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Common chronic diseases such as hypertension are costly and difficult to manage. Our ultimate goal is to use data from electronic health records to predict the risk and timing of deterioration in hypertension control. Towards this goal, this work predicts the transition points at which hypertension is brought into, as well as pushed out of, control.

An innovative web-based system was developed to allow patient-reported outcome measures (PROMs) to be easily administered. Stakeholders guided the design and implementation. The software gives patients access to their current and previous scores. This pilot study focused on patients undergoing arthroscopic subacromial decompression, evaluated using the Oxford shoulder score (OSS). Patients showing good improvement in their OSS were offered the choice to return for routine follow-up clinic appointments, or continue [...]

The database of genotypes and phenotypes (dbGaP) developed by the National Center for Biotechnology Information (NCBI) is a resource that contains information on various genome-wide association studies (GWAS) and is currently available via NCBI's dbGaP Entrez interface. The database is an important resource, providing GWAS data that can be used for new exploratory research or cross-study validation by authorized users. However, finding studies relevant to a particular phenotype of interest [...]

High-performance computing centers (HPC) traditionally have far less restrictive privacy management policies than those encountered in healthcare. We show how an HPC can be re-engineered to accommodate clinical data while retaining its utility in computationally intensive tasks such as data mining, machine learning, and statistics. We also discuss deploying protected virtual machines. A critical planning step was to engage the university's information security operations and the information security and privacy [...]

To assess the perceived readiness of Medicaid and Children's Health Insurance Program (CHIP) enrollees to use information technologies (IT) in order to facilitate improvements in the application processes for these public insurance programs.

The purpose of this study was to describe adults who use Twitter during a weight loss attempt and to compare the positive and negative social influences they experience from their offline friends, online friends, and family members.

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 [...]

Larry Weed, MD is widely known as the father of the problem-oriented medical record and inventor of the now-ubiquitous SOAP (subjective/objective/assessment/plan) note, for developing an electronic health record system (Problem-Oriented Medical Information System, PROMIS), and for founding a company (since acquired), which developed problem-knowledge couplers. However, Dr Weed's vision for medicine goes far beyond software--over the course of his storied career, he has relentlessly sought to bring the scientific method [...]

This paper presents an automated system for classifying the results of imaging examinations (CT, MRI, positron emission tomography) into reportable and non-reportable cancer cases. This system is part of an industrial-strength processing pipeline built to extract content from radiology reports for use in the Victorian Cancer Registry.

To specify the problem of patient-level temporal aggregation from clinical text and introduce several probabilistic methods for addressing that problem. The patient-level perspective differs from the prevailing natural language processing (NLP) practice of evaluating at the term, event, sentence, document, or visit level.