The purpose of this study was to validate a previously developed heart failure readmission predictive algorithm based on\r\npsychosocial factors, develop a new model based on patient-reported symptoms from a telemonitoring program, and assess the\r\nimpact of weight fluctuations and other factors on hospital readmission. Clinical, demographic, and telemonitoring data was\r\ncollected from 100 patients enrolled in the Partners Connected Cardiac Care Program between July 2008 and November 2011. 38%\r\nof study participants were readmitted to the hospital within 30 days. Ten different heart-failure-related symptoms were reported\r\n17,389 times, with the top three contributing approximately 50% of the volume. The psychosocial readmission model yielded an\r\nAUC of 0.67, along with sensitivity 0.87, specificity 0.32, positive predictive value 0.44, and negative predictive value 0.8 at a cutoff\r\nvalue of 0.30. In summary, hospital readmission models based on psychosocial characteristics, standardized changes in weight, or\r\npatient-reported symptoms can be developed and validated in heart failure patients participating in an institutional telemonitoring\r\nprogram. However, more robust models will need to be developed that use a comprehensive set of factors in order to have a\r\nsignificant impact on population health.
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