Healthcare Providers’ Perceptions and Multi-Level Determinants of Adoption of an AI-Powered Electrocardiography Interpretation Clinical Decision Support System in Ethiopia: A Formative Qualitative Study

Abstract

Cardiovascular diseases (CVDs) are a leading cause of morbidity and mortality globally, with low-resource settings, including Ethiopia facing challenges due to limited early diagnostic services. AI-powered electrocardiography (ECG) interpretation has the potential to improve diagnostic accuracy, decentralize care, and support timely clinical decisions, but evidence on healthcare providers' perspectives and adoption determinants is limited. This exploratory descriptive qualitative study employed 31 in-depth interviews with healthcare providers. Healthcare providers (cardiologists, internists, cardiac and critical care nurses, critical care specialists, and general practitioners) were purposively selected through maximum variation sampling from ten hospitals in four regions of Ethiopia. Data were transcribed verbatim, coded inductively, and analyzed thematically. The data analysis identified six themes: perceived benefit of AI-powered ECG interpretation CDSS, trust development, workflow integration, ethical concerns, functionality, and adoption determinants. Participants emphasized AI's potential to enhance accessibility, consistency, and diagnostic accuracy while reducing subjectivity and unnecessary referrals. Acceptance relied on high accuracy, reliable data, and rigorous validation, with the technology seen as supportive rather than replacing clinicians. Material resources, human resource readiness, and leadership engagement were key factors for adoption. Recommendations included phased implementation, continuous training, and model expansion to ensure sustainability and clinical utility. The AI-powered ECG interpretation CDSS was viewed as a valuable adjunct for strengthening cardiovascular care in Ethiopia, highlighting the need for context-sensitive strategies, ethical safeguards, and multi-level system readiness for successful adoption.

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