Patient‐controlled use of nonphysician providers: Appointment scheduling in mixed‐provider settings

Enayon Sunday Taiwo, Sergei Savin, Yuohua Chen (Frank) and Kwai‐Sang Chin

Production and Operations Management, 2023, vol. 32, issue 8, 2656-2673

Abstract: The aging population and increasing chronic disease load are rapidly changing the face of primary care delivery, with mid‐level (e.g., nurse) practitioners providing growing proportion of patient care. Potential differences in the quality of care offered by physicians and nurse practitioners may affect patient preferences, thus leading to patient choice behavior. This paper focuses on the problem of appointment scheduling for physician–nurse teams in the presence of patient choice and no‐shows. We propose a novel model that accounts for patient choices in a system with two provider types. Despite the increased structural complexity of the model, we derive sufficient conditions under which the problem is efficiently solvable. To counter the computational challenges arising in the general setting, we propose an easy‐to‐implement heuristic, which is proven to be optimal in the absence of patient no‐shows. Our numerical study shows how the ratio of qualities of care delivered by nurses and physicians affect the profitability of the medical practice, enabling the analysis of the trade‐offs involved in hiring a nurse practitioner. This paper introduces a patient‐controlled approach to incorporating nonphysician providers into physician‐led outpatient care delivery systems and compares it to widely used “ice breaker” and “standalone” modes of using nonphysician providers. Our findings reveal that clinical practices that employ mixed (physicians and nonphysicians) provider pools can significantly improve their financial and operational performance by moving away from the “ice breaker” and “standalone” use of nonphysician providers by delaying the selection of an appropriate care provider till the actual day of care delivery.

Date: 2023
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