Data for program management: An accuracy assessment of data collected in household registers by community health workers in southern Kayonza, Rwanda

Tisha Mitsunaga*, Bethany L. Hedt-Gauthier, Elias Ngizwenayo, Didi Bertr Farmer, Erick Gaju, Peter Drobac, Paulin Basinga, Lisa Hirschhorn, Michael L. Rich, Peter J. Winch, Fidele Ngabo, Cathy Mugeni

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

11 Scopus citations

Abstract

Community health workers (CHWs) collect data for routine services, surveys and research in their communities. However, quality of these data is largely unknown. Utilizing poor quality data can result in inefficient resource use, misinformation about system gaps, and poor program management and effectiveness. This study aims to measure CHW data accuracy, defined as agreement between household registers compared to household member interview and client records in one district in Eastern province, Rwanda. We used cluster-lot quality assurance sampling to randomly sample six CHWs per cell and six households per CHW. We classified cells as having ‘poor’ or ‘good’ accuracy for household registers for five indicators, calculating point estimates of percent of households with accurate data by health center. We evaluated 204 CHW registers and 1,224 households for accuracy across 34 cells in southern Kayonza. Point estimates across health centers ranged from 79 to 100 % for individual indicators and 61 to 72 % for the composite indicator. Recording error appeared random for all but the widely under-reported number of women on modern family planning method. Overall, accuracy was largely ‘good’ across cells, with varying results by indicator. Program managers should identify optimum thresholds for ‘good’ data quality and interventions to reach them according to data use. Decreasing variability and improving quality will facilitate potential of these routinely-collected data to be more meaningful for community health program management. We encourage further studies assessing CHW data quality and the impact training, supervision and other strategies have on improving it.

Original languageEnglish (US)
Article numberA003
Pages (from-to)625-632
Number of pages8
JournalJournal of Community Health
Volume40
Issue number4
DOIs
StatePublished - Aug 1 2015

Funding

Community health workers and supervisors in southern Kayonza; Rwinkwavu District Hospital Medical Director Adolphe Karamaga and Community Health Supervisor Denys Ndanurura; and members of the IMB/PIH Monitoring, Evaluation and Research Department. The study was conducted as part of the Rwanda Population Health Implementation and Training (PHIT) Partnership, and funded by the Doris Duke Charitable Foundation’s African Health Initiative. The Rwanda PHIT Partnership is co-led by the Rwanda Ministry of Health and Partners In Health with key involvement from the National University of Rwanda School of Public Health (NURSPH), Rwanda National Institute of Statistics, as well as Harvard Medical School, and Brigham and Women’s Hospital in Boston, USA.

Keywords

  • Community health worker
  • Data quality
  • Lot quality assurance sampling
  • Rwanda

ASJC Scopus subject areas

  • Health(social science)
  • Public Health, Environmental and Occupational Health

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