Pre-Interventional Electrocardiography Identification of First, Second, and Third-Degree Heart Block in Level IV & V Hospitals in Kakamega County

Introduction. Cardiac conduction disorders, particularly heart blocks, are frequently underdiagnosed in many resource-limited health systems despite being significant contributors to morbidity and mortality. Accurate interpretation of electrocardiograms (ECGs) is central to early detection, yet many frontline healthcare providers continue to experience challenges in identifying and classifying heart block patterns.
Materials and Methods. The study adopted a mixed-methods quasi-experimental research design. It combined a cross-sectional baseline assessment with a pre-test intervention approach to evaluate changes in healthcare providers’ competence in ECG-based heart block risk prediction.
Results. The analysis was conducted to determine whether differences in pre-intervention competence were associated with respondents’ professional category and years of experience. The overall fit is indicated by the results of corrected model which was statistically significant (F (13;114) = 8.975, p<0.001), indicating that the independent variables included in the model significantly explained variation in respondents’ baseline competence scores.
Conclusions. There were significant differences in baseline competence among respondents based on their professional category and years of experience, suggesting that both factors play an important role in shaping initial competence levels prior to the intervention.

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