DR. MITTALI SETHI
IAS, District Collector, Nandurbar
“What makes me really happy is that it’s such a bottom-to-top exercise. We are actually listening to our health workers. At the core of everything that is being done, the intention is that we are doing it for them. So, it should make their lives easier.
They should find more happiness in what they are doing and, therefore, the people they are serving would also be benefitted.”
FAMILY PLANNING
Identifying high-risk mothers in time and connecting them to the follow-up care they need
Unmet need for family planning remains one of the most persistent and preventable gaps in India's reproductive health system. Eligible couples who want to space or limit pregnancies are not being reached — not because the services don't exist, but because the system lacks the precision to identify who needs support and where targeted outreach is most urgently required.
Using CHIP platform data combined with NFHS population data, Pali district in Rajasthan was identified as a priority geography — with the lowest modern contraceptive use and the highest unmet need in the state. Five priority sectors within the district were selected for targeted intervention, and a sector-level analysis of eligible couples pinpointed exactly where to focus outreach.
CHIP's digital health census provided a live, household-level view of eligible couples with unmet family planning need, giving health workers a ready-to-action due-list rather than a population-wide mandate to work through.
Sector-level analysis surfaced the specific geographies and households where unmet need was highest, enabling supervisors and health officials to prioritise outreach strategically rather than uniformly. Statewide, over 310,000 beneficiaries have been screened through this process.
ASHAs used CHIP due-lists to conduct targeted household visits — reaching 413 households with identified unmet need, of whom 268 have agreed to adopt an appropriate family planning method. Early data shows a 38.7% increase in Antara uptake in intervention areas — a measurable shift in service delivery directly attributable to data-driven targeting.
The intervention was conducted in close partnership with the Government of Rajasthan's Department of Health and Family Welfare. A formal mandate letter issued by the state directed health workers to use CHIP due-lists for their outreach thereby embedding the approach within official government workflows rather than operating as a parallel program.
310K+
BENEFICIARIES SCREENED STATE-WIDE
38.7%
INCREASE IN ANTARA UPTAKE IN INTERVENTION AREAS
MATERNAL HEALTH
Identifying high-risk mothers in time and connecting them to the follow-up care they need
Nandurbar is one of India's Aspirational Districts identified by the Government of India as a high focus geography for social and health upliftment. It carries Maharashtra's highest rate of maternal and infant mortality. Despite high coverage of frontline health workers in the area, fragmented data systems meant that identification of high-risk mothers and children was happening but coordinated action was not.
The Khushi Baby team engaged with the district leadership and local partners to identify key priorities and gaps. As a solution a physical command center called the Health Action Centre (HAC) was set up in Nandurbar, staffed with a lean six-person team.
To address foundational data gaps, KB deployed its CHIP application, locally named "E-Suchi”. This enabled community health workers to conduct a 90% digital health census of the district's 1.5 million residents. The census identified village-level, multi-dimensional vulnerability at a granularity previously unavailable to district planners.
Over 40 village-level datasets were aggregated into a single integrated map, providing a unified view of system gaps, resource distribution, and local partner activity. This map is now actively informing facility upgrade decisions and resource reallocations. New data sets were also gathered such as high-risk nominations from community health workers and high-risk discharge lists from the newborn intensive care unit.
Khushi Baby's maternal and child health work in Nandurbar was established in close partnership with the District Administration of Nandurbar, Maharashtra. The district government co-financed the Health Action Center from inception. Khushi Baby works with the Department of Health and Family Welfare and the Department of Women and Child Development to consolidate data and coordinate action across departments.
60 - 100
BENEFICIARIES REACHED BY CALL CENTER OPERATORS DAILY
70%
DAILY FOLLOW-UP RATE ACHIEVED FOR HIGH-RISK MOTHERS & INFANTS
ANEMIA PREVENTION
AI-Enabled Anemia Screening for Pregnant Women
Maternal anemia affects 12 million pregnant women annually in India and is a leading contributor to adverse maternal and neonatal outcomes. Yet screening at the last mile remains constrained by invasive, costly, and often unreliable tools. Moderate anemia frequently goes undetected and opportunities for early intervention are missed. Of the estimated 2 to 3 million women with moderate or worse anemia, many never receive the timely referral or treatment they need.
