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Research
Methods for Medication Error Report Databases Our work is
motivated by the United States Pharmacopoeia's MEDMARX ® database,
a national, internet-accessible database of medication error reports.
The primary aim of my thesis research will be to develop statistical
methodology to extract useful information from medication error
reporting systems such as MEDMARX. Identifying the types and root
causes of error is crucial to implementing interventions to reduce
error, but no general statistical framework exists for making
inference on these variables. As a means to that end we have begun by
developing methodology to evaluate the causal continuumn hypothesis
with respect to medication errors and quantify the evidence and
uncertainty for this hypothesis in the MEDMARX database. The causal
continuum hypothesis states that the causes and contributing factors
of error that frequently lead to near-misses (errors that do not
result in patient harm) are the same as the causes and contributing
factors that frequently lead to adverse events (errors that do result
in patient harm). This work is being conducted with Laura
Morlock of the Department of Health Policy and Management and Francesca Dominici.
Optimal Propensity Score Stratification Tom Louis and I have
been investigating the optimal way to choose strata in a stratified
propensity score analysis of bivariate treatment effect as a function
of the amount of imbalance in propensity between the two groups. We
are considering a strata to be optimal if it produces an effect
estimate with minimum MSE.
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