ArticleJournal of the American Medical Informatics Association : JAMIA2016
Data quality of electronic medical records in Manitoba: do problem lists accurately reflect chronic disease billing diagnoses?
Article in Journal of the American Medical Informatics Association : JAMIA, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 33 papers, 1 of them a synthesis that pooled it.
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Who cites it
33 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Electronic health record data quality assessment and tools: a systematic review.Journal of the American Medical Informatics Association : JAMIA · 2023Pooled it
- Current state of electronic problems lists in primary care: a rapid scoping review.Family practice · 2026Article
- Child and youth chronic physical health conditions: a comparison of survey data and linked administrative health data in Ontario.BMC pediatrics · 2025Article
- Analyzing the medical record homepages quality in a Chinese EMR system.BMC medical informatics and decision making · 2025Article
- Assessing the capture of sociodemographic information in electronic medical records to inform clinical decision making.PloS one · 2025Article
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- Using artificial intelligence to identify patients with migraine and associated symptoms and conditions within electronic health records.BMC medical informatics and decision making · 2023Article
- Validation of a Case Definition to Identify Patients Diagnosed With Cardiovascular Disease in Canadian Primary Care Practices.CJC open · 2023Article
- Validation of a primary care electronic medical records case definition for eczema: retrospective cross-sectional study.Allergy, asthma, and clinical immunology : official journal of the Canadian Society of Allergy and Clinical Immunology · 2023Article
- Primary care asthma surveillance: a review of knowledge translation tools and strategies for quality improvement.Allergy, asthma, and clinical immunology : official journal of the Canadian Society of Allergy and Clinical Immunology · 2023Review
- The Registrar Clinical Encounters in Training (ReCEnT) cohort study: updated protocol.BMC primary care · 2022Article
- Pan-Canadian Electronic Medical Record Diagnostic and Unstructured Text Data for Capturing PTSD: Retrospective Observational Study.JMIR medical informatics · 2022Article
- Electronic Health Records That Support Health Professional Reflective Practice: a Missed Opportunity in Digital Health.Journal of healthcare informatics research · 2022Article
- Comparing ascertainment of chronic condition status with problem lists versus encounter diagnoses from electronic health records.Journal of the American Medical Informatics Association : JAMIA · 2022Article
- Increasing likelihood of prescribing recommended lipid management: Primary care providers' participation in cardiology continuing medical education.Canadian family physician Medecin de famille canadien · 2022Article
- A data quality assessment to inform hypertension surveillance using primary care electronic medical record data from Alberta, Canada.BMC public health · 2021Article
- Development of standard indicators to assess use of electronic health record systems implemented in low-and medium-income countries.PloS one · 2021Article
- Article
- Embedding "Smart" Disease Coding Within Routine Electronic Medical Record Workflow: Prospective Single-Arm Trial.JMIR medical informatics · 2020Article
Corrections and comments
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectiveTo determine problem list completeness related to chronic diseases in electronic medical records (EMRs) and explore clinic and physician factors influencing completeness.
methodsA retrospective analysis of primary care EMR data quality related to seven chronic diseases (hypertension, diabetes, asthma, congestive heart failure, coronary artery disease, hypothyroidism, and chronic obstructive pulmonary disorder) in Manitoba, Canada. We included 119 practices in 18 primary care clinics across urban and rural Manitoba. The main outcome measure was EMR problem list completeness. Completeness was measured by comparing the number of EMR-documented diagnoses to the number of billings associated with each disease. We calculated odds ratios for the effect of clinic patient load and salary type on EMR problem list completeness of the 7 chronic diseases.
resultsCompleteness of EMR problem list for each disease varied widely among clinics. Factors that significantly affected EMR problem list completeness included the primary care provider, the patient load, and the clinic's funding and organization model (ie, salaried, fee-for-service, or residency training clinics). Average rates of completeness were: hypertension, 72%; diabetes, 80%; hypothyroidism, 63%; asthma, 56%; chronic obstructive pulmonary disorder, 43%; congestive heart failure, 54%; and coronary artery disease, 64%.
conclusionThis study demonstrates the high variability but generally low quality of problem lists (health condition records) related to 7 common chronic diseases in EMRs. There are systematic physician- and clinic-level factors associated with low data quality completeness. This information may be useful to support improvement in EMR data quality in primary care.
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