4.7 Review

An integrative review on the acceptance of artificial intelligence among healthcare professionals in hospitals

Related references

Note: Only part of the references are listed.
Article Information Science & Library Science

Acceptance of clinical decision support systems in Saudi healthcare organisations

Soliman Aljarboa et al.

Summary: This study examines the factors influencing the acceptance of CDSS by physicians in Saudi Arabia. The findings suggest that all factors of UTAUT and TTF, except for social influence, influence the acceptance of CDSS by GPs. In-depth interviews also revealed additional factors such as accessibility, patient satisfaction, informativeness, connectedness, communication and shared knowledge, privacy and security, and perceived risk.

INFORMATION DEVELOPMENT (2023)

Article Health Care Sciences & Services

Clinicians' Perceptions of an Artificial Intelligence-Based Blood Utilization Calculator: Qualitative Exploratory Study

Avishek Choudhury et al.

Summary: This study explores how clinicians perceive an AI-based decision support system and identifies workload and usability, as well as clinical decision-making, as factors hindering its use. The findings emphasize that effective integration of AI-based decision support systems requires multidisciplinary engagement and user training, in addition to analytical efficacy.

JMIR HUMAN FACTORS (2022)

Article Education, Scientific Disciplines

Needs, Challenges, and Applications of Artificial Intelligence in Medical Education Curriculum

Joel Grunhut et al.

Summary: Artificial intelligence is set to play an important role in healthcare, but current medical education is not adequately preparing physicians to incorporate AI into their practice. Medical schools should include AI in their curriculum and emphasize ethical considerations.

JMIR MEDICAL EDUCATION (2022)

Article Health Care Sciences & Services

Barriers to and Facilitators for Acceptance of Comprehensive Clinical Decision Support System-Driven Care Maps for Patients With Thoracic Trauma: Interview Study Among Health Care Providers and Nurses

Emma K. Jones et al.

Summary: This study aims to understand the factors influencing the design and use of comprehensive clinical decision support (CDS) care maps and to identify themes associated with end-user acceptance of a thoracic trauma CDS care map. Through interviews and analysis, eight dominant themes were identified, including alert fatigue, automation, redundancy, minimalistic design, evidence-based, prevent errors, comprehensive care, and malleability. The findings of this study can guide user-centered design and improve adoption.

JMIR HUMAN FACTORS (2022)

Article Health Care Sciences & Services

Attitudes of medical workers in China toward artificial intelligence in ophthalmology: a comparative survey

Bo Zheng et al.

Summary: The survey showed that medical workers have a higher level of understanding of AI in ophthalmology compared to other professional technicians, highlighting the need to promote ophthalmic AI education among the latter group. Most respondents lacked experience in ophthalmic AI but generally exhibited a high acceptance level towards AI in ophthalmology, indicating a necessity to enhance research on medical ethics issues.

BMC HEALTH SERVICES RESEARCH (2021)

Article Computer Science, Information Systems

Medical practitioner's adoption of intelligent clinical diagnostic decision support systems: A mixed-methods study

Ashish Viswanath Prakash et al.

Summary: This study utilizes a mixed methods approach to develop and test a model based on the Unified Theory of Acceptance and Use of Technology, status quo bias, and technology trust. The findings suggest that performance expectancy, effort expectancy, social influence, initial trust, and resistance to change can predict intention to use, while inertia, perceived threat, and risks determine resistance to change. Recommendations for alleviating resistance and improving adoption are proposed.

INFORMATION & MANAGEMENT (2021)

Article Health Care Sciences & Services

Radiation Oncologists' Perceptions of Adopting an Artificial Intelligence-Assisted Contouring Technology: Model Development and Questionnaire Study

Huiwen Zhai et al.

Summary: The study found that Chinese radiation oncologists had a high overall acceptance of AI-assisted technology for contouring, with low technology resistance and no relation to behavioral intention. Not all factors in the Venkatesh UTAUT model applied to AI technology adoption among physicians in a Chinese context.

JOURNAL OF MEDICAL INTERNET RESEARCH (2021)

Article Health Care Sciences & Services

Adoption of Machine Learning Systems for Medical Diagnostics in Clinics: Qualitative Interview Study

Luisa Pumplun et al.

Summary: This study explores the factors influencing the adoption process of ML systems for medical diagnostics in clinics through qualitative interviews with medical experts. It provides a holistic ML adoption framework for clinics and an applicable maturity model to assess the current state in the adoption process of ML systems.

