YUEHWERN YIH, PHD
Professor of Industrial Engineering, Associate Director of Regenstrief Center for Healthcare Engineering, Purdue University
Health Supply Chain for improving Maternal and Child Health: A Case Study in Uganda
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 UN has identified 9 commodities that could potentially save 6 million lives though timely availability and use across the MCH ‘continuum of care’. This project is targeting this area.
We proposed a Diagnosis-Based Demand sensing and Digital tracking (DBDD) approach to use last mile data, which is currently captured in paper-based formats, to improve the availability and reduce stock-outs of essential maternal health supplies in primary care facilities. DBDD will triangulate patient data, consumption data and laboratory data to optimize ordering practices in primary care facilities. This includes the digitization of those data so as to greatly simplify its capture and management at primary care facility level. In this talk I will present our current work and the challenges and barriers we encounter so far.
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 UN has identified 9 commodities that could potentially save 6 million lives though timely availability and use across the MCH ‘continuum of care’. This project is targeting this area.
We proposed a Diagnosis-Based Demand sensing and Digital tracking (DBDD) approach to use last mile data, which is currently captured in paper-based formats, to improve the availability and reduce stock-outs of essential maternal health supplies in primary care facilities. DBDD will triangulate patient data, consumption data and laboratory data to optimize ordering practices in primary care facilities. This includes the digitization of those data so as to greatly simplify its capture and management at primary care facility level. In this talk I will present our current work and the challenges and barriers we encounter so far.