title: Predicting Tests Ordered in Hospital Laboratories using Generalized Linear Modeling.
abstract: Laboratory services in healthcare systems play a vital role in inpatient care. Most hospital laboratories are facing the challenge of reducing cost and improving service quality. The author focuses on identifying test order patterns in a laboratory for a large urban hospital. The data collected from this facility consists of all tests ordered over a three-month time frame and contains test orders for approximately 17,500 patients. Poisson and negative binomial regression models are used to determine how well patient characteristics (patient length of stay and the medical units in which patients are placed) will predict the number of tests being ordered. The test order prediction model developed in this study will aid the management and phlebotomists in the hospital laboratory in securing methods to satisfy the test order demand. By implementing the recommendations of this study, hospital laboratories should see significant improvements in phlebotomist productivity and resource utilization, implementation of which could result in cost savings.
authors.affiliation: a Department of Marketing, Transportation, and Supply Chain , College of Business and Economics, North Carolina Agricultural and Technical State University , Greensboro , North Carolina , USA.
authors.forename: Laquanda T
authors.initials: LT
authors.lastname: Leaven
keywords: Generalized linear modeling; healthcare; hospital laboratory; test orders