JOURNAL OF MEDICAL INTERNET RESEARCH (2021)

Article Health Care Sciences & Services

Technology Acceptance of a Machine Learning Algorithm Predicting Delirium in a Clinical Setting: a Mixed-Methods Study

Stefanie Jauk et al.

Summary: This study evaluated the user acceptance of a machine learning-based application supporting delirium management in hospitals. Results showed that healthcare professionals found the application useful, easy to understand, and appreciated the additional information provided. However, actual system use was still low during the pilot study.

JOURNAL OF MEDICAL SYSTEMS (2021)

Article Clinical Neurology

Attitudes of the Surgical Team Toward Artificial Intelligence in Neurosurgery: International 2-Stage Cross-Sectional Survey

Hugo Layard Horsfall et al.

Summary: The majority of surgeons and the wider surgical team agree and are comfortable with the application of AI in neurosurgery, particularly in areas such as imaging interpretation, operative planning, and coordination of the surgical team.

WORLD NEUROSURGERY (2021)

Review Medicine, Research & Experimental

Opportunities and challenges of artificial intelligence in the medical field: current application, emerging problems, and problem-solving strategies

Lushun Jiang et al.

Summary: Recent advancements in artificial intelligence have shown success in clinical tasks, but issues such as standardized processes and ethical supervision hinder large-scale application in real practice. To ensure the safety and orderly development of AI in the medical industry, establishing a process framework is crucial.

JOURNAL OF INTERNATIONAL MEDICAL RESEARCH (2021)

Article Radiology, Nuclear Medicine & Medical Imaging

Implementation of artificial intelligence (AI) applications in radiology: hindering and facilitating factors

Lea Strohm et al.

EUROPEAN RADIOLOGY (2020)

Article Health Care Sciences & Services

Health Care Employees' Perceptions of the Use of Artificial Intelligence Applications: Survey Study

Rana Abdullah et al.

JOURNAL OF MEDICAL INTERNET RESEARCH (2020)

Article Health Care Sciences & Services

Improvements in Patient Monitoring in the Intensive Care Unit: Survey Study

Akira-Sebastian Poncette et al.

JOURNAL OF MEDICAL INTERNET RESEARCH (2020)

Article Health Care Sciences & Services

Integrating a Machine Learning System Into Clinical Workflows: Qualitative Study

Sahil Sandhu et al.

JOURNAL OF MEDICAL INTERNET RESEARCH (2020)

Article Psychology, Multidisciplinary

Trust Toward Robots and Artificial Intelligence: An Experimental Approach to Human-Technology Interactions Online

Atte Oksanen et al.

FRONTIERS IN PSYCHOLOGY (2020)

Article Operations Research & Management Science

Transparency and trust in artificial intelligence systems

Philipp Schmidt et al.

JOURNAL OF DECISION SYSTEMS (2020)

Article Health Care Sciences & Services

Utilization of an Electronic Triage System by Emergency Department Nurses

Arwa Alumran et al.

JOURNAL OF MULTIDISCIPLINARY HEALTHCARE (2020)

Article Medical Informatics

Diffusing an Innovation: Clinician Perceptions of Continuous Predictive Analytics Monitoring in Intensive Care

Rebecca R. Kitzmiller et al.

APPLIED CLINICAL INFORMATICS (2019)

Article Nursing

Nurses' Views on the Potential Use of Robots in the Pediatric Unit

Hwey-Fang Liang et al.

JOURNAL OF PEDIATRIC NURSING-NURSING CARE OF CHILDREN & FAMILIES (2019)

Article Radiology, Nuclear Medicine & Medical Imaging

Impact of the rise of artificial intelligence in radiology: What do radiologists think?

Q. Waymel et al.

DIAGNOSTIC AND INTERVENTIONAL IMAGING (2019)

Article Computer Science, Artificial Intelligence

A hybrid machine learning approach to cerebral stroke prediction based on imbalanced medical dataset

Tianyu Liu et al.

ARTIFICIAL INTELLIGENCE IN MEDICINE (2019)

Article Health Care Sciences & Services

Physician Confidence in Artificial Intelligence: An Online Mobile Survey

Songhee Oh et al.

JOURNAL OF MEDICAL INTERNET RESEARCH (2019)

Review Health Care Sciences & Services

Artificial intelligence, bias and clinical safety

Robert Challen et al.

BMJ QUALITY & SAFETY (2019)

Article Health Care Sciences & Services

Physician perspectives on integration of artificial intelligence into diagnostic pathology

Shihab Sarwar et al.

NPJ DIGITAL MEDICINE (2019)

Article Radiology, Nuclear Medicine & Medical Imaging

Artificial intelligence and deep learning - Radiology's next frontier?

