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Final Dissertation Seth Duffy.pdf (2.45 MB)
ETD Abstract Container
Abstract Header
Leveraging Evidence-Based Innovation to Mitigate Stratified Cancer Disparities
Author Info
Duffy, Seth Robert
Permalink:
http://rave.ohiolink.edu/etdc/view?acc_num=frank1649886436049268
Abstract Details
Year and Degree
2022, Doctorate of Healthcare Administration, Franklin University, Health Programs.
Abstract
Background: Epidemiological evidence illustrates cancer as a leading cause of global morbidity and mortality, approaching 20 million new diagnoses annually and exhibiting one of the most complex and nonuniform burdens throughout high-income countries (HIC) and developing nations alike. Despite an ongoing “War on Cancer”, significant translational disconnects are hypothesized as impeding the diffusion of critical health innovations, resulting in low-impact implementation as well as rural and isolated America experiencing dichotomous rates of cancer survival when compared to metropolitan areas (Freeman, 2004; Gemert-Pijnen, 2011; NIH, 2007; Rodin, 2017). While parallel healthcare disciplines have successfully leveraged Rogers’ Diffusion of Innovation (DOI) towards efficacious adoption of EBI, a persistent void within radiation oncology literature was identified. A DOI theoretical framework provided means through which fundamental differences in perceptions could be identified and contextualized. Methods: The current study conducted a cross-sectional exploration of geographically stratified radiation oncology treatment planners’ perceptions as they pertained to evidence-based innovations (EBI). University IRB approval was obtained in Winter of 2021. Through the use of randomized sampling and validated DOI instrumentation, the perceptions of 165 practitioners were collected across 48 states using an electronic survey. Respondents were stratified along the USDA ERS rural-urban codification continuum (RUCC) and in accordance with historical workforce reporting. Techniques to ensure data reliability and that all statistical assumptions had been satisfied were performed prior to analysis. Final results were calculated using SAS. Results: Fundamental intra-strata differences in the perceptions of EBI were identified for the perceived characteristics (PCI) of compatibility (t(160) = 4.12, P < 0.0001, d = 0.7708), relative advantage (t(161) = 3.72, P = 0.0003, d = 0.6960), visibility (t(161) = 2.99, P = 0.0032, d = 0.5453), and result demonstrability (t(161) = 2.98, P = 0.0034, d = 0.5565). Metropolitan respondents expressed strongest agreement with survey items related to relative advantage, while nonmetropolitan respondents exhibited strong agreement with survey items related to voluntariness. Innovation attributes of voluntariness, ease of use, trialability, and image did not exhibit statistically significant differences when comparing metropolitan and nonmetropolitan responses. Nearly three-quarters (72 percent) of respondents indicated the adoption of EBI into clinical practice within the past year. Conclusions: Study outcomes directly substantiate earlier assertions by the NIH Center to Reduce Cancer Health Disparities (2007) and shed new light on persistent barriers to diffusing EBI towards improving cancer survival across rural-urban strata. Intra-strata differences in the perceptions of valuable EBI may ultimately manifest as poorer rates of adoption and nascent implementation, thus failing to bridge rural-urban divides. The diffusion theoretical framework employed within this study demonstrated vast potential in analyzing fundamental perceptions of cancer care professionals, as well as validating practical mechanisms by which outcomes could be translated towards effectively leveraging critical health innovations. Future research is encouraged to not only reproduce the findings herein, but also to pursue correlational designs that examine specific innovations that may truly mitigate disparities in cancer survival.
Committee
Dale Gooden (Committee Chair)
Gail Frankle (Committee Member)
Lewis Chongwony (Committee Member)
Pages
171 p.
Subject Headings
Health Care
;
Health Care Management
;
Health Sciences
;
Information Systems
;
Information Technology
;
Medicine
;
Philosophy
;
Physics
;
Public Health
;
Radiation
Keywords
Innovation, Radiation Oncology, Radiotherapy, Treatment Planning, Artificial Intelligence, Machine Learning, Automation, Diffusion of Innovation Theory, DOI, Perceived Characteristics of Innovation (PCI)
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Citations
Duffy, S. R. (2022).
Leveraging Evidence-Based Innovation to Mitigate Stratified Cancer Disparities
[Doctoral dissertation, Franklin University]. OhioLINK Electronic Theses and Dissertations Center. http://rave.ohiolink.edu/etdc/view?acc_num=frank1649886436049268
APA Style (7th edition)
Duffy, Seth.
Leveraging Evidence-Based Innovation to Mitigate Stratified Cancer Disparities.
2022. Franklin University, Doctoral dissertation.
OhioLINK Electronic Theses and Dissertations Center
, http://rave.ohiolink.edu/etdc/view?acc_num=frank1649886436049268.
MLA Style (8th edition)
Duffy, Seth. "Leveraging Evidence-Based Innovation to Mitigate Stratified Cancer Disparities." Doctoral dissertation, Franklin University, 2022. http://rave.ohiolink.edu/etdc/view?acc_num=frank1649886436049268
Chicago Manual of Style (17th edition)
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Document number:
frank1649886436049268
Download Count:
197
Copyright Info
© 2022, all rights reserved.
This open access ETD is published by Franklin University and OhioLINK.