffrey W. Herrmann,et al.  A Survey of Queuing Theory Applications in Healthcare , 2007 .

[31]  Vijayan Sugumaran,et al.  Collection and Preparation of Sensor Network Data to Support Modeling and Analysis of Outpatient Clinics , 2005, Health care management science.

[32]  K. Preston White,et al.  Using RFID Technologies to Capture Simulation Data in a Hospital Emergency Department , 2006, Proceedings of the 2006 Winter Simulation Conference.

[33]  Chuan Zhou,et al.  Forecasting emergency department crowding: a prospective, real-time evaluation. , 2009, Journal of the American Medical Informatics Association : JAMIA.

[34]  Eric Howell,et al.  Hospital Strategies for Reducing Emergency Department Crowding: A Mixed‐Methods Study , 2016, Annals of emergency medicine.

[35]  Fatah Chetouane,et al.  Modeling and Improving Emergency Department Systems using Discrete Event Simulation , 2007, Simul..

[36]  Sheldon Howard Jacobson,et al.  Application of discrete-event simulation in health care clinics: A survey , 1999, J. Oper. Res. Soc..

[37]  Sander M. Bohte,et al.  Adaptive resource allocation for efficient patient scheduling , 2009, Artif. Intell. Medicine.

[38]  R. Derlet,et al.  Overcrowding in emergency departments: increased demand and decreased capacity. , 2002, Annals of emergency medicine.