Geographic analysis for efficiency in healthcare subsidies

By |2022-03-18T05:32:24-08:00March 17th, 2022|Uncategorized|0 Comments

By  Florence Muriuki and Odette Melvin High prices of pharmaceutical commodities in low-to-middle-income countries (LMICs) is a great impediment to improved healthcare outcomes in these countries. In Kenya’s private sector, the patient prices for generic medicines range between 3 and 20 times the international reference prices. Patient prices for innovator brand medicines range between 1.8 to 140 times the international reference prices. These high prices of pharmaceutical commodities coupled with 75% of Kenyans paying out of pocket for healthcare, make access and affordability of essential quality medicines difficult. In other countries insurance would pay for the majority of costs. For example in the United States 84% of people have some form of healthcare insurance; and some African countries like Rwanda and Ghana have implemented national health insurance schemes achieving coverage of 91% and 74% respectively. Maisha Meds is working to improve accessibility and affordability of malaria and reproductive health commodities in the private sector by managing a digital platform that offers subsidized commodities at pharmacies and clinics distributed across Kenya and Uganda. Through our reimbursement program, Maisha Meds helps supply subsidised malaria and family planning (FP) products to healthcare facilities and tracks their dispensation to verified patients. In 2021, Maisha Meds supported tech for 875 facilities with 2.6 million patient encounters and directly paid for care on behalf of approximately 30,000 patients in 154 facilities across Kenya. In our endeavour to scale the reimbursement program cost effectively to reach more patients in low income areas, at Maisha Meds we’re working on a geospatial analysis project aimed at better targeting regions and individuals in need of the program. The targeting project consolidates data on disease burden, relative wealth and access to healthcare by region to create an index that optimally determines which regions to target and potentially what level of subsidies to provide in various regions.  The purpose of this is to make sure that we’re optimising funding to reach patients who most need the subsidies that our technology systems provide. Mapping malaria by sub-county In previous mapping of disease burden, counties (the highest administrative level in Kenya) were used to identify malaria and HIV endemic regions, which are mostly in the western and coastal parts of the country. The targeting project is taking this a step further by collating malaria parasite rate and mortality data at sub-county level from the Malaria Atlas Project and the District Health Information Software (DHIS2) malaria positivity rate at ward level (a small administrative level) to  localise targeting at a more granular level.  Data source: The Malaria Atlas Project https://malariaatlas.org/explorer/#/ The Maisha Meds Malaria reimbursement program currently focuses on the Malaria Endemic counties represented by dark red on the map on the left. As the program expands, more attention will be paid to the sub-counties in the same areas which have the highest malaria mortality rates and plasmodium falciparum parasite rate. Assessing need using micro-estimates of wealth Family planning commodities are often unequally distributed.  For example, use of modern family planning methods remains lower in [...]