Pre-population of data: Improving efficiency of frontline workers while maintaining a single source of data based on AAA’s roles and responsibilities.

Reduced data redundancy: Following a roles and responsibilities based grid while designing workflows for the three frontline workers and allowing auto flow of common data.

Summary statistics: Depicting summary data to supplement line-list data to support data-based decision making by frontline workers.

Real-time case specific counselling: Enabling frontline workers to readily access a repository for counselling and awareness material when they are providing and recording services.

Knowledge building during reporting of services: Providing health workers with critical information regarding different services while registering a beneficiary.

Auto-identification of critical beneficiaries: Identifying critical beneficiaries directly using service delivery data to improve identification and under-reporting of critical beneficiaries.

Data for over 1,600 pregnant women for ANC check-ups, over 1,500 deliveries, and more than 11,500 children till the age of six was recording using the Integrated AAA App. The impact figures are based on data from 150 AWCs in Khanpur block of Jhalawar district in Rajasthan, from May to December 2018.

• The common database ensured that beneficiaries registered for nutrition services at the Anganwadi center increased by 40% after using the application
• The app captured twice the data points per pregnant woman during the ante-natal checkup data, as compared to data captured manually
• There was an eight-fold increase in the identification of high-risk pregnancies (HRP) after using the app; the HRPs were categorized at a granular level, covering more than 30 reasons for classification as high-risk
• Identification of severely underweight and underweight children increased by over 100% (from 3% to 8% and from 15% to 34% respectively)