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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.

There have been growing concerns about the impact of drug allergy alerts on patient safety and provider alert fatigue. The authors aimed to explore the common drug allergy alerts over the last 10 years and the reasons why providers tend to override these alerts.

Health care proxy (HCP) documentation is suboptimal. To improve rates of proxy selection and documentation, we sought to develop and evaluate a web-based interview to guide patients in their selection, and to capture their choices in their electronic health record (EHR).

To document national trends of electronic medication history use in the ambulatory setting and describe the characteristics and predicting factors of providers who regularly use medication history transaction capabilities through their e-prescribing systems.

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).

To investigate how individuals with diabetes and diabetes educators reason about data collected through self-monitoring and to draw implications for the design of data-driven self-management technologies.

The proposed Meaningful Use Stage 3 recommendations require healthcare providers to accept patient-generated health data (PGHD) by 2017. Yet, we know little about the tensions that arise in supporting the needs of both patients and providers in this context. We sought to examine these tensions when designing a novel, patient-centered technology - mobile Post-Operative Wound Evaluator (mPOWEr) - that uses PGHD for post-discharge surgical wound monitoring.

To evaluate the feasibility of automatically assessing the Social Rhythm Metric (SRM), a clinically-validated marker of stability and rhythmicity for individuals with bipolar disorder (BD), using passively-sensed data from smartphones.