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Am J Perinatol 2015; 32(08): 761-770
DOI: 10.1055/s-0034-1396074
Original Article
Thieme Medical Publishers 333 Seventh Avenue, New York, NY 10001, USA.

Capacity Planning for Maternal–Fetal Medicine Using Discrete Event Simulation

Nicole M. Ferraro
1   School of Biomedical Engineering, Science, and Health Systems, Drexel University, Philadelphia, Pennsylvania
,
Courtney B. Reamer
2   Department of Electrical and Systems Engineering, University of Pennsylvania, Philadelphia, Pennsylvania
,
Thomas A. Reynolds
3   Center for Fetal Diagnosis and Treatment, The Children's Hospital of Philadelphia, Philadelphia, Pennsylvania
,
Lori J. Howell
3   Center for Fetal Diagnosis and Treatment, The Children's Hospital of Philadelphia, Philadelphia, Pennsylvania
,
Julie S. Moldenhauer
3   Center for Fetal Diagnosis and Treatment, The Children's Hospital of Philadelphia, Philadelphia, Pennsylvania
4   Clinical Obstetrics and Gynecology in Surgery, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania
,
Theodore Eugene Day
5   Office of Safety and Medical Operations, The Children's Hospital of Philadelphia, Philadelphia, Pennsylvania
› Author Affiliations
Further Information

Publication History

05 June 2014

02 October 2014

Publication Date:
17 December 2014 (online)

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Abstract

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.

Keywords

Maternal–fetal medicine - discrete event simulation - planning - operations research
 

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