Ray Cody Mayo et al.

CLINICAL IMAGING (2018)

Article Oncology

A Clinical Decision Support System to Assist Pediatric Oncofertility: A Short Report

Meredith Hand et al.

JOURNAL OF ADOLESCENT AND YOUNG ADULT ONCOLOGY (2018)

Editorial Material Education, Scientific Disciplines

Medical Education Must Move From the Information Age to the Age of Artificial Intelligence

Steven A. Wartman et al.

ACADEMIC MEDICINE (2018)

Article Health Care Sciences & Services

Machine learning and medical education

Vijaya B. Kolachalama et al.

NPJ DIGITAL MEDICINE (2018)

Review Engineering, Manufacturing

Perspectives on the Impact of Machine Learning, Deep Learning, and Artificial Intelligence on Materials, Processes, and Structures Engineering

Dennis M. Dimiduk et al.

INTEGRATING MATERIALS AND MANUFACTURING INNOVATION (2018)

Article Rehabilitation

A multi-perspective evaluation of a service robot for seniors: the voice of different stakeholders

Sandra Bedaf et al.

DISABILITY AND REHABILITATION-ASSISTIVE TECHNOLOGY (2018)

Article Health Care Sciences & Services

Acceptance of clinical decision support surveillance technology in the clinical pharmacy

Dan English et al.

INFORMATICS FOR HEALTH & SOCIAL CARE (2017)

Article Radiology, Nuclear Medicine & Medical Imaging

Artificial Intelligence: Threat or Boon to Radiologists?

Michael Recht et al.

JOURNAL OF THE AMERICAN COLLEGE OF RADIOLOGY (2017)

Article Multidisciplinary Sciences

Can machine-learning improve cardiovascular risk prediction using routine clinical data?

Stephen F. Weng et al.

PLOS ONE (2017)

Article Health Care Sciences & Services

Telemedicine in diabetes foot care delivery: health care professionals' experience

Beate-Christin Hope Kolltveit et al.

BMC HEALTH SERVICES RESEARCH (2016)

Review Medicine, General & Internal

Rayyan-a web and mobile app for systematic reviews

Mourad Ouzzani et al.

SYSTEMATIC REVIEWS (2016)

Article Urology & Nephrology

Provider acceptance of an automated electronic alert for acute kidney injury

Janice Oh et al.

CLINICAL KIDNEY JOURNAL (2016)

Article Surgery

Acceptability of the decision support for safer surgery tool

Wynne E. Norton et al.

AMERICAN JOURNAL OF SURGERY (2015)

Article Medical Informatics

Implementation of multiple-domain covering computerized decision support systems in primary care: a focus group study on perceived barriers

Marjolein Lugtenberg et al.

BMC MEDICAL INFORMATICS AND DECISION MAKING (2015)

Article Computer Science, Interdisciplinary Applications

Nurses' Clinical Decision Making on Adopting a Wound Clinical Decision Support System

Peck Chui Betty Khong et al.

CIN-COMPUTERS INFORMATICS NURSING (2015)

Review Anesthesiology

Alarm fatigue: impacts on patient safety

Keith J. Ruskin et al.

CURRENT OPINION IN ANESTHESIOLOGY (2015)

Article Computer Science, Information Systems

Adoption of clinical decision support systems in a developing country: Antecedents and outcomes of physician's threat to perceived professional autonomy

Pouyan Esmaeilzadeh et al.

INTERNATIONAL JOURNAL OF MEDICAL INFORMATICS (2015)

Review Behavioral Sciences

Trust in Automation: Integrating Empirical Evidence on Factors That Influence Trust

Kevin Anthony Hoff et al.

HUMAN FACTORS (2015)

Article Medical Informatics

Factors of accepting pain management decision support systems by nurse anesthetists

Ju-Ling Hsiao et al.

BMC MEDICAL INFORMATICS AND DECISION MAKING (2013)

Article Health Care Sciences & Services

Barriers to Telemedicine: Survey of Current Users in Acute Care Units

Herbert J. Rogove et al.

TELEMEDICINE AND E-HEALTH (2012)

Article Computer Science, Information Systems

Practitioners' views on computerized drug-drug interaction alerts in the VA system

Yu Ko et al.

JOURNAL OF THE AMERICAN MEDICAL INFORMATICS ASSOCIATION (2007)

Review Nursing

The integrative review: updated methodology

R Whittemore et al.

JOURNAL OF ADVANCED NURSING (2005)

Article Computer Science, Information Systems

User acceptance of information technology: Toward a unified view

V Venkatesh et al.

MIS QUARTERLY (2003)