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|Title:||INTRA-HOSPITAL PATIENT TRANSPORTATION SYSTEM PLANNING USING BI-LEVEL DECISION MODEL|
|Keywords:||Business, Management and Accounting;Decision Sciences|
|Abstract:||Background: The intra-hospital patient transportation is an important aspect of patient care. It is about the transfer of patients between different healthcare units in the hospital. Many tasks are required for transferring the patients from one to another unit depending on available resources and the needs of the patients, such as types of supporting equipment, transfer routes, and supporters. Limited and unprepared resources for transferring the patients, such as lack of supporting equipment and available supporters, may impact the patient treatment and service quality. Therefore, these resources should be managed effectively in order to minimize these impacts. The case study hospital located in Chiang Mai province, northern Thailand is currently encountering the problem in managing and planning the intra-hospital transportation process. Therefore, this research aimed to propose a mathematical model for planning the intra-hospital transportation system in this case study hospital. Methods: Our research proposed a bi-level mathematical model to tackle the intra-hospital transportation planning problems. The system is represented by a deterministic model using integer linear programming. The first level of the mathematical model is for identifying the locations and setting them as transportation depots. The second level of the model is to optimize the number of resources used for intra-hospital patient transportation. The model was then validated by using two sets of instances via LINGO solver. Results: This research proposed a bi-level mathematical model that could help to manage the intra-hospital transportation challenges in the case study hospital. Furthermore, the outcomes from the test with two instances were depots positioned at a set of feasible locations. The model was used to designate resources to each depot for the instance, such as wheelchairs, stretchers, oxygen tanks, and employees. In each case, the outcomes are dependent on varying service timings and demands. Conclusion: This research used the deterministic mathematical model for planning the intra-hospital transportation system consisting of the location assignment and resource allocation. The model, in addition, can solve with the exact method. Consequently, we can ensure that the presented model can apply to real situations in further study.|
|Appears in Collections:||CMUL: Journal Articles|
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