Appointment scheduling strategies in primary care clinics and surgical operating units

Sangbok Lee, Purdue University

Abstract

The principal of scheduling in healthcare delivery systems is to control conflicting preferences and priorities of its stakeholders under the restrictions of limited clinical resources. In most instances of that domain, the number of stakeholders is large and there are a lot of human-associated uncertainties, and thus the scheduling problems are very challenging. However, if we consider this era's escalating healthcare costs and aging population, tackling those problems needs prompt attention. Out of various fields in the healthcare delivery systems, this dissertation has mainly focused on appointment scheduling strategies in primary care clinics and surgical operating units. First, we conducted a simulation study to propose operational guidelines for open access (OA) scheduling strategies in primary care clinics. OA, sometimes so called advanced scheduling, leaves majority of the slots open to same day appointments (SDA) and thus it is expected to reduce patients' waiting times that may result in patient no-shows and cancellations. This research provides the rules of thumb for appropriate proportion of SDA slots to daily capacity, which takes into account the patients waiting times, successful appointment rates, and resource utilization. Overbooking strategies in primary care clinics also have been noted by many researchers due to its ability of working as buffers to uncertain events. Both OA and OB function as alternatives to the conventional appointment scheduling. However, their fundamental comparisons in practice have not been studied a lot. The goal of this study is to compare the two scheduling strategies in terms of overtime staffing, patient waiting, missing appointment opportunities, and time slot utilization. A discrete-event simulation was employed to model the primary care clinic settings with different demand levels. Under the uncertainties in surgical operations, efficient scheduling of surgery starting times before their execution is one of the difficult tasks. Moreover, in a setting of multiple operating rooms (OR), there may be the congestion in admission to PACU after surgeries unless enough PACU resource is provided nor efficient scheduling strategy is applied. In this study, we have developed a two-phased approach to determine the surgery starting times for multiple ORs under limited resources of PACU. The first phase formulates this problem as a flexible job shop scheduling with fuzzy sets for modeling uncertain service durations. From the obtained solution represented as fuzzy numbers, a newsvendor-like heuristic was proposed to establish precise time schedules in the second phase. The performance of the approach was shown superiority over a simulation-based optimization technique from a literature. Finally, we investigated suitable proportion of PACU resources to OR with the obtained start-time schedule from our approach.

Degree

Ph.D.

Advisors

Yih, Purdue University.

Subject Area

Industrial engineering|Surgery|Health care management

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