Comparing clinician descriptions of frailty and geriatric syndromes using electronic health records: a retrospective cohort study
Abstract Background Geriatric 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. Methods We conducted a...
| Main Authors: | , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
BMC
2017-10-01
|
| Series: | BMC Geriatrics |
| Subjects: | |
| Online Access: | http://link.springer.com/article/10.1186/s12877-017-0645-7 |
| _version_ | 1818408870383452160 |
|---|---|
| author | Laura J. Anzaldi Ashwini Davison Cynthia M. Boyd Bruce Leff Hadi Kharrazi |
| author_facet | Laura J. Anzaldi Ashwini Davison Cynthia M. Boyd Bruce Leff Hadi Kharrazi |
| author_sort | Laura J. Anzaldi |
| collection | DOAJ |
| description | Abstract Background Geriatric 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. Methods We 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. Results Of 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. Conclusions Patients 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. |
| first_indexed | 2024-12-14T09:50:36Z |
| format | Article |
| id | doaj.art-b5147a7166704440b87147fd1c1e8245 |
| institution | Directory Open Access Journal |
| issn | 1471-2318 |
| language | English |
| last_indexed | 2024-12-14T09:50:36Z |
| publishDate | 2017-10-01 |
| publisher | BMC |
| record_format | Article |
| series | BMC Geriatrics |
| spelling | doaj.art-b5147a7166704440b87147fd1c1e82452022-12-21T23:07:32ZengBMCBMC Geriatrics1471-23182017-10-011711710.1186/s12877-017-0645-7Comparing clinician descriptions of frailty and geriatric syndromes using electronic health records: a retrospective cohort studyLaura J. Anzaldi0Ashwini Davison1Cynthia M. Boyd2Bruce Leff3Hadi Kharrazi4Department of General Internal Medicine, Johns Hopkins University School of MedicineDepartment of General Internal Medicine, Johns Hopkins University School of MedicineCenter for Transformative Geriatric Research, Division of Geriatric Medicine and Gerontology, Johns Hopkins University School of MedicineCenter for Transformative Geriatric Research, Division of Geriatric Medicine and Gerontology, Johns Hopkins University School of MedicineCenter for Population Health IT, Department of Health Policy and Management, Johns Hopkins Bloomberg School of Public HealthAbstract Background Geriatric 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. Methods We 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. Results Of 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. Conclusions Patients 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.http://link.springer.com/article/10.1186/s12877-017-0645-7FrailtyGeriatric syndromesElectronic health recordsUnstructured dataNatural language processing |
| spellingShingle | Laura J. Anzaldi Ashwini Davison Cynthia M. Boyd Bruce Leff Hadi Kharrazi Comparing clinician descriptions of frailty and geriatric syndromes using electronic health records: a retrospective cohort study BMC Geriatrics Frailty Geriatric syndromes Electronic health records Unstructured data Natural language processing |
| title | Comparing clinician descriptions of frailty and geriatric syndromes using electronic health records: a retrospective cohort study |
| title_full | Comparing clinician descriptions of frailty and geriatric syndromes using electronic health records: a retrospective cohort study |
| title_fullStr | Comparing clinician descriptions of frailty and geriatric syndromes using electronic health records: a retrospective cohort study |
| title_full_unstemmed | Comparing clinician descriptions of frailty and geriatric syndromes using electronic health records: a retrospective cohort study |
| title_short | Comparing clinician descriptions of frailty and geriatric syndromes using electronic health records: a retrospective cohort study |
| title_sort | comparing clinician descriptions of frailty and geriatric syndromes using electronic health records a retrospective cohort study |
| topic | Frailty Geriatric syndromes Electronic health records Unstructured data Natural language processing |
| url | http://link.springer.com/article/10.1186/s12877-017-0645-7 |
| work_keys_str_mv | AT laurajanzaldi comparingcliniciandescriptionsoffrailtyandgeriatricsyndromesusingelectronichealthrecordsaretrospectivecohortstudy AT ashwinidavison comparingcliniciandescriptionsoffrailtyandgeriatricsyndromesusingelectronichealthrecordsaretrospectivecohortstudy AT cynthiamboyd comparingcliniciandescriptionsoffrailtyandgeriatricsyndromesusingelectronichealthrecordsaretrospectivecohortstudy AT bruceleff comparingcliniciandescriptionsoffrailtyandgeriatricsyndromesusingelectronichealthrecordsaretrospectivecohortstudy AT hadikharrazi comparingcliniciandescriptionsoffrailtyandgeriatricsyndromesusingelectronichealthrecordsaretrospectivecohortstudy |