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To demonstrate a process of calculating the maximum potential morphine milligram equivalent daily dose (MEDD) based on the prescription Sig for use in quality improvement initiatives. To calculate an opioid prescription's maximum potential Sig-MEDD, we developed SQL code to determine a prescription's maximum units/day using discrete field data and text-parsing in the prescription instructions. We validated the derived units/day calculation using 3000 Sigs, then compared the Sig-MEDD calculation against the [...]

To investigate using patient posts in social media as a resource to profile off-label prescriptions of cancer drugs.

The risk of medical errors increases upon transfer out of the intensive care unit (ICU). Discrepancies in the documented care plan between notes at the time of transfer may contribute to communication errors. We sought to determine the frequency of clinically meaningful discrepancies in the documented care plan for patients transferred from the pediatric ICU to the medical wards and identified risk factors.

Identifying new relations between medical entities, such as drugs, diseases, and side effects, is typically a resource-intensive task, involving experimentation and clinical trials. The increased availability of related data and curated knowledge enables a computational approach to this task, notably by training models to predict likely relations. Such models rely on meaningful representations of the medical entities being studied. We propose a generic features vector representation that leverages co-occurrences of [...]

To predict 72-h and 9-day emergency department (ED) return by using gradient boosting on an expansive set of clinical variables from the electronic health record.

Our objective was to develop and test a new concept (affinity) analogous to multimorbidity of chronic conditions for individuals at census tract level in Memphis, TN. The use of affinity will improve the surveillance of multiple chronic conditions and facilitate the design of effective interventions.

Zoonotic disease surveillance presents a substantial problem in the management of public health. Globally, zoonoses have the potential to spread and negatively impact population health economic growth, and security. This research was conducted to investigate the current data sources, analytical methods, and limitations for cluster detection and prediction with particular interest in emerging bioinformatics tools and resources to inform the development of zoonotic surveillance spatial decision support systems. We recruited [...]

This case study describes the implementation of the Research Electronic Data Capture (REDCap) software at the United States Department of Veterans Affairs Veterans Health Administration (VA). VA REDCap enables secure and standardized data collection, fosters collaboration with external researchers through use of a widely used data management tool, facilitates multisite studies through use of data forms that can be shared across sites within and outside the VA, is well suited [...]

To understand if providers who had additional electronic health record (EHR) training improved their satisfaction, decreased personal EHR-use time, and decreased turnaround time on tasks.