These are our stories—stories about how Data.FI and its partners are having an impact in the world in responding to the HIV and emerging epidemics, and supporting improve client care through integrated primary health care information systems. Told through the voices of our teams on the front line, these stories illustrate how Data.FI is working to innovate and implement solutions to address important health needs in their countries.
How an Information System Can Fight HIV and Improve Patient Care in Nigeria
In 2019, when we began implementing the Data.FI project in Nigeria, each USAID- and PEPFAR-supported implementing partner maintained its own system for collecting and analyzing HIV data, but few of these systems were sharing data. Moreover, the country’s HIV information systems lacked a solid architecture for housing and using the data, which made it difficult for the government, funding agencies, and other stakeholders to have an accurate picture of the HIV epidemic.
In Nigeria, a systematic and collaborative community of practice approach involving informatics staff from seven USAID-funded partner organizations is creating an enhanced system that will capture comprehensive client records for HIV services at the facility level. An informatics bootcamp, hackathons, and openly shared programming code were tools for this collaboration. Read more in a blog by Dauda Sulaiman Dauda, country director, Data.FI/Nigeria.
Deduplication to consolidate a patient’s history
Digital health records are an essential tool for managing client care and monitoring the HIV pandemic, but duplicate records provide healthcare workers and decision makers with fragmented information. Duplicate client entries mask the true values of indicators across the clinical cascade, disable efforts to track clients through differentiated care models, and reduce data use among decision makers due to concerns about the accuracy of the data. Learn about removing duplicate records using a process that does NOT require a universal, unique ID for HIV clients, i.e., deduplication, in a blog published by Science Speaks.
Risk mapping to improve targeting
Reaching HIV epidemic control requires protecting the most at-risk adolescent girls and young women and other populations mostly likely to acquire HIV before they are infected. Using all the tools we have available, including artificial intelligence, allows us to better locate the most vulnerable and more equitably inform prevention services. How we do this? Read about an innovate approach employed by Data.FI and published by Science Speaks.
A Walk in My Shoes
Data.FI’s senior technical advisor in Malawi uses “shoe-leather data inquiry” to find out what is going on behind the numbers in the electronic medical record (EMR) system. His approach builds trust in electronic data collection systems, which leads to better use, and ultimately, better data for decision making.
Résoudre les problèmes de qualité des données pour améliorer leur utilisation au Burundi
Au Burundi, Data.FI aide le personnel du gouvernement impliqué dans la gestion des données à identifier les problèmes de qualité des données et à y remédier, et soutient les responsables et superviseurs sanitaires chargés de gérer et de coordonner les activités programmatiques en matière de lutte contre le VIH.