Optimizing nurse capacity in a teaching hospital neonatal intensive care unit

Abstract

Patients in intensive care units need special attention. Therefore, nurses are one of the most important resources in a neonatal intensive care unit. These nurses are required to have highly specialized training. The random number of patient arrivals, rejections, or transfers due to lack of capacity (such as nurse, equipment, bed etc.) and the random length of stays, make advanced knowledge of the optimal nurse a requirement, for levels of the unit behave as a stochastic process. This stochastic nature creates difficulties in finding optimal nurse staffing levels. In this paper, a stochastic approximation which is based on the required nurse: patient ratio and the number of patients in a neonatal intensive care unit of a teaching hospital, has been developed. First, a meta-model was built to generate simulation results under various numbers of nurses. Then, those experimented data were used to obtain the mathematical relationship between inputs (number of nurses at each level) and performance measures (admission number, occupation rate, and satisfaction rate) using statistical regression analysis. Finally, several integer nonlinear mathematical models were proposed to find optimal nurse capacity subject to the targeted levels on multiple performance measures. The proposed approximation was applied to a Neonatal Intensive Care Unit of a large hospital and the obtained results were investigated.

An Overview of Hospital Capacity Planning and Optimisation

“…It is suggested that these are the predominant reasons accounting for the increasing trend for stochastic approaches in research papers compared to deterministic ones as seen in Figure 5. Many of the papers use both stochastic and deterministic approaches, generally using stochastic simulation to evaluate and test the deterministic approach [17,99,103,[121][122][123][124][125][126][127][128]. When commenting on research trends, Madell, Villa, Hayward and Comte [89] observed that the increased computational complexity inherent with these types of questions explains the current trend of researchers to focus on deterministic approaches.…”

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

“…Managing an optimum resource configuration is difficult for many countries, owing to increased demand and limited hospital resources [34][35][36][37][38][39][40][41]. Researchers have used simulation and optimisation techniques to generate optimum resource profiles for a given scenario.…”

“…Kokangul et al [38] focus on nurse capacity in this regard. In these units, responsibility for the care of newborns, equipment, and employee capacity is very important.…”

“…If equipment and employee capacity meet the needs, the service can be provided easily. Therefore, according to Kokangul et al [38], nurses are one of the most essential resources in the neonatal intensive care unit, and should receive specialist training.…”

An approach by human and material resources combination to reduce hospitals crowding

“…Hospitals crowding problem is defined in detail (context, causes, effects […]) by many works (Jebbor et al , 2018), (Boyle et al , 2012) and (Casalino et al , 2013). Works dealing with this problem focus their studies either on human resources (de Bruin et al , 2010), (Beeknoo and Jones, 2016), (Green and Liu, 2015), (Boulton et al , 2016) and (Kokangul et al , 2017) or material resources (Izady and Worthington, 2012), (Zeltyn et al , 2011), (Green et al , 2006), (Vass and Szabo, 2015) and (Bekker et al , 2017). Only few ones study both resources types, but separately (without being combined) (Mital, 2010).…”