Data cleaning process for HIV-indicator data extracted from DHIS2 national reporting system: a case study of Kenya
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RESEARCH ARTICLE
Data cleaning process for HIV‑indicator data extracted from DHIS2 national reporting system: a case study of Kenya Milka Bochere Gesicho1,4* , Martin Chieng Were2,4 and Ankica Babic1,3
Abstract Background: The District Health Information Software-2 (DHIS2) is widely used by countries for national-level aggregate reporting of health-data. To best leverage DHIS2 data for decision-making, countries need to ensure that data within their systems are of the highest quality. Comprehensive, systematic, and transparent data cleaning approaches form a core component of preparing DHIS2 data for analyses. Unfortunately, there is paucity of exhaustive and systematic descriptions of data cleaning processes employed on DHIS2-based data. The aim of this study was to report on methods and results of a systematic and replicable data cleaning approach applied on HIV-data gathered within DHIS2 from 2011 to 2018 in Kenya, for secondary analyses. Methods: Six programmatic area reports containing HIV-indicators were extracted from DHIS2 for all care facilities in all counties in Kenya from 2011 to 2018. Data variables extracted included reporting rate, reporting timeliness, and HIV-indicator data elements per facility per year. 93,179 facility-records from 11,446 health facilities were extracted from year 2011 to 2018. Van den Broeck et al.’s framework, involving repeated cycles of a three-phase process (data screening, data diagnosis and data treatment), was employed semi-automatically within a generic five-step data-cleaning sequence, which was developed and applied in cleaning the extracted data. Various quality issues were identified, and Friedman analysis of variance conducted to examine differences in distribution of records with selected issues across eight years. Results: Facility-records with no data accounted for 50.23% and were removed. Of the remaining, 0.03% had over 100% in reporting rates. Of facility-records with reporting data, 0.66% and 0.46% were retained for voluntary medical male circumcision and blood safety programmatic area reports respectively, given that few facilities submitted data or offered these services. Distribution of facility-records with selected quality issues varied significantly by programmatic area (p 100%” represents a situation where percentage is more than 100. This data points
Table 1 Categorization of the various situations within DHIS2 and actions taken Situation CPCa RRb
RRTc
Diagnosis
Action
A
0
0
0
Nothing was reported by facilities during this period, signifying that the facility does not report to DHIS2. This could be a true normal
Facility records excluded
B
0
X
X
Submitted reports might be on time, but are empty. Can result from programs wanting to have full MOH731 submission even though they do not offer services in all the 6 programmatic areas—hence submitting empty reports from non-required programmatic areas (Report is useless to decision-maker as it is empty)
Facility records excluded
C
0
X
0
Submitted reports are empty an
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