Factors Affecting the Use of Electronic Logistics Management Information System (eLMIS) Data in Bottom-up Quantification of Health Commodities in Public Health Facilities in Coast Region, Tanzania: A mixed-methods study

Abstract Background: Effective supply chain management is an essential component of effective/affordable healthcare services. It ensures accurate quantification and availability of health commodities. Bottom-up quantification has proved the most effective in Tanzania, it relies mostly on electronic logistic management information system (eLMIS). This study aims to explore factors influencing the use of eLMIS data in bottom-up quantification of health commodities in Coast region, Tanzania. Methods: An explorative cross-sectional study design employing mixed-method approach (qualitative and quantitative for data collectiona and analysis) was conducted. We focused on healthcare workers whose role is to create health commodities report by eLMIS and finally aggregate in bottom-up quantification tools (N=30). Structured interviews and checklist were adopted for qualitative and quantitative data collection, respectively. Data analyses were achieved with help of NVivo 12 and SPSS version 23. Results: We found that lack of training to healthcare workers on bottom-up quantification was one of the key factors affecting them to use eLMIS data. Furthermore, insufficient infrastructure such as computers, poor ICT skills to using computers and eLMIS software, lack of regular supportive supervision on the use of eLMIS data, and inadequate fund and qualified staff emerged as other major factors that affect the use of eLMIS data in bottom-up quantification of health commodities in public health facilities. Training was shown to be a significant source of knowledge to improve eLMIS system use, and to enhance positive attitude toward the use of eLMIS data (p=0.003). Conclusion: In summary, the factors unveiled in the present study may affect forecasting which relies on data that comes from eLMIS which tracks the demand for use of commodities over time. This is of particular concern for consistent availability and affordability of health commodities in public health facilities, as inaccurate forecasting may lead to inaccurate quantification of the commodities.