Ontology highlight
ABSTRACT: Objective
To examine the effects of potentially inappropriate medication (PIM) use on health care outcomes in elderly individuals using an instrumental variable (IV) approach.Data sources/study setting
Representative claim data from the universal health insurance program in Taiwan from 2007 to 2010.Study design
We employed a panel study design to examine the relationship between PIM and hospitalization. We applied both the naive generalized estimating equation (GEE) model, which controlled for the observed patient and hospital characteristics, and the two-stage residual inclusion (2SRI) GEE model, which further accounted for the unobserved confounding factors. The PIM prescription rate of the physician most frequently visited by each patient was used as the IV.Principal findings
The naive GEE models indicated that patient PIM use was associated with a higher likelihood of hospitalization (odds ratio [OR], 1.399; 95 percent confidence interval [CI], 1.363-1.435). Using the physician PIM prescribing rate as an IV, we identified a stronger significant association between PIM and hospitalization (OR, 1.990; 95 percent CI, 1.647-2.403).Conclusions
PIM use is associated with increased hospitalization in elderly individuals. Adjusting for unobserved confounders is needed to obtain unbiased estimates of the relationship between PIM and health care outcomes.
SUBMITTER: Chen CC
PROVIDER: S-EPMC4946035 | biostudies-literature | 2016 Aug
REPOSITORIES: biostudies-literature
Chen Chi-Chen CC Cheng Shou-Hsia SH
Health services research 20151125 4
<h4>Objective</h4>To examine the effects of potentially inappropriate medication (PIM) use on health care outcomes in elderly individuals using an instrumental variable (IV) approach.<h4>Data sources/study setting</h4>Representative claim data from the universal health insurance program in Taiwan from 2007 to 2010.<h4>Study design</h4>We employed a panel study design to examine the relationship between PIM and hospitalization. We applied both the naive generalized estimating equation (GEE) model ...[more]