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Venous thromboembolisms (VTEs), which include deep vein thrombosis (DVT) and pulmonary embolism (PE), are associated with significant mortality, morbidity, and cost in hospitalized patients. To evaluate the success of preventive measures, accurate and efficient methods for monitoring VTE rates are needed. Therefore, we sought to determine the accuracy of statistical natural language processing (NLP) for identifying DVT and PE from electronic health record data.

To investigate organizational strategies to promote personal health records (PHRs) adoption with a focus on patients with chronic disease.

To test the effectiveness of multiple interventions on increasing the response rate of text messaging for longitudinal data collection.

Smartphone applications (apps) have the potential to be valuable self-help interventions for depression screening. However, information about their feasibility and effectiveness and the characteristics of app users is limited. The aim of this study is to explore the uptake, utilization, and characteristics of voluntary users of an app for depression screening.

To develop expeditiously a pragmatic, modular, and extensible software framework for understanding and improving healthcare value (costs relative to outcomes).

Reporting of hospital adverse events relies on Patient Safety Indicators (PSIs) using International Classification of Diseases, Ninth Edition, Clinical Modification (ICD-9-CM) codes. The US transition to ICD-10-CM in 2015 could result in erroneous comparisons of PSIs. Using the General Equivalent Mappings (GEMs), we compared the accuracy of ICD-9-CM coded PSIs against recommended ICD-10-CM codes from the Centers for Medicaid/Medicare Services (CMS). We further predict their impact in a cohort of [...]

The ShARe/CLEF eHealth 2013 Evaluation Lab Task 1 was organized to evaluate the state of the art on the clinical text in (i) disorder mention identification/recognition based on Unified Medical Language System (UMLS) definition (Task 1a) and (ii) disorder mention normalization to an ontology (Task 1b). Such a community evaluation has not been previously executed. Task 1a included a total of 22 system submissions, and Task 1b included 17. Most [...]

To assess the effectiveness of computer-aided clinical decision support systems (CDSS) in improving antibiotic prescribing in primary care.

Extracting accurate information from complex biological processes involved in diseases, such as cancers, requires the simultaneous targeting of multiple proteins and locating their respective expression in tissue samples. This information can be collected by imaging and registering adjacent sections from the same tissue sample and stained by immunohistochemistry (IHC). Registration accuracy should be on the scale of a few cells to enable protein colocalization to be assessed.

Designing patient-centered consumer health informatics (CHI) applications requires understanding and creating alignment with patients' and their family members' health-related activities, referred to here as 'patient work'. A patient work approach to CHI draws on medical social science and human factors engineering models and simultaneously attends to patients, their family members, activities, and context. A patient work approach extends existing approaches to CHI design that are responsive to patients' biomedical realities [...]