Assessing and improving data quality from community health workers: a successful intervention in Neno, Malawi
OBJECTIVES: 1) To establish the quality of aggregated measures contained in CHW reports; 2) to develop interventions to address poor data quality; and 3) to evaluate changes in data quality following the intervention.
DESIGN: We developed a lot quality assurance sampling-based data quality assessment tool to identify sites with high or low reporting quality. Following the first assessment, we identified challenges and best practices and followed the interventions with two subsequent assessments.
RESULTS: At baseline, four of five areas were classified as low data quality. After 8 months, all five areas had achieved high data quality, and the reports generated from our electronic database became consistent and plausible.
CONCLUSION: Program changes included improving the usability of the reporting forms, shifting aggregation responsibility to designated assistants and providing aggregation support tools. Local quality assessments and targeted interventions resulted in immediate improvements in data quality.
Document Type: Research Article
Affiliations: 1: Department of Internal Medicine, University of Michigan, Ann Arbor, Michigan, USA 2: Partners In Health, Boston, Massachusetts, USA; and Abwenzi Pa Za Umoyo, Neno, Malawi 3: Abwenzi Pa Za Umoyo, Neno, Malawi 4: Partners In Health, Boston, Massachusetts, USA; and Department of Global Health and Social Medicine, Harvard Medical School, Cambridge, Massachusetts, USA 5: Partners In Health, Boston, Massachusetts, USA 6: Ministry of Health, Neno District, Malawi 7: Department of Internal Medicine, University of Michigan, Ann Arbor, Michigan, USA; and Veterans Affairs Ann Arbor Healthcare System, Ann Arbor, Michigan, USA 8: Department of Global Health and Social Medicine, Harvard Medical School, Cambridge, Massachusetts, USA
Publication date: 21 March 2013
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