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Electronic health records (EHRs) are an increasingly common data source for clinical risk prediction, presenting both unique analytic opportunities and challenges. We sought to evaluate the current state of EHR based risk prediction modeling through a systematic review of clinical prediction studies using EHR data.

The purpose of this study was to measure the number of repeat computed tomography (CT) scans performed across an established health information exchange (HIE) in New York City. The long-term objective is to build an HIE-based duplicate CT alerting system to reduce potentially avoidable duplicate CTs.

To reduce wasteful ordering of rare 1,25-OH vitamin D lab tests through use of a noninterruptive decision support tool.

To provide a report on year 1 results of a national study investigating nursing home information technology (IT) adoption, called IT sophistication.

The adoption of electronic health records (EHRs) across the United States has impacted the methods by which health care professionals care for their patients. It is not always recognized, however, that pharmacists also actively use advanced functionality within the EHR. As critical members of the health care team, pharmacists utilize many different features of the EHR. The literature focuses on 3 main roles: documentation, medication reconciliation, and patient evaluation and [...]

Event notifications are real-time, electronic, automatic alerts to providers of their patients' health care encounters at other facilities. Our objective was to examine the effects of organizational capability and related social/organizational issues upon users' perceptions of the impact of event notifications on quality, efficiency, and satisfaction.

Electronic health records (EHRs) are a resource for "big data" analytics, containing a variety of data elements. We investigate how different categories of information contribute to prediction of mortality over different time horizons among patients undergoing hemodialysis treatment.

This paper outlines the implementation of a comprehensive clinical pharmacogenomics (PGx) service within a pediatric teaching hospital and the integration of clinical decision support in the electronic health record (EHR).

Assess parent use and perceptions of an inpatient portal application on a tablet computer that provides information about a child's hospital stay.

Inductive machine learning, and in particular extraction of association rules from data, has been successfully used in multiple application domains, such as market basket analysis, disease prognosis, fraud detection, and protein sequencing. The appeal of rule extraction techniques stems from their ability to handle intricate problems yet produce models based on rules that can be comprehended by humans, and are therefore more transparent. Human comprehension is a factor that may [...]