Abstract
Clinics with a large volume of patients are often burdened with limited resources such as nurses and providers. Also, an efficient health system seeks short wait times for the patients to see the provider (indirect wait time) and within the clinic (direct wait time) during the day of the appointment. Additionally, the appointment duration, volume of patients, no-show behavior are uncertain. The direct and indirect wait times, stochastic parameters, rising treatment costs, and increased demand of patients motivate the need for efficient appointment schedules and clinic operations. In this paper, we develop a two-stage stochastic mixed-integer linear programming model (SMILP) integrated with a simulation model to generate a scheduling template for the providers to schedule individual patient appointments and resources. The model minimizes the expected wait times for the patients with a fair and equitable utilization of the resources. Computational experiments were conducted using a data-driven simulation model, and the results indicate that the proposed approach can significantly decrease patients’ direct and indirect wait times when compared to a deterministic indexing policy used for scheduling appointments.
Highlights
A variety of studies have documented the substantial deficiencies in the quality of healthcare delivered across the United States ([1]–[5])
The survey was organized in 2004, 2009, 2014, and 2017, and the results show an increase in the indirect wait time in 2017 compared to other years
We present an integrated approach of twostage stochastic and simulation models to generate scheduling template while considering the sources of uncertainties such as no-show behavior, direct and indirect wait times, and fair and equitable assignments of new patients to the providers
Summary
A variety of studies have documented the substantial deficiencies in the quality of healthcare delivered across the United States ([1]–[5]). Anvaryazdi et al.: Appointment Scheduling at Outpatient Clinics Using Two-Stage Stochastic Programming Approach to overcome the following problems: the no-show behavior of patient arrival, patient/provider check-in delays, overbookings, long wait times, and poor provider/staff utilization. We present an integrated approach of twostage stochastic and simulation models to generate scheduling template while considering the sources of uncertainties such as no-show behavior, direct and indirect wait times, and fair and equitable assignments of new patients to the providers. Following are the major contributions of this paper: 1) a two-stage stochastic model to generate a weekly scheduling pattern for individual providers that gets updated at regular intervals based on the type and mix of services rendered; 2) a clinic simulation model to determine sequencing rules to maintain the direct wait times within a threshold; FIGURE 1.
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