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Comparison of Instrumental Variable Analysis Using a New Instrument With Risk Adjustment Methods to Reduce Confounding by Indication
Author(s) -
Gang Fang,
John M. Brooks,
Elizabeth A. Chrischilles
Publication year - 2012
Publication title -
american journal of epidemiology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.33
H-Index - 256
eISSN - 1476-6256
pISSN - 0002-9262
DOI - 10.1093/aje/kwr448
Subject(s) - medicine , confounding , propensity score matching , exacerbation , observational study , asthma , medicaid , instrumental variable , marginal structural model , multivariate statistics , randomized controlled trial , multivariate analysis , intensive care medicine , statistics , health care , mathematics , economics , economic growth
Confounding by indication is a vexing problem, especially in evaluating treatment effects using observational data, since treatment decisions are often related to disease severity, prognosis, and frailty. To compare the ability of the instrumental variable (IV) approach with a new instrument based on the local-area practice style and risk adjustment methods, including conventional multivariate regression and propensity score adjustment, to reduce confounding by indication, the authors investigated the effects of long-term control (LTC) therapy on the occurrence of acute asthma exacerbation events among children and young adults with incident and uncontrolled persistent asthma, using Iowa Medicaid claims files from 1997-1999. Established evidence from clinical trials has demonstrated the protective benefits of LTC therapy for persistent asthma. Among patients identified (n = 4,275), those with higher asthma severity at baseline were more likely to receive LTC therapy. The multivariate regression and propensity score adjustment methods suggested that LTC therapy had no effect on the occurrence of acute exacerbation events. Estimates from the new IV approach showed that LTC therapy significantly decreased the occurrence of acute exacerbation events, which is consistent with established clinical evidence. The authors discuss how to interpret estimates from the risk adjustment and IV methods when the treatment effect is heterogeneous.

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