ORAHS2024
Abstract Submission

155. An optimization decision support tool for patient assignments based on clinical pathways

Contributed abstract in session MC-5: (Multi)Appointment /1, stream Regular talks.

Monday, 11:00-12:30
Room: Room S6

Authors (first author is the speaker)

1. Valérie Bélanger
Logistics and Operations management, HEC Montréal
2. Eduardo Redondo
Operations and Decisión Systems - FSA, Université Laval
3. Angel Ruiz
Opérations et systèmes de décision, Université Laval

Abstract

Patient-to-worker assignment in healthcare clinics is crucial for ensuring quality care delivery while optimizing resource utilization. As new patients arrive dynamically, clinics face the challenge of efficiently assigning them to healthcare professionals for appropriate treatment. This process involves scheduling a series of clinical activities, such as examinations, consultations, and follow-ups, over days or months. This study proposes an optimization decision support tool to address the challenges of patient-to-worker assignment, leveraging the concept of clinical pathways. Clinical pathways guide healthcare professionals through patient treatment stages. By integrating clinical pathways into the assignment process, we aim to enhance the consideration of patients' overall treatment requirements, thus improving resource utilization and reducing delays. Through empirical analysis using a discrete-event simulation model, we have compared the performance of our approach with standard practices. The results demonstrate the effectiveness of our tool in minimizing patient wait times and optimizing resource utilization. This comparative analysis not only validates the efficacy of our tool but also provides decision-makers with valuable insights into the tangible impact of different management strategies on patient care and resource allocation, thereby enhancing their ability to make informed decisions.

Keywords

Status: accepted


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