Author ORCID Identifier

https://orcid.org/0000-0003-3497-0411

Date Available

11-3-2021

Year of Publication

2021

Degree Name

Doctor of Philosophy (PhD)

Document Type

Doctoral Dissertation

College

Health Sciences

Department/School/Program

Rehabilitation Sciences

First Advisor

Dr. Anne L. Harrison

Second Advisor

Dr. Joseph C. Stemple

Abstract

Non-communicable, chronic diseases are highly prevalent in the United States, reducing the quality of life for those affected and contributing to the majority of the nation’s healthcare expenditure. These conditions include, among others, cardiovascular disease, diabetes, and musculoskeletal disease. Musculoskeletal disease is particularly of interest for the field of physical therapy as the vast majority of patients seeking care in the outpatient setting present with musculoskeletal pain complaints, resulting in limitations in function, participation, and quality of life for the patient.

The factors influencing health outcomes are diverse and include a person’s physical environment, social and economic factors, access to quality clinical care, and health behaviors. Thus, managing chronic disease requires intervention at the level of the patient, provider, healthcare organization, community, and the local, state, and federal governments. Implementing multilevel intervention and advocacy can reduce the impact of chronic disease and allow people to more meaningfully engage in their lives. The purpose of this dissertation was to first describe a population attending a pro bono physical therapy clinic for musculoskeletal pain complaints in the southeastern United States in regards to measures of physical health, emotional health, socioeconomic status, and pain presentation. These measures were then assessed to discover their usefulness in identifying chronic disease as well as their ability to identify clinically-important patient subgroups that may require a more tailored treatment approach. By understanding the patient population more completely, future directions for addressing patient needs through clinical intervention, clinical programming, and advocacy endeavors can be implemented to produce more positive health outcomes.

Theoretical foundation for the management of chronic disease was informed by the Innovative Care for Chronic Conditions framework (World Health Organization, 2002). The County Health Ratings Model (University of Wisconsin Population Health Institute, 2019) and the Tool for Health & Resilience in Vulnerable Environments (Prevention Institute, 2004) were used as guides in determining the important factors influencing health outcomes and routes of intervention to improve health equity. Models of the pathophysiology of metabolic syndrome (Eckel et al, 2005), a precursor to cardiovascular disease and diabetes, and their impact on musculoskeletal disease (Collins et al, 2018) were also considered to identify clinical measures in the physical therapy setting that can better inform the clinician of the patient’s condition.

A clinically-based, standardized intake process was created and implemented at a pro bono physical therapy clinic to capture measures of physical health, emotional health, health behaviors, and social and economic variables. The measures chosen fall within the scope of physical therapy practice and were selected to bolster the treating clinician’s clinical decision making to provide patient-centered care. A retrospective chart review was performed over a two-year period (December 2017 to December 2019) to collect these data from the initial patient evaluation. Descriptive statistics were used to define the population attending the clinic and their potential healthcare needs. Regression analysis was then performed to determine which measures best inform the clinician regarding metabolic disease status in this population and whether those at risk of metabolic disease presented differently from those without. Finally, a latent class analysis was performed to identify unique patient subgroups within those presenting to the clinic and the distinguishing features of these subgroups.

Digital Object Identifier (DOI)

https://doi.org/10.13023/etd.2021.060

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