Longitudinal Health Outcomes Tracking
An offline-first data capture framework lets community health workers record maternal and child follow-ups from villages with no signal — and lets program leads see outcomes within the same fiscal year they occurred.
The challenge
The organization's community health workers cover six rural districts with intermittent-to-no mobile connectivity, following up with mothers and children after enrollment. Before this engagement:
- Follow-up visits were logged on paper registers that were routinely lost, water-damaged, or delayed in reaching the district office
- Fewer than 3 in 10 scheduled follow-ups were ever recorded in a usable, timestamped form
- Data reached the central system weeks after the visit, introducing significant recall error
- There was no mechanism to flag a mother-child pair who had silently dropped out of the follow-up schedule
- Program redesign decisions relied on an annual household survey rather than current field data
- Health workers had no way to see a beneficiary's prior visit history in the field
How it works
Designing for the connectivity you actually have, not the connectivity you wish you had
The build started from the field conditions, not the server architecture:
- 01
Mapped connectivity patterns and device usage across all six districts before designing any interface
- 02
Built a mobile data capture app on structured forms that runs fully offline on low-cost Android devices
- 03
Implemented local on-device storage with conflict-aware sync so entries survive days without a signal
- 04
Added automatic case flagging so a missed follow-up surfaces the moment the device reconnects
- 05
Set background sync to push data the moment a worker enters a connectivity zone, no manual upload step
- 06
Built a program-lead dashboard refreshed weekly instead of annually
- 07
Established a quarterly cohort review so field data feeds directly into program design decisions
What we built
Key capabilities
Offline-first by design
Health workers capture full visit records with no connectivity and no risk of losing data to a damaged paper register.
Automatic risk flagging
A mother-child pair who misses a scheduled follow-up is flagged the moment the worker's device syncs — no waiting for a manual review.
Weekly program visibility
Program leads see follow-up trends within days of a visit instead of within a year of a household survey.
Full longitudinal history in the field
Workers can see a beneficiary's prior visits on-device, even offline, changing how each follow-up conversation starts.
Before vs after
What changed for field teams
- Follow-up capture rate
- 27% → 71%
- Data lag to central system
- Weeks → days
- Missed-visit flagging
- None → automatic on sync
- Program redesign cycle
- Annual survey → same fiscal year
- Visit record medium
- Paper register → offline mobile form
Business impact
What it changed
2.6x more follow-ups captured
Recorded follow-up visits rose from 27% to 71% of the scheduled cohort — the difference between a program that knows its outcomes and one that estimates them.
Program design now runs on current data
The quarterly cohort review replaced the annual survey as the primary input to program adjustments, closing the feedback loop to within the same fiscal year.
At-risk cases caught earlier
Automatic flagging on sync means a missed follow-up prompts outreach within days, not at the next annual count.
Technology stack
“Better outcomes tracking didn't require a better survey — it required a system that worked in the villages where the visits actually happen.”
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