The DOI matches its Crossref record; 26 of the 26 references it cites were found in a registry or an index.
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.
Overview
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
In the citing paper
“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]
Citations
Cites
A Simplex Method for Function Minimization
Nelder, J. A., & Mead, R. (1965) · The Computer Journal · doi:10.1093/comjnl/7.4.308 · Cited by 28,905
Classification and Regression Trees.
Gordon, A. D., Breiman, L., Friedman, J. H., Olshen, R. A., & Stone, C. J. (1984) · Biometrics · doi:10.2307/2530946 · Cited by 23,867
Classification and Regression Trees.
Ryzin, J. V., Breiman, L., Friedman, J. H., Olshen, R. A., & Stone, C. J. (1986) · Journal of the American Statistical Association · doi:10.2307/2288003 · Cited by 21,030
Dynamics of bed use in accommodating emergency admissions: stochastic simulation model
Bagust, A., Place, M., & Posnett, J. W. (1999) · BMJ · doi:10.1136/bmj.319.7203.155 · Cited by 485
Algorithm AS 47: Function Minimization Using a Simplex Procedure
O’Neill, R. P. (1971) · Journal of the Royal Statistical Society Series C (Applied Statistics) · doi:10.2307/2346772 · Cited by 285
Akitt, J. W. (1977) · The Computer Journal · doi:10.1093/comjnl/20.1.84 · Cited by 164
Solving a nurse scheduling problem with knapsacks, networks and tabu search
Dowsland, K. A., & Thompson, J. M. (2000) · Journal of the Operational Research Society · doi:10.1057/palgrave.jors.2600970 · Cited by 146
Statistical Modeling to Predict Elective Surgery Time
Wright, I. H., Kooperberg, C. L., Bonar, B. A., & Bashein, G. (1996) · Anesthesiology · doi:10.1097/00000542-199612000-00003 · Cited by 136
The continuing rise in emergency admissions
Capewell, S. (1996) · BMJ · doi:10.1136/bmj.312.7037.991 · Cited by 134
Bed Allocation in a Public Health Care Delivery System
Kao, E. P. C., & Tung, G. G. (1981) · Management Science · doi:10.1287/mnsc.27.5.507 · Cited by 114
Flagged first, then by citations
Research works printed but not linked: 1
- J.D. Hawkins et al., TOCHSIM manual (Southampton Centre for Operational Research, University of Southampton, UK, 1992).
Cited by
Sorted by citations
Items 201–279 of 279
Clinical Activity and Schedule Management with a Fuzzy Social Preference System
Woźniak, P. W., Jaworski, T., Fiderek, P., Kucharski, J., & Romanowski, A. (2012) · Studies in computational intelligence · doi:10.1007/978-3-642-34300-1_33 · Cited by 2
Analytical framework to establish requisite bed capacity when cohorting paediatric patients
Chia, L., & Lin, W. (2015) · doi:10.1109/ieem.2015.7385743 · Cited by 2
Noyes, C. W. (2008) · DSpace@MIT (Massachusetts Institute of Technology) · Cited by 2
Generic Discrete-Event Simulation Model of a PrisonPreprint
Bartos, B. J., & McCleary, R. (2015) · SSRN Electronic Journal · doi:10.2139/ssrn.2622783 · Cited by 2
Primary Healthcare Staffing Needs Assessment-- A Discrete Event Simulation Study
Abe, T. (2014) · ResearchWorks at the University of Washington (University of Washington) · Cited by 2
Lusby, R. M., Schwierz, M., Range, T. M., & Larsen, J. (2016) · SSRN Electronic Journal · doi:10.2139/ssrn.2749619 · Cited by 2
Dynamic Job Assignment: A Column Generation Approach with an Application to Surgery AllocationPreprint
Range, T. M., & Petersen, N. C. (2016) · SSRN Electronic Journal · doi:10.2139/ssrn.2798618 · Cited by 2
Agent simulation in healthcare.
