Document Type

Dissertation

Degree

Doctor of Philosophy

Major

Business Administration

Date of Defense

9-28-2018

Graduate Advisor

Dr L. Douglas Smith

Co-Advisor

Haitao Li

Committee

Donald C. Sweeney II

Lorena Bearzotti

Abstract

This research focuses on the design of a procurement model for expensive medical supplies in a healthcare supply chain. A deterministic optimization model generates recommendations for optimal purchases of products in a given planning period. The model combines common concepts of supply chain procurement such as leveraging tiered pricing, ensuring supply base diversity with phenomena unique to healthcare supply chain such as consideration of physician preference for products. The deterministic optimization model minimizes total spend over a chosen planning period with consideration of four key decision parameters:

  • Physician preference requirements (which are imposed as rules on product substitutability),
  • Upper limits on vendor market share to ensure a suitably diverse supply base
  • Vendors’ performance scores to impose standards for product pricing, quality, service, etc.
  • Quantity discount rebate parameters for bulk purchasing to help contain medical costs

The optimization model reveals the extent to which higher product substitutability and lower supply base diversity may help hospitals reduce total procurement costs. Experiments with the optimization model also reveal the potential consequences of rater biases in vendor scorecards on procurement cost. The various parameter combinations listed above may be used in negotiating contracts for better pricing.

In summary, this research addresses questions pertinent to healthcare supply chains concerning the possible cost of physician preference for products, the impact of subjective scorecards on procurement costs, the effect of planning period on procurement plans, and the cost of vendor diversity.

OCLC Number

1101187306

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