Reengineered DHIS 2 to Capture Maternal and Child Data at Point of Service for Prompt Intelligent Decision Making and Data Visualisation: A Case of Kiambu County - Waiganjo, Sarah; Muliaro, Joseph Wafula; Karanja, Simon (Indonesian Scientific Publication, 2025)
Reengineering of health information systems (HIS) involves restructuring system functionality to improve efficiency, usability, and reliability for rapid, evidence-based decision-making. This study presents a reengineered District Health Information Software 2 (DHIS2) prototype designed to capture maternal and child health (MCH) data at the point of service in Kiambu County, Kenya. By integrating key measures of data quality – namely completeness, timeliness, accuracy, and consistency – the prototype aligns with the four Vs of big data. A cross-sectional study involving 23 health facilities used questionnaires, interviews, and desk research to assess existing data management processes. Findings revealed heavy reliance on manual registers, resulting in duplicated entries, incomplete records, and delayed reporting. The reengineered DHIS2 prototype automated these processes, enabling real-time data capture and improved tracking of maternal and child health indicators. Testing at a pilot facility demonstrated improved attendance tracking, reduced data entry errors, and real-time dashboard and GIS analytics supporting decisions on ANC follow-up, HIV prevention, and maternal delivery outcomes. The number of mothers served per day increased from an average of 60–100 to 120–150, while reporting timeliness improved from 20% to over 95%. This study highlights the potential of customizing DHIS2 to strengthen maternal and child health data systems in resource-limited settings, offering a cost-effective alternative to proprietary electronic health records.