Low health literacy is associated with increased risks of hospitalization and death in patients with HF. The clinical evaluation of health literacy could help design interventions individualized for patients with low health literacy.

BackgroundPerceived social isolation has been shown to have a negative impact on health outcomes, particularly among older adults. However, these relationships have not been fully examined among patients with heart failure.Methods and ResultsResidents from 11 southeast Minnesota counties with a first‐ever International Classification of Diseases, Ninth Revision (ICD‐9) code 428 for heart failure between January 1, 2013, and March 31, 2015 (N=3867), were prospectively surveyed to measure perceived social isolation. A total of 2003 patients returned the survey (response rate, 52%); 1681 patients completed all questions and were retained for analysis. Among these patients (53% men; mean age, 73 years), ≈19% (n=312) had moderate perceived social isolation and 6% (n=108) had high perceived social isolation. After adjustment, patients reporting moderate perceived social isolation did not have an increased risk of death, hospitalizations, or emergency department visits compared with patients reporting low perceived social isolation; however, patients reporting high perceived social isolation had >3.5 times increased risk of death (hazard ratio, 3.74; 95% confidence interval [CI], 1.82–7.70), 68% increased risk of hospitalization (hazard ratio, 1.68; 95% CI, 1.18–2.39), and 57% increased risk of emergency department visits (hazard ratio, 1.57; 95% CI, 1.09–2.27). Compared with patients who self‐reported low perceived social isolation, patients reporting moderate perceived social isolation had a 16% increased risk of outpatient visits (rate ratio, 1.16; 95% CI, 1.03–1.31), whereas those reporting high perceived social isolation had a 26% increased risk (rate ratio, 1.26; 95% CI, 1.04–1.53).ConclusionsIn patients with heart failure, greater perceived social isolation is associated with an increased risk of death and healthcare use. Assessing perceived social isolation during the clinical encounter with a brief screening tool may help identify patients with heart failure at greater risk of poor outcomes.

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Jeff Sloan and colleagues describe the development of the Patient-Reported Outcomes Quality of Life (PROQOL) instrument, which captures and stores patient-recorded outcomes in the medical record for patients with diabetes. Please see later in the article for the Editors' Summary

IntroductionThe goal of this project was to develop an interactive, web-based tool to explore patterns of prevalence and co-occurrence of diseases using data from the expanded Rochester Epidemiology Project (E-REP) medical records-linkage system.MethodsWe designed the REP Data Exploration Portal (REP DEP) to include summary information for people who lived in a 27-county region of southern Minnesota and western Wisconsin on January 1, 2014 (n = 694,506; 61% of the entire population). We obtained diagnostic codes of the International Classification of Diseases, 9th edition, from the medical records-linkage system in 2009 through 2013 (5 years) and grouped them into 717 disease categories. For each condition or combination of 2 conditions (dyad), we calculated prevalence by dividing the number of persons with a specified condition (numerator) by the total number of persons in the population (denominator). We calculated observed-to-expected ratios (OERs) to test whether 2 conditions co-occur more frequently than would co-occur as a result of chance alone.ResultsWe launched the first version of the REP DEP in May 2017. The REP DEP can be accessed at http://rochesterproject.org/portal/. Users can select 2 conditions of interest, and the REP DEP displays the overall prevalence, age-specific prevalence, and sex-specific prevalence for each condition and dyad. Also displayed are OERs overall and by age and sex and maps of county-specific prevalence of each condition and OER.ConclusionThe REP DEP draws upon a medical records-linkage system to provide an innovative, rapid, interactive, free-of-charge method to examine the prevalence and co-occurrence of 717 diseases and conditions in a geographically defined population.