ArticleBMC health services research2012
Measuring data reliability for preventive services in electronic medical records.
Article in BMC health services research, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers, 1 of them a synthesis that pooled it.
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Who cites it
23 citing papers in PubMed, 1 synthesis or guideline pooled it.
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- Data quality in electronic medical records in Manitoba: Do problem lists reflect chronic disease as defined by prescriptions?Canadian family physician Medecin de famille canadien · 2017Article
- Improving the quality of EHR recording in primary care: a data quality feedback tool.Journal of the American Medical Informatics Association : JAMIA · 2017Article
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- Using a Data Quality Framework to Clean Data Extracted from the Electronic Health Record: A Case Study.EGEMS (Washington, DC) · 2016Article
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- Mixed Influence of Electronic Health Record Implementation on Diabetes Order Patterns for Michigan Medicaid Adults.Journal of diabetes science and technology · 2015Article
- Are family physicians comprehensively using electronic medical records such that the data can be used for secondary purposes? A Canadian perspective.BMC medical informatics and decision making · 2015Article
- Variability in screening prevention activities in primary care in Spain: a multilevel analysis.BMC public health · 2015Article
- Reasons for non-response to a direct-mailed FIT kit program: lessons learned from a pragmatic colorectal-cancer screening study in a federally sponsored health center.Translational behavioral medicine · 2015Article
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- Electronic health records and community health surveillance of childhood obesity.American journal of preventive medicine · 2015Article
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundImprovements in the quality of health care services are often measured using data present in medical records. Electronic Medical Records (EMRs) contain potentially valuable new sources of health data. However, data quality in EMRs may not be optimal and should be assessed. Data reliability (are the same data elements being measured over time?) is a prerequisite for data validity (are the data accurate?). Our objective was to measure the reliability of data for preventive services in primary care EMRs during the transition to EMR.
methodsOur data sources were randomly selected eligible patients' medical records and data obtained from provincial administrative datasets. Eighteen community-based family physicians in Toronto, Ontario that implemented EMRs starting in 2006 participated in this study. We measured the proportion of patients eligible for a service (Pap smear, screening mammogram or influenza vaccination) that received the service. We compared the change in rates of selected preventive services calculated from the medical record audits with the change in administrative datasets.
resultsIn the first year of EMR use (2006) services decreased by 8.7% more (95% CI -11.0%- - 6.4%, p < 0.0001) when measured through medical record audits as compared with administrative datasets. Services increased by 2.4% more (95% CI 0%-4.9%, p = 0.05) in the medical record audits during the second year of EMR use (2007).
conclusionThere were differences between the change measured through medical record audits and administrative datasets. Problems could include difficulties with organizing new data entry processes as well as continued use of both paper and EMRs. Data extracted from EMRs had limited reliability during the initial phase of EMR implementation. Unreliable data interferes with the ability to measure and improve health care quality.
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