Salman, Hamdy
(2019)
Workflow Analysis, Scheduling, and Chance Constraint Models in Community Pharmacy Operations.
Doctoral Dissertation, University of Pittsburgh.
(Unpublished)
Abstract
Community pharmacy networks provide most of the US population's prescribed medication, but not picking up the medication or using it improperly can lead to problems such as medication non-adherence and medication misuse. This research focuses on improving community pharmacy network services by proposing a change in the role pharmacists play in these networks. A key task pharmacists perform which is a critical step in the medication dispensing process is verifying that the medication filled is the one prescribed and that it does not conflict with other medications the patient is taking. This dissertation proposes that pharmacists provide important counseling services (i.e. PDPC services) to patients inside community pharmacies. We discuss how adding PDPC services changes the workflow of a community pharmacy and discuss strategies to overcome obstacles preventing pharmacists from providing PDPC services.
We use a Discrete Event Simulation (DES) model to simulate a local community pharmacy as well as a community pharmacy network to evaluate strategies that can be used to either improve the workflow process internally (internal strategies) or provide an external resource that can be used to provide support to the pharmacy (external strategies). The internal strategies studied are adding a staff member, predicting prescription pick up times, and providing short duration PDPC services in busy hours. The external strategies studied are utilizing a central fill to dispense part of the pharmacy's demand and adding PDPC kiosks to provide PDPC services inside the pharmacy. The effect of each strategy and the extent of its benefits are studied and highlighted in chapters 2 & 3.
The central fill location problem was modeled as a chance constraint stochastic P-median capacitated facility location problem. Three extensions to the location model are added and discussed in detail. Several lower bounds were provided to the problem and an efficient solution method was used to solve the problem. Finally the model was applied to a community pharmacy network in PA in a case study. The results showed that ignoring the highest demand scenarios can save the community pharmacy network from having to add an additional central fill.
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Details
| Item Type: |
University of Pittsburgh ETD
|
| Status: |
Unpublished |
| Creators/Authors: |
|
| ETD Committee: |
|
| Date: |
11 September 2019 |
| Date Type: |
Publication |
| Defense Date: |
6 May 2018 |
| Approval Date: |
11 September 2019 |
| Submission Date: |
23 April 2019 |
| Access Restriction: |
No restriction; Release the ETD for access worldwide immediately. |
| Number of Pages: |
111 |
| Institution: |
University of Pittsburgh |
| Schools and Programs: |
Swanson School of Engineering > Industrial Engineering |
| Degree: |
PhD - Doctor of Philosophy |
| Thesis Type: |
Doctoral Dissertation |
| Refereed: |
Yes |
| Uncontrolled Keywords: |
Community pharmacy operations |
| Date Deposited: |
11 Sep 2019 14:52 |
| Last Modified: |
11 Sep 2019 14:52 |
| URI: |
http://d-scholarship.pitt.edu/id/eprint/36594 |
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