ArticleBMC geriatrics2017
Comparing clinician descriptions of frailty and geriatric syndromes using electronic health records: a retrospective cohort study.
Article in BMC geriatrics, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 44 papers, 3 of them syntheses that pooled it.
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Who cites it
44 citing papers in PubMed, 3 syntheses or guidelines pooled it.
- Natural language processing for geriatric syndromes: a systematic review of methods, applications, and challenges.BMC medical informatics and decision making · 2026Pooled it
- The use of natural language processing in detecting and predicting falls within the healthcare setting: a systematic review.International journal for quality in health care : journal of the International Society for Quality in Health Care · 2023Pooled it
- Use of Machine Learning and Artificial Intelligence Methods in Geriatric Mental Health Research Involving Electronic Health Record or Administrative Claims Data: A Systematic Review.Frontiers in psychiatry · 2021Pooled it
- Article
- Use of Conventional Artificial Intelligence Methods in the Identification of Frailty: A Scoping Review.Journal of the American Geriatrics Society · 2026Article
- Extracting geriatric syndromes from electronic health records: a scoping review.European geriatric medicine · 2026Article
- Article
- Geriatric syndromes extraction from discharge summaries: a new dataset, annotation scheme and initial findings.Frontiers in digital health · 2026Article
- Data-driven frailty and reserve phenotypes in older outpatients: a cluster analysis of complementary geriatric assessment.Frontiers in aging · 2025Article
- Unleashing frailty from laboratory into real world: A critical step toward frailty-guided clinical care of older adults.Journal of the American Geriatrics Society · 2024Article
- Extracting Critical Information from Unstructured Clinicians' Notes Data to Identify Dementia Severity Using a Rule-Based Approach: Feasibility Study.JMIR aging · 2024Article
- Assessing the Benefits and Harms of Pharmacotherapy in Older Adults with Frailty: Insights from Pharmacoepidemiologic Studies of Routine Health Care Data.Drugs & aging · 2024Review
- Natural language processing systems for extracting information from electronic health records about activities of daily living. A systematic review.JAMIA open · 2024Review
- Identifying Functional Status Impairment in People Living With Dementia Through Natural Language Processing of Clinical Documents: Cross-Sectional Study.Journal of medical Internet research · 2024Article
- Use of Artificial Intelligence in the Identification and Management of Frailty: A Scoping Review Protocol.BMJ open · 2023Article
- Article
- Characterizing Fall Circumstances in Community-Dwelling Older Adults: A Mixed Methods Approach.The journals of gerontology. Series A, Biological sciences and medical sciences · 2023Article
- Using electronic consultation (eConsult) to identify frailty in provider-to-provider communication: a feasibility and validation study.BMC geriatrics · 2023Review
- Can Patients with Dementia Be Identified in Primary Care Electronic Medical Records Using Natural Language Processing?Journal of healthcare informatics research · 2023Article
- Recommended practices and ethical considerations for natural language processing-assisted observational research: A scoping review.Clinical and translational science · 2023Article
Corrections and comments
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundGeriatric syndromes, including frailty, are common in older adults and associated with adverse outcomes. We compared patients described in clinical notes as "frail" to other older adults with respect to geriatric syndrome burden and healthcare utilization.
methodsWe conducted a retrospective cohort study on 18,341 Medicare Advantage enrollees aged 65+ (members of a large nonprofit medical group in Massachusetts), analyzing up to three years of administrative claims and structured and unstructured electronic health record (EHR) data. We determined the presence of ten geriatric syndromes (falls, malnutrition, dementia, severe urinary control issues, absence of fecal control, visual impairment, walking difficulty, pressure ulcers, lack of social support, and weight loss) from claims and EHR data, and the presence of frailty descriptions in clinical notes with a pattern-matching natural language processing (NLP) algorithm.
resultsOf the 18,341 patients, we found that 2202 (12%) were described as "frail" in clinical notes. "Frail" patients were older (82.3 ± 6.8 vs 75.9 ± 5.9, p < .001) and had higher rates of healthcare utilization, including number of inpatient hospitalizations and emergency department visits, than the rest of the population (p < .001). "Frail" patients had on average 4.85 ± 1.72 of the ten geriatric syndromes studied, while non-frail patients had 2.35 ± 1.71 (p = .013). Falls, walking difficulty, malnutrition, weight loss, lack of social support and dementia were more highly correlated with frailty descriptions. The most common geriatric syndrome pattern among "frail" patients was a combination of walking difficulty, lack of social support, falls, and weight loss.
conclusionsPatients identified as "frail" by providers in clinical notes have higher rates of healthcare utilization and more geriatric syndromes than other patients. Certain geriatric syndromes were more highly correlated with descriptions of frailty than others.
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