Methodological framework to identify possible adverse drug reactions using population-based administrative data

Purpose: We present a framework for detecting possible adverse drug reactions (ADRs) using the Utah Medicaid administrative data. We examined four classes of ADRs associated with treatment of dementia by acetylcholinesterase inhibitors (AChEIs): known reactions (gastrointestinal, psychological disturbances), potential reactions (respiratory disturbance), novel reactions (hepatic, hematological disturbances), and death. Methods: Our cohort design linked drug utilization data to medical claims from Utah Medicaid recipients. We restricted the analysis to 50 years-old and older beneficiaries diagnosed with dementia-related diseases. We compared patients treated with AChEI to patients untreated with anti-dementia medication therapy. We attempted to remove confounding by establishing propensity-score-matched cohorts for each outcome investigated; we then evaluated the effects of drug treatment by conditional multivariable Cox-proportional-hazard regression. Acute and transient effects were evaluated by a crossover design using conditional logistic regression. Results: Propensity-matched analysis of expected reactions revealed that AChEI treatment was associated with gastrointestinal episodes (Hazard Ratio [HR]: 2.02; 95%CI: 1.28-3.2), but not psychological episodes, respiratory disturbance, or death. Among the unexpected reactions, the risk of hematological episodes was higher (HR: 2.32; 95%CI: 1.47-3.6) in patients exposed to AChEI. AChEI exposure was not associated with an increase in hepatic episodes. We also noted a trend, identified in the case-crossover design, toward increase odds of experiencing acute hematological events during AChEI exposure (Odds Ratio: 3.0; 95% CI: 0.97 - 9.3). Conclusions: We observed an expected association between AChEIs treatment and gastrointestinal disturbances and detected a signal of possible hematological ADR after treatment with AChEIs in this pilot study. Using this analytic framework may raise awareness of potential ADEs and generate hypotheses for future investigations. Early findings, or signal detection, are considered hypothesis generating since confirmatory studies must be designed to determine if the signal represents a true drug safety problem.