Research · Epidemiology
Sufficient and appropriate data
Enough data, of the right kind, to identify preventable cases, epidemiological patterns and the risk factors associated with a disease.
Why 'appropriate' does the work in that sentence
Volume is not the constraint
Screening programmes generate large volumes of data and very little usable epidemiology, for one reason: the findings are recorded as prose. Prose cannot be counted, cannot be compared between years, and cannot be pooled across districts.
Everything in our capture design follows from this. Coding at source is not a technical preference; it is the difference between a programme that produces epidemiology and one that produces paperwork.
What we collect
And at what granularity
| Data | Granularity | Purpose |
|---|---|---|
| Screening findings | Per beneficiary, coded | Case identification and referral |
| Laboratory results | Per beneficiary, LOINC coded | Deficiency and disease detection |
| Demographics | Age band, sex, location to block level | Stratification |
| Referral outcome | Per referral, status tracked | Whether care actually happened |
| Coverage | Screened, declined, absent | Denominators, without which rates are meaningless |
Denominators
The part most programmes skip
Screened-negative is not the same as not-screened
A programme that reports only positive findings cannot produce a rate. We record absence and refusal explicitly so that the denominator is real.
See how it is reported.
What partners receive.