ArticlePloS one2018
The impact of routine data quality assessments on electronic medical record data quality in Kenya.
Article in PloS one, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 34 papers, 4 of them syntheses that pooled it.
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The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
34 citing papers in PubMed, 4 syntheses or guidelines pooled it.
- Data Quality-Driven Improvement in Health Care: Systematic Literature Review.Journal of medical Internet research · 2024Pooled it
- Electronic health record data quality assessment and tools: a systematic review.Journal of the American Medical Informatics Association : JAMIA · 2023Pooled it
- Digital Health Data Quality Issues: Systematic Review.Journal of medical Internet research · 2023Pooled it
- A realist systematic review of evidence from low- and middle-income countries of interventions to improve immunization data use.BMC health services research · 2021Pooled it
- User and Provider Experiences with a Digital Health Family Planning Counseling Tool for Women Living with HIV in Kenya.Studies in family planning · 2026Trial
- Improving Trauma Data Quality in Rwanda: A Prospective Assessment of Registry Completeness and Accuracy.Journal of clinical medicine · 2026Article
- A framework for identifying cost efficiencies in malaria routine data quality audits: methodology and application in Zambia.Malaria journal · 2026Article
- Optimizing adolescent HIV care: a review of EMR system quality for clinical monitoring in Zambia.Frontiers in public health · 2026Article
- Barriers and facilitators to implementing an integrated electronic health records system to improve tuberculosis preventive treatment among people living with HIV: a content analysis study from Georgia.Frontiers in digital health · 2026Article
- User experiences with a digital health family planning counseling tool for women living with HIV in Kenya.medRxiv : the preprint server for health sciences · 2025Article
- Article
- Optimizing the Delivery of Routine Malaria Data Quality Assessments: A Two-Level Logistic Regression Model to Inform an Institutionalized Approach in Mozambique.The American journal of tropical medicine and hygiene · 2025Article
- Examine frameworks policies and strategies for effective information governance in healthcare organizations.PloS one · 2025Article
- The Impact of Health Information System Interventions on Maternal and Child Health Service Utilizations in Ethiopia: A Quasi-Experimental Study.Global health, science and practice · 2024Article
- Factors Influencing Data Quality in Electronic Health Record Systems in 50 Health Facilities in Rwanda and the Role of Clinical Alerts: Cross-Sectional Observational Study.JMIR public health and surveillance · 2024Observational
- Health Information System Strengthening During Antenatal Care in Haiti: Continuous Quality Improvement Study.JMIR formative research · 2024Article
- Barriers to healthcare data quality and recommendations in public health facilities in Dire Dawa city administration, eastern Ethiopia: a qualitative study.Frontiers in digital health · 2024Article
- Development of novel composite data quality scores to evaluate facility-level data quality in electronic data in Kenya: a nationwide retrospective cohort study.BMC health services research · 2023Article
- Automating Electronic Health Record Data Quality Assessment.Journal of medical systems · 2023Review
- Prediction and analysis of time series data based on granular computing.Frontiers in computational neuroscience · 2023Article
Corrections and comments
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Authors and funding
11 authors.
Funding
Abstract
backgroundRoutine Data Quality Assessments (RDQAs) were developed to measure and improve facility-level electronic medical record (EMR) data quality. We assessed if RDQAs were associated with improvements in data quality in KenyaEMR, an HIV care and treatment EMR used at 341 facilities in Kenya.
methodsRDQAs assess data quality by comparing information recorded in paper records to KenyaEMR. RDQAs are conducted during a one-day site visit, where approximately 100 records are randomly selected and 24 data elements are reviewed to assess data completeness and concordance. Results are immediately provided to facility staff and action plans are developed for data quality improvement. For facilities that had received more than one RDQA (baseline and follow-up), we used generalized estimating equation models to determine if data completeness or concordance improved from the baseline to the follow-up RDQAs.
results27 facilities received two RDQAs and were included in the analysis, with 2369 and 2355 records reviewed from baseline and follow-up RDQAs, respectively. The frequency of missing data in KenyaEMR declined from the baseline (31% missing) to the follow-up (13% missing) RDQAs. After adjusting for facility characteristics, records from follow-up RDQAs had 0.43-times the risk (95% CI: 0.32-0.58) of having at least one missing value among nine required data elements compared to records from baseline RDQAs. Using a scale with one point awarded for each of 20 data elements with concordant values in paper records and KenyaEMR, we found that data concordance improved from baseline (11.9/20) to follow-up (13.6/20) RDQAs, with the mean concordance score increasing by 1.79 (95% CI: 0.25-3.33).
conclusionsThis manuscript demonstrates that RDQAs can be implemented on a large scale and used to identify EMR data quality problems. RDQAs were associated with meaningful improvements in data quality and could be adapted for implementation in other settings.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.