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Clinical genome and exome sequencing can diagnose pediatric patients with complex conditions that often require follow-up care with multiple specialties. The American Academy of Pediatrics emphasizes the role of the medical home and the primary care pediatrician in coordinating care for patients who need multidisciplinary support. In addition, the electronic health record (EHR) with embedded clinical decision support is recognized as an important component in providing care in this setting [...]

Comorbidity adjustment is often performed during outcomes and health care resource utilization research. Our goal was to develop an efficient algorithm in structured query language (SQL) to determine the Elixhauser comorbidity index.

To investigate time differences in recording observations and an early warning score using traditional paper charts and a novel e-Obs system in clinical practice.

It is increasingly recognized that some patients self-manage in the context of social networks rather than alone. Consumer health information technology (IT) designed to support socially embedded self-management must be responsive to patients' everyday communication practices. There is an opportunity to improve consumer health IT design by explicating how patients currently leverage social media to support health information communication.

Large and readily-available clinical datasets combined with improved computational resources have permitted the exploration of many new research and clinical questions. Predictive analytics, especially for adverse events, has surfaced as one promising application of big data, and although statistical results can be highly accurate, little is known about how nurses perceive this new information and how they might act upon it.

Social media is an important pharmacovigilance data source for adverse drug reaction (ADR) identification. Human review of social media data is infeasible due to data quantity, thus natural language processing techniques are necessary. Social media includes informal vocabulary and irregular grammar, which challenge natural language processing methods. Our objective is to develop a scalable, deep-learning approach that exceeds state-of-the-art ADR detection performance in social media.

Despite federal policies put in place by the Office of the National Coordinator (ONC) to promote safe and usable electronic health record (EHR) products, the usability of EHRs continues to frustrate providers and have patient safety implications. This study sought to compare government policies on usability and safety, and methods of examining compliance to those policies, across 3 federal agencies: the ONC and EHRs, the Federal Aviation Administration (FAA) and [...]

To examine, using a smartphone application, whether mood is related to daily movement patterns in pregnant women at risk for perinatal depression.

To better understand clinician information needs and learning opportunities by exploring the use of best-practice algorithms across different training levels and specialties.

Nationwide initiatives have promoted greater adoption of health information technology as a means to reduce adverse drug events (ADEs). Hospital adoption of electronic health records with Meaningful Use (MU) capabilities expected to improve medication safety has grown rapidly. However, evidence that MU capabilities are associated with declines in in-hospital ADEs is lacking.