Immeasurable time bias due to hospitalization in medico-administrative databases: which impact for pharmacoepidemiological studies?

PurposeDrugs administered to hospitalized patients are not available within almost all health insurance databases. However, this unobservable exposure time bias is very rarely taken into account in pharmacoepidemiology. The objective was to model unobservable periods due to hospitalization and to assess their impact on risk estimates in the context of the association between benzodiazepines and mortality. MethodsA cohort study was identified using the General Sample of Beneficiaries in France for the period 2006-2012. Benzodiazepines incident users were matched to incident users of antidepressants/non-benzodiazepine sedatives and to controls (non-users) according to age and gender. All-cause mortality at 1year (Cox regression model) was studied using time-dependent variables (exposed/unexposed or under two hypotheses, inpatients are exposed or inpatients are unexposed), complemented with a multistate model based on observable/unobservable/death status. ResultsIn each group, 57242 patients were included. All-cause mortality was significantly higher among those exposed to benzodiazepines (adjusted hazard ratio (aHR)=1.17, 95% confidence interval (CI)=1.04, 1.32), as compared with controls. Use of benzodiazepines exposure as a time-dependent variable resulted in significant results after adjustment (aHR=1.45, 95%CI=1.16, 1.80). When inpatients were considered as unexposed, all-cause mortality was not significantly increased (aHR=0.85, 95%CI=0.76, 1.10), but was significantly augmented when inpatients were considered as exposed (aHR=2.93, 95%CI=2.46, 3.48). ConclusionsThis study highlights the need to take account of the impact of unobservable exposure periods on risk estimates. Copyright (c) 2017 John Wiley & Sons, Ltd.