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Readmission following colorectal surgery, typically due to surgery-related complications, is common. Patient-centered discharge warnings may guide recognition of early complication signs after colorectal surgery.

It is critical to integrate and analyze data from biological, translational, and clinical studies with data from health systems; however, electronic artifacts are stored in thousands of disparate systems that are often unable to readily exchange data.

Patient reported outcomes (PROs) are reports of health conditions that come directly from patients. Use of PROs has been associated with improved patient outcomes, enhanced quality of life, and reduced end-of-life spending. Yet there are still outstanding questions regarding the process of implementing PRO collection in routine practice. In this article, we describe the experience of selecting and implementing PROs in a multisite, multidisease academic medical center-based radiation oncology practice [...]

The Patient Reported Outcomes Measurement Information System (PROMIS) initiative developed an array of patient reported outcome (PRO) measures. To reduce the number of questions administered, PROMIS utilizes unidimensional item response theory and unidimensional computer adaptive testing (UCAT), which means a separate set of questions is administered for each measured trait. Multidimensional item response theory (MIRT) and multidimensional computer adaptive testing (MCAT) simultaneously assess correlated traits. The objective was to investigate [...]

Quality assurance of large ontological systems such as SNOMED CT is an indispensable part of the terminology management lifecycle. We introduce a hybrid structural-lexical method for scalable and systematic discovery of missing hierarchical relations and concepts in SNOMED CT.

Social media is an important pharmacovigilance data source for adverse drug reaction (ADR) identification. Human review of social media data is infeasible due to data quantity, thus natural language processing techniques are necessary. Social media includes informal vocabulary and irregular grammar, which challenge natural language processing methods. Our objective is to develop a scalable, deep-learning approach that exceeds state-of-the-art ADR detection performance in social media.

To compare 3 commercial knowledge bases (KBs) used for detection and avoidance of potential drug-drug interactions (DDIs) in clinical practice.

Despite federal policies put in place by the Office of the National Coordinator (ONC) to promote safe and usable electronic health record (EHR) products, the usability of EHRs continues to frustrate providers and have patient safety implications. This study sought to compare government policies on usability and safety, and methods of examining compliance to those policies, across 3 federal agencies: the ONC and EHRs, the Federal Aviation Administration (FAA) and [...]

To develop automated classification methods for eligibility criteria in ClinicalTrials.gov to facilitate patient-trial matching for specific populations such as persons living with HIV or pregnant women.

To examine, using a smartphone application, whether mood is related to daily movement patterns in pregnant women at risk for perinatal depression.