No abstract

Objective: Millions of medical consultations are conducted each year in Burkina Faso using the Electronic Register of Consultations (REC). Based on the consultation data collected, we present a method to quantify the quality of individual and ensembles of consultations conducted by frontline healthcare workers (FHWs). Methods: We focus on anthropometric measurements and vital signs (age, weight, height, mid-upper arm circumference and temperature) of children aged between two months and five years old. We compare individual and ensemble of consultations to a multivariate probability distribution defined by an external population-specific, gold standard consultation dataset. By comparing the distributions of consultations to the reference probability distribution, we define a score to rate the quality of measurements and data entry of each FHW. Findings: The defined scores allow us to detect which measurements are most problematic. They also allow us to detect potential biases in the consultation and treatment of different patient groups. No systematic gender-bias was found among FHWs. Height measurements were the most challenging; consultations with the lowest scores were associated with underestimated heights in children. Among these consultations, height was found to be even more underestimated among boys than girls. Conclusion: Our findings enable us to support capacity building of frontline healthcare workers. The REC can be enriched with real-time specific alert on errors, individual FHW can be proposed targeted trainings, and dynamic dashboards can support district managers to navigate the entire population of FHWs and understand which problems should be prioritised.