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Open Access Dissertation
Doctor of Philosophy (PhD)
Industrial Engineering & Operations Research
Year Degree Awarded
Month Degree Awarded
In this dissertation, we are applying and extending well-established concepts of flexibility in manufacturing and service sectors to a healthcare setting: primary care. In the healthcare scenarios, appointments are booked over time and thus future resource capacity is sequentially being allocated under partial demand information. In manufacturing flexibility is typically presented as a technology choice that requires heavy investment for expensive flexible equipment, or highly cross-trained workers, but can then be used at little or no cost to satisfy demand. In primary care, however, the resources are inherently flexible, as primary care physicians are naturally able to see other panel's patients. There is therefore no long-term cost to the system for ``installing'' flexibility, but a cost for ``using" this flexibility. This cost results from the loss of patient-physician continuity which may induce patient dissatisfaction, require longer appointment durations as the physician needs to study the unfamiliar patient's history, and potentially lead to poorer medical outcomes.
Appointments in primary care are of two types: 1) prescheduled appointments, which are booked in advance of a given workday; and 2) same-day appointments, which are booked as calls come during the course of the workday. This creates two competing demand streams with different continuity needs. For same-day patients, the need for timely access often outweighs the need for continuity. Prescheduled appointments, on the other hand, include patients with chronic conditions who require regular monitoring and follow ups, and for whom continuity is essential.
Within this context, we address two interrelated problems: 1) the capacity allocation between prescheduled and same-day patients and how it is impacted by flexibility and the addition of extra resources; 2) the dynamic allocation of same-day patients to an existing schedule as they call over the day. The study of the former aggregate capacity allocation problem is based on a 3-stage framework. We assume different flexibility configuration to study the impact of flexibility in primary care practices. Our study of flexibility in primary care practices suggest that better management of the inherently flexibility inside primary care practices helps to balance prescheduled and same-day demand streams. We then study the latter dynamic allocation problem based on a simulation model, which captures several realistic issues like, patient' preferences, call-in frequency of same-day requests, and policies to reserve time blocks for prescheduled patients, etc. Our study provides guidelines for clinic to provide better quality of care for patients.
Gao, Xiaoling, "Flexibility and Capacity Allocation under Uncertain Prescheduled (Non-urgent) Demand and Same-day (Urgent) Demand in Primary Care Practices" (2015). Doctoral Dissertations. 299.