Developing Clinical Risk Prediction Models for Worsening Heart Failure Events and Death by Left Ventricular Ejection Fraction.

Background There is a need to develop electronic health record-based predictive models for worsening heart failure (WHF) events across clinical settings and across the spectrum of left ventricular ejection fraction (LVEF). Methods and Results We studied adults with heart failure (HF) from 2011 to 2019 within an integrated health care delivery system. WHF encounters were ascertained using natural language processing and structured data. We conducted boