Abstract. The adoption of electronically formatted medical records, so called Electronic Health Records (EHRs), has become extremely important in healthcare systems to enable the exchange of medical information among stakeholders. An EHR generally consists of data with different types and sensitivity degrees which must be selectively shared based on the need-to-know principle. Security mechanis...

Clinical documentation using free text to describe a patient's medical status is an essential component of electronic health records (EHRs), and the quality of information in documents plays a critical role in clinical practice and translational research. Physicians are the primary creators of EHRs, but their clinical practices vary substantially, resulting in variations in clinical documentati...

Genomic medicine attempts to build individualized strategies for diagnostic or therapeutic decision-making by utilizing patients' genomic information. Big Data analytics uncovers hidden patterns, unknown correlations, and other insights through examining large-scale various data sets. While integration and manipulation of diverse genomic data and comprehensive electronic health records (EHRs) o...

In 2007, Canada Health Infoway surveyed Canadians’ attitudes toward electronic health records (EHRs). Among the significant findings was the fact that 88% of respondents endorsed “the idea” of EHRs. The main reasons for their support included a belief that EHRs would accelerate and improve the accuracy of diagnoses as well as reduce prescription errors (Canada Health Infoway 2007). “EHRs benefi...

Electronic health records (EHRs) provide timely access to millions of patient data records while limiting errors associated with manual data extraction. To demonstrate these advantages of EHRs to public health practice, we examine the ability of a EHR calculated blood-pressure (BP) measure to replicate seasonal variation as reported by prior studies that used manual data extraction. Our sample ...

Electronic health records (EHRs) are an emerging relational domain with large potential to improve clinical outcomes. We apply two statistical relational learning (SRL) algorithms to the task of predicting primary myocardial infarction. We show that one SRL algorithm, relational functional gradient boosting, outperforms propositional learners particularly in the medically-relevant high recall r...

The comparison of the patient's current medication list with the medication being ordered when admitted to Hospital, identifying omissions, duplications, dosing errors, and potential interactions, constitutes the core process of medicines reconciliation. Access to the medication the patient is taking at home could be unfeasible as this information is frequently stored in various locations and i...

Drug-drug interactions (DDI) account for 30% of all adverse drug reactions, which are the fourth leading cause of death in the US. Current methods for post marketing surveillance primarily use spontaneous reporting systems for learning DDI signals and validate their signals using the structured portions of Electronic Health Records (EHRs). We demonstrate a fast, annotation-based approach, which...

Health Records The United States is spending up to an unprecedented $30 billion on electronic health records (EHRs) through the 2009 Health Information Technology for Economic and Clinical Health Act, colloquially known as the federal meaningful use program (1). This is one of the largest public infrastructural investments made by the federal government in health care or any other industry (2)....

BACKGROUND Personalized medicine approaches provide opportunities for predictive and preventive medicine. Using genomic, clinical, environmental, and behavioral data, tracking and management of individual wellness is possible. A prolific way to carry this personalized approach into routine practices can be accomplished by integrating clinical interpretations of genomic variations into electroni...