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Phenotyping algorithms applied to electronic health record (EHR) data enable investigators to identify large cohorts for clinical and genomic research. Algorithm development is often iterative, depends on fallible investigator intuition, and is time- and labor-intensive. We developed and evaluated 4 types of phenotyping algorithms and categories of EHR information to identify hypertensive individuals and controls and provide a portable module for implementation at other sites.

As EHR adoption in US hospitals becomes ubiquitous, a wide range of IT options are theoretically available to facilitate physician-nurse communication, but we know little about the adoption rate of specific technologies or the impact of their use.

To understand and build a collective vision of all existing institutions in the Portuguese National Health Service as well as to perceive how and how far the interaction between those multiple institutions is supported by Information Systems (IS).

Approximately one fifth of school-aged children spend a significant portion of their year at residential summer camp, and a growing number have chronic medical conditions. Camp health records are essential for safe, efficient care and for transitions between camp and home providers, yet little research exists regarding these systems.

Spending on pharmaceuticals in the US reached $373.9 billion in 2014. Therapeutic interchange offers potential medication cost savings by replacing a prescribed drug for an equally efficacious therapeutic alternative.

EHR systems have high potential to improve healthcare delivery and management. Although structured EHR data generates information in machine-readable formats, their use for decision support still poses technical challenges for researchers due to the need to preprocess and convert data into a matrix format. During our research, we observed that clinical informatics literature does not provide guidance for researchers on how to build this matrix while avoiding potential pitfalls.

Hypertension or high blood pressure is on the rise. Not only does it affect the elderly but is also increasingly spreading to younger sectors of the population. Treating this condition involves exhaustive monitoring of patients. The current mobile health services can be improved to perform this task more effectively.

We aimed to determine the characteristics of quantitative metrics for nursing narratives documented in electronic nursing records and their association with hospital admission traits and diagnoses in a large data set not limited to specific patient events or hypotheses.