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The objective of this project was to use statistical techniques to determine the completeness and accuracy of data migrated during electronic health record conversion.

To systematically review studies assessing the effects of health information technology (health IT) on patient safety outcomes.

Quantitative Structure-Activity Relationship (QSAR) models can predict adverse drug reactions (ADRs), and thus provide early warnings of potential hazards. Timely identification of potential safety concerns could protect patients and aid early diagnosis of ADRs among the exposed. Our objective was to determine whether global spontaneous reporting patterns might allow chemical substructures associated with Stevens-Johnson Syndrome (SJS) to be identified and utilized for ADR prediction by QSAR models.

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.

Quantify the variability of patients' problem lists - in terms of the number, type, and ordering of problems - across multiple physicians and assess physicians' criteria for organizing and ranking diagnoses.

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

Patients in intensive care units (ICUs) may lack decisional capacity and may depend on proxy decision makers (PDMs) to make medical decisions on their behalf. High-quality information-sharing with PDMs, including through such means as health information technology, could improve communication and decision making and could potentially minimize the psychological consequences of an ICU stay for both patients and their family members. However, alongside these anticipated benefits of information-sharing are risks [...]

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.

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).