Automated alerts and reminders targeting patients: A review of the literature.

Objective: Information technology supporting patient self-management has the potential to foster shared accountability for healthcare outcomes by improving patient adherence. There is growing interest in providing alerts and reminders to patients to improve healthcare self-management. This paper describes a literature review of automated alerts and reminders directed to patients, the technology used, and their efficacy.

Ginkgo and Warfarin Interaction in a Large Veterans Administration Population.

Ginkgo biloba is a widely used herbal product that could potentially have a severe interaction with warfarin, which is the most frequently prescribed anticoagulant agent in North America. Literature, however, provides conflicting evidence on the presence and severity of the interaction. In this study, we developed text processing methods to extract the ginkgo usage and combined it with prescription data on warfarin from a very large clinical data respository.

Identifying and Communicating Clinically Meaningful Drug-Drug Interactions.

Objective: Providing care to patients with comorbid medical problems may result in complicated, multiple drug therapy regimens, increasing the risk of clinically meaningful drug-drug interactions (DDIs). The purpose of this article is to describe the prevalence of DDIs and provide examples on how to identify and intervene on DDIs.

Methods: We described DDI data from the Utah Drug Regimen Review Center, where adult Medicaid patients were reviewed by pharmacists from 2005 to 2009.

Development of an Alert System to Detect Drug Interactions with Herbal Supplements using Medical Record Data.

While potential medication-to-medication interaction alerting engines exist in many clinical applications, few systems exist to automatically alert on potential medication to herbal supplement interactions. We have developed a preliminary knowledge base and rules alerting engine that detects 259 potential interactions between 9 supplements, 62 cardiac medications, and 19 drug classes. The rules engine takes into consideration 12 patient risk factors and 30 interaction warning signs to help determine which of three different alert levels to categorize each potential interaction.