A door-to-door treatment programme, a community clinic, a hospital referral network and a district training unit do not need the same system. Use this playbook to find the model closest to your work, see what your team needs to follow and choose the parts worth building first.
| Ramesh Y. | cough 3 wk | sample?? |
| Ramesh Yadav | cough | dup? |
Five places, one patient. Nobody can see he's stopped his doses.
Most nonprofits combine two or three of these. Pick the closest starting point, not a perfect label. It changes what your team must keep track of, what can wait and what a useful first version should do.
Your team finds people in homes, camps or workplaces and stays with them through diagnosis, treatment and follow-up.
You run a clinic, mobile unit or telehealth service where people return for consultations, tests, medicines and referrals.
You help families move through hospitals, funding, documents, treatment milestones and practical support.
You work through hospitals, diagnostic centres or specialist providers rather than delivering every service yourself.
You work with schools, communities, workplaces or peer groups before illness becomes a treatment journey.
You improve how facilities, districts or frontline teams perform through assessment, training, mentoring and technical support.
Run a hybrid model? That is normal. A community clinic may also run camps, referrals and entitlements. Keep one shared picture of the person and programme, then add only the workflows each service needs.
These come up in almost every first conversation we have with health & wellbeing teams.
"His result was positive. Nobody told him for three weeks."
The lab register and the treatment register don't talk, so people get lost between the test and the first dose.
"We screened the same easy houses three times."
The screening count looked good. The migrant colony at the edge of the block was never visited.
"We screen 2,000 workers a month. We can't tell you whose BP came down."
Camp readings sit in one sheet per factory, so nobody can see who got medicine, who came back for a refill and who's now in the normal range.
"Our success rate leaves out everyone we lost."
'Not evaluated' and 'transferred out' quietly drop from the denominator, and the report looks better than the programme.
We haven't published a health programme case study yet. We've worked with health organisations including FMCH and The Antara Foundation, and these are real systems built on the same foundations: eligibility and application tracking for families, and field systems used by 20,000+ people.
A master list of government schemes and their eligibility rules matches each family to the right ones, and each application is tracked until the benefit arrives. Live in four months.
Read the case study →Simple Education Foundation20,000+teachers across four statesCompass MIS runs state-wide teacher training, classroom observations and multilingual assessments. The first week of a new-state pilot logged 2 million interactions.
Read the case study →Recognise your programme? Tell us where the work gets stuck and we'll suggest a useful first version.
This is one programme model, not a template for every health nonprofit. Pick a stage to see what the field team does, what can happen automatically and what the programme manager needs to see.
Stage 01 · Find every case
Clinics catch the people well enough to walk in. The rest cough at home for months. Door-to-door screening closes that gap, if the register shows which houses you've actually covered.
| Case ref. | Person | Village | Status |
|---|---|---|---|
| HL-3308 | Ramesh Yadav | Ward 12 | Sample collected |
| HL-3321 | Shabana Bano | Brick kiln colony | Sample overdue |
| HL-3317 | Mohan Lal | Chaubeypur | Pickup today |
| HL-3302 | Geeta Devi | Ward 12 | Ruled out |
Stage 02 · Start treatment fast
A sample leaves the village, the result comes back positive, and nobody tells the patient. Every day between diagnosis and the first dose is another day of infection at home.
| Case ref. | Patient | Days since result | Status |
|---|---|---|---|
| HL-3294 | Salim Ansari | 12 | Not reached |
| HL-3289 | Kamla Devi | 6 | Visit today |
| HL-3311 | Vinod Kumar | 4 | Referred to DR-TB |
| HL-3308 | Ramesh Yadav | 2 | Started |
Stage 03 · Keep them on treatment
A six-month course feels endless by week eight, when symptoms fade and side effects don't. Missed doses usually trace back to travel cost, lost wages, nausea or stigma.
| Case ref. | Patient | Last 14 days | Action |
|---|---|---|---|
| HL-3308 | Ramesh Yadav | 11 of 14 | Tracing today |
| HL-3276 | Rekha Pal | 12 of 14 | Nausea, MO review |
| HL-3281 | Ajay Maurya | 13 of 14 | Wage loss support |
| HL-3269 | Farida Khatoon | 14 of 14 | On track |
Stage 04 · Record every outcome
A success rate only means something if everyone enrolled gets an outcome. 'Not evaluated' and 'lost to follow-up' are where programmes hide their failures.
| Case ref. | Patient | Outcome | Status |
|---|---|---|---|
| HL-3151 | Suresh Bind | None recorded | MO review |
| HL-3162 | Anita Kumari | Transferred out | Not yet registered |
| HL-3148 | Raju Prajapati | Cured | 12-month check due |
| HL-3155 | Sarita Devi | Completed | 6-month check due |
Your programme will have different questions. A clinic may ask who is waiting, a navigation team which approval is stuck, and a district team which facility action is overdue. Return to the six programme models ↑
The same pattern, whatever the condition. Switch between two illustrative programmes.
Illustrative numbers. The unknowns stay in the base.
Do not begin with a long software wish list. Begin with the work that falls between people today. Most organisations need a small shared foundation, then two or three building blocks shaped to their model.
Your system should help a real person decide what to do next, not just create another report.
Count the people who disappear between steps, not only the people who complete them.
Use automation to reduce repetition. Keep judgement, care and accountability with people.
In plain language: the goal is not “one Patient ID.” The goal is that the outreach worker, clinic, programme manager and referral partner can each see the part they need, and that no person, family or unresolved action disappears between them.
A health programme needs a person-level record that outlasts any single visit. These short reads cover what to collect and protect, what to connect to, what goes wrong and what success means in health.
Rule of thumb. Follow one person closely, because continuity of care is the point. The discipline is purpose and consent: join up visits, referrals and tests for the person, and show everyone else only what their role needs. Education is the opposite case: collect less. See education →
Systems and rules change. We confirm what applies to you in the first conversation, and we use the equivalent in your country.
What goes wrongA patient list in a shared sheet, or a visible home visit, discloses HIV, TB or another condition.
How it is designed outRole-based masking, discreet contact preferences recorded with the person, and no condition names in reports or chat.
What goes wrongOne tick-box at registration is treated as permission for every later use.
How it is designed outConsent recorded for each purpose, easy to withdraw, and checked before data goes to a partner or donor.
What goes wrongA person is screened, referred and never seen again because nobody owns the handoff.
How it is designed outEvery referral has an owner, a due date and a closure. The follow-up list is the main screen.
What goes wrongTest results are pasted into public AI tools or personal messaging apps.
How it is designed outAI runs only inside your account, on approved fields, with a person reviewing. No patient data in public tools.
A clinic and a foundation can both ask for an MIS and need different answers. Start from the question the person at the table will ask.
Who has missed a visit or a refill, and who is going to call them today?
Watch outCounting screenings tells you about outreach, not whether anyone got treated.
Are people getting timely follow-up, and does it change their health?
Watch outCoverage figures hide who is lost after the first visit.
Do your numbers match ours, and can we trust them?
Watch outParallel reporting that disagrees with the official system costs you the partnership.
This is India's financial year and seasons. Many countries report on a calendar year or a July to June year, and rainy seasons and malaria peaks vary a lot by region.
Most AI projects stall because the records underneath are messy. So we work in a fixed order.
Every question on a form should help someone decide or act. If nobody uses the answer, your team should not have to collect it.
A system people avoid is worse than a spreadsheet. We design around shared phones, patchy signal and WhatsApp.
On clean, connected records, AI can read paperwork, draft reports and flag who needs attention. A person always checks.
Where you start depends on where you are. If your records are already in good shape, we can move to AI quickly. If they're in notebooks, we start there, and we don't start from zero.
