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Measuring Frailty in Health Care Databases for Clinical Care and Research

Considering the increasing burden and serious consequences of frailty in aging populations, there is increasing interest in measuring frailty in health care databases for clinical care and research. This review synthesizes the latest research on the development and application of 21 frailty measures...

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Autor principal: Kim, Dae Hyun
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Korean Geriatrics Society 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7370795/
https://www.ncbi.nlm.nih.gov/pubmed/32743326
http://dx.doi.org/10.4235/agmr.20.0002
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author Kim, Dae Hyun
author_facet Kim, Dae Hyun
author_sort Kim, Dae Hyun
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description Considering the increasing burden and serious consequences of frailty in aging populations, there is increasing interest in measuring frailty in health care databases for clinical care and research. This review synthesizes the latest research on the development and application of 21 frailty measures for health care databases. Frailty measures varied widely in terms of target population (16 ambulatory, 1 long-term care, and 4 inpatient), data source (16 claims-based and 5 electronic health records [EHR]-based measures), assessment period (6 months to 36 months), data types (diagnosis codes required for 17 measures, health service codes for 7 measures, pharmacy data for 4 measures, and other information for 9 measures), and outcomes for validation (clinical frailty for 7 measures, disability for 7 measures, and mortality for 16 measures). These frailty measures may be useful to facilitate frailty screening in clinical care and quantify frailty for large database research in which clinical assessment is not feasible.
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spelling pubmed-73707952020-07-30 Measuring Frailty in Health Care Databases for Clinical Care and Research Kim, Dae Hyun Ann Geriatr Med Res Invited Review Considering the increasing burden and serious consequences of frailty in aging populations, there is increasing interest in measuring frailty in health care databases for clinical care and research. This review synthesizes the latest research on the development and application of 21 frailty measures for health care databases. Frailty measures varied widely in terms of target population (16 ambulatory, 1 long-term care, and 4 inpatient), data source (16 claims-based and 5 electronic health records [EHR]-based measures), assessment period (6 months to 36 months), data types (diagnosis codes required for 17 measures, health service codes for 7 measures, pharmacy data for 4 measures, and other information for 9 measures), and outcomes for validation (clinical frailty for 7 measures, disability for 7 measures, and mortality for 16 measures). These frailty measures may be useful to facilitate frailty screening in clinical care and quantify frailty for large database research in which clinical assessment is not feasible. Korean Geriatrics Society 2020-06 2020-04-03 /pmc/articles/PMC7370795/ /pubmed/32743326 http://dx.doi.org/10.4235/agmr.20.0002 Text en Copyright © 2020 Korean Geriatrics Society This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Invited Review
Kim, Dae Hyun
Measuring Frailty in Health Care Databases for Clinical Care and Research
title Measuring Frailty in Health Care Databases for Clinical Care and Research
title_full Measuring Frailty in Health Care Databases for Clinical Care and Research
title_fullStr Measuring Frailty in Health Care Databases for Clinical Care and Research
title_full_unstemmed Measuring Frailty in Health Care Databases for Clinical Care and Research
title_short Measuring Frailty in Health Care Databases for Clinical Care and Research
title_sort measuring frailty in health care databases for clinical care and research
topic Invited Review
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7370795/
https://www.ncbi.nlm.nih.gov/pubmed/32743326
http://dx.doi.org/10.4235/agmr.20.0002
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