Nejad, S. G. (2008) · Cited by 2
Factor analysis of dynamic capabilities on public health centers operation performance
Perdana, R., Kartini, D., Azis, Y., & Kaltum, U. (2023) · Journal of Industrial Engineering and Management · doi:10.3926/jiem.4644 · Cited by 1
How Middle Managers Affect Frontline Idea Generation: Evidence From Healthcare Operations
Mosner, F. L., Sting, F. J., & Chandrasekaran, A. (2025) · Journal of Operations Management · doi:10.1002/joom.70018 · Cited by 1
Data-driven identification of outpatient-suitable procedures: a machine learning approach
Messerle, R., & Schreyögg, J. (2026) · Health Care Management Science · doi:10.1007/s10729-026-09758-6 · Cited by 1
Factors affecting patient flow planning in hospitals
Ezzat, A. E. M., Hamoud, H. S., & Fadlallah, B. E. (2014) · IOSR Journal of Dental and Medical Sciences · doi:10.9790/0853-131222224 · Cited by 1
Modelling Interpersonal Relations in Surgical Teams with Fuzzy Logic
Romanowski, A., Woźniak, P. W., Jaworski, T., Fiderek, P., & Kucharski, J. (2013) · Lecture notes in computer science · doi:10.1007/978-3-642-37807-2_40 · Cited by 1
Lamé, G., Duong, T. A., Janković, M., Cardinal, J. S.-L., & Jouini, O. (2015) · Springer eBooks · doi:10.1007/978-3-319-26109-6_8 · Cited by 1
Using Patient Flow to Examine Hospital Operations
Konrad, R., Küçükyazicı, B., & Lawley, M. A. (2011) · IGI Global eBooks · doi:10.4018/978-1-60960-872-9.ch019 · Cited by 1
Situation of Resource Management
Lin, Q. (2016) · Springer eBooks · doi:10.1007/978-981-10-2170-1_4 · Cited by 1
Rashwan, W., Habib, H., Arisha, A., Courtney, G., & Kennelly, S. (2016) · Arrow - TU Dublin (Technological University Dublin) · doi:10.5555/3042094.3042333 · Cited by 1
Hospital Scheduling Analysis: A Contemporary Review and Proposed Schematic Understanding
Ali, H. H., Lamsali, H., & Othman, S. N. (2018) · Universiti Utara Malaysia Institutional Repository (Universiti Utara Malaysia) · Cited by 1
Bed Census Predictions and Nurse Staffing
Braaksma, A., Kortbeek, N., & Boucherie, R. J. (2021) · International series in management science/operations research/International series in operations research & management science · doi:10.1007/978-3-030-60212-3_9 · Cited by 1
Lin, Q. (2016) · Springer eBooks · doi:10.1007/978-981-10-2170-1_9 · Cited by 1
One Transfer per Patient Suffices: Structural Insights About Patient-to-Room Assignment
Brandt, T., Büsing, C., & Knust, S. (2022) · Lecture notes in computer science · doi:10.1007/978-3-031-18530-4_18 · Cited by 1
Structural insights about avoiding transfers in the patient-to-room assignment problem
Brandt, T., Büsing, C., & Knust, S. (2024) · Discrete Applied Mathematics · doi:10.1016/j.dam.2023.12.025 · Cited by 1
Het raamwerk en het proces van capaciteitsmanagement
Winasti, W., van Merode, F., & Berrevoets, L. (2021) · Bohn Stafleu van Loghum eBooks · doi:10.1007/978-90-368-2567-2_2 · Cited by 1
Addressing artificial variability in patient flow
Asgari, F., & Asgari, S. (2021) · Operations Research for Health Care · doi:10.1016/j.orhc.2021.100288 · Cited by 1
Understanding the work and decision-making strategies of bed management nurses: a systematic review
Benjamin, E. (2021) · Nursing Management · doi:10.7748/nm.2021.e2016 · Cited by 1
Information Management for Tactical Decision-making in the Cardiac Care Process
Kontio, E. (2013) · UTUPub (University of Turku) · Cited by 1
Kortbeek, N., Braaksma, A., Smeenk, H. F., Bakker, P. J. M., & Boucherie, R. J. (2012) · Data Archiving and Networked Services (DANS) · Cited by 1
An Optimisation-based Framework for Complex Business Process: Healthcare Application
