Use this URL to cite or link to this record in EThOS: https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.759706
Title: Dynamically accepting and scheduling patients for home healthcare
Author: Demirbilek, Mustafa
ISNI:       0000 0004 7431 7350
Awarding Body: University of Warwick
Current Institution: University of Warwick
Date of Award: 2018
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Abstract:
Importance of home healthcare is growing rapidly since populations of developed and even developing countries are getting older quickly and the number of hospitals, retirement homes, and medical staff do not increase at the same rate. We present Scenario Based Approach (SBA) for the Home Healthcare Nurse Scheduling Problem. In this problem, arrivals of patients are dynamic and acceptance and appointment time decisions have to be made as soon as patients arrive. The primary objective is to maximise the average number of daily visits. For the sake of service continuity, patients have to be visited at the same days and times each week during their service horizon. SBA is basically a simulation procedure based on generating several scenarios and scheduling new customers with a simple but fast heuristic. Then results are analysed to decide whether to accept the new patient and at which appointment day/time. First, two different versions of SBA, Daily and Weekly SBA are developed and analysed for a single nurse. We compare Daily SBA to two greedy heuristics from the literature, distance and capacity based, and computational studies show that Daily SBA makes significant improvements compared to these other two methods for a single nurse. Next, we extend SBA for a multi-nurse case. SBA is compared to a greedy heuristic under different conditions such as same depot case where nurses start their visits from and return to same place, clustered service area, and nurses with different qualification level. SBA gives superior results under all experiment conditions compared to the greedy heuristic.
Supervisor: Not available Sponsor: Millî Eğitim Bakanlığı (Turkey)
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID: uk.bl.ethos.759706  DOI: Not available
Keywords: HD Industries. Land use. Labor ; RA Public aspects of medicine
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