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Controlling for Frailty in Pharmacoepidemiologic Studies of Older Adults: Validation of an Existing Medicare Claims-based Algorithm.

TitleControlling for Frailty in Pharmacoepidemiologic Studies of Older Adults: Validation of an Existing Medicare Claims-based Algorithm.
Publication TypeJournal Article
Year of Publication2018
AuthorsCuthbertson CC, Kucharska-Newton AMaria, Faurot KR, Sturmer T, Funk MJonsson, Palta P, B Windham G, Thai S
Secondary AuthorsLund JL
JournalEpidemiology
Volume29
Issue4
Pagination556-561
Date Published2018 07
ISSN1531-5487
KeywordsActivities of Daily Living, Aged, Aged, 80 and over, Algorithms, Comparative Effectiveness Research, Confounding Factors, Epidemiologic, Female, Frailty, Humans, Insurance Claim Review, Male, Medicare, Pharmacoepidemiology, United States
Abstract

BACKGROUND: Frailty is a geriatric syndrome characterized by weakness and weight loss and is associated with adverse health outcomes. It is often an unmeasured confounder in pharmacoepidemiologic and comparative effectiveness studies using administrative claims data.

METHODS: Among the Atherosclerosis Risk in Communities (ARIC) Study Visit 5 participants (2011-2013; n = 3,146), we conducted a validation study to compare a Medicare claims-based algorithm of dependency in activities of daily living (or dependency) developed as a proxy for frailty with a reference standard measure of phenotypic frailty. We applied the algorithm to the ARIC participants' claims data to generate a predicted probability of dependency. Using the claims-based algorithm, we estimated the C-statistic for predicting phenotypic frailty. We further categorized participants by their predicted probability of dependency (

RESULTS: The claims-based algorithm showed good discrimination of phenotypic frailty (C-statistic = 0.71; 95% confidence interval [CI] = 0.67, 0.74). Participants classified with a high predicted probability of dependency (≥20%) had higher prevalence of falls and difficulty in physical ability, and a greater risk of 1-year all-cause mortality (hazard ratio = 5.7 [95% CI = 2.5, 13]) than participants classified with a low predicted probability (

CONCLUSIONS: The Medicare claims-based algorithm showed good discrimination of phenotypic frailty and high predictive ability with adverse health outcomes. This algorithm can be used in future Medicare claims analyses to reduce confounding by frailty and improve study validity.

DOI10.1097/EDE.0000000000000833
Alternate JournalEpidemiology
PubMed ID29621057
PubMed Central IDPMC5980766
Grant ListK12 CA120780 / CA / NCI NIH HHS / United States
HHSN268201100012C / HL / NHLBI NIH HHS / United States
HHSN268201100009I / HL / NHLBI NIH HHS / United States
UL1 TR001111 / TR / NCATS NIH HHS / United States
HHSN268201100010C / HL / NHLBI NIH HHS / United States
HHSN268201100008C / HL / NHLBI NIH HHS / United States
HHSN268201100005G / HL / NHLBI NIH HHS / United States
HHSN268201100008I / HL / NHLBI NIH HHS / United States
HHSN268201100007C / HL / NHLBI NIH HHS / United States
R01 HL118255 / HL / NHLBI NIH HHS / United States
HHSN268201100011I / HL / NHLBI NIH HHS / United States
HHSN268201100011C / HL / NHLBI NIH HHS / United States
R01 AG023178 / AG / NIA NIH HHS / United States
HHSN268201100006C / HL / NHLBI NIH HHS / United States
HHSN268201100005I / HL / NHLBI NIH HHS / United States
R21 HD080214 / HD / NICHD NIH HHS / United States
R56 AG023178 / AG / NIA NIH HHS / United States
HHSN268201100009C / HL / NHLBI NIH HHS / United States
HHSN268201100005C / HL / NHLBI NIH HHS / United States
R01 CA174453 / CA / NCI NIH HHS / United States
HHSN268201100007I / HL / NHLBI NIH HHS / United States
R01 AG056479 / AG / NIA NIH HHS / United States
T32 HL007055 / HL / NHLBI NIH HHS / United States
K99 AG052830 / AG / NIA NIH HHS / United States