A data-driven hierarchical MILP approach for scheduling clinical pathways: a real-world case study from a German university hospital

Abstract

Facing economic pressure and case-based compensation systems, hospitals strive for effectively planning patient hospitalization and making efficient use of their resources. To support this endeavor, this paper proposes a flexible hierarchical mixed-integer linear programming (MILP)-based approach for the day-level scheduling of clinical pathways (CP). CP form sequences of ward stays and treatments to be performed during a patient's hospitalization under consideration of all relevant resources such as beds, operating rooms and clinical staff. Since in most hospitals CP-related information needed for planning is not readily available, we propose a data-driven approach in which the structure of the CP to be scheduled including all CP-related constraints is automatically extracted from standardized hospital billing data available in every German hospital. The approach uses a flexible multi-criteria objective function considering several patient-and hospitalrelated aspects which makes our approach applicable in various scenarios. Furthermore, in contrast to other approaches, it considers several practically relevant aspects ensuring the implementability of the scheduling results such as multiple ward stays per hospitalization and gender-separated room assignments. Regarding the treatment resources such as operation rooms and clinical staff, it considers the eligibility of resources for treatments based on information such as special

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“…Also in that case, the proposed approach was designed with the intention of optimizing the non-disease-specific aspects of health care. Recently, a mixed-integer linear programming-based approach for day-level scheduling of CPs has been proposed (Schwarz et al, 2019). The approach used a multi-criteria objective function considering several hospital-related aspects; however, also in that case, the proposed method targeted mainly the optimization of health care management.…”