Assessment of Perception and Utilization of Artificial Intelligence Tools Among Health Information Management Practioners in Tertiary Hospitals in Bayelsa State

Artificial Intelligence (AI) is increasingly transforming healthcare through automated data processing, intelligent information management, predictive analytics and decision support. However, effective integration of AI into Health Information Management (HIM) depends largely on healthcare workers’ awareness, perceptions, competencies and actual utilization of AI tools. This study assessed the perception and utilization of AI tools among healthcare workers in tertiary hospitals in Bayelsa State, Nigeria. A descriptive cross-sectional research design was adopted. The study was conducted among 112 healthcare workers in selected tertiary hospitals in Bayelsa State. Data were collected using a structured self-administered questionnaire and analysed using the Statistical Package for the Social Sciences (SPSS) Version 27. Descriptive statistics comprising frequency, percentage, mean and standard deviation were used, while inferential statistics, including independent samples t-test and Pearson Product Moment Correlation, were employed at the 0.05 level of significance. The findings revealed a low level of awareness of AI tools among respondents, with a grand mean of 2.43. Perception of the usefulness of AI tools in HIM practices were also low (x̄ = 2.48), indicating limited confidence in their overall usefulness. However, the level of AI utilization was moderate (x̄ = 2.52), suggesting that AI tools were being used to some extent but had not been fully integrated into routine HIM practices. Significant differences were found between healthcare workers in Federal and State hospitals in terms of awareness, perception, utilization and challenges, with Federal healthcare workers generally reporting more favourable outcomes. Furthermore, a strong positive and statistically significant relationship was found between perception of AI tools and utilization (r = 0.62, p < 0.001), resulting in the rejection of the null hypothesis. The study concluded that AI adoption in HIM practices in tertiary hospitals in Bayelsa State remained suboptimal due to gaps in awareness, skills, training, institutional support and infrastructure. It recommended sustained AI training and capacity building, improved digital infrastructure, institutional support, clear governance frameworks and interventions aimed at improving healthcare workers’ confidence and positive perception of AI.