Clinical acceptance of a digital health clinical decision support algorithm for children in Tanzania and Rwanda: A mixed-method and before-after analysis from the DYNAMIC study

Background: Digital clinical decision support algorithms (CDSAs) can improve healthcare provider adherence to guidelines by streamlining clinical assessments and suggesting appropriate diagnoses and treatments. However, low uptake, acceptance, and adherence to CDSAs hinder their potential for improving quality of care. We conducted a mixed-methods study to evaluate healthcare provider acceptance of proposed diagnoses by ePOCT+, a digital CDSA used in Tanzania and Rwanda for the management of sick children age 1 day to 14 years in primary care health facilities, complemented by 13 semi-structured interviews with healthcare providers. A before–after analysis assessed changes in diagnosis acceptance following adaptations informed by the study findings. Results: Between December 2021 and October 2022, 27,593 new consultations using ePOCT + were completed at 36 Tanzanian and Rwandan health facilities. In Tanzania, 94.1% of diagnoses for children aged 2 months to 14 years of age were accepted, compared to 67.2% in Rwanda. In the ePOCT + algorithms for children < 2 months old, 61.5% of diagnoses were accepted in Tanzania, and 45.3% in Rwanda. Qualitative interviews revealed three major reasons for rejecting proposed diagnoses: 1) mismatch between clinical judgment and the proposed diagnosis based on clinical and anthropometric data (e.g. malnutrition diagnoses), 2) misunderstanding of diagnosis terms, criteria, or management recommendations, and 3) hesitancy to refer patients to the hospital (i.e., severe diagnoses). The algorithms were adapted based on these findings and expert input. A before–after analysis showed improved acceptance for some diagnoses following adaptations. Conclusions: Allowing healthcare providers to accept or reject diagnoses proposed by digital CDSAs, combined with qualitative feedback to explore reasons for rejection, provides useful insights into the acceptance of clinical content and should be considered by other CDSAs to inform approaches to address and improve acceptability. Differences in acceptance of diagnoses between Tanzania and Rwanda underscore contextual differences related to clinician autonomy, training, implementation, and acceptability. These findings can inform refinements and corrections to clinical algorithms, and help tailor strategies, such as targeted training, to enhance CDSA adoption.