ArticleJournal of the American Medical Informatics Association : JAMIA
Computerized extraction of information on the quality of diabetes care from free text in electronic patient records of general practitioners.
Article in Journal of the American Medical Informatics Association : JAMIA. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 33 papers, 2 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
33 citing papers in PubMed, 2 syntheses or guidelines pooled it, 81 citations in OpenAlex.
- The Identification of Diabetes Mellitus Subtypes Applying Cluster Analysis Techniques: A Systematic Review.International journal of environmental research and public health · 2020Pooled it
- Natural language processing systems for capturing and standardizing unstructured clinical information: A systematic review.Journal of biomedical informatics · 2017Pooled it
- Trial
- Tailoring Type II Diabetes Treatment: Investigating the Effect of 5-HTT Polymorphisms on HbA1c Levels after Metformin Initiation.Journal of diabetes research · 2024Article
- RegEMR: a natural language processing system to automatically identify premature ovarian decline from Chinese electronic medical records.BMC medical informatics and decision making · 2023Article
- Role of Serum Lipids, Blood Glucose and Blood Pressure in Breast Cancer Risk for Women with Type 2 Diabetes Mellitus.Clinical epidemiology · 2023Article
- Identifying patients at increased risk of hypoglycaemia in primary care: Development of a machine learning-based screening tool.Diabetes/metabolism research and reviews · 2021Article
- Predicting short- and long-term glycated haemoglobin response after insulin initiation in patients with type 2 diabetes mellitus using machine-learning algorithms.Diabetes, obesity & metabolism · 2019Observational
- No significant association of type 2 diabetes-related genetic risk scores with glycated haemoglobin levels after initiating metformin or sulphonylurea derivatives.Diabetes, obesity & metabolism · 2019Observational
- Article
- HbA1c response after insulin initiation in patients with type 2 diabetes mellitus in real life practice: Identifying distinct subgroups.Diabetes, obesity & metabolism · 2018Observational
- Identification of Four Novel Loci in Asthma in European American and African American Populations.American journal of respiratory and critical care medicine · 2017Article
- Overcoming the Challenges of Unstructured Data in Multisite, Electronic Medical Record-based Abstraction.Medical care · 2016Article
- Identification of major cardiovascular events in patients with diabetes using primary care data.BMC health services research · 2016Article
- Role of Patient and Practice Characteristics in Variance of Treatment Quality in Type 2 Diabetes between General Practices.PloS one · 2016Article
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- Article
- Practical challenges in integrating genomic data into the electronic health record.Genetics in medicine : official journal of the American College of Medical Genetics · 2013Review
- Optimising the use of electronic health records to estimate the incidence of rheumatoid arthritis in primary care: what information is hidden in free text?BMC medical research methodology · 2013Article
- Advancing current approaches to disease management evaluation: capitalizing on heterogeneity to understand what works and for whom.BMC medical research methodology · 2013Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectiveThis study evaluated a computerized method for extracting numeric clinical measurements related to diabetes care from free text in electronic patient records (EPR) of general practitioners. DESIGN AND MEASUREMENTS: Accuracy of this number-oriented approach was compared to manual chart abstraction. Audits measured performance in clinical practice for two commonly used electronic record systems.
resultsNumeric measurements embedded within free text of the EPRs constituted 80% of relevant measurements. For 11 of 13 clinical measurements, the study extraction method was 94%-100% sensitive with a positive predictive value (PPV) of 85%-100%. Post-processing increased sensitivity several points and improved PPV to 100%. Application in clinical practice involved processing times averaging 7.8 minutes per 100 patients to extract all relevant data.
conclusionThe study method converted numeric clinical information to structured data with high accuracy, and enabled research and quality of care assessments for practices lacking structured data entry.
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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.