Controlling Understaffing with Conditional Value-at-Risk Constraint for an Integrated Nurse Scheduling Problem under Patient Demand Uncertainty
- Submitting institution
-
The University of Westminster
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- qvv40
- Type
- D - Journal article
- DOI
-
10.1016/j.orp.2019.100119
- Title of journal
- Operations Research Perspectives
- Article number
- 100119
- First page
- -
- Volume
- 6
- Issue
- 2019
- ISSN
- 2214-7160
- Open access status
- Compliant
- Month of publication
- July
- Year of publication
- 2019
- URL
-
-
- Supplementary information
-
-
- Request cross-referral to
- -
- Output has been delayed by COVID-19
- No
- COVID-19 affected output statement
- -
- Forensic science
- No
- Criminology
- No
- Interdisciplinary
- No
- Number of additional authors
-
2
- Research group(s)
-
-
- Citation count
- 2
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- Nursing workforce management is an essential and challenging decision-making task in hospitals as a sufficient and cost-efficient staffing level with desirable schedule is essential to provide good working conditions for nurses and consequently good quality of care for patients. This paper is significant because it proposes an integrated nurse staffing and scheduling model under patient demand uncertainty with understaffing risk control. Our research showed how a nurse schedule can be adjusted with respect to the level of risk the decision maker is willing to take. Using our model could potentially lead to healthcare quality improvement and result in cost benefit.
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -
