Abstract
Background: Artificial Intelligence–driven Clinical Decision Support Systems (AI-CDSS) offer transformative potential in healthcare by enhancing diagnostic accuracy and efficiency. In Iran, the lack of a nationwide electronic health record (EHR) system, combined with international sanctions limiting IT infrastructure development and cultural factors affecting technology trust, creates unique barriers to AI-CDSS adoption. This study aimed to explore factors influencing the adoption and implementation of AI-CDSS in Iranian hospitals.
Methods: This cross-sectional descriptive study was conducted between March and June 2025 across five tertiary care hospitals affiliated with Tabriz University of Medical Sciences, Iran. Using stratified random sampling, 442 healthcare professionals (physicians, nurses, and health IT staff) were targeted, yielding 376 valid responses (response rate: 85.1%). Data were collected using a validated 38-item questionnaire (Cronbach’s alpha=0.89), assessing demographics, digital literacy, AI knowledge, perceptions, and barriers. Data were analyzed using SPSS version 29, employing descriptive and inferential statistics, including regression analysis with Unified Theory of Acceptance and Use of Technology (UTAUT) moderators (age, gender, experience).
Results: Respondents included physicians (41.8%), nurses (38.6%), and health IT staff (19.7%). Levels of digital literacy were high (47.6%), moderate (38.3%), or low (14.1%). Only 28.8% had prior experience with AI-CDSS. Reported benefits included improved diagnostic accuracy (72.1%), faster decision-making (65.7%), and reduced medical errors (54.3%). Major barriers were a lack of integrated EHR systems (86.9%), insufficient training (74.0%), and limited organizational support (62.1%), compounded by sanctions affecting access to hardware and software. Regression analysis, incorporating moderators, showed that performance expectancy was the strongest predictor of adoption (β=0.45, P<0.001), with age significantly moderating effort expectancy (β=-0.12, P=0.02).
Conclusion: Despite positive attitudes toward AI-CDSS, their adoption in Iran is hindered by infrastructural limitations, international sanctions, and cultural trust barriers. National policies must prioritize sanctions’ impact, targeted training (e.g., hands-on workshops), and phased implementation are essential for achieving successful implementation in resource-constrained settings such as low- and middle-income countries (LMICs).