Analytical framework to establish requisite bed capacity when cohorting paediatric patients

Chia, Linda; Lin, W. D.

doi:10.1109/ieem.2015.7385743

Cited by 2 publications

(1 citation statement)

References 9 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The authors present a stochastic optimization model with a revenue maximization objective to decide on the beds to be reserved for isolation and non-isolation patients, where the two groups have different requirements for spacing and admission criteria. Chia and Lin (2015) analyze the effectiveness of different cohorting strategies in a pediatric hospital for allocating beds among different patient types. Wang et al (2020) focus on allocating beds among different departments in a hospital in a setting with stochastic patient arrival and service times and propose an approach that combines a MIP and a simulation model to minimize the expected cost of rejection and waiting.…”

Section: Health Care Capacity Planning In Resource-limited Settingsmentioning

confidence: 99%

Capacity Planning for Effective Cohorting of Dialysis Patients during the Coronavirus Pandemic: A Case Study

Bozkir,

Ozmemis,

Kurbanzade

et al. 2021

Preprint

View full text Add to dashboard Cite

Chronic dialysis patients have been among the most vulnerable groups of the society during the coronavirus (COVID-19) pandemic as they need regular treatments in a hospital environment, facing infection risk. Moreover, the demand for dialysis resources has significantly increased since many COVID-19 patients need acute dialysis due to kidney failure. In this study, we address capacity planning decisions of a hemodialysis clinic located within a major hospital in Istanbul, designated to serve both infected and uninfected patients during the pandemic with limited resources (i.e., dialysis machines). The hemodialysis clinic applies a three-unit cohorting strategy to treat four types of patients in separate units and at different times to mitigate infection spread risk among patients.Accordingly, at the beginning of each week, the clinic needs to determine the number of available dialysis machines to allocate to each unit that serves different patient cohorts. Given the uncertainties in the number of different types of patients that will need dialysis, it is a challenge to allocate the scarce dialysis resources effectively by evaluating which capacity configuration would minimize the overlapping treatment sessions of infected and uninfected patients over a week. We represent the uncertainties in the number of patients by a set of scenarios and present a two-stage stochastic programming approach to support capacity allocation decisions of the clinic. We present a case study based on the real-world patient data obtained from the clinic to illustrate the effectiveness of the proposed modeling approach and compare the performance of different cohorting strategies.

show abstract

Section: Health Care Capacity Planning In Resource-limited Settingsmentioning

confidence: 99%

Capacity Planning for Effective Cohorting of Dialysis Patients during the Coronavirus Pandemic: A Case Study

Bozkir,

Ozmemis,

Kurbanzade

et al. 2021

Preprint

View full text Add to dashboard Cite

show abstract

Simulation study of patient arrivals and doctors scheduling in a children's emergency department

Chia

Lin

2016

2016 IEEE International Conference on Industrial Engineering and Engineering Management (IEEM)

View full text Add to dashboard Cite

Analytical framework to establish requisite bed capacity when cohorting paediatric patients

Cited by 2 publications

References 9 publications

Capacity Planning for Effective Cohorting of Dialysis Patients during the Coronavirus Pandemic: A Case Study

Capacity Planning for Effective Cohorting of Dialysis Patients during the Coronavirus Pandemic: A Case Study

Simulation study of patient arrivals and doctors scheduling in a children's emergency department

Contact Info

Product

Resources

About