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Depression is a prevalent disorder difficult to diagnose and treat. In particular, depressed patients exhibit largely unpredictable responses to treatment. Toward the goal of personalizing treatment for depression, we develop and evaluate computational models that use electronic health record (EHR) data for predicting the diagnosis and severity of depression, and response to treatment.

A recent Institute of Medicine report called for attention to safety issues related to electronic health records (EHRs). We analyzed EHR-related safety concerns reported within a large, integrated healthcare system.

The study of utilization patterns can quantify potential overuse of laboratory tests and find new ways to reduce healthcare costs. We demonstrate the use of distributional analytics for comparing electronic health record (EHR) laboratory test orders across time to diagnose and quantify overutilization.

Online physician reviews are a massive and potentially rich source of information capturing patient sentiment regarding healthcare. We analyze a corpus comprising nearly 60,000 such reviews with a state-of-the-art probabilistic model of text. We describe a probabilistic generative model that captures latent sentiment across aspects of care (eg, interpersonal manner). We target specific aspects by leveraging a small set of manually annotated reviews. We perform regression analysis to assess whether [...]

To assess the effects of librarian-provided services in healthcare settings on patient, healthcare provider, and researcher outcomes.

To examine whether there is a common sequence of adoption of electronic health record (EHR) functions among US hospitals, identify differences by hospital type, and assess the impact of meaningful use.

The PaTH (University of Pittsburgh/UPMC, Penn State College of Medicine, Temple University Hospital, and Johns Hopkins University) clinical data research network initiative is a collaborative effort among four academic health centers in the Mid-Atlantic region. PaTH will provide robust infrastructure to conduct research, explore clinical outcomes, link with biospecimens, and improve methods for sharing and analyzing data across our diverse populations. Our disease foci are idiopathic pulmonary fibrosis, atrial fibrillation [...]

The Patient-Centered Outcomes Research Institute (PCORI) recently launched PCORnet to establish a single inter-operable multicenter data research network that will support observational research and randomized clinical trials. This paper provides an overview of the patient-powered research networks (PPRNs), networks of patient organizations focused on a particular health condition that are interested in sharing health information and engaging in research. PPRNs will build on their foundation of trust within the patient [...]

A learning health system (LHS) integrates research done in routine care settings, structured data capture during every encounter, and quality improvement processes to rapidly implement advances in new knowledge, all with active and meaningful patient participation. While disease-specific pediatric LHSs have shown tremendous impact on improved clinical outcomes, a national digital architecture to rapidly implement LHSs across multiple pediatric conditions does not exist. PEDSnet is a clinical data research network [...]