Off-campus UMass Amherst users: To download campus access theses, please use the following link to log into our proxy server with your UMass Amherst user name and password.
Non-UMass Amherst users: Please talk to your librarian about requesting this thesis through interlibrary loan.
Theses that have an embargo placed on them will not be available to anyone until the embargo expires.
Access Type
Campus Access
Document Type
thesis
Degree Program
Industrial Engineering & Operations Research
Degree Type
Master of Science in Industrial Engineering and Operations Research (M.S.I.E.O.R.)
Year Degree Awarded
2012
Month Degree Awarded
February
Keywords
Capacity Allocation, Flexibility, Primary Care, Physician Flexibility, Scheduling
Abstract
Key performance measures for PC performance are timeliness and continuity. Whereas the first refers to the ability to obtain an appointment as soon as possible, the latter warrants a patient being able to see a familiar physician. In this context one has to consider the two types of appointments - same-day and prescheduled. The former is characterized by an urgent need of the patient to see a physician, the latter embodies non-urgent follow-up visits or regular appointments due to a chronic comorbidity. How should requests for appointments be assigned in order to deliver on the conflicting key metrics? What impact does the presence and the location of prescheduled appointments have in this context? How does the capacity allocation between prescheduled and same-day demand influence the decision making in the clinic? Using a stochastic dynamic program to model the dynamics of practice, we explore various ways of managing the inherent flexibility of physicians to see each others’ patients. Patients are calling in for same-day appointments. Thus, assignment decisions have to be made dynamically in real time under uncertainty of future demand and in presence of prescheduled appointment slots. The study consists of three parts: first, we examine the impact of the location of prescheduled appointments on the performance of the clinic. Second, we use our structural insights gained in the first part in order to derive implementable heuristic assignment policies. Third, we evaluate the performance of the heuristics in comparison to the optimal solution gained in the stochastic dynamic program and derive implications for the practice of primary care.
DOI
https://doi.org/10.7275/2392948
First Advisor
Hari J. Balasubramanian
Second Advisor
Ana Muriel