Exploring healthcare professionals’ understanding and experiences of artificial intelligence technology use in the delivery of healthcare: An integrative review
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Background: The integration of artificial intelligence (AI) into our digital healthcare system is seen as a significant strategy to contain Australia’s rising healthcare costs, support clinical decision making, manage chronic disease burden and support our ageing population. With the increasing roll-out of ‘digital hospitals’, electronic medical records, new data capture and analysis technologies, as well as a digitally enabled health consumer, the Australian healthcare workforce is required to become digitally literate to manage the significant changes in the healthcare landscape. To ensure that new innovations such as AI are inclusive of clinicians, an understanding of how the technology will impact the healthcare professions is imperative. Method: In order to explore the complex phenomenon of healthcare professionals’ understanding and experiences of AI use in the delivery of healthcare, an integrative review inclusive of quantitative and qualitative studies was undertaken in June 2018. Results: One study met all inclusion criteria. This study was an observational study which used a questionnaire to measure healthcare professional’s intrinsic motivation in adoption behaviour when using an artificially intelligent medical diagnosis support system (AIMDSS). Discussion: The study found that healthcare professionals were less likely to use AI in the delivery of healthcare if they did not trust the technology or understand how it was used to improve patient outcomes or the delivery of care which is specific to the healthcare setting. The perception that AI would replace them in the healthcare setting was not evident. This may be due to the fact that AI is not yet at the forefront of technology use in healthcare setting. More research is needed to examine the experiences and perceptions of healthcare professionals using AI in the delivery of healthcare.
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The adoption of AI in nursing raises critical ethical, social, and educational concerns.
“Despite these promising developments, the adoption of AI in nursing raises critical ethical, social, and educational concerns.”
From The Role of AI in Nursing Education and Practice: Umbrella Review (2025) · cites this paper as [9]
Social barriers including resistance to change among health care professionals and unequal access to AI technologies risk widening existing gaps in health care delivery and outcomes.
“Social barriers, including resistance to change among health care professionals and unequal access to AI technologies, risk widening existing gaps in health care delivery and outcomes [9,10].”
From The Role of AI in Nursing Education and Practice: Umbrella Review (2025) · cites this paper as [9]
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- Authors
- Shinners, L., Aggar, C., Grace, S., & Smith, S.
- Affiliations
- Southern Cross University (AU)
- Corresponding author
- Shinners, Lucy
- Venue
- Health Informatics Journal
- Publisher
- SAGE Publications
- Published
- 2019-09-30
- Volume
- 26
- Issue
- 2
- Pages
- 1225-1236
- ISSN
- 1355-4743 (ISSN-L)
- 1460-4582
- 1741-2811
- OpenAlex
- W2979226802
- Cited by
- 148
- References
- 48
- Citations by year
- 2026: 21 · 2025: 47 · 2024: 26 · 2023: 25 · 2022: 14 · 2021: 12 · 2020: 3
- FWCI
- 0.36
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- Locations
- Health Informatics Journal (publishedVersion, cc-by-nc)
- PubMed (publishedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Topics
- Health Sciences › Medicine › Health Informatics › Artificial Intelligence in Healthcare and Education
- Health Sciences › Health Professions › Health Information Management › Electronic Health Records Systems
- Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Technology and Human Factors in Education and Health
- Keywords
- artificial intelligence in healthcare, healthcare professionals' perceptions, technology adoption, trust in AI, digital literacy, clinical decision support, intrinsic motivation
- MeSH terms
- Artificial Intelligence, Australia, Delivery of Health Care, Health Personnel, Humans, Technology, Observational Studies as Topic
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