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Describe the change in mobile technology used by an urban Latino population between 2011 and 2014, and compare findings with national estimates.

To examine whether patients invited to review their clinicians' notes continue to access them and to assess the impact of reminders on whether patients continued to view notes.

Develop and evaluate an automated identification and predictive risk report for hospitalized heart failure (HF) patients.

Reinventing data extraction from electronic health records (EHRs) to meet new analytical needs is slow and expensive. However, each new data research network that wishes to support its own analytics tends to develop its own data model. Joining these different networks without new data extraction, transform, and load (ETL) processes can reduce the time and expense needed to participate. The Informatics for Integrating Biology and the Bedside (i2b2) project supports [...]

We sought to assess the potential of a widely available source of electronic medication data to prevent medication history errors and resultant inpatient order errors.

A software tool is developed to facilitate data entry and to monitor research projects in under-resourced countries in real-time.

A fundamental challenge in the field of clinical decision support is to determine what characteristics of systems make them effective in supporting particular types of clinical decisions. However, we lack such a theory of decision support itself and a model to describe clinical decisions and the systems to support them. This article outlines such a framework. We present a two-stream model of information flow within clinical decision-support systems (CDSSs): reasoning [...]

Experts suggest that formulary alerts at the time of medication order entry are the most effective form of clinical decision support to automate formulary management.

In early 2010, Harvard Medical School and Boston Children's Hospital began an interoperability project with the distinctive goal of developing a platform to enable medical applications to be written once and run unmodified across different healthcare IT systems. The project was called Substitutable Medical Applications and Reusable Technologies (SMART).

Natural language processing methods for medical auto-coding, or automatic generation of medical billing codes from electronic health records, generally assign each code independently of the others. They may thus assign codes for closely related procedures or diagnoses to the same document, even when they do not tend to occur together in practice, simply because the right choice can be difficult to infer from the clinical narrative.