Evaluating intensive care unit admission and discharge policies using a discrete event simulation model

Hasan, Imran; Bahalkeh, Esmaeil; Yih, Yuehwern

doi:10.1177/0037549720914749

Cited by 26 publications

(15 citation statements)

References 52 publications

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“…Similarly, Grida and Zeid 44 developed a systems dynamics simulation model of a medium-sized hospital with the focus of their analysis being identification of throughput improvement policies for the surgical department via a theory of constraints approach. Of the third type, Hasan et al 45 developed a DES of an ICU in a hospital catering to patients of multiple types from upstream hospital units, such as the ED, elective surgery, and emergency surgery. The objective of the study was to find suitable admissions and discharge policies to improve both patient and provider outcomes.…”

Section: Background and Literature Reviewmentioning

confidence: 99%

Simulation modeling and analysis of primary health center operations

Mohd

Ramamohan

2021

SIMULATION

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We present discrete-event simulation models of the operations of primary health centers (PHCs) in the Indian context. Our PHC simulation models incorporate four types of patients seeking medical care: outpatients, inpatients, childbirth cases, and patients seeking antenatal care. A generic modeling approach was adopted to develop simulation models of PHC operations. This involved developing an archetype PHC simulation, which was then adapted to represent two other PHC configurations, differing in numbers of resources and types of services provided, encountered during PHC visits. A model representing a benchmark configuration conforming to government-mandated operational guidelines, with demand estimated from disease burden data and service times closer to international estimates (higher than observed), was also developed. Simulation outcomes for the three observed configurations indicate negligible patient waiting times and low resource utilization values at observed patient demand estimates. However, simulation outcomes for the benchmark configuration indicated significantly higher resource utilization. Simulation experiments to evaluate the effect of potential changes in operational patterns on reducing the utilization of stressed resources for the benchmark case were performed. Our analysis also motivated the development of simple analytical approximations of the average utilization of a server in a queueing system with characteristics similar to the PHC doctor/patient system. Our study represents the first step in an ongoing effort to establish the computational infrastructure required to analyze public health operations in India and can provide researchers in other settings with hierarchical health systems, a template for the development of simulation models of their primary healthcare facilities.

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Section: Background and Literature Reviewmentioning

confidence: 99%

Simulation modeling and analysis of primary health center operations

Mohd

Ramamohan

2021

SIMULATION

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“…operations 24 ) or a single hospital unit (e.g. laboratory 25 ; ED 26,27,28 ; radiology 29 ; OR 30 ; ICU 31 ). The authors are not aware of any works in the literature that take a similar whole-hospital approach.…”

Section: Discussionmentioning

confidence: 99%

Models for Assessing Strategies for Improving Hospital Capacity for Handling Patients during a Pandemic

Shahverdi

Miller-Hooks

Tariverdi

et al. 2022

Disaster med. public health prep.

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Objective: The aim of this study was to investigate the performance of key hospital units associated with emergency care of both routine emergency and pandemic (COVID-19) patients under capacity enhancing strategies. Methods: This investigation was conducted using whole-hospital, resource-constrained, patient-based, stochastic, discrete-event simulation models of a generic 200-bed urban U.S. tertiary hospital serving routine emergency and COVID-19 patients. Systematically designed numerical experiments were conducted to provide generalizable insights into how hospital functionality may be affected by the care of COVID-19 pandemic patients along specially designated care paths under changing pandemic situations from getting ready to turning all of its resources to pandemic care. Results: Several insights are presented. For example, each day of reduction in average ICU length of stay increases intensive care unit patient throughput by up to 24% for high COVID-19 daily patient arrival levels. The potential of five specific interventions and two critical shifts in care strategies to significantly increase hospital capacity is described. Conclusions: These estimates enable hospitals to repurpose space, modify operations, implement crisis standards of care, prepare to collaborate with other health care facilities, or request external support, increasing the likelihood that arriving patients will find an open staffed bed when one is needed.

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“… 20 The participants in this study also reported changes to ICU triage criteria through triaging patients out of the ICU based on acuity if a surge occurred, caring for patients in the progressive care unit instead of the ICU, and disallowing COVID-19 trauma patients in the ICU. Hasan et al 2 22 evaluated ICU admission and discharge policies and reported that increasing discharge windows, the times of the day when patients are considered for discharge, significantly lowered the average wait times for ICU admission, and increased the amount of patients able to be admitted to the ICU. Revising ICU discharge criteria during COVID-19 could allow for more patients in need of an ICU bed to be admitted.…”

Section: Discussionmentioning

confidence: 99%

Processes for Trauma Care at Six Level I Trauma Centers During the COVID-19 Pandemic

et al. 2021

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Introduction: As the COVID-19 pandemic spread, patient care guidelines were published and elective surgeries postponed. However, trauma admissions are not scheduled and cannot be postponed. There is a paucity of information available on continuing trauma care during the pandemic. The study purpose was to describe multicenter trauma care process changes made during the COVID-19 pandemic. Methods: This descriptive survey summarized the response to the COVID-19 pandemic at six Level I trauma centers. The survey was completed in 05/2020. Questions were asked about personal protective equipment, ventilators, intensive care unit (ICU) beds, and negative pressure rooms. Data were summarized as proportions. Results: The survey took an average of 5 days. Sixty-seven percent reused N-95 respirators; 50% sanitized them with 25% using ultraviolet light. One hospital (17%) had regional resources impacted. Thirty-three percent created ventilator allocation protocols. Most hospitals (83%) designated more beds to the ICU; 50% of hospitals designated an ICU for COVID-19 patients. COVID-19 patients were isolated in negative pressure rooms at all hospitals. Conclusions: In response to the COVID-19 pandemic, Level I trauma centers created processes to provide optimal trauma patient care and still protect providers. Other centers can use the processes described to continue care of trauma patients during the COVID-19 pandemic.

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Evaluating intensive care unit admission and discharge policies using a discrete event simulation model

Cited by 26 publications

References 52 publications

Simulation modeling and analysis of primary health center operations

Simulation modeling and analysis of primary health center operations

Models for Assessing Strategies for Improving Hospital Capacity for Handling Patients during a Pandemic

Processes for Trauma Care at Six Level I Trauma Centers During the COVID-19 Pandemic

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