Sentiment Measured in Hospital Discharge Notes Is Associated with Readmission and Mortality Risk: An Electronic Health Record Study

<div><p>Natural language processing tools allow the characterization of sentiment–that is, terms expressing positive and negative emotion–in text. Applying such tools to electronic health records may provide insight into meaningful patient or clinician features not captured in coded data alone. We performed sentiment analysis on 2,484 hospital discharge notes for 2,010 individuals from a psychiatric inpatient unit, as well as 20,859 hospital discharges for 15,011 individuals from general medical units, in a large New England health system between January 2011 and 2014. The primary measures of sentiment captured intensity of subjective positive or negative sentiment expressed in the discharge notes. Mean scores were contrasted between sociodemographic and clinical groups in mixed effects regression models. Discharge note sentiment was then examined for association with risk for readmission in Cox regression models. Discharge notes for individuals with greater medical comorbidity were modestly but significantly lower in positive sentiment among both psychiatric and general medical cohorts (p<0.001 in each). Greater positive sentiment at discharge was associated with significantly decreased risk of hospital readmission in each cohort (~12% decrease per standard deviation above the mean). Automated characterization of discharge notes in terms of sentiment identifies differences between sociodemographic groups, as well as in clinical outcomes, and is not explained by differences in diagnosis. Clinician sentiment merits investigation to understand why and how it reflects or impacts outcomes.</p></div

Resting Heart Rate Variability (HRV) in Adolescents and Young Adults from a Genetically-Informed Perspective

Reduced heart rate variability (HRV) is associated with cardiac morbidity, mortality, and negative psychopathology. Most research concerning genetic influences on HRV has focused on adult populations, with fewer studies investigating the developmental period of adolescence and emerging adulthood. The current study estimated the genetic and environmental contributions to resting HRV in a sample of twins using various HRV time domain metrics to assess autonomic function across two different time measurement intervals (2.5- and 10-min). Five metrics of resting HRV [mean interbeat interval (IBI), the standard deviation of normal IBIs (SDNN), root square mean of successive differences between IBIs (RMSSD), cardiac vagal index (CVI), and cardiac sympathetic index (CSI)] were assessed in 421 twin pairs aged 14-20 during a baseline electrocardiogram. This was done for four successive 2.5-min intervals as well as the overall 10-min interval. Heritability (h2) appeared consistent across intervals within each metric with the following estimates (collapsed across time intervals): mean IBI (h2 = 0.36-0.46), SDNN (h2 = 0.23-0.30), RMSSD (h2 = 0.36-0.39), CVI (h2 = 0.37-0.42), CSI (h2 = 0.33-0.46). Beyond additive genetic contributions, unique environment also was an important influence on HRV. Within each metric, a multivariate Cholesky decomposition further revealed evidence of genetic stability across the four successive 2.5-min intervals. The same models showed evidence for both genetic and environmental stability with some environmental attenuation and innovation. All measures of HRV were moderately heritable across time, with further analyses revealing consistent patterns of genetic and environmental influences over time. This study confirms that in an adolescent sample, the time interval used (2.5- vs. 10-min) to measure HRV time domain metrics does not affect the relative proportions of genetic and environmental influences

Cox regression examining association between sentiment and mortality in a general medical cohort.

<p>Cox regression examining association between sentiment and mortality in a general medical cohort.</p

Association between sociodemographic features and sentiment in a psychiatric inpatient cohort.

<p>Coefficients refer to standard deviation units of positive or negative sentiment.</p

Cox regression examining association between sentiment and readmission hazard in a psychiatric inpatient cohort.

<p>Cox regression examining association between sentiment and readmission hazard in a psychiatric inpatient cohort.</p

Genetic and Environmental Contributions of Negative Valence Systems to Internalizing Pathways

The genetic and environmental contributions of negative valence systems (NVS) to internalizing pathways study (also referred to as the Adolescent and Young Adult Twin Study) was designed to examine varying constructs of the NVS as they relate to the development of internalizing disorders from a genetically informed perspective. The goal of this study was to evaluate genetic and environmental contributions to potential psychiatric endophenotypes that contribute to internalizing psychopathology by studying adolescent and young adult twins longitudinally over a 2-year period. This report details the sample characteristics, study design, and methodology of this study. The first wave of data collection (i.e., time 1) is complete; the 2-year follow-up (i.e., time 2) is currently underway. A total of 430 twin pairs (N = 860 individual twins; 166 monozygotic pairs; 57.2% female) and 422 parents or legal guardians participated at time 1. Twin participants completed self-report surveys and participated in experimental paradigms to assess processes within the NVS. Additionally, parents completed surveys to report on themselves and their twin children. Findings from this study will help clarify the genetic and environmental influences of the NVS and their association with internalizing risk. The goal of this line of research is to develop methods for early internalizing disorder risk detection