Healthcare Operations
Care services · decision horizons · twelve models
Healthcare operations research asks how hospitals, ambulance services, home–care agencies, and long–term care facilities allocate limited staff, beds, operating theatres, equipment, and time to deliver care that is clinically effective, equitable, and affordable — across horizons that stretch from a triage decision made in seconds to a regional facility plan made over years. This section presents twelve canonical healthcare OR problems, each as a live interactive solver grounded in a real clinical–operations decision, organized along the Hulshof et al. (2012) 2–axis taxonomy — decision horizon × care service — which specializes the generic healthcare planning–and–control framework of Hans, van Houdenhoven & Hulshof (2012) to the managerial area of resource capacity planning.
Why healthcare OR matters
Scale of the problem · three anchor statistics
Decision framework
Four lenses on the same twelve applications
The canonical taxonomy of Hulshof, Kortbeek, Boucherie, Hans & Bakker (2012) — itself specializing the Hans et al. (2012) framework to resource capacity planning — organizes healthcare decisions along two axes: the decision horizon (strategic, tactical, offline operational, online operational) and the care service (ambulatory, emergency, surgical, inpatient, home, residential). Every application in this section occupies one cell. Dashed cells are honest gaps — decisions that exist in practice but are not yet modelled here.
The Hans, van Houdenhoven & Hulshof (2012) generic framework puts decisions along the horizon axis against four managerial areas: medical planning (clinician-driven protocol, triage, treatment decisions), resource capacity planning (staff, facilities, equipment), materials planning (supplies, pharmacy, blood), and financial planning. Our current catalog is concentrated in resource capacity — the Medical, Materials, and Financial columns surface honest blind spots.
The patient-centric complement: every application has a primary point of intervention along the clinical pathway from prevention through palliation. Aringhieri et al. (2017) apply this pathway lens to emergency medical services; care–chain surveys (Vanberkel et al. 2010) generalize it to cross-department planning.
A resource-centric cut: the OR problem family each application belongs to depends largely on the renewable resource being scheduled or the consumable being distributed. Surveys like Van den Bergh et al. (2013) (personnel scheduling) and Ernst et al. (2004) (staff rostering) use this lens to categorize the vast healthcare workforce literature; Cardoen et al. (2010) does the same for surgical resources.
Application catalog
All twelve pages · click a card to open the interactive solver
Current research frontiers
Where healthcare OR is actively evolving
Integrated care-chain planning
Hulshof et al. (2012) flag the persistent void in OR/MS models that span multiple departments along a patient's care pathway. Joint inpatient-surgical-outpatient capacity planning, and the bed–to–OR–to–ward cascade, are active research targets.
Stochastic & robust scheduling under demand uncertainty
Arrival rates, service times, and no-show behavior are inherently stochastic. Two-stage SP, distributionally robust optimization (DRO), and chance-constrained ILPs for nurse rostering and OR scheduling are a dominant frontier (Erhard et al. 2018; Gupta & Denton 2008).
Online learning & real-time dispatching
Reinforcement-learning-augmented decision policies for ambulance dispatching, ED patient flow, and add-on surgery scheduling — leveraging electronic health records and sensor streams for online operational control.
Equity-aware healthcare operations
Formalizing fairness objectives — nurse-preference balance, geographical equity of access, wait-time fairness across patient classes — alongside efficiency. Linking OR to health-disparities measurement is a growing area.
Key references
Foundational surveys · cited above · DOIs included