Please use this identifier to cite or link to this item: https://scholarbank.nus.edu.sg/handle/10635/135218
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dc.titleSTRATEGIC HOSPITAL CAPACITY PLANNING IN A COUNTRY EXPERIENCING RAPID POPULATION AGING
dc.contributor.authorZHOU KE
dc.date.accessioned2017-04-04T18:00:30Z
dc.date.available2017-04-04T18:00:30Z
dc.date.issued2016-12-16
dc.identifier.citationZHOU KE (2016-12-16). STRATEGIC HOSPITAL CAPACITY PLANNING IN A COUNTRY EXPERIENCING RAPID POPULATION AGING. ScholarBank@NUS Repository.
dc.identifier.urihttp://scholarbank.nus.edu.sg/handle/10635/135218
dc.description.abstractAcute hospital (AH) capacity needs to be planned carefully to avoid the high cost associated with overbuilding and delays and potentially compromised patient outcomes associated with underbuilding. Hospital capacity planning is complicated by the rapidly changing health care needs of the ageing population, like that of Singapore. This thesis examines the AH capacity planning issue in Singapore. I first conducted empirical studies to examine the nature and determinants of current hospital utilization. I observed that about half of geriatric beds in one AH is occupied for non-acute care due to delays in discharge planning and insufficient non-acute services. I also determined that at one AH the length of stay (LOS), but not re-hospitalization or mortality rate, was inversely related to physician workload. This suggests that there is potential to safely reduce LOS by reducing non-acute use of AH beds. I then developed a system dynamics model based on the empirical findings noted, as well as a national survey of elders to project the elderly population’s need for hospital beds and examine the impact of different capacity planning strategies on system-level outcomes. I found that the extent of growth in demand for AH beds primarily depends on chronic health and social characteristics of the population. I also found, with reasonable certainty, that a policy of using projected demand to guide capacity planning outperforms a policy of building hospitals based on bed to population ratio, in all system-level outcome measures. This highlights the value of collecting longitudinal data on population health care needs to refine the projection.
dc.language.isoen
dc.subjectageing population, health care needs, simulation model, planning, health service research, Singapore
dc.typeThesis
dc.contributor.departmentDUKE-NUS MEDICAL SCHOOL
dc.description.degreePh.D
dc.description.degreeconferredDOCTOR OF PHILOSOPHY
dc.identifier.isiutNOT_IN_WOS
Appears in Collections:Ph.D Theses (Open)

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