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HEALTH ACTION CENTERS

We’re deploying sustainable team units and processes within health departments to make informed decisions with the community

A Health Action Center is a lean, multidisciplinary unit co-established by the Khushi Baby team, the relevant government health department, and local partners. It identifies the primary health priorities within its geography, conducts a structured gap analysis across the DIA cycle, and then co-designs, implements, and iteratively refines targeted interventions.

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SWIPE TO UNDERSTAND THE HAC MODEL
SETUP

HAC Gets Setup

KB team, Health Dept. and local partner form the Health Action Committee.

FOCUS

Primary health issue identified

The committee selects the primary health priority to address in the community.

ANALYSE

DIA gap analysis conducted

A data-informed analysis maps the gaps in current health delivery — identifying what is missing, overlapping, or low quality.

IMPLEMENT "DIA"

Collection Systems, Gap analysis tools, Service delivery

CHIP app, dashboard, WhatsApp group. Data collection infrastructure established.

Triage lists, hotspot maps, blindspots, overlaps, data-quality checks applied to identified gaps.

Trainings, screening camps, resource reallocations, call centre modules, public health mandates.

REVIEW

Periodic review & DIA adaptation

Iterative learning cycle — findings feed back into gap analysis and solution refinement.

SCALE

Playbook documentation

Process documented for replication and scale across other communities and health issues.

THE DIA LOOP IN ACTION

Nandurbar Health Action Center

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Nandurbar Health Action Center

  • Nandurbar sits in northwestern Maharashtra — dense forests, hilly terrain, deeply rooted tribal communities with a 69% Scheduled Tribe population. The Maternal mortality is  4× the state average.

     

    In Nandurbar, we set up a six-person embedded team operating from the district administrative headquarters— program manager, data analyst, four nurses as call center operators — tthat turns routine health data into real-time action — ensuring no high-risk mother or child falls through the cracks.

  • The CHIP digital health census surveys 87.7% of 1.8M residents. It integrates 47+ datasets: WhatsApp group intelligence from CHWs, SNCU discharge lists, health worker high-risk nominations, ad hoc surveys. Every household is GPS-tagged. 2,085 ASHAs are digitally enabled on e-SUCHI.

  • Our integrated dashboard with 40+ layers identifies which PHCs reported zero high-risk pregnancies despite 1,591 estimated cases. Prioritized triage lists tell each worker exactly who to visit. Multi-dimensional vulnerability maps are shared directly with the District Collector.

  • Four call center operators follow up with 500+ highest-risk mothers and children weekly. Field teams coordinate home visits, emergency transport, and focused investigations. Weekly government reviews convert gaps into assigned, time-bound actions.

CLOSING THE LOOP: MARCH 2026

HAC Associates identified 3 high-risk newborns in Akkalkuwa, Dhadgaon, and Taloda blocks who had not received mandated home-based newborn care visits. Through 1–2 targeted follow-ups and coordination with frontline workers, all three were converted to compliance. Two low-birth-weight children showed significant weight gain. In one case, the child's weight was recorded for the first time since birth.

SCALING HAC

Tele-HAC: Scaling the Action Layer for Community Outreach

The current HAC model is powerful but human-intensive. TeleHAC is a forthcoming AI-augmented module within the CHIP dashboard that transforms the manual call center operation into a scalable, quality-monitored community outreach system.


Where a manual call center is constrained by operator bandwidth and supervision capacity, TeleHAC brings in automated triage prioritization — surfacing the highest-risk beneficiaries for next follow-up — structured counseling support for operators, and longitudinal tracking of conversation quality. The goal is to extend the reach and depth of community follow-up without proportionally scaling the team size, and to generate the kind of systematic learning about what counseling approaches work that a manual system cannot produce.

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