Abo-Hamad, W. (2011) · Arrow - TU Dublin (Technological University Dublin) · doi:10.21427/d7n597 · Cited by 1
Hospital management knowledge discovery using discrete event simulation
Bain, C., Raikundalia, G. K., & Mehta, S. (2007) · Victoria University Research Repository (Victoria University) · Cited by 1
Using operations research methodologies to improve operating theatre scheduling
Stuart, K. (2010) · Cited by 1
Perioperative Process Improvement using Discrete Event Simulation
Azari-Rad, S. (2010) · TSpace (University of Toronto) · Cited by 1
Suen, D. (2015) · Lancaster EPrints (Lancaster University) · Cited by 1
Improving service delivery of the MR department of MST
Koenderink, M. (2010)
Chakravarty, A. K. (2013) · Springer texts in business and economics · doi:10.1007/978-3-642-41911-9_10
A study of human behaviour in Libyan healthcare
Aboukanda, E. K. (2026) · e-space (Manchester Metropolitan University) · doi:10.83056/mmu.32435265
Kil, S.-H. (2011)
Modelling the Shift in the Balance of Care in the NHS
Marshall, C. (2013) · Stirling Online Research Repository (University of Stirling)
Strategic capacity planning within the Erasmus MC
Heckler, U. R. (2012)
A framework to provide clarity in the use of predictive technologies in health care management
Bain, C., & Au, L. K. (2007) · Australian Health Review · doi:10.1071/ah070073
The optimal allocation model of doctor's surgical time in China's Large Public Hospital
Luo, L., Qin, C., You, Y., & Yan, J. (2013) · International Conference on Service Systems and Service Management · doi:10.1109/icsssm.2013.6602634
Gong, X. Y. (2026) · University of Southern Queensland ePrints (University of Southern Queensland) · doi:10.26192/9z530
Optimizing hospital bed capacity at the department of hematology, UMCN
Hollander, D. J. J. (2012)
Development of an Operating Room Scheduling Support Information System.
Li, Y. (2012) · NCSU Libraries Repository (North Carolina State University Libraries)
Wanyonyi, K. (2015) · Research Portal (King's College London)
Agency in Health Care System Modeling and Analysis
Paranjape, R. B., & Gill, S. (2010) · IGI Global eBooks · doi:10.4018/978-1-60566-772-0.ch004
Lin, Q. (2016) · Springer eBooks · doi:10.1007/978-981-10-2170-1_2
Flexibiliteit in personele planning
Winasti, W., Peters, M., & Berrevoets, L. (2016) · Bohn Stafleu van Loghum eBooks · doi:10.1007/978-90-368-1340-2_14
Resource Allocation for an Inpatient Pharmacy.
Miles, L. (2011) · NCSU Libraries Repository (North Carolina State University Libraries)
New opportunities for industrial engineering in hospital emergency departments
Ceglowski, A. S., Churilov, L. P., & Wassertheil, J. (2004)
Scheduling Elective Surgeries with Emergency Arrivals in Operating Rooms
Xiao, Y. (2017) · Brock University Digital Repository (Brock University)
Improving the Performance of an MRI Department Through Appointment Scheduling
Bhattacharjee, P. (2017) · Managing the Asian century · doi:10.1007/978-981-10-5631-4_1
Production Planning and Control in an Ambulatory Care Service Provider in Sweden
Thelin, C., & Wallander, P. (2015) · KTH Publication Database DiVA (KTH Royal Institute of Technology)
Ontology for Healthcare Systems Modeling and Simulation
Traoré, M. K. (2018) · Summer Computer Simulation Conference · doi:10.22360/summersim.2018.scsc.009
Improving Operation Rooms and Planning to Reduce Surgery Cancelations and Inpatient Length of Stay
Marchesi, J. F., Hamacher, S., & Oliveira, F. L. C. (2019) · Springer proceedings in business and economics · doi:10.1007/978-3-030-23816-2_14
