Digital Clinical Decision Support Algorithms Enhance Quality of Care in Rwandan Primary Health Centers

Strategic Insights -

A study published in PLOS One has found that digital clinical decision support algorithms (CDSAs) can improve the quality of care in primary health centers in Rwanda, but only if the accuracy of inputs into the digital tool is ensured. Researchers from the Swiss Tropical and Public Health Institute analyzed data from 20,085 pediatric consultations and identified clinical skill gaps among healthcare workers, particularly in the assessment of basic measurements such as weight, mid-upper arm circumference, and temperature.

Key Takeaways:

  • The study found that digital CDSAs can enhance adherence to guidelines and improve the quality of care, but this improvement depends on the accuracy of inputs entered by healthcare workers.
  • Healthcare workers in primary care settings in Rwanda often lack the necessary clinical skills to accurately assess patients, with 70% of weight measurements, 69% of mid-upper arm circumference measurements, and 67% of temperature measurements being conducted incorrectly.
  • The study identified 10 health centers with irregular data patterns signaling potential clinical skill gaps, which were later found to be caused by basic measurements not being assessed correctly in most children.
  • In-person training, eLearning, and regular personalized mentoring tailored to specific health center needs are necessary to improve the quality of care and enhance the benefits of CDSAs.

Statistics:

  • 20,085 pediatric consultations were analyzed in the study.
  • 10 health centers were identified with irregular data patterns, signaling potential clinical skill gaps.
  • 70% of weight measurements, 69% of mid-upper arm circumference measurements, and 67% of temperature measurements were conducted incorrectly.
  • 43% of respiratory rate measurements, 37% of heart rate measurements, and 33% of blood oxygen saturation measurements were skipped.
  • 188 consultations were observed in the identified health centers to understand potential error causes.

Sources:

  • Rwandarwacu, V.P., Karoui, H., Niyonzima, J., Makuza, A., Nkuranga, J.B., D'Acremont, V., & Kulinkina, A.V. (2025). Identifying clinical skill gaps of healthcare workers using a digital clinical decision support algorithm during outpatient pediatric consultations in primary health centers in Rwanda. PLOS One, 20(6).