Characterizing the Relationship Between Hospital Google Star Ratings, Hospital Consumer Assessment of Healthcare Providers and Systems (HCAHPS) Scores, and Quality.

Google searches for hospitals typically yield a Google star rating (GSR). These ratings are an important source of information for consumers. The degree to which GSRs are associated with traditional quality measures has not been evaluated recently. We sought to characterize the relationship between a hospital's GSR, its Hospital Consumer Assessment of Healthcare Providers and Systems (HCAHPS) scores, and Centers for Medicare and Medicaid Services (CMS) quality measures. We found a moderate association between a hospital's GSR and its HCAHPS score. The relationship between a hospital's GSR and CMS quality measures was statistically significant, but the magnitude was quite low. Our findings suggest that consumers should not use GSRs as a hospital quality proxy.

Integrative annotation of chromatin elements from ENCODE data.

The ENCODE Project has generated a wealth of experimental information mapping diverse chromatin properties in several human cell lines. Although each such data track is independently informative toward the annotation of regulatory elements, their interrelations contain much richer information for the systematic annotation of regulatory elements. To uncover these interrelations and to generate an interpretable summary of the massive datasets of the ENCODE Project, we apply unsupervised learning methodologies, converting dozens of chromatin datasets into discrete annotation maps of regulatory regions and other chromatin elements across the human genome. These methods rediscover and summarize diverse aspects of chromatin architecture, elucidate the interplay between chromatin activity and RNA transcription, and reveal that a large proportion of the genome lies in a quiescent state, even across multiple cell types. The resulting annotation of non-coding regulatory elements correlate strongly with mammalian evolutionary constraint, and provide an unbiased approach for evaluating metrics of evolutionary constraint in human. Lastly, we use the regulatory annotations to revisit previously uncharacterized disease-associated loci, resulting in focused, testable hypotheses through the lens of the chromatin landscape.