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Surveillance for surgical site infections (SSIs) after ambulatory surgery in children requires a detailed manual chart review to assess criteria defined by the National Health and Safety Network (NHSN). Electronic health records (EHRs) impose an inefficient search process where infection preventionists must manually review every postsurgical encounter ( 30 days). Using text mining and business intelligence software, we developed an information foraging application, the SSI Workbench, to visually present which [...]

Clinician progress notes are an important record for care and communication, but there is a perception that electronic notes take too long to write and may not accurately reflect the patient encounter, threatening quality of care. Automatic speech recognition (ASR) has the potential to improve clinical documentation process; however, ASR inaccuracy and editing time are barriers to wider use. We hypothesized that automatic text processing technologies could decrease editing time [...]

Legislation aimed at increasing the use of a health information exchange (HIE) in healthcare has excluded long-term care facilities, resulting in a vulnerable patient population that can benefit from the improvement of communication and reduction of waste.

We describe a scalable platform for research-oriented analyses of routine data in hospitals, which evolved from a state-of-the-art business intelligence architecture for enterprise resource planning. This platform involves an in-memory database management system for data modeling and analytics and a high-performance cluster for more computing-intensive analytical tasks. Setting up platforms for research-oriented analyses is a highly dynamic, time-consuming, and costly process. In some health care institutions, effective research platforms may [...]

There are an ever-increasing number of reports and commentaries that describe the challenges and opportunities associated with the use of big data and data science (DS) in the context of biomedical education, research, and practice. These publications argue that there are substantial benefits resulting from the use of data-centric approaches to solve complex biomedical problems, including an acceleration in the rate of scientific discovery, improved clinical decision making, and the [...]

Hospitalized patients often receive opioids. There is a lack of consensus regarding evidence-based guidelines or training programs for effective management of pain in the hospital. We investigated the viability of using an Internet-based opioid dosing simulator to teach residents appropriate use of opioids to treat and manage acute pain.

Drug-drug interaction (DDI) alerts are often implemented in the hospital computerized provider order entry (CPOE) systems with limited evaluation. This increases the risk of prescribers experiencing too many irrelevant alerts, resulting in alert fatigue. In this study, we aimed to evaluate clinical relevance of alerts prior to implementation in CPOE using two common approaches: compendia and expert panel review.

Traditionally, summarization of research themes and trends within a given discipline was accomplished by manual review of scientific works in the field. However, with the ushering in of the age of "big data," new methods for discovery of such information become necessary as traditional techniques become increasingly difficult to apply due to the exponential growth of document repositories. Our objectives are to develop a pipeline for unsupervised theme extraction and [...]

We explored how judgements provided by physicians can be used to learn relevance models that enhance the quality of patient cohorts retrieved from Electronic Health Records (EHRs) collections.