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Modelling the requirement for supplementary nurses in an intensive care unit
- Source :
- Journal of the Operational Research Society. 56:126-133
- Publication Year :
- 2005
- Publisher :
- Informa UK Limited, 2005.
-
Abstract
- The intensive care unit (ICU) of a hospital is an essential yet costly resource. Consequently, intensive care modelling has become increasingly prevalent in recent years in attempts to increase efficiency and reduce costs. Previous models have usually assumed that the numbers of beds available are restricted; when all beds are occupied, any additional patients are referred elsewhere or elective surgeries are cancelled. In this study, activities at the ICU at a large teaching hospital were modelled using data relating to all admissions to the ICU during the year 2000—a total of 1084 admissions. The unit is unusual in that the majority of patients referred for intensive care therapy are admitted. Bed numbers are increased when necessary to cope with demand. However, nurses are a restricted resource. In order to maintain the required nurse:patient ratio of at least one:one, supplementary nurses are employed during busy periods. Supplementary nurse costs are substantial and so nurse utilization must be closely monitored. The development of a model that calculates the required number of supplementary nurses per shift, and also encapsulates the time-dependent nature of elective surgery admissions and complex duration-of-stay profiles, is presented in this paper. In particular, the model is used to determine the number of rostered nurses that are required to minimize overall nursing staff costs.
- Subjects :
- Marketing
021103 operations research
Nursing staff
Strategy and Management
0211 other engineering and technologies
02 engineering and technology
Management Science and Operations Research
medicine.disease
Intensive care unit
Management Information Systems
Teaching hospital
Unit (housing)
law.invention
Resource (project management)
law
Intensive care
Hospital admission
0202 electrical engineering, electronic engineering, information engineering
medicine
020201 artificial intelligence & image processing
Medical emergency
Elective surgery
Subjects
Details
- ISSN :
- 14769360 and 01605682
- Volume :
- 56
- Database :
- OpenAIRE
- Journal :
- Journal of the Operational Research Society
- Accession number :
- edsair.doi...........08b96197854cb5df04f9d093cf3d33e0