This abstract has been accepted at the 2024 DHIS2 Annual Conference
Data use in action: Balancing ordering of malaria commodities versus actual consumption using DHIS2 routine malaria treatment data
Public health facilities order ALu commodities using eLMIS bi monthly. There has been an uncontrolled pulling rate of commodities from these health facilities, resulting in overstocking, hence expiry and losses & unbalance of limited commodities resources between health facilities. A notable ratio of consumption data to service data is up to 3+. Controls were necessary to balance the ordered amount of ALu commodities and malaria treated clients. Missing service data to control ordered commodities is the primary reason for the significant difference; others are data quality, irrational use of medicines, and Possible pilferage/ unaccounted losses that can contribute to the difference. Due to the difference in the usage of ALu categories (ALu 1x4, 2x4, 3x4, and 4x4) in terms of age group and weights, a percentage composition to the total clients treated for malaria was established by NMCP. An MoH led task force for implementing control measures was formed to define an approach towards having adequate validation controls on eLMIS using HMIS DHIS2 service data; one was having defined percentage composition of ALu 1x6, ALu 2x6, ALu 3x6 and ALu 4x6 from a total number of malaria cases treated for malaria. Another one was Integration between DHIS2 and eLMIS via HIM. On this integration, eLMIS defined variables to capture service data from DHIS2 as per the percentages of ALu compositions, an endpoint was established on HIM to facilitate the flow of data from DHIS2 to eLMIS, and DHIS2 introduced a service script for extracting routine malaria treatment data, recalculating to different ALus as per established percentage compositions. On the 25th of each month, data for the last 2 months are sent to eLMIS on validation controls, and then eLMIS uses them to limit the amount of commodities an HF can order. Notifications by DHIS2 to the appropriate team were essential to ensure responsible people get information. The validation process has been active since January 2023, resulting in an improved ratio of ALu commodity consumption data to service data to around 1 from around 3 before validation controls. The process revealed missing HFs on eLMIS compared to HMIS DHIS2, triggering actions. HFs not reporting routine service data on HMIS DHIS2 cannot request commodities via eLMIS. Also, notification mechanisms through the DHIS2 feedback & message module ensured easy process management. Due to the positive results of the established ALu control measures, MoH has decided to add control measures for other commodities.
Primary Author: Josephat Mwakyusa
Keywords:
DHIS2-eLMIS Integration, eLMIS data validation, HMIS DHIS2 service data, Tanzania
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