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 Blood product ordering is a complex process and mistakes can harm patients and lead to poor outcomes. Orders and order sets can be designed to help mitigate errors, but major changes in design can unintentionally cause new errors.

Designing a framework representing radiology results in a standards-based data structure using joint Radiological Society of North America/American College of Radiology Common Data Elements (CDEs) as the semantic labels on standard structures. This allows radiologist-created report data to integrate with artificial intelligence-generated results for use throughout downstream systems.

To use workflow execution models to highlight new considerations for patient-centered clinical decision support policies (PC CDS), processes, procedures, technology, and expertise required to support new workflows.

Develop a novel technique to identify an optimal number of regression units corresponding to a single risk point, while creating risk scoring systems from logistic regression-based disease predictive models. The optimal value of this hyperparameter balances simplicity and accuracy, yielding risk scores of small scale and high accuracy for patient risk stratification.

 Clinical decision support systems (CDSSs) are computer applications, which can be applied to give guidance to practitioners in antimicrobial stewardship (AS) activities; however, further information is needed for their optimal use.

 Millions of Americans manage their health care with the help of a trusted individual. Shared access to a patient's online patient portal is one tool that can assist their care partner(s) in gaining access to the patient's health information and allow for easy exchange with the patient's care team. Shared access provides care partners with a validated and secure method for accessing the patient's portal account using their own login [...]

Heart failure (HF) impacts millions of patients worldwide, yet the variability in treatment responses remains a major challenge for healthcare professionals. The current treatment strategies, largely derived from population based evidence, often fail to consider the unique characteristics of individual patients, resulting in suboptimal outcomes. This study aims to develop computational models that are patient-specific in predicting treatment outcomes, by utilizing a large Electronic Health Records (EHR) database. The goal [...]

To identify impacts of different survey methodologies assessing primary care physicians' (PCPs') experiences with electronic health records (EHRs), we compared three surveys: the 2022 Continuous Certification Questionnaire (CCQ) from the American Board of Family Medicine, the 2022 University of California San Francisco (UCSF) Physician Health IT Survey, and the 2021 National Electronic Health Records Survey (NEHRS).