Modelling and analysis of resource allocation for hospital inpatient operations
{Introduction} More patients are opting to go for Same-Day admissions, where they can register and go for their operations with significantly reduced waiting time. The objective of this paper is to find out the optimal schedule (for eight specialty groups for every weekday) to release beds to redu...
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sg-ntu-dr.10356-771492023-02-28T23:11:29Z Modelling and analysis of resource allocation for hospital inpatient operations Lum, Jocelyn, Wei Xin Nicolas Privault School of Physical and Mathematical Sciences DRNTU::Science::Mathematics {Introduction} More patients are opting to go for Same-Day admissions, where they can register and go for their operations with significantly reduced waiting time. The objective of this paper is to find out the optimal schedule (for eight specialty groups for every weekday) to release beds to reduce patient waiting time and maximise bed utilisation. {Methodology} Discrete Event Simulation (DES) is useful in simulating real-life conditions where the beds are finite and sought after by many patients. The patients’ arrival in this paper is generated using a Poisson Process with Exponential Jumps, and parameters obtained from past records. Random Optimization was used to compare inputs and minimize the DES output for different inputs. {Results} This entire process was run 56 times and 56 specific results were obtained. Further, entries with satisfactory estimated distribution fits were re-run with schedules generated from past patient arrival timing distribution. Bachelor of Science in Mathematical Sciences 2019-05-14T04:41:08Z 2019-05-14T04:41:08Z 2019 Final Year Project (FYP) http://hdl.handle.net/10356/77149 en 50 p. application/pdf |
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DRNTU::Science::Mathematics Lum, Jocelyn, Wei Xin Modelling and analysis of resource allocation for hospital inpatient operations |
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{Introduction}
More patients are opting to go for Same-Day admissions, where they can register and go for their operations with significantly reduced waiting time. The objective of this paper is to find out the optimal schedule (for eight specialty groups for every weekday) to release beds to reduce patient waiting time and maximise bed utilisation.
{Methodology}
Discrete Event Simulation (DES) is useful in simulating real-life conditions where the beds are finite and sought after by many patients. The patients’ arrival in this paper is generated using a Poisson Process with Exponential Jumps, and parameters obtained from past records. Random Optimization was used to compare inputs and minimize the DES output for different inputs.
{Results} This entire process was run 56 times and 56 specific results were obtained. Further, entries with satisfactory estimated distribution fits were re-run with schedules generated from past patient arrival timing distribution. |
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Nicolas Privault |
author_facet |
Nicolas Privault Lum, Jocelyn, Wei Xin |
format |
Final Year Project |
author |
Lum, Jocelyn, Wei Xin |
author_sort |
Lum, Jocelyn, Wei Xin |
title |
Modelling and analysis of resource allocation for hospital inpatient operations |
title_short |
Modelling and analysis of resource allocation for hospital inpatient operations |
title_full |
Modelling and analysis of resource allocation for hospital inpatient operations |
title_fullStr |
Modelling and analysis of resource allocation for hospital inpatient operations |
title_full_unstemmed |
Modelling and analysis of resource allocation for hospital inpatient operations |
title_sort |
modelling and analysis of resource allocation for hospital inpatient operations |
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2019 |
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http://hdl.handle.net/10356/77149 |
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1759853391056470016 |