EURO 2024 Copenhagen
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2559. Optimizing physician allocation in an imaging diagnostic company

Invited abstract in session TC-15: Staffing and workforce planning and scheduling, stream OR in Health Services (ORAHS).

Tuesday, 12:30-14:00
Room: 18 (building: 116)

Authors (first author is the speaker)

1. Maristela Santos
Department of Applied Mathematics and Statistics, University of Sao Paulo
2. Vladimir Yuri Tasso
ICMC/USP
3. Caio Tomazella
UFSCar
4. Thiago Mariotti
ICMC/USP

Abstract

Imaging diagnostic companies primarily rely on specialized medical workforce to deliver their services. However, there has been a stagnation in the number of specialist physicians over the years, making the workforce scarcer and more expensive. Another factor negatively impacting imaging diagnostic companies is health insurance providers' current financial status due to the sector's costs. Given this scenario, optimizing the allocation of medical resources in shifts is mandatory to achieve optimal outcomes, maximizing revenue and reducing costs associated with idleness. Idleness occurs when the demand is low for one examination unit, and physicians are over-allocated. In contrast, the demand for examinations in another unit can be high, but there is a need for more physicians. An integer linear optimization model was developed to allocate physicians in shifts and medical units, allowing physicians to be allocated in nearby units with available rooms. Additionally, two objective functions were analyzed: minimizing the number of unmet examinations, maximizing the lowest coverage considering units and shifts. Instances from an imaging diagnostic company were used for computational tests. When comparing the results obtained with data from the company, the model demonstrated a significant reduction in unmet demand and superior overall coverage, proving to be a practical approach to optimizing the allocation of medical resources.

Keywords

Status: accepted

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