Document Type

Thesis - Open Access

Award Date

2019

Degree Name

Master of Science (MS)

Department

Mathematics and Statistics

First Advisor

Semhar Michael

Keywords

Finite mixture models, Multiple linear regression, Patient activation measure, Patient engagement

Abstract

Patient activation measure (PAM) is widely adopted by health care providers to access individual's knowledge, skill, and confidence for managing one's health and healthcare. Patient activation measure (PAM), licensed by Insignia Health, is widely adopted by health care providers to access individual's knowledge, skill, and confidence for managing one's health and healthcare. Multiple studies corroborate the effectiveness of activation measure in predicting most health behaviors, including preventive behaviors, healthy behaviors, self-management behaviors, and health information seeking. However, PAM is heavily dependent on subjective patient-reported data, which are often incomplete. The purpose of this study is to develop an objective statistical model to create a score derived from patient behavioral measurements. Ranging from 1 to 3, the score, which we named patient engagement score (PES), was derived entirely from three objective variables-number of immunization, number of missed scheduled visits, and rate of patient adherence to prescription refill using finite mixture model and EM algorithm. Finally, we performed simple and multiple linear regressions for the association between PES and each of the health-related outcomes.

Format

application/pdf

Number of Pages

71

Publisher

South Dakota State University

Rights

In Copyright - Educational Use Permitted
http://rightsstatements.org/vocab/InC-EDU/1.0/

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