Capacity Planning for Maternal–Fetal Medicine Using Discrete Event Simulation

Ferraro, Nicole M.; Reamer, Courtney; Reynolds, Thomas A.; Howell, Lori J.; Moldenhauer, Julie S.; Day, Theodore E.

doi:10.1055/s-0034-1396074

Cited by 13 publications

(6 citation statements)

References 26 publications

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“…We developed the DES model of the ED at the CHOP according to a standardized 4-step process previously described by our group. 13 – 15 Briefly, model development includes (1) decomposition of the system into its constituent elements (eg, locations, entities, resources, paths); (2) development of a system flow (ie, how do patients move from one location to another and consume system resources at each location); (3) implementation of these elements in a computer model using MedModel 2011 (Promodel Corp, Allentown, PA); and (4) validation of the model using face, internal, and external validation techniques. The model was developed and validated according to best practices promulgated by the Society for Medical Decision Making.…”

Section: Methodsmentioning

confidence: 99%

Simulation to Predict Effect of Citywide Events on Emergency Department Operations

Ferraro

Day

2017

Pediatric Quality &Amp; Safety

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Summary:Medical emergency preparedness has been an issue of medical relevance since the advent of hospital care. Studies have simulated emergency department (ED) overcrowding but not yet characterized effects of large-scale, planned events that drastically alter a city’s demography, such as in Philadelphia, Pennsylvania during the 2015 World Meeting of Families. A discrete event simulation of the ED at the Children’s Hospital of Philadelphia was designed and validated using past data. The model was used to predict the patient length of stay (LOS) and number of admitted patients if the arrival stream to the ED were to change by 50% from typical arrivals in either direction. We compared the model’s estimations with data produced during the papal visit that had 39.65% fewer patient arrivals. For validation, the simulated mean LOS was 226.1 ± 173.3 minutes (mean ± SD) for all patients and 352.1 ± 170.3 minutes for admitted patients. Real-world mean LOSs for the fiscal year 2014 were 230.6 ± 134.8 for all patients and 345.0 ± 147.7 for admitted patients. For the estimation of the World Meeting of Families, the simulation accurately estimated the LOS of both patients overall and admitted patients within 10%. These results show that it is possible to use simulations to project the patient flow effects in EDs in case of large-scale events. Providing efficient care is essential to emergency operations, and projections of demand are crucial for targeting appropriate changes during large-scale events. Analysis of validated computer simulations allows for evidence-based decision making in a complex clinical environment.

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Section: Methodsmentioning

confidence: 99%

Simulation to Predict Effect of Citywide Events on Emergency Department Operations

Ferraro

Day

2017

Pediatric Quality &Amp; Safety

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“…to model, predict, and examine human performance and system evaluations. Such modeling and simulation capabilities have dramatically improved quality and safety in manufacturing and decision making (Eldabi & Young, 2007; Hamrock, Paige, Parks, Scheulen, & Levin, 2013; Kuljis, Paul, & Stergioulas, 2007; Young, 2005) and, within HC, have been applied to enhancing patient flow and analyzing risk factors for transfer to higher-acuity care (Day, Al-Roubaie, & Goldlust, 2013; Day, Sarawgi, Perri, & Nicolson, 2015; Ferraro et al, 2014; Pitt, Monks, Crowe, & Vasilakis, 2015; van Lent, Vanberkel, & van Harten, 2012; Zhai et al, 2014).…”

Section: What Is Hc Simulation?mentioning

confidence: 99%

Leveraging Health Care Simulation Technology for Human Factors Research

et al. 2016

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“…Capacity-planning studies, which determine how many cots/staff are needed for a given patient admission pattern and mix, have often used discrete-event simulation platforms [3][4][5][6]. However, studies so far have assumed a unidirectional flow of patients -i.e., patients gradually move to lower levels of care from the type of care required at admission.…”

Section: Introductionmentioning

confidence: 99%

Simulation Analysis of a Neonatal Unit With Complex Patient Flow Patterns – An Enhanced Model for Capacity Planning

Perera

Uslu

2022

SAJIE

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Steadily increasing demand requires neonatal units and networks to improve their overall capacities. Given the operational complexities involved, simulation is a popular choice for capacity planning studies. , For efficient model building, simulation exercises typically assume unidirectional flow of patients i.e., infants progressively move to lower levels of care. Patient flows are, however, much more complex i.e., time-to-time patients may require a higher level of care than the current level of care. This paper argues that bi-directional flow modelling is required to produce accurate capacity estimates thereby improving the quality decision making.

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Capacity Planning for Maternal–Fetal Medicine Using Discrete Event Simulation

Abstract: 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.

Cited by 13 publications

References 26 publications

Simulation to Predict Effect of Citywide Events on Emergency Department Operations

Simulation to Predict Effect of Citywide Events on Emergency Department Operations

Leveraging Health Care Simulation Technology for Human Factors Research

Simulation Analysis of a Neonatal Unit With Complex Patient Flow Patterns – An Enhanced Model for Capacity Planning

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