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A key challenge in clinical data mining is that most clinical datasets contain missing data. Since many commonly used machine learning algorithms require complete datasets (no missing data), clinical analytic approaches often entail an imputation procedure to "fill in" missing data. However, although most clinical datasets contain a temporal component, most commonly used imputation methods do not adequately accommodate longitudinal time-based data. We sought to develop a new imputation algorithm [...]

Electronic pharmacovigilance reporting systems are being implemented in many developing countries in an effort to improve reporting rates. This study sought to establish the factors that acted as barriers to the success of an electronic pharmacovigilance reporting system in Kenya 3 years after its implementation.

We assessed changes in the percentage of providers with positive perceptions of electronic health record (EHR) benefit before and after transition from a local basic to a commercial comprehensive EHR.

To describe a new, comprehensive process model of clinical information interaction in primary care (Clinical Information Interaction Model, or CIIM) based on a systematic synthesis of published research.

To reduce the risk of wrong-patient errors, safety experts recommend allowing only one patient chart to be open at a time. Due to the lack of empirical evidence, the number of allowable open charts is often based on anecdotal evidence or institutional preference, and hence varies across institutions. Using an interrupted time series analysis of intercepted wrong-patient medication orders in an emergency department during 2010-2016 (83.6 intercepted wrong-patient events per [...]

To develop a comprehensive value set for documenting and encoding adverse reactions in the allergy module of an electronic health record.

The federal electronic health record (EHR) certification process was intended to ensure a baseline level of system quality and the ability to support meaningful use criteria. We sought to assess whether there was variation across EHR vendors in the degree to which hospitals using products from those vendors were able to achieve high levels of performance on meaningful use criteria.

Demonstrate how observational causal inference methods can generate insights into the impact of chronic disease combinations on patients' 30-day hospital readmissions.