Part of the DHIS2 as Data Warehouse - Country implementation stories DAC2021 Session: Wednesday 23nd June 15:00
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DHIS2 Implementation in Immunization Local Area Monitoring (PWS) System: A Pilot Project in Jakarta, Indonesia
High-quality data is among the backbone of public health. One of the main challenges in developing countries, including Indonesia, is unintegrated data, leading to time-consuming data analysis.
In the middle of 2019, the Jakarta Department of Health initiates the use of DHIS2 for immunization program to the Ministry of Health, Republic Indonesia, and both decide to start a Pilot Project for Child Immunization Data Integration using DHIS2 in Jakarta (Capital City of Indonesia). The aim is to trial this new system before being implemented in the national program.
Before DHIS2 utilization, the district-level immunization program coordinator manually entered data into Microsoft Excel and sent it to the Jakarta sub-department of health for recapitulation. From the perspective of digital-based health systems, the PWS system is somewhat outdated, and it has been in use since 2004 until now. Another weakness of this system is the time consumed for data cleaning due to technical obstacles, such as an error in the excel cell formula. It will have an impact on the results of the final recap and the officers have to re-check the accuracy of the calculation results for each cell, which results in the longer time it takes for reporting. The consequences are delayed data analysis and program evaluation. After implementing DHIS2 in the PWS system, immunization reports are directly entered by the district-level program coordinator into the system, thus bypassing reporting to the sub-department of health, prevent data duplication (due to data validation in the system), and reduce data mismatching reported between different programs. A significant advantage is direct data visualization in the immunization dashboard that accessible for all. This visualization let all related stakeholders keep on track on immunization trend, make simple and fast data analysis, and direct inspection for odd/ accidental data error (such as higher DPT-3 coverage compared to DPT-2 coverage, which logically impossible but had been happened before). This data also then connected to the vaccine logistic system to crosscheck the number of vaccine use and expired date reminders. This optimizes logistic budgeting, especially for financial audits.
Data integration using DHIS2 facilitates data integration for the immunization program in Jakarta. At the end of this pilot project in 2021, a comprehensive approach to immunization data management should be finalized and further able to be implemented for the national immunization program in 2022.