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To assess the effect of a clinical decision support system (CDSS) integrated into an electronic health record (EHR) on antibiotic prescribing for acute respiratory infections (ARIs) in primary care.

To evaluate systems for estimating and preventing wrong-patient electronic orders in computerized physician order entry systems with a two-phase study.

The aim of this paper is to summarize concerns with the de-identification standard and methodologies established under the Health Insurance Portability and Accountability Act (HIPAA) regulations, and report some potential policies to address those concerns that were discussed at a recent workshop attended by industry, consumer, academic and research stakeholders.

To review the methods and dimensions of data quality assessment in the context of electronic health record (EHR) data reuse for research.

We explore relationships between health information seeking activities and engagement with healthcare professionals via a privacy-sensitive analysis of geo-tagged data from mobile devices.

To model the financial effects of implementing a hospital-wide electronic medical record (EMR) system in a tertiary facility in Malawi.

Ascertainment of potential subjects has been a longstanding problem in clinical research. Various methods have been proposed, including using data in electronic health records. However, these methods typically suffer from scaling effects-some methods work well for large cohorts; others work for small cohorts only.

The term informatics is currently enveloped in chaos. One way to clarify the meaning of informatics is to identify the competencies associated with training in the field, but this approach can conceal the whole that the competencies atomistically describe. This work takes a different approach by offering three higher-level visions of what characterizes the field, viewing informatics as: (1) cross-training between basic informational sciences and an application domain, (2) the [...]

In order for computers to extract useful information from unstructured text, a concept normalization system is needed to link relevant concepts in a text to sources that contain further information about the concept. Popular concept normalization tools in the biomedical field are dictionary-based. In this study we investigate the usefulness of natural language processing (NLP) as an adjunct to dictionary-based concept normalization.

We describe an approach for modeling temporal relationships in a large scale association analysis of electronic health record data. The addition of temporal information can inform hypothesis generation and help to explain the relationships. We applied this approach on a dataset containing 41.2 million time-stamped International Classification of Diseases, Ninth Revision (ICD-9) codes from 1.6 million patients.