Demand Sensing and Digital Tracking for MCH in Uganda
Purdue Collaborator: Regenstrief Center for Healthcare Engineering, School of Industrial Engineering
Many healthcare systems, such as in Uganda, implementing standardized data capture registers, lack responsiveness due to paper-based reporting and requisition systems, which impede access to data for timely decision-making. At the district level, a lack of such data results in pharmaceutical supply stock-outs and expired medications and negatively impacts system responsiveness to the needs of lower-level health facilities. In this scenario, one of the key vulnerable populations is pregnant women. The United Nations has identified 9 commodities that could potentially save 6 million lives though timely availability and use across the MCH ‘continuum of care’. Our project is targeting this area
The Purdue Innovation:
Purdue University’s Diagnosis-Based Demand Sensing and Digital Tracking (DBDD) in Uganda will match demand with supply by applying systems engineering principles and cloud-based smart sync technology to sense future demand by triangulating patient data in registers, diagnostic data in laboratories and consumption data in inventory tracking for improved Maternal and Child Health (MCH) care in Uganda. Our theory of change for this project is based on the following hypotheses: Hypothesis 1: The DBDD approach will reduce the time needed to prepare orders; Hypothesis 2: The DBDD approach will reduce the cases of stock-out and overstock of targeted medical supplies; and Hypothesis 3: The DBDD approach will result in improved patient outcomes (e.g. reduction in maternal mortality rate, infant mortality and under-5 mortality rates).
DBDD will be implemented by an interdisciplinary team (experts in public health, system engineering, optimization, manufacturing operations, mHealth, software engineering, health supply chains) from Purdue University’s School of Industrial Engineering, the Purdue Innovation for International Development Lab, and the Purdue Regenstrief Center in the United States, and Makerere University’s School of Public Health with the Resilient Africa Network (RAN) Lab in Uganda. At the core of our intervention is the improvement of health outcomes for pregnant women and neonates, through better management and use of data. Last mile data is currently captured in paper-based format, will be digitized in order to optimize demand forecasts and so to reduce stock-outs of essential maternal health supplies in primary care facilities. This project will triangulate three key data sets: (1) patient data captured in the key maternal/child health registers (antenatal care, delivery, and immunization), (2) consumption data captured in stock cards, and (3) laboratory data for maternal health conditions requiring laboratory-based diagnosis), together with the essential drugs and supplies for maternal and child care to optimize ordering practices in primary care facilities. The digitization of critical aspects of these data will greatly simplify their capture and management at primary care facility level and it can rapidly transform how health facilities use data to improve their operational efficiency, including how they prioritize the use of conditional PHC funds to stabilize errant supply from the national supply mechanism.
- The Bill and Melinda Gates Foundation (BMGF); Resilient Africa Network; Management Sciences for Health
- Dr. Yuehwern Yih, Purdue University. School of Industrial Engineering; Regenstrief Center for Healthcare Engineering Faculty Scholar; Director, Smart Systems and Operations Laboratory
- Dr. Md. Munirul Haque, Purdue University. Research Scientist, Regenstrief Center for Healthcare Engineering
- Dr. Seokcheon Lee, Purdue University. Associate Professor School of Industrial Engineering
- Dr. Roy William Mayega, Resilient Africa Network. Deputy Chief-of-Party; School of Public Health, Makerere University
- Andualem Oumer, Management Sciences for Health. Senior technical advisor, Systems for Improved Access to Pharmaceuticals and Service (SIAPS) project