Matching Items (3)
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- All Subjects: Electronic Health Records
- All Subjects: Radiology
- Creators: Chiou, Erin
- Creators: Kaldawi, Nicholas Emad
- Member of: Barrett, The Honors College Thesis/Creative Project Collection
Description
This thesis concerns the adoption of health information technology in the medical sector, specifically electronic health records (EHRs). EHRs have been seen as a great benefit to the healthcare system and will improve the quality of patient care. The federal government, has seen the benefit EHRs can offer, has been advocating the use and adoption of EHR for nearly a decade now. They have created policies that guide medical providers on how to implement EHRs. However, this thesis concerns the attitudes medical providers in Phoenix have towards government implementation. By interviewing these individuals and cross-referencing their answers with the literature this thesis wants to discover the pitfalls of federal government policy toward EHR implementation and EHR implementation in general. What this thesis found was that there are pitfalls that the federal government has failed to address including loss of provider productivity, lack of interoperability, and workflow improvement. However, the providers do say there is still a place for government to be involved in the implementation of EHR.
ContributorsKaldawi, Nicholas Emad (Author) / Lewis, Paul (Thesis director) / Cortese, Denis (Committee member) / Jones, Ruth (Committee member) / Barrett, The Honors College (Contributor) / School of Politics and Global Studies (Contributor) / School of Human Evolution and Social Change (Contributor)
Created2013-05
Description
Electronic Health Records (EHRs) began to be introduced in the 1960s. Government-run hospitals were the primary adopters of technology. The rate of adoption continually rose from there, doubling from 2007 to 2012 from 34.8% to about 71%. Most of the growth seen from 2007 to 2012 is a result of the passage of the Health Information Technology for Economic and Clinical Health (HITECH) Act as part of the American Reinvestment and Recovery (ARRA) Act. $19 billion dollars were made available as part of these two acts to increase the rate of Health Information Technology (HIT), of which EHRs are a large part. A national health information network is envisioned for the end stages of HITECH which will enable health information to be exchanged immediately from one health network to another. While the ability to exchange data quickly appears to be an achievable goal, it might come with the cost of loss of usability and functionality for providers who interact with the EHRs and often enter health data into an EHR. The loss of usability can be attributed to how the EHR was designed.
ContributorsRobinson, Lillie Elizabeth (Author) / Doebbeling, Bradley (Thesis director) / Chiou, Erin (Committee member) / College of Health Solutions (Contributor) / Barrett, The Honors College (Contributor)
Created2020-05
Description
Rapid advancements in Artificial Intelligence (AI), Machine Learning, and Deep Learning technologies are widening the playing field for automated decision assistants in healthcare. The field of radiology offers a unique platform for this technology due to its repetitive work structure, ability to leverage large data sets, and high position for clinical and social impact. Several technologies in cancer screening, such as Computer Aided Detection (CAD), have broken the barrier of research into reality through successful outcomes with patient data (Morton, Whaley, Brandt, & Amrami, 2006; Patel et al, 2018). Technologies, such as the IBM Medical Sieve, are growing excitement with the potential for increased impact through the addition of medical record information ("Medical Sieve Radiology Grand Challenge", 2018). As the capabilities of automation increase and become a part of expert-decision-making jobs, however, the careful consideration of its integration into human systems is often overlooked. This paper aims to identify how healthcare professionals and system engineers implementing and interacting with automated decision-making aids in Radiology should take bureaucratic, legal, professional, and political accountability concerns into consideration. This Accountability Framework is modeled after Romzek and Dubnick’s (1987) public administration framework and expanded on through an analysis of literature on accountability definitions and examples in military, healthcare, and research sectors. A cohesive understanding of this framework and the human concerns it raises helps drive the questions that, if fully addressed, create the potential for a successful integration and adoption of AI in radiology and ultimately the care environment.
ContributorsGilmore, Emily Anne (Author) / Chiou, Erin (Thesis director) / Wu, Teresa (Committee member) / Industrial, Systems & Operations Engineering Prgm (Contributor, Contributor) / Barrett, The Honors College (Contributor)
Created2019-05