DOI: 10.11648/j.ajhr.20261405.11 ISSN: 2330-8796

Evaluating the Readiness of Health Information Management Professionals for AI Integration in Healthcare Systems in Bayelsa State, Nigeria

Kurokeyi Teddy, Victor Ayebanengimote
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Artificial intelligence (AI) is revolutionizing healthcare delivery globally. But existing literature on the extent of AI computer literacy among respectively physicians in Nigeria as an evidence of its level of integration into healthcare is insufficient. This study was designed to evaluate the level of AI awareness and knowledge, digital competence, organizational readiness, professional development, and AI preparedness of healthcare provider (HIM professionals’) towards healthcare integration in Bayelsa State. The study adopted a descriptive cross-sectional survey design. The study population comprised 332 members of AHRIMPN Bayelsa chapter WhattsApp platform. From which 205 turned out to be the respondents and were analyzed with the use of structured 36-item self-administered questionnaire. Data were analyzed by descriptive statistics, Cronbach‘s alpha reliability analysis, Spearman‘s rank correlation, Mann Whitney U test, exploratory factor analysis, relative importance analysis, and multivariable regression at 5% significance level. The results showed moderate AI knowledge and awareness (3.052±0.116), digital competence (2.923±0.100), organizational readiness (3.141±0.124), professional development (3.143± 0.158) and AI readiness for healthcare integration (3.115±0.101). The instrument possessed Cronbach‘s α of 0.760 0.887 while Kaiser–Meyer–Olkin of 0.820 and significant Bartlett‘s Test of 19.155, P value = 0.000 validated the data for factor analysis. There were strong positive relationships between AI knowledge, digital competence and organizational readiness. But multivariable regression analysis revealed none of the observed four explanatory variables individually and significantly predicted AI readiness (p > 0.05). Respondents who had previous AI/digital health training had significantly better reported knowledge, digital competence, organizational readiness and professional development than those who did not have such training. The study revealed moderate AI readiness among healthcare professionals into AI-enabled health systems, though lack of the requisite AI skills and lack of standardized, continuous and obligatory AI capacity building interventions as well as poor investment in digital technology, robustness of organization, and health institution-related variations in knowledge, digital competence, organizational readiness and professional development are impeding AI integration into healthcare. The study concludes that continuous AI capacity development programmes, digital infrastructure investment, organizational autonomy and investment, and well-articulated AI curriculum into practitioner education, healthcare professional professional development programmes and organization-related accreditation are indispensable to successful, affordable and sustainable AI-enabled health systems.

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