Restructuring national health information system software to improve malaria data quality: activation of zero values and ninety-nine validation rules in Cameroon's DHIS2

Abstract Background The District Health Information System 2 (DHIS2) has been Cameroon's principal platform for routine health facility reporting since 2015. A 2023 assessment of malaria surveillance identified inaccurate French–English translation, misalignment between the paper Monthly Activity Report (RMA) and the DHIS2 form, and automated deletion of zero values, which made true zeros indistinguishable from missing values. The 2024 RMA revision also rendered the 52 existing malaria validation rules obsolete. Methods In this national before-and-after operational study, four linked changes were made to the malaria section of DHIS2 in 2024: variables were renamed and retyped as positive integer or zero; storage of zero values was enabled in April 2024; ninety-nine validation rules were configured and tested at a four-day workshop in May 2024; and variables and error messages were translated bilingually and aligned with the paper RMA. Completeness of malaria variables and internal consistency (five indicator-pair relationships) were compared between January–March and April–June 2024. Analyses were descriptive; no significance tests were applied. Results The restructured malaria section comprised seven sub-sections, 91 variables and 416 bilingual entry fields. Validation rules rose from 52 to 99, all configured and tested within the workshop. Mean completeness across the ten regions rose from 51.3% to 69.7%, an increase of 18.4 percentage points, and rose in every region, from + 7.6 percentage points in Far North to + 24.4 in Adamawa. Across the five indicator pairs, the proportion of reports free of the specified inconsistency rose from a mean of 88.2% to 92.6%. Conclusions Small, inexpensive configuration changes to a national reporting platform were followed by measurable improvements in the completeness and internal consistency of routine malaria data. The completeness gain must be interpreted with care: enabling storage of zero values changed what completeness measures as well as what facilities report, so part of the increase is definitional. The consistency gain is more directly attributable to the rules, which act at the point of data entry. Sustaining these gains will require replacing the annual deletion of zero values with archiving, differentiating rule importance levels, and adding visual alerts to the entry form.