Offline forms, local languages, links to government IDs and AI features are set up to suit each programme's needs and consent rules, so not every build includes all of them.
We picked the jobs that save health & wellbeing teams the most hours. Each starts with a problem we hear often, and each keeps a person in charge of the decision. How we think about AI →
“We lose half a CHW's day typing symptom screens on a small phone screen in a language the keyboard doesn't handle well.”
Your team still decides: the CHW confirms each answer on screen before saving.
“We only find out someone has dropped off when they've missed a month of doses or refills.”
Your team still decides: the supervisor reviews the list weekly and notes whether each flag helped.
“Our counsellors hear why people stop treatment, but it stays in their heads or in voice notes nobody reads.”
Your team still decides: the counsellor confirms each barrier before saving.
“We know families are missing out on schemes that would keep them on treatment, but nobody has time to check eligibility one by one.”
Your team still decides: the help desk worker checks documents with the family before any application goes in.
“We type the same numbers into our own sheets and then again into the government's format every month.”
Your team still decides: the M&E officer matches totals to the register before submitting.
“Every funder and brand wants a quarterly report in its own template, and our MEL team spends a week on each.”
Your team still decides: the programme manager checks every figure and caveat before sending.
Health records are the most sensitive data you hold. These lines don't move, whoever's asking.
Each person she flagged shows up later as ruled out, diagnosed, cured or traced. The walk counts.
Today's patients, yesterday's missed doses and who reported side effects, without flipping through cards.
Patients due for a monthly review or sputum test, with dose history and side effects on one screen.
Screened to diagnosed to started to cured, by block, every week.
Treatment success with full denominators, and 'not evaluated' and transfers counted in.
If 'not evaluated' and 'transferred out' drop from your denominator, your treatment success rate looks better than your programme is. We record an outcome for every patient who started, and count the unknowns.
District reviewers notice. So do funders.Most systems launch in three to four months. The timeline moves with the number of programmes and roles, how messy the old data is, and how many tools need connecting.
Tell us where the work gets stuck today. Spreadsheets, notebooks, WhatsApp groups, all of it.
You show us how the programme runs. We'll tell you straight if you need a new system, a better workflow or nothing at all.
We map how your programme works, talk to the people who'll use it, review the tools you use today and hand you a System Blueprint, a clear plan of what we'll build.
Working screens every 2 to 4 weeks, tested by your field team in your own terms. We clean up your old spreadsheets and move them across.
Field training and launch, then 30 to 60 days of close support. After that, the system keeps changing as your programmes do.
We connect to Nikshay, ABHA and NCD portal exports, point-of-care devices, WhatsApp, SMS and IVRS, and the apps your own tech team already runs, rather than replacing what already works. Zoho licences sit in your organisation's name, and everything exports whenever you want it.
The questions your finance head and IT lead will ask, answered before the call.
Zoho licences are bought in your organisation's name and hosted in the Zoho data centre region you choose, including India. We work inside your account.
Every record exports to Excel or CSV whenever you want, including the day you stop working with us. You're not locked in to us for support either.
Each person sees only the records their role needs. Identities of key populations are hidden from roles that don't need them. Employers and brands see totals, never a worker's name.
Edits are logged with who made them and when, so an audit or a funder query doesn't start from memory.
Consent is recorded for each purpose, and we agree up front how long data is kept and when it's deleted. ZolaShield, our DPDP platform, shows where you stand.
AI features run on your records under your account's controls. Beneficiary records never go into public AI tools.
Use these focused implementation guides alongside the sector playbook.
Bring one tracker, one donor report and the process your team dreads. In 30 minutes we'll show you where the handoffs break, and tell you whether you need a better workflow, a connected programme system or no new software at all.
If budget is tight, ask about the Built for Impact Programme, which gives eligible nonprofits free Zoho credits.
The same approach, shaped to each kind of work.
