ArticleJMIR medical informatics2021
Electronic Medical Record-Based Case Phenotyping for the Charlson Conditions: Scoping Review.
Article in JMIR medical informatics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.
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Who cites it
16 citing papers in PubMed.
- Use of machine learning for chronic disease case identification in primary care settings: A scoping review of methods, validation, and clinical relevance.The Journal of international medical research · 2026Article
- INSIGHTS Asthma Pragmatic Registry - A Pragmatic Approach to High-Validity Real-World Evidence for Asthma.Pragmatic and observational research · 2025Article
- Case Identification of Depression in Inpatient Electronic Medical Records: Scoping Review.JMIR medical informatics · 2024Article
- Collaborative and privacy-enhancing workflows on a clinical data warehouse: an example developing natural language processing pipelines to detect medical conditions.Journal of the American Medical Informatics Association : JAMIA · 2024Article
- Prevalence and Diagnosis of PCOS Using Electronic Health Records: A Scoping Review and a Database Analysis.International journal of environmental research and public health · 2024Article
- Automated extraction of weight, height, and obesity in electronic medical records are highly valid.Obesity science & practice · 2024Article
- Exploring the reliability of inpatient EMR algorithms for diabetes identification.BMJ health & care informatics · 2023Article
- High-throughput target trial emulation for Alzheimer's disease drug repurposing with real-world data.Nature communications · 2023Article
- Is Dementia Related to a Longer Wait Time to be Assigned a New Primary Care Provider? An Analysis of the Nova Scotia Need a Family Practice Registry Derived from the PUPPY-Study.Canadian geriatrics journal : CGJ · 2023Article
- Leveraging Electronic Health Records to Construct a Phenotype for Hypertension Surveillance in the United States.American journal of hypertension · 2023Article
- Cerebrovascular disease case identification in inpatient electronic medical record data using natural language processing.Brain informatics · 2023Article
- Dementia and electronic health record phenotypes: a scoping review of available phenotypes and opportunities for future research.Journal of the American Medical Informatics Association : JAMIA · 2023Article
- The microbiological landscape and epidemiology of ocular infections in a multi-tier ophthalmology network in India: an electronic medical record driven analytics report.Eye (London, England) · 2023Article
- Pan-Canadian Electronic Medical Record Diagnostic and Unstructured Text Data for Capturing PTSD: Retrospective Observational Study.JMIR medical informatics · 2022Article
- Incidence of Avoidable 30-Day Readmissions Following Hospitalization for Community-Acquired Pneumonia in France.JAMA network open · 2022Article
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9 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundElectronic medical records (EMRs) contain large amounts of rich clinical information. Developing EMR-based case definitions, also known as EMR phenotyping, is an active area of research that has implications for epidemiology, clinical care, and health services research.
objectiveThis review aims to describe and assess the present landscape of EMR-based case phenotyping for the Charlson conditions.
methodsA scoping review of EMR-based algorithms for defining the Charlson comorbidity index conditions was completed. This study covered articles published between January 2000 and April 2020, both inclusive. Embase (Excerpta Medica database) and MEDLINE (Medical Literature Analysis and Retrieval System Online) were searched using keywords developed in the following 3 domains: terms related to EMR, terms related to case finding, and disease-specific terms. The manuscript follows the Preferred Reporting Items for Systematic reviews and Meta-analyses extension for Scoping Reviews (PRISMA) guidelines.
resultsA total of 274 articles representing 299 algorithms were assessed and summarized. Most studies were undertaken in the United States (181/299, 60.5%), followed by the United Kingdom (42/299, 14.0%) and Canada (15/299, 5.0%). These algorithms were mostly developed either in primary care (103/299, 34.4%) or inpatient (168/299, 56.2%) settings. Diabetes, congestive heart failure, myocardial infarction, and rheumatology had the highest number of developed algorithms. Data-driven and clinical rule-based approaches have been identified. EMR-based phenotype and algorithm development reflect the data access allowed by respective health systems, and algorithms vary in their performance.
conclusionsRecognizing similarities and differences in health systems, data collection strategies, extraction, data release protocols, and existing clinical pathways is critical to algorithm development strategies. Several strategies to assist with phenotype-based case definitions have been proposed.
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