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Medication errors in hospitals are common, expensive, and sometimes harmful to patients. This study's objective was to derive a nationally representative estimate of medication error reduction in hospitals attributable to electronic prescribing through computerized provider order entry (CPOE) systems.

A sizable fraction of patients experiences adverse drug events or lack of drug efficacy. A part of this variability in drug response can be explained by genetic differences between patients. However, pharmacogenomic data as well as computational clinical decision support systems for interpreting such data are still unavailable in most healthcare settings. We address this problem by introducing the medicine safety code (MSC), which captures compressed pharmacogenomic data in a [...]

Privacy-preserving data publishing addresses the problem of disclosing sensitive data when mining for useful information. Among existing privacy models, ε-differential privacy provides one of the strongest privacy guarantees and makes no assumptions about an adversary's background knowledge. All existing solutions that ensure ε-differential privacy handle the problem of disclosing relational and set-valued data in a privacy-preserving manner separately. In this paper, we propose an algorithm that considers both relational and [...]

To explore the applicability of a syndromic surveillance method to the early detection of health information technology (HIT) system failures.

This paper summarizes much of the research that is applicable to the design of auditory alarms in a medical context. It also summarizes research that demonstrates that false alarm rates are unacceptably high, meaning that the proper application of auditory alarm design principles are compromised.

The internet is increasingly being used to conduct randomized controlled trials (RCTs). Knowledge of the types of interventions evaluated and the methodological quality of these trials could inform decisions about whether to conduct future trials using conventional methods, fully online or a mixture of the two.

The increasing availability of clinical data from electronic medical records (EMRs) has created opportunities for secondary uses of health information. When used in machine learning classification, many data features must first be transformed by discretization.

To summarize the literature describing computer-based interventions aimed at improving bidirectional communication between clinical and public health.

To determine whether indication-based computer order entry alerts intercept wrong-patient medication errors.