Clinical Decision-Making: Developing a 4 C Model Using Graph Theoretic Approach
Mishra, R. P., Mundra, N., Upreti, G., & Villa, M. (2020) · Studies in Engineering and Technology · doi:10.11114/set.v7i1.4781
Bahmani, A., & Bidhandi, H. M. (2020) · Mudīrīyyat-i salāmat. · doi:10.29252/jha.23.2.28
De spanning tussen vraag en aanbod van verpleegkundige zorg: flexibiliteitstrategieën
Winasti, W., Peters, M., & Berrevoets, L. (2021) · Bohn Stafleu van Loghum eBooks · doi:10.1007/978-90-368-2567-2_21
Implementing Algorithms to Reduce Ward Occupancy Fluctuation Through Advanced Planning
Vanberkel, P. T., Boucherie, R. J., Hans, E. W., Hurink, J. L., van Lent, W. A. M., & van Harten, W. H. (2021) · International series in management science/operations research/International series in operations research & management science · doi:10.1007/978-3-030-60212-3_8
Saville, C. E., Smith, H. K., Bijak, K., & Leonard, P. (2022) · Journal of the Operational Research Society · doi:10.1080/01605682.2022.2096497
Yamada, T., Karube, K., Ijuin, H., Takanokura, M., & Kakehi, M. (2023) · Information Engineering Express · doi:10.52731/iee.v9.i2.762
A Classification and Regression Tree Analysis for Prediction of Surgical Patient Lengths of Stay
Umarani, K., Ramakrishna, G., Reddy, G. V., Akshay, N., & Varshitha, M. H. V. (2023) · Türk bilgisayar ve matematik eğitimi dergisi · doi:10.61841/turcomat.v14i03.14522
Engineering Data-Driven Strategies for Reducing The Cost Of CarePreprint
Arepalli, B. R. (2024) · SSRN Electronic Journal · doi:10.2139/ssrn.5027147
Демушкина, К. М., & Kuzmin, A. V. (2025) · Известия высших учебных заведений. Приборостроение · doi:10.17586/0021-3454-2025-68-5-427-437
Kwon, Y. G., Namgung, M., Park, S. H., Kim, M. K., Choi, J. C., Jeong, D., & Kim, C. W. (2025) · International Journal for Quality in Health Care · doi:10.1093/intqhc/mzaf060
Weerdt, C. V. (2014) · Journal of the Association for Information Systems
Modelling of Operating Theatres Using Simulation
Stuart, K., & Kozan, E. (2007)
Konios, A., Barrios, M. A. O., & Fernández-Mendoza, Z. (2026) · Lecture notes in computer science · doi:10.1007/978-3-032-13012-9_20
Saha, E., & Rathore, P. K. (2026) · SSRN Electronic Journal · doi:10.2139/ssrn.6270281
Het raamwerk en het proces van capaciteitsmanagement
Winasti, W., van Merode, F., & Berrevoets, L. (2026) · doi:10.1007/978-90-368-3206-9_2
De spanning tussen vraag en aanbod van verpleegkundige zorg: flexibiliteitsstrategieën
Winasti, W., van Aspert, M., & Berrevoets, L. (2026) · doi:10.1007/978-90-368-3206-9_16
A data-driven utility framework for dynamic critical care capacity management
Rachaniotis, N. P., Giannopoulos, P. G., Fotopoulos, F., & Dasaklis, T. K. (2026) · Healthcare Analytics · doi:10.1016/j.health.2026.100466
Akalai, N., Doudach, L., Benba, A., & Belfkih, S. (2026) · International Conference on Innovative Research in Applied Science, Engineering and Technology (IRASET) · doi:10.1109/iraset68627.2026.11538491
Implementation of OR in healthcare services: a systematic review
Lamé, G., Newton, C., Grieco, L., Crowe, S., Bashford, T., & Hinrichs, S. (2026) · Journal of the Operational Research Society · doi:10.1080/01605682.2026.2712994
Metadata
- 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
- Social Sciences › Decision Sciences › Management Science and Operations Research › Healthcare Operations and Scheduling Optimization
- Health Sciences › Medicine › Public Health, Environmental and Occupational Health › 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
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