MAHILA is a non-invasive, smartphone-based screening tool. MAHILA uses machine learning to classify anemia severity from images of the conjunctiva (the inner lining of the eyelid). It requires no laboratory diagnostics and a frontline health worker can conduct a screen with nothing more than a smartphone. MAHILA is meant to enable frontline workers to screen pregnant women more frequently and refer only those who require confirmatory testing or facility based treatment.
Results from the first phase of research demonstrate over 94% sensitivity and 100% specificity for detection of moderate severity anemia in pregnant women. The model has been trained on a dataset of 3,021 pregnant women.
MAHILA is designed for integration into existing government digital health systems. Beyond India, the model is being designed for global adaptation with training datasets expanded to include African and Southeast Asian populations. This will enable contextualised deployment through local government health systems.
MAHILA was developed in partnership with state governments in Rajasthan, Maharashtra, and Karnataka, alongside AIIMS and ICMR. Currently it is being validated across medical colleges in Rajasthan and Karnataka and primary health centres in Nandurbar
INFANT IMMUNISATION
Finding children the system has missed and connecting them to the vaccinations they need
Rajasthan's zero-dose children (those who have never received a single routine vaccination) are concentrated among mobile, remote, and marginalised communities that health systems consistently struggle to see and reach. Despite high overall immunisation coverage in the state, fragmented data, paper registers, and limited cross-departmental visibility left health workers without a real-time view of who had been missed.
Through the Community Health Integrated Platform (CHIP) Khushi Baby supported the Government of Rajasthan to operationalise a state-wide, data-driven zero-dose strategy.
CHIP enabled a digital health census of children under two years across the state, automatically identifying suspected zero-dose cases from within an existing linelist of over 40 million people.
Geospatial hotspot mapping translated a statewide challenge into targeted, district-level action plans turning aggregated data into something frontline workers could act on directly. Integrated dashboards gave state leadership routine, real-time visibility into where children were being missed and where catch-up efforts were gaining ground.
Insights were converted into action through coordinated follow-up. Frontline health workers, call-centre operators, and field monitors worked together to reach identified children, verify vaccination status, and close the gap between identification and immunisation.
Khushi Baby's zero-dose immunisation work in Rajasthan was developed in close partnership with the Department of Medical, Health and Family Welfare, Government of Rajasthan, and Gavi — the global vaccine alliance.
96,000+
SUSPECTED ZERO-DOSE CHILDREN WERE IDENTIFIED ACROSS RAJASTHAN
6,700+
CHILDREN RECEIVED CATCH-UP IMMUNISATION
CHILD NUTRITION
The Government of Maharashtra was seeking a mechanism to improve tracking of high-risk children with severe acute malnutrition (SAM). A gap analysis conducted by the Khushi Baby team revealed that although there was a village-level list of identified SAM cases, there was no mechanism to follow-up which children completed treatment due to an interoperability gap in tracking systems between the nutrition and health departments.
We extended the CHIP dashboard framework to deploy NURTURE, an end-to-end child nutrition and health tracking system that bridges the distance between identification and recovery. It links identification data from the national Poshan Tracker with treatment pathways across Village Child Development Centres and Nutrition Rehabilitation Centres creating a single unified view of every child's journey across departments.
Every child identified as severely malnourished enters the system and is tracked across each stage of their care journey, creating a complete, cross-department picture of who has been reached and who has been lost.
Community health worker supervisors use NURTURE to ensure assessments are performed on identified children, and to follow up on whether referrals have been completed. Supervisors and district officials gain real-time visibility into where children are lost in the continuum and can act accordingly.
