A Framework for Operational Modelling of Hospital Resources
Abstract
The provision of hospital resources, such as beds, operating theatres and nurses, is a matter of considerable public and political concern and has been the subject of widespread debate [1,2,31. The political element of healthcare emphasises the need for objective methods and tools to inform the debate and provide a better foundation for decision-making. There is considerable scope for operational models to be widely used for this purpose. An appreciation of the dynamics governing a hospital system, and the flow of patients through it, point towards the need for sophisticated capacity models reflecting the complexity, uncertainty, variability and limited resources. Working alongside managers and clinicians from participating hospitals, this paper proposes a generic framework for modelling of hospital resources in the light of perceived user-needs and real-life hospital processes. The proposed framework incorporates the need for patient classification techniques to be adopted, which forms a key differentiator between this approach and other attempts to produce practical capacity planning and management tools. Statistically and clinically meaningful patient groupings may then be fed into developed simulation models and individual patients from each group passed through the particular hospital system of concern. The effectiveness of the framework is demonstrated through the development and use of an integrated hospital capacity tool.
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Currently, most hospitals use simple heuristics to make short-term forecasts of numbers of emergency admissions, based on rolling averages for each day of the week.
“Currently, most hospitals use simple heuristics to make short-term forecasts of numbers of emergency admissions, which are based on rolling averages for each day of the week10.”
From Machine learning for real-time aggregated prediction of hospital admission for emergency patients (2022) · cites this paper as [10]
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- Authors
- Harper, P. R.
- Affiliations
- University of Southampton (GB)
- Corresponding author
- Harper, Paul R.
- ORCID
- Harper, Paul R.
- Venue
- Health Care Management Science
- Published
- 2002-08
- Volume
- 5
- Issue
- 3
- Pages
- 165-173
- ISSN
- 1386-9620 (ISSN-L)
- 1572-9389
- OpenAlex
- W1608285042
- Cited by
- 279
- References
- 26
- Citations by year
- 2026: 10 · 2025: 5 · 2024: 6 · 2023: 6 · 2022: 9 · 2021: 11 · 2020: 13 · 2019: 14 · 2018: 12 · 2017: 14 · 2016: 23 · 2015: 16 · 2014: 14 · 2013: 18 · 2012: 25
- FWCI
- 5.52
- Type
- journal article
- Language
- en
- Open access
- closed
- Licence
- Locations
- Health Care Management Science (publishedVersion)
- PubMed (publishedVersion)
- ePrints Soton (University of Southampton) (submittedVersion)
- ORCA Online Research @Cardiff (Cardiff University) (submittedVersion)
- Funders
- University of Southampton
- Topics
- Health Sciences › Health Professions › Emergency Medical Services › Healthcare Operations and Scheduling Optimization
- Health Sciences › Health Professions › Health Information Management › Healthcare Quality and Management
- Health Sciences › Medicine › Emergency Medicine › Emergency and Acute Care Studies
- Keywords
- hospital capacity planning, patient classification, patient flow, hospital operations, healthcare decision-making, computer simulation, hospital bed capacity, operating theatre capacity, nurse staffing
- MeSH terms
- Algorithms, Appointments and Schedules, Bed Occupancy, Computer Simulation, Decision Support Systems, Management, United Kingdom, Hospital Administration, Hospital Bed Capacity, Humans, Patients, Planning Techniques, Politics, Health Care Rationing, Models, Organizational, Efficiency, Organizational, Needs Assessment
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