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Acceptance and Use of Artificial Intelligence in Healthcare: A System Dynamics Approach
Acceptance and Use of Artificial Intelligence in Healthcare: A System Dynamics Approach
상세정보
- 자료유형
- 학위논문 서양
- 최종처리일시
- 20260202104729
- ISBN
- 9798315778448
- DDC
- 610
- 서명/저자
- Acceptance and Use of Artificial Intelligence in Healthcare: A System Dynamics Approach
- 발행사항
- [Sl] : Case Western Reserve University, 2024
- 발행사항
- Ann Arbor : ProQuest Dissertations & Theses, 2024
- 형태사항
- 119 p
- 주기사항
- Source: Dissertations Abstracts International, Volume: 86-12, Section: B.
- 주기사항
- Advisor: Rose, Susannah;Dolansky, Mary A.
- 학위논문주기
- Thesis (Ph.D.)--Case Western Reserve University, 2024.
- 초록/해제
- 요약Artificial intelligence (AI) is a transformative force in healthcare, holding the potential to revolutionize patient care, diagnostics, treatment plans, and administration. The applications of AI in healthcare range from wearable devices with AI-powered algorithms monitoring vital signs to sophisticated clinical decision support tools used by healthcare professionals. For AI to have successful implementation in healthcare, there must be a deeper understanding of both the technical aspects of AI and the human dimension, considering the experiences, expectations, and needs of key stakeholders, including patients, physicians, and data scientists developing healthcare applications. The purpose of this research was to (1) characterize patient, physician, and data scientist perspectives and acceptance of the integration of artificial intelligence (AI) into healthcare (Section 2) and (2) use this qualitative data collected to understand acceptance and use of AI by key stakeholders using a system dynamics approach (Section 3).In the first part of this work, semi-structured individual interviews and focus groups were held with patients (n=23), primary care physicians (n=26), and data scientists (n=14) at the Cleveland Clinic. While recognizing the value of AI as a diagnostic aid, patients envisioned a collaborative approach where physicians retain the role of final decision-makers. Data scientists described systems they use to develop, implement, and maintain AI tools used in healthcare and agreed that a system for monitoring the performance of an AI tool post-implementation must be in place. Physicians placed specific emphasis on improving efficiencies and reducing their burden of work in providing care. All stakeholders regarded AI as a tool, not a replacement for the human aspect in the provision of care. As the second step of this work, data from the focus groups was then viewed with a system dynamics perspective to an existing frameworks of understanding technology acceptance: the Technology Acceptance Model (TAM) and the Unified Theory of Acceptance and Use of Technology (UTAUT). The system dynamics perspective applied to the use of AI in healthcare highlighted the causality and interrelations between variables at play within technology acceptance and the implications on use of AI-enabled technologies. The key enhancements to the TAM when contemporized as a complex adaptive system include the acknowledgement of dynamic interactions, feedback loops, the time dimension in acceptance and use, adaptability and learning, non-linearity, and considerations of human behavioral complexity.At the core of translational research is the process of moving evidence and innovations into the public sector to improve the health of individuals and the public. Combining stakeholder perspectives with a system dynamics approach is a strategy for the successful development and implementation of AI in healthcare. This work not only addresses the individual stakeholder but also considers the broader societal and organizational factors to ensure implementation is timely, relevant, and useful to the populations to which it is intended to serve.
- 일반주제명
- Medicine
- 키워드
- System dynamics
- 기타저자
- Case Western Reserve University Clinical Translational Science
- 기본자료저록
- Dissertations Abstracts International. 86-12B.
- 전자적 위치 및 접속
- 로그인 후 원문을 볼 수 있습니다.
MARC
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■1001 ▼aMoennich, Laurie Ann.
■24510▼aAcceptance and Use of Artificial Intelligence in Healthcare: A System Dynamics Approach
■260 ▼a[Sl]▼bCase Western Reserve University▼c2024
■260 1▼aAnn Arbor▼bProQuest Dissertations & Theses▼c2024
■300 ▼a119 p
■500 ▼aSource: Dissertations Abstracts International, Volume: 86-12, Section: B.
■500 ▼aAdvisor: Rose, Susannah;Dolansky, Mary A.
■5021 ▼aThesis (Ph.D.)--Case Western Reserve University, 2024.
■520 ▼aArtificial intelligence (AI) is a transformative force in healthcare, holding the potential to revolutionize patient care, diagnostics, treatment plans, and administration. The applications of AI in healthcare range from wearable devices with AI-powered algorithms monitoring vital signs to sophisticated clinical decision support tools used by healthcare professionals. For AI to have successful implementation in healthcare, there must be a deeper understanding of both the technical aspects of AI and the human dimension, considering the experiences, expectations, and needs of key stakeholders, including patients, physicians, and data scientists developing healthcare applications. The purpose of this research was to (1) characterize patient, physician, and data scientist perspectives and acceptance of the integration of artificial intelligence (AI) into healthcare (Section 2) and (2) use this qualitative data collected to understand acceptance and use of AI by key stakeholders using a system dynamics approach (Section 3).In the first part of this work, semi-structured individual interviews and focus groups were held with patients (n=23), primary care physicians (n=26), and data scientists (n=14) at the Cleveland Clinic. While recognizing the value of AI as a diagnostic aid, patients envisioned a collaborative approach where physicians retain the role of final decision-makers. Data scientists described systems they use to develop, implement, and maintain AI tools used in healthcare and agreed that a system for monitoring the performance of an AI tool post-implementation must be in place. Physicians placed specific emphasis on improving efficiencies and reducing their burden of work in providing care. All stakeholders regarded AI as a tool, not a replacement for the human aspect in the provision of care. As the second step of this work, data from the focus groups was then viewed with a system dynamics perspective to an existing frameworks of understanding technology acceptance: the Technology Acceptance Model (TAM) and the Unified Theory of Acceptance and Use of Technology (UTAUT). The system dynamics perspective applied to the use of AI in healthcare highlighted the causality and interrelations between variables at play within technology acceptance and the implications on use of AI-enabled technologies. The key enhancements to the TAM when contemporized as a complex adaptive system include the acknowledgement of dynamic interactions, feedback loops, the time dimension in acceptance and use, adaptability and learning, non-linearity, and considerations of human behavioral complexity.At the core of translational research is the process of moving evidence and innovations into the public sector to improve the health of individuals and the public. Combining stakeholder perspectives with a system dynamics approach is a strategy for the successful development and implementation of AI in healthcare. This work not only addresses the individual stakeholder but also considers the broader societal and organizational factors to ensure implementation is timely, relevant, and useful to the populations to which it is intended to serve.
■590 ▼aSchool code: 0042.
■650 4▼aMedicine
■653 ▼aSystem dynamics
■653 ▼aTechnology Acceptance Model
■653 ▼aDynamic interactions
■690 ▼a0564
■690 ▼a0769
■690 ▼a0800
■71020▼aCase Western Reserve University▼bClinical Translational Science.
■7730 ▼tDissertations Abstracts International▼g86-12B.
■790 ▼a0042
■791 ▼aPh.D.
■792 ▼a2024
■793 ▼aEnglish
■85640▼uhttp://www.riss.kr/pdu/ddodLink.do?id=T17358637▼nKERIS▼z이 자료의 원문은 한국교육학술정보원에서 제공합니다.
