Healthcare professionals' and students' perspectives on artificial intelligence in clinical documentation in eastern Saudi Arabia: Factors influencing adoption and utilization
The increasing universal acceptance of artificial intelligence (AI) in healthcare systems is driving advancements, with clinical documentation at the forefront. This research aimed to gain insight into the views, perspectives, and influencing factors on AI implementation in clinical documentation among healthcare professionals [HCPs] and students, with special consideration for the obstacles and driving factors that influence the adoption of AI. A cross-sectional survey design was employed, involving 437 participants, comprising HCPs (n = 173) and health science students (n = 264). Statistical analysis, including descriptive and inferential methods, was applied to interpret the gathered data. Most participants (68.3%) had previously learned about AI for application in clinical documentation, but fewer (41.2%) were actively using it. HCPs, as well as students, demonstrated a positive perception of AI performance (76.5%), but expressed concerns about accuracy (53.8%) and the need for data privacy (61.4%). Reliability and accuracy (92.7%) emerged as key factors, followed by efficiency (87.3%), maintaining data privacy (84.9%), and peer adoption (72.1%), which influenced adoption. AI benefits were viewed differently by HCPs and students, with the students being more optimistic (p < 0.05). The successful implementation of AI in clinical documentation was considered to rely on training requirements (89.6%), the presence of technical support (76.2%), and the development of guidelines (81.5%). Although there is widespread acceptance of AI for clinical documentation among the participants, the success of implementation can only be realized by addressing areas such as accuracy, data privacy concerns, and providing adequate training and support to relevant stakeholders involved.
Authors
- Nouf Al-Kahtani (ORCID: https://orcid.org/0000-0003-0211-5461)
- Naof Al-Ansary (ORCID: https://orcid.org/0000-0003-1289-6329)
- Zahraa Alakrawi (ORCID: https://orcid.org/0000-0002-2890-8833)
- Mona Jamjoom (ORCID: https://orcid.org/0000-0001-9149-2810)
- Arun Vijay Subbarayalu (ORCID: https://orcid.org/0000-0002-5758-118X)
- Vinoth Raman
- Rawan Jawad AL-Ibrahim
- Walla Abdulhamid Al-Zaki
Institutions
- Princess Nourah bint Abdulrahman University (SA)
- Arabian Gulf University (BH)
- Imam Abdulrahman Bin Faisal University (SA)
Publication Details
- Journal
- Informatics in Medicine Unlocked
- Published
- 2025-01-01
- DOI
- https://doi.org/10.1016/j.imu.2025.101710
- Citations
- 1
- Primary Topic
- Artificial Intelligence in Healthcare and Education
- Type
- article
- Field-Weighted Citation Impact
- 0.65