Title |
Methodologic framework to identify possible adverse drug reactions using population-based administrative data |
Publication Type |
thesis |
School or College |
School of Medicine |
Department |
Biomedical Informatics |
Author |
Sauer, Brian C. |
Date |
2010-05 |
Description |
We present a framework for detecting possible adverse drug reactions (ADRs) using 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. Our cohort design linked drug utilization data to medical claims from Utah Medicaid recipients. We restricted the analysis to beneficiaries 50 years and older who had a dementia-related diagnosis. We compared patients treated with AChEIs to patients untreated with antidementia medication therapy. We attempted to remove confounding by establishing propensity-score-matched cohorts for each outcome investigated; we then evaluated 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. Propensity-matched analysis of expected reactions found that AChEI treatment was associated with gastrointestinal episodes (hazards ratio [HR]: 2.02; 95% confidence interval [CI]: 1.28-3.2) but not psychological episodes, respiratory disturbance, or death. Among the tested unexpected reactions, the risk was higher with hematological episodes (HR: 2.32; 95% CI: 1.47-3.6) but not hepatic episodes. We also noted a trend towards an increase in the odds of experiencing acute hematological events in the treated group (odds ratio [OR]: 3.0; 95% CI: 0.97-9.3). We observed an expected association between AChEIs and gastrointestinal disturbances and detected a signal of hematological adverse drug events (ADEs) after treatment with AChEIs in this pilot study. Using our analytic framework may raise awareness of potential ADEs and generate hypotheses for future investigations. |
Type |
Text |
Publisher |
University of Utah |
Subject |
Drugs - Side effects; Drugs - Side effects - Data processing; Medical informatics |
Subject MESH |
Adverse Drug Reaction Reporting Systems; Cholinesterase Inhibitors; Drug Toxicity; Regression Analysis |
Dissertation Institution |
University of Utah |
Dissertation Name |
Master of Science |
Language |
eng |
Relation is Version of |
Digital reproduction of "Methodologic framework to identify possible adverse reactions using population-based administrative data." Spencer S. Eccles Health Sciences Library. Print version of "Methodological framework to identify possible adverse reactions using population-based administrative data." available at J. Willard Marriott Library Special Collection. |
Rights Management |
© Brian C. Sauer |
Format |
application/pdf |
Format Medium |
application/pdf |
Format Extent |
8,517,722 bytes |
Identifier |
etd2/id/1106 |
Source |
Original: University of Utah Spencer S. Eccles Health Sciences Library |
Conversion Specifications |
Original scanned on Fujitsu fi-5220G as 400 dpi to pdf using ABBYY FineReader 10 |
ARK |
ark:/87278/s6vq3h8f |
Setname |
ir_etd |
ID |
193153 |
Reference URL |
https://collections.lib.utah.edu/ark:/87278/s6vq3h8f |