Trial reportAnnals of family medicine
Typical electronic health record use in primary care practices and the quality of diabetes care.
Trial report in Annals of family medicine. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 28 papers, 3 of them syntheses that pooled it.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
28 citing papers in PubMed, 3 syntheses or guidelines pooled it.
- The effect of computerized decision support systems on cardiovascular risk factors: a systematic review and meta-analysis.BMC medical informatics and decision making · 2019Pooled it
- Electronic tools for health information exchange: an evidence-based analysis.Ontario health technology assessment series · 2013Pooled it
- The effects of on-screen, point of care computer reminders on processes and outcomes of care.The Cochrane database of systematic reviews · 2009Pooled it
- Supporting Practices to Adopt Registry-Based Care (SPARC): protocol for a randomized controlled trial.Implementation science : IS · 2015Trial
- Practice context affects efforts to improve diabetes care for primary care patients: a pragmatic cluster randomized trial.Journal of general internal medicine · 2015Trial
- The Key Digital Tool Features of Complex Telehealth Interventions Used for Type 2 Diabetes Self-Management and Monitoring With Health Professional Involvement: Scoping Review.JMIR medical informatics · 2024Article
- Basic electronic health record (EHR) adoption inBMC health services research · 2023Article
- Article
- Assessment of Variation in Electronic Health Record Capabilities and Reported Clinical Quality Performance in Ambulatory Care Clinics, 2014-2017.JAMA network open · 2021Article
- Adoption rates of electronic health records in Turkish Hospitals and the relation with hospital sizes.BMC health services research · 2020Article
- Guiding Glucose Management Discussions Among Adults With Type 2 Diabetes in General Practice: Development and Pretesting of a Clinical Decision Support Tool Prototype Embedded in an Electronic Medical Record.JMIR formative research · 2020Article
- An Optimization Program to Help Practices Assess Data Quality and Workflow With Their Electronic Medical Records: Observational Study.JMIR human factors · 2018Article
- Designing health information technology tools for behavioral health clinicians integrated within a primary care team.Journal of innovation in health informatics · 2018Article
- Smart Diabetic Screening and Managing Software, A Novel Decision Support System.Journal of biomedical physics & engineering · 2018Article
- E-healthcare for Diabetes Mellitus Type 2 Patients - A Randomised Controlled Trial in Slovenia.Zdravstveno varstvo · 2017Article
- Electronic Health Records and Quality of Care: An Observational Study Modeling Impact on Mortality, Readmissions, and Complications.Medicine · 2016Observational
- The impact of electronic health records and teamwork on diabetes care quality.The American journal of managed care · 2015Article
- A qualitative study identifying the cost categories associated with electronic health record implementation in the UK.Journal of the American Medical Informatics Association : JAMIA · 2014Article
- Rational use of electronic health records for diabetes population management.Current diabetes reports · 2014Review
- The impact of electronic health records on workflow and financial measures in primary care practices.Health services research · 2014Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
Abstract
purposeRecent efforts to encourage meaningful use of electronic health records (EHRs) assume that widespread adoption will improve the quality of ambulatory care, especially for complex clinical conditions such as diabetes. Cross-sectional studies of typical uses of commercially available ambulatory EHRs provide conflicting evidence for an association between EHR use and improved care, and effects of longer-term EHR use in community-based primary care settings on the quality of care are not well understood.
methodsWe analyzed data from 16 EHR-using and 26 non-EHR-using practices in 2 northeastern states participating in a group-randomized quality improvement trial. Measures of care were assessed for 798 patients with diabetes. We used hierarchical linear models to examine the relationship between EHR use and adherence to evidence-based diabetes care guidelines, and hierarchical logistic models to compare rates of improvement over 3 years.
resultsEHR use was not associated with better adherence to care guidelines or a more rapid improvement in adherence. In fact, patients in practices that did not use an EHR were more likely than those in practices that used an EHR to meet all of 3 intermediate outcomes targets for hemoglobin A(1c), low-density lipoprotein cholesterol, and blood pressure at the 2-year follow-up (odds ratio = 1.67; 95% CI, 1.12-2.51). Although the quality of care improved across all practices, rates of improvement did not differ between the 2 groups.
conclusionsConsistent use of an EHR over 3 years does not ensure successful use for improving the quality of diabetes care. Ongoing efforts to encourage adoption and meaningful use of EHRs in primary care should focus on ensuring that use succeeds in improving care. These efforts will need to include provision of assistance to longer-term EHR users.
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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.