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The growing ability to collect and transmit patient-generated health data, also referred to as people-generated health data and patient-reported outcomes, is creating an opportunity to greatly improve how cancer survivors and their providers manage survivors' health in the months and years following cancer treatment. Although cancer survivors are at higher risk of chronic health problems and early death as a result of cancer treatment, some experience difficulty identifying and receiving [...]

Measurement of patient race/ethnicity in electronic health records is mandated and important for tracking health disparities.

The objective of openFDA is to facilitate access and use of big important Food and Drug Administration public datasets by developers, researchers, and the public through harmonization of data across disparate FDA datasets provided via application programming interfaces (APIs).

Patients with kidney disease are at risk for adverse events due to improper medication prescribing. Few randomized controlled trials of clinical decision support (CDS) utilizing dynamic assessment of patients' kidney function to improve prescribing for patients with kidney disease have been published.

To develop an accurate logistic regression (LR) algorithm to support federated data analysis of vertically partitioned distributed data sets.

To develop a predictive model for real-time predictions of length of stay, mortality, and readmission for hospitalized patients using electronic health records (EHRs).

Efficient, effective health care requires rapid availability of patient information. We designed, implemented, and assessed the impact of a primary care electronic medical record (EMR) in three rural Kenyan health centers.