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We aimed to explore stakeholder views, attitudes, needs, and expectations regarding likely benefits and risks resulting from increased structuring and coding of clinical information within electronic health records (EHRs).

Large amounts of personal health data are being collected and made available through existing and emerging technological media and tools. While use of these data has significant potential to facilitate research, improve quality of care for individuals and populations, and reduce healthcare costs, many policy-related issues must be addressed before their full value can be realized. These include the need for widely agreed-on data stewardship principles and effective approaches to [...]

Electronic prescribing is increasingly used, in part because of government incentives for its use. Many of its benefits come from clinical decision support (CDS), but often too many alerts are displayed, resulting in alert fatigue.

To evaluate a proposed natural language processing (NLP) and machine-learning based automated method to risk stratify abdominal pain patients by analyzing the content of the electronic health record (EHR).

To study the relation between electronic health record (EHR) variables and healthcare process events.

Celiac disease (CD) is a lifelong immune-mediated disease with excess mortality. Early diagnosis is important to minimize disease symptoms, complications, and consumption of healthcare resources. Most patients remain undiagnosed. We developed two electronic medical record (EMR)-based algorithms to identify patients at high risk of CD and in need of CD screening.

The secondary use of electronic healthcare records (EHRs) often requires the identification of patient cohorts. In this context, an important problem is the heterogeneity of clinical data sources, which can be overcome with the combined use of standardized information models, virtual health records, and semantic technologies, since each of them contributes to solving aspects related to the semantic interoperability of EHR data.

Over 8 years, we have developed an innovative computer decision support system that improves appropriate delivery of pediatric screening and care. This system employs a guidelines evaluation engine using data from the electronic health record (EHR) and input from patients and caregivers. Because guideline recommendations typically exceed the scope of one visit, the engine uses a static prioritization scheme to select recommendations. Here we extend an earlier idea to create [...]