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To evaluate the benefit of a health information exchange (HIE) between hospitals, we examine the rate of crossover among neurosurgical inpatients treated at Emory University Hospital (EUH) and Grady Memorial Hospital (GMH) in Atlanta, Georgia. To inform decisions regarding investment in HIE, we develop a methodology analyzing crossover behavior for application to larger more general patient populations.

To assess intensive care unit (ICU) nurses' acceptance of electronic health records (EHR) technology and examine the relationship between EHR design, implementation factors, and nurse acceptance.

Health-information exchange, that is, enabling the interoperability of automated health data, can facilitate important improvements in healthcare quality and efficiency. A vision of interoperability and its benefits was articulated more than a decade ago. Since then, important advances toward the goal have been made. The advent of the Health Information Technology for Economic and Clinical Health Act and the meaningful use program is already having a significant impact on the [...]

To understand how the source of information affects different adverse event (AE) surveillance methods.

Predicting patient outcomes from genome-wide measurements holds significant promise for improving clinical care. The large number of measurements (eg, single nucleotide polymorphisms (SNPs)), however, makes this task computationally challenging. This paper evaluates the performance of an algorithm that predicts patient outcomes from genome-wide data by efficiently model averaging over an exponential number of naive Bayes (NB) models.

We have reported that implementation of an electronic health record (EHR) based quality improvement system that included point-of-care electronic reminders accelerated improvement in performance for multiple measures of chronic disease care and preventive care during a 1-year period. This study examined whether providing pre-visit paper quality reminders could further improve performance, especially for physicians whose performance had not improved much during the first year.

Open-source clinical natural-language-processing (NLP) systems have lowered the barrier to the development of effective clinical document classification systems. Clinical natural-language-processing systems annotate the syntax and semantics of clinical text; however, feature extraction and representation for document classification pose technical challenges.

We developed an accurate and valid medication order algorithm to identify from electronic health records the definitive medication order intended for dispensing and applied this process to identify a cohort of patients and to stratify them into one of three medication adherence groups: early non-persistence, primary non-adherence, or ongoing adherence. We identified medication order data from electronic health record tables, obtained the orders, and linked the orders to dispensings. These [...]

This paper describes the approaches the authors developed while participating in the i2b2/VA 2010 challenge to automatically extract medical concepts and annotate assertions on concepts and relations between concepts.