Date of Conferral
2015
Degree
Ph.D.
School
Management
Advisor
Robert Kilmer
Abstract
The prevalence of medical misdiagnosis has remained high despite the adoption of diagnostic software. This ongoing controversy about the role of technology in mitigating the problem of misdiagnosis centers on the question of whether diagnostic software does reduce the incidence of misdiagnosis if properly relied upon by physicians. The purpose of this quantitative, cross-sectional study based on planned behavior theory was to measure doctors' opinions of diagnostic technology's medical utility. Recruitment e-mails were sent to 3,100 AMA-accredited physicians through their database that yielded a sample of 99 physicians for the study. One-sample t tests and, where appropriate because of non-normal data, one-sample Wilcoxon signed-rank tests were conducted on the data to address the following key research questions on whether diagnostic software decreases misdiagnosis in healthcare versus unassisted human diagnostic method, if physicians use diagnostic software frequently enough to decrease misdiagnosis in healthcare, and if liability concerns prevent physicians from using diagnostic software. It was found that in the opinion of those surveyed (a) diagnostic software was likely to result in fewer misdiagnoses in healthcare than unassisted human diagnostic methods, (b) when speaking for themselves, physicians thought they used diagnostic software frequently enough to decrease misdiagnoses, and (c) physicians agreed they were not prevented from using diagnostic software because of liability concerns. The study's social significance is the affirmation of diagnostic software's usefulness: Policy and technology stakeholders can use this finding to speed the adoption of diagnostic software, leading to a reduction in the socially costly problem of misdiagnosis.
Recommended Citation
Alaofin, Babatunde Ayodele, "The Value of Diagnostic Software and Doctors' Decision Making" (2015). Walden Dissertations and Doctoral Studies. 344.
https://scholarworks.waldenu.edu/dissertations/344
Included in
Artificial Intelligence and Robotics Commons, Business Administration, Management, and Operations Commons, Databases and Information Systems Commons, Management Sciences and Quantitative Methods Commons