Capacity Planning for Maternal–Fetal Medicine Using Discrete Event Simulation

BACKGROUND Maternal-fetal medicine is a rapidly growing field requiring collaboration from many subspecialties. We provide an evidence-based estimate of capacity needs for our clinic, as well as demonstrate how simulation can aid in capacity planning in similar environments. METHODS A Discrete Event Simulation of the Center for Fetal Diagnosis and Treatment and Special Delivery Unit at The Children's Hospital of Philadelphia was designed and validated. This model was then used to determine the time until demand overwhelms inpatient bed availability under increasing capacity. FINDINGS No significant deviation was found between historical inpatient censuses and simulated censuses for the validation phase (p = 0.889). Prospectively increasing capacity was found to delay time to balk (the inability of the center to provide bed space for a patient in need of admission). With current capacity, the model predicts mean time to balk of 276 days. Adding three beds delays mean time to first balk to 762 days; an additional six beds to 1,335 days. CONCLUSION Providing sufficient access is a patient safety issue, and good planning is crucial for targeting infrastructure investments appropriately. Computer-simulated analysis can provide an evidence base for both medical and administrative decision making in a complex clinical environment.

[1]  Michael Pidd,et al.  Discrete event simulation for performance modelling in health care: a review of the literature , 2010, J. Simulation.

[2]  Alain Guinet,et al.  An integer linear model for hospital bed planning , 2012 .

[3]  L. Howell The Garbose Family Special Delivery Unit: a new paradigm for maternal-fetal and neonatal care. , 2013, Seminars in pediatric surgery.

[4]  R. Hall,et al.  Patient flow : reducing delay in healthcare delivery , 2006 .

[5]  M. Mackay,et al.  Modelling Variability in Hospital Bed Occupancy , 2005, Health care management science.

[6]  Manuel D. Rossetti,et al.  Emergency department simulation and determination of optimal attending physician staffing schedules , 1999, WSC '99.

[7]  D. Wright,et al.  Economic modelling of antenatal screening and ultrasound scanning programmes for identification of fetal abnormalities , 2005, BJOG : an international journal of obstetrics and gynaecology.

[8]  J. Cochran,et al.  Stochastic bed balancing of an obstetrics hospital , 2006, Health care management science.

[9]  Omar Al-Araidah,et al.  Reducing Delay in Healthcare Delivery at Outpatients Clinics Using Discrete Event Simulation , 2012 .

[10]  Stavros T. Ponis,et al.  Applying Discrete Event Simulation (DES) in Healthcare: The Case for Outpatient Facility Capacity Planning , 2013, Int. J. Heal. Inf. Syst. Informatics.

[11]  Frank McGuire Using simulation to reduce length of stay in emergency departments , 1994, Proceedings of Winter Simulation Conference.

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

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

[14]  Simon J. E. Taylor,et al.  Economics of modeling and simulation: Reflections and implications for healthcare , 2010, Proceedings of the 2010 Winter Simulation Conference.

[15]  S Vemuri,et al.  Simulated analysis of patient waiting time in an outpatient pharmacy. , 1984, American journal of hospital pharmacy.

[16]  A. W. Liley Intrauterine Transfusion of Foetus in Haemolytic Disease , 1963, British medical journal.

[17]  Bryony Dean Franklin,et al.  Using discrete event simulation to design a more efficient hospital pharmacy for outpatients , 2011, Health care management science.

[18]  Jeffery K. Cochran,et al.  A queuing-based decision support methodology to estimate hospital inpatient bed demand , 2008, J. Oper. Res. Soc..

[19]  J. Caro,et al.  Model transparency and validation: a report of the ISPOR-SMDM Modeling Good Research Practices Task Force--7. , 2012, Value in health : the journal of the International Society for Pharmacoeconomics and Outcomes Research.

[20]  Fu-Shan Jaw,et al.  Using discrete-event simulation in strategic capacity planning for an outpatient physical therapy service , 2013, Health care management science.

[21]  A. Lander,et al.  Advances in fetal surgery , 2013 .

[22]  N. Adzick Prospects for fetal surgery. , 2013, Early human development.

[23]  Nathan Ravi,et al.  A Novel Use for Real Time Locating Systems: Discrete Event Simulation Validation in Medical Systems , 2010 .

[24]  Amber Kunkel,et al.  Determining minimum staffing levels during snowstorms using an integrated simulation, regression, and reliability model , 2013, Health care management science.

[25]  Zhecheng Zhu,et al.  Estimating ICU bed capacity using discrete event simulation. , 2012, International journal of health care quality assurance.

[26]  Thomas R Rohleder,et al.  Recovery bed planning in cardiovascular surgery: a simulation case study , 2013, Health care management science.

[27]  Jonathan Karnon,et al.  Modeling using discrete event simulation: a report of the ISPOR-SMDM Modeling Good Research Practices Task Force--4. , 2012, Value in health : the journal of the International Society for Pharmacoeconomics and Outcomes Research.