Analysis of variability in neonatal care units: A retrospective analysis

Adeyemi, Shola; Demir, Eren; Chahed, Salma; Chaussalet, Thierry J.

doi:10.1109/whcm.2010.5441246

Cited by 2 publications

(4 citation statements)

References 4 publications

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“…In their study, a discrete event simulation model is used to assess demand predictions for healthcare resources, and machine learning is added to their model to increase the model's validity. Adeyemi et al [31] suggest that a lack of capacity is mostly associated with increased infant births. Demir et al [5] examine the effects of different variables.…”

Section: Predicting the Length Of Staymentioning

confidence: 99%

“…Researchers in the UK have based their studies on the duration of stay of infants by analysing the duration of stay in premature infants, having been observed to be more intensive [31,13,32,33].…”

Section: Predicting the Length Of Staymentioning

confidence: 99%

“…Owing to a lack of capacity (nurses, equipment, beds, etc. ), the length of stay, and the random number of patients, the rejection or transfer number is determined by nurses [31,38]. Torabipour et al [23] study the management of hospital beds, and state that the statistic and stochastic simulation model is an efficient tool to estimate the needed number of beds, considering the LoS, admission rate, and discharge rate.…”

Section: Generating Optimum Resource (Bed/staff) Configurationsmentioning

confidence: 99%

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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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Section: Predicting the Length Of Staymentioning

confidence: 99%

Section: Predicting the Length Of Staymentioning

confidence: 99%

Section: Generating Optimum Resource (Bed/staff) Configurationsmentioning

confidence: 99%

See 1 more Smart Citation

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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“…Patterns in the allocation of scarce resources within the neonatal system in particular are reflected in LOS trends, among other indicators. 8 Prior research studies estimate that overall mean LOS for all births may have increased over time, with significant variation among demographic groups. 9,10,11 …”

Section: Introductionmentioning

confidence: 99%

Time Trends and Payer Differences in Lengths of Initial Hospitalization for Preterm Infants, Arkansas, 2004 to 2010

et al. 2014

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Objective To examine the time trend in length of stay (LOS) and explore potential differences in neonatal LOS by insurance type for preterm infants in Arkansas between 2004 and 2010. Study Design There were 18,712 preterm infants included in our analyses. Accelerated failure time (AFT) models were used to model neonatal LOS as a function of insurance type and discharge year while adjusting for key maternal and infant characteristics, and complication/anomaly indicators. Results Prior to adjusting for the complication/anomaly indicators, the LOS for preterm infants delivered to mothers in the Medicaid group was 3.2% shorter than those in the private payer group. Furthermore, each subsequent year was associated with a 1.6% increase in the expected LOS. However, after accounting for complications and anomalies, insurance coverage differences in neonatal LOS were not statistically significant while the trend in LOS persisted at a 0.59% increase for each succeeding year. Conclusion All of the apparent differences in LOS by insurance type and more than half of the apparent increase in LOS over time are accounted for by higher rates of complications among privately insured preterm infants and increasing rates of complications for all surviving preterm infants between 2004 and 2010.

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Analysis of variability in neonatal care units: A retrospective analysis

Cited by 2 publications

References 4 publications

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

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

Time Trends and Payer Differences in Lengths of Initial Hospitalization for Preterm Infants, Arkansas, 2004 to 2010

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