Every two minutes, a preventable death occurs during childbirth in Low-and-Middle-Income countries (LMICs). Complications from pregnancy and childbirth are the leading cause of death among girls aged from 15 to 19 [1, 2]. Inadequate inventory and supplies contribute significantly to preventable death in LMIC settings [1, 3,4,5]. UN Commission on Life-Saving Commodities for Women and Children identified and endorsed an initial list of 13 overlooked life-saving commodities that could save the lives of more than 6 million women and children, if more widely accessed and properly used . Bill and Melinda Gates Foundation targeted this area in the Round 19 Global Grand ChallengesFootnote 1 to ensure effective health supply chains in LMICs. This paper is based on the project selected to develop and pilot a digital solution (E+TRA Health) to strengthen the supply chains of medical commodities to support maternal child health (MCH) in Uganda.
Healthcare delivery systems
Information of Healthcare delivery is usually captured in two independent systems: health information system and healthcare supply chain management system. Health information system is typically known as the electronic medical record system (EMR), and collects health information about the patients, such as medical history. While, healthcare supply chain management system logs the dispensing of healthcare commodities, monitors inventory levels and restocks? replenishments. The following subsection presents the health information and health supply chain management systems in the context of the Ugandan health system.
Health information system in Uganda
Uganda health governance is divided into regions, districts, sub-districts, health facilities, and villages . Accordingly, the health services are structured into National Referral Hospitals (NRHs) and Regional Referral Hospitals (RRHs), General Hospitals, Health Center (HC) IVs, HC IIIs, HC IIs and Village Health Teams (HC Is). At the highest level, NRHs, RRHs, and General Hospitals provide specialist clinical and comprehensive services. At the secondary district level, HC IIIs offer basic preventive, promotive and curative care. HC IIs only provide outpatient care and community outreach services. At the lowest level, Village Health Teams (VHTs)/HC Is facilitate health promotion, service delivery, and community participation .
Uganda’s first Health Information System (HIS) was designed in 1985 to capture and analyze data on communicable and non-communicable diseases [8, 9]. A centralized health management information system (HMIS) was introduced in 1993 that focused on morbidity and mortality reporting, collecting data from health units to the districts and national levels [10, 11]. The HMIS was completely paper-based. Monthly reports were generated from VHTs at the lowest level and submitted to HCs. HCs aggregated and submitted reports to the District Health Office (DHO). DHOs compiled reports and submitted to the Ministry of Health (MoH). This cumbersome monthly reporting process that required health workers lots of time to tally by going through logs often results in inaccurate data . There are also other HIS tools, such as “mTrack”, a SMS-based HMIS tool designed to report on disease surveillance, “WinSenga”, a fetal heart rate monitor using smartphones (ibid), etc. Various HIS interventions emerged in Uganda but often ended in pilot phases due to lack of clear evaluation or limited skills, inadequate policy and low adoption by health workers .
Uganda’s health system recognizes the benefits of electronic medical record (EMR) systems [12,13,14,15], mobile health [16, 17], and risk surveillance systems [18, 19]. However, limited infrastructure and resources hinder the design and implementation of these systems. In addition, current EMR systems in Uganda scarcely address the needs of MCH or primary care, mostly focusing on specifically communicable diseases such as HIV, malaria, and tuberculosis. (i.e., Uamuzi Bora Kenya , PIH-EMR Peru , HIV-EMR Haiti , OpenMRS Uganda , Lilongwe EMR Malawi ).
A system to capture the consumption and needs of maternal child health (MCH) commodities at each health facility is needed to guarantee high levels of service and minimize stockouts . Many healthcare systems in Uganda implement standardized data registers to capture patient information and health product inventory status. However, in lower-level health facilities (e.g., Healthcare Center IV), limited computer resources prevent digitizing up-to-date recordkeeping . Consequently, there is no digital data management system to capture information about product consumption and inventory. Staff at these healthcare facilities manually collect information from multiple paper-based registers. The main challenge for these paper registries is that health workers do not have consistent standards in maintaining records which makes accurate data capture impossible and hard to support real time decisions [26, 27]. At the district level, lack of patient registers, stock cards, and lab results brings barriers for stakeholders to make evidence-based commodity orders. Long resupply intervals aggravate stockout and expired medication problems . Lack of coordination and human errors cause delays and waste resources, weakening responsiveness of the healthcare supply chain and putting patients at risk.
Healthcare supply management system
Although some EMR systems are increasingly amenable to monitor and integrate maternal and child health services in developing countries , few studies have addressed the application of EMR in inventory management [8, 29]. Tracking medicines, supplies and lab reagents in developing countries including Uganda is still paper-based stock books/stock cards/dispensing logs. This analog and manual tracking leads to difficulty in recording transactions in real time and requires tremendous effort and time to compile information. Duplications and errors of information make it difficult for store managers to prepare accurate consumption reports to generate right orders. Also, lack of coordination between MCH units and the main store causes difficulties in future demand/order forecasting [30, 31]. This results in stockout or overstock issues, which jeopardize the access to specific medical supplies, thus impacting survival and safety of pregnant women and their newborns. Therefore, there is a need for a digital healthcare supply management system that is tailored to meet MCH patient needs. Thus, in resource limited settings like Uganda, evidence based, coordinated, accurate stock management and quantification can prevent dangerous stockouts of health products. Also, precise ordering requires integration of quantification, EMR, dispensing and inventory control.
Several computerized systems need to be combined for a healthcare supply chain system EMR systems record patient history, medicine regimens and dosages. Dispensing systems record health products dispensed (i.e., mSupply, iDart, RxSolution, ADT). Inventory control systems track individual supplies by names, batch numbers, stock quantities and expiration dates (i.e., SIGMED, ORION, mSupply, HIV-EMR Pharmacy system, Navision, Syspro, ePICs). Quantification systems assist in calculating budget requirements and order quantities (i.e., FoCaMed, Quantimed, RxSolution, PIH-EMR, MSF ARV Drug Order Tool). However, EMR, Inventory control, and Dispensing systems manage patient data, inventory data and dispensing data separately. Moreover, all these tools have been mainly applied at the national and/or regional/state levels, not at the clinical level. Therefore, there is no all-in-one solution that has the capability to integrate all demand and supply data together to suggest a procurement plan at the clinical level.
Despite substantial needs, very few software applications are available in resource scarce environments. Current limitations include: (1) none of the existing systems combine the EMR, inventory control, dispensing and quantification systems. (2) Not all datasets are considered when preparing order quantities, which diminishes accuracy of order data due to the lack of data accessibility. (3) Most application designs are complex and geared toward national warehouses or retail pharmacies. (4) Most systems are proprietary, making customization and technical support difficult and costly. (5) Systems are designed under the assumption that high-bandwidth internet networks are available. (6) Supplies for test and laboratory regiments for preventive/diagnostic care are often not linked to the patient demands.
The focus of this study is to analyze information flow and design a health information technology solution to address gaps in the last mile supply chain associated with MCH in the Ugandan health system.