Editor's Choice: Toward high-throughput phenotyping: unbiased automated feature extraction and selection from knowledge sources

Objective Analysis of narrative (text) data from electronic health records (EHRs) can improve population-scale phenotyping for clinical and genetic research. Currently, selection of text features for phenotyping algorithms is slow and laborious, requiring extensive and iterative involvement by domain experts. This paper introduces a method to develop phenotyping algorithms in an unbiased manner by automatically extracting and selecting informative features, which can be comparable to expert-curated ones in classification accuracy.Materials and methods Comprehensive medical concepts were collected from publicly available knowledge sources in an automated, unbiased fashion. Natural language processing (NLP) revealed the occurrence patterns of these concepts in EHR narrative notes, which enabled selection of informative features for phenotype classification. When combined with additional codified features, a penalized logistic regression model was trained to classify the target phenotype.Results The authors applied our method to develop algorithms to identify patients with rheumatoid arthritis and coronary artery disease cases among those with rheumatoid arthritis from a large multi-institutional EHR. The area under the receiver operating characteristic curves (AUC) for classifying RA and CAD using models trained with automated features were 0.951 and 0.929, respectively, compared to the AUCs of 0.938 and 0.929 by models trained with expert-curated features.Discussion Models trained with NLP text features selected through an unbiased, automated procedure achieved comparable or slightly higher accuracy than those trained with expert-curated features. The majority of the selected model features were interpretable.Conclusion The proposed automated feature extraction method, generating highly accurate phenotyping algorithms with improved efficiency, is a significant step toward high-throughput phenotyping.     

Innovative information visualization of electronic health record data: a systematic review

Objective This study investigates the use of visualization techniques reported between 1996 and 2013 and evaluates innovative approaches to information visualization of electronic health record (EHR) data for knowledge discovery.Methods An electronic literature search was conducted May–July 2013 using MEDLINE and Web of Knowledge, supplemented by citation searching, gray literature searching, and reference list reviews. General search terms were used to assure a comprehensive document search.Results Beginning with 891 articles, the number of articles was reduced by eliminating 191 duplicates. A matrix was developed for categorizing all abstracts and to assist with determining those to be excluded for review. Eighteen articles were included in the final analysis.Discussion Several visualization techniques have been extensively researched. The most mature system is LifeLines and its applications as LifeLines2, EventFlow, and LifeFlow. Initially, research focused on records from a single patient and visualization of the complex data related to one patient. Since 2010, the techniques under investigation are for use with large numbers of patient records and events. Most are linear and allow interaction through scaling and zooming to resize. Color, density, and filter techniques are commonly used for visualization.Conclusions With the burgeoning increase in the amount of electronic healthcare data, the potential for knowledge discovery is significant if data are managed in innovative and effective ways. We identify challenges discovered by previous EHR visualization research, which will help researchers who seek to design and improve visualization techniques.     

Value Driven Outcomes (VDO): a pragmatic,modular, and extensible software framework for understanding and improving health care costs and outcomes

Objective To develop expeditiously a pragmatic, modular, and extensible software framework for understanding and improving healthcare value (costs relative to outcomes).Materials and methods In 2012, a multidisciplinary team was assembled by the leadership of the University of Utah Health Sciences Center and charged with rapidly developing a pragmatic and actionable analytics framework for understanding and enhancing healthcare value. Based on an analysis of relevant prior work, a value analytics framework known as Value Driven Outcomes (VDO) was developed using an agile methodology. Evaluation consisted of measurement against project objectives, including implementation timeliness, system performance, completeness, accuracy, extensibility, adoption, satisfaction, and the ability to support value improvement.Results A modular, extensible framework was developed to allocate clinical care costs to individual patient encounters. For example, labor costs in a hospital unit are allocated to patients based on the hours they spent in the unit; actual medication acquisition costs are allocated to patients based on utilization; and radiology costs are allocated based on the minutes required for study performance. Relevant process and outcome measures are also available. A visualization layer facilitates the identification of value improvement opportunities, such as high-volume, high-cost case types with high variability in costs across providers. Initial implementation was completed within 6 months, and all project objectives were fulfilled. The framework has been improved iteratively and is now a foundational tool for delivering high-value care.Conclusions The framework described can be expeditiously implemented to provide a pragmatic, modular, and extensible approach to understanding and improving healthcare value.     

Do Fructose-Containing Sugars Lead to Adverse Health Consequences? Results of Recent Systematic Reviews and Meta-analyses

Sugars have replaced fat as the dominant public health nutrition concern. A fructose-centric view of cardiometabolic disease has emerged whereby fructose-containing sugars are thought to have deleterious effects on body weight, fasting and postprandial blood lipids, glycemia, blood pressure, uric acid, and markers of nonalcoholic fatty liver disease. Long-term prospective cohort studies have not supported these associations when assessing the relation between total fructose-containing sugars at any amount of intake and incident cardiometabolic disease. Conversely, a consistent signal for harm has been reported for sugary beverages when comparing the highest with the lowest intakes. These associations, however, do not hold at moderate intakes, which are more reflective of real-world intakes, are subject to important collinearity effects, and have small risk estimates with modest population-attributable risk fractions. Higher-level evidence from controlled feeding trials shows that fructose-containing sugars in either liquid or solid form have adverse cardiometabolic effects only when they supplement diets with excess calories compared with the same diets without the excess calories. In the absence of harm when fructose-containing sugars are exchanged for other sources of carbohydrate under energy-matched conditions, excess calories appear to be the dominant consideration. Like with the earlier fat story, it is difficult to separate the contribution of fructose-containing sugars from that of other sources of excess calories in the epidemic of obesity and cardiometabolic disease. Attention needs to remain focused on reducing the overconsumption of all caloric foods associated with obesity and cardiometabolic disease, including sugary beverages and foods, and promoting greater physical activity.     

Primary aortic sarcoma with widespread vascular embolic metastases

Intimal sarcoma of the aorta is a rare and aggressive mesenchymal neoplasm with a propensity to metastasize and to embolize distant arteries. The diagnosis is most commonly made by autopsy or after surgery for an aortic aneurysm. Surgery is the treatment of choice in patients who do not have metastatic disease. The prognosis is generally poor, with death resulting in most patients within a few months from diagnosis. We describe a rare case of intimal sarcoma of the aorta that showed simultaneous involvement of the thoracic and abdominal aorta and also widespread embolic metastases to the main large vessels of the brain, heart, liver, kidneys, and spleen.