NURTURE was built in partnership with the Department of Women and Child Development (DWCD) and Department of Health in Maharashtra and has been handed over to DWCD for long term ownership.
46,000+
FOLLOW-UP ASSESSMENTS OF 72,000 SAM SUSPECTS
60%
FOLLOW-UP AND REFERRAL COMPLETION OF TARGETED 9K CONFIRMED SAM CASES
TUBERCULOSIS CONTROL
Improving the identification of Tuberculosis cases at the community level to ensure timely treatment to all affected
In Rajasthan, where Khushi Baby operates, TB prevalence was significantly higher than the national average. Active case finding, the most effective method for identifying high-risk populations, was not being implemented at scale or with optimal quality. The Tuberculosis Program under the Rajasthan Department of Health needed a stronger mechanism to monitor and streamline active surveillance campaigns across the state.
Khushi Baby’s digital health expertise and established CHIP platform was identified as a platform that could be leveraged for longitudinal tracking not currently available in the national Ni-kshay system. Khushi Baby identified data gaps and appropriate digital formats and trained community health workers. Five rounds of active surveillance were performed digitally on the CHIP platform. From these active case finding cycles, new insights emerged, raising concern for underreporting of symptomatic cases and resource efficiency.
Khushi Baby proposed a change in surveillance strategy to focus on vulnerable populations already known from prior digital health census data. This strategy proved to be successful in increasing the rate of presumptive TB case detection. Now new insights are being derived including prioritizing suspects who have multiple symptoms, and identifying geographic hotspots. These insights are being linked into targeted individual and community based outreach by public health call center operators and local health officials.
Khushi Baby supported the Rajasthan Department of Health in achieving a shift that was recognised and adopted at the national level.
40,000+
SUSPECTS DETECTED IN ONE ACTIVE-CASE FINDING CYCLE
8x
INCREASE IN PRESUMPTIVE CASE DETECTION RATE
CLIMATE & HEALTH
Using data to identify communities most vulnerable to climate-related health risks before it is too late to act
Climate change is reshaping the health landscape of the communities Khushi Baby serves but India's public health system has no reliable way of seeing where that risk is highest. By 2030, between 160 and 200 million people are at risk of lethal heat exposure. 1.3 billion live at air pollution levels above WHO guidelines. India carries the world's largest share of dengue and tuberculosis cases, and 500 million people live in pandemic jump zones.
India's existing Climate Vulnerability Index operates only at the state level which is too broad to direct targeted action, and limited to climate factors alone without accounting for health. Communities in remote villages, tribal districts, and areas with the highest burden of malnutrition, communicable disease, and maternal mortality remain invisible to the systems designed to protect them.
To this end, Khushi Baby in partnership with Google is developing India's first village-level Climate Health Vulnerability Index to make intersections between climate and health visible within public health systems and enable targeted, data-driven action before health crises occur.
Khushi Baby's CHIP platform already holds health, social vulnerability, and demographic data on over 60 million people across 40,000 villages. The CHVI combines CHIPs data with high-resolution climate data from Google Earth Engine and the Indian Meteorological Department. These datasets are integrated, geocoded, and run through high-performance geospatial models to produce a village-level index that overlays climate risk with health vulnerability across multiple dimensions, including health, social and economic conditions, infrastructure, and environment.
The CHVI is hosted within the CHIP dashboard, allowing health officials to visualise interactions between climate factors and health outcomes at the village level, drill down to identify specific hotspots, and take targeted action directly from the platform. Over the last 9 months since launch, CHVI has already been used to inform over 15 district action plans*
The CHVI is being developed in partnership with Google Health, which provides Environmental Insights Explorer data and geospatial modelling capabilities. Research partnerships with the Public Health Foundation of India, J-PAL South Asia at IFMR, and Audere support impact evaluation and evidence generation. The initiative is being co-created with state governments across Rajasthan, Maharashtra, and Karnataka, with the goal of eventual government adoption and integration into state digital health missions as an open-source digital public good.
