An electronic patient risk communication board.

Communication failures have been identified as the root cause of the majority of medical malpractice claims and patient safety violations. We believe it is essential to share key patient risk information with healthcare team members at the patient's bedside. In this study, we developed an electronic Patient Risk Communication Board (ePRCB) to assist in bridging the communication gap between all health care team members. The goal of the ePRCB is to effectively communicate the patient's key risk factors, such as a fall risk or risk of aspiration, to the healthcare team and to reduce adverse events caused by communication failures. The ePRCB will transmit patient risk information and tailored interventions with easy-to-understand icons on an LCD screen at the point of care. A set of patient risk reminder icons was developed and validated by focus groups. We used the results of the evaluation to refine the icons for the ePRCB.

Identification of inactive medications in narrative medical text.

Discontinued medications are frequently not removed from EMR medication lists - a patient safety risk. We developed an algorithm to identify inactive medications using in the text of narrative notes in the EMR. The algorithm was evaluated against manual review of 297 randomly selected notes. One in five notes documented inactive medications. Sensitivity and precision of 87.7% and 80.7%, respectively, on per-note basis and 66.3% and 80.0%, respectively, on per-medication basis. When medication names missing from the dictionary were excluded, the algorithm achieved sensitivity of 91.4%. Using real clinical data, the algorithm identified inactive medications documented in the note but still listed as active on the patients medication list in more than one in ten notes. Documentation of inactive medications is common in narrative provider notes and can be computationally extracted. This technology could be employed in real-time patient care as well as for research and quality of care monitoring.

Identification of inactive medications in narrative physician notes.

Information about inactive medications is important for patient safety but is frequently missing from the electronic medical record. We investigated the feasibility of extracting this information from narrative physician notes. Our analysis of 298 physician notes showed that 1 in 3 notes contains documentation of medication discontinuation. This documentation can be described by one of six semantic fields. Documentation of inactive medications is common in narrative documents and could potentially be extracted using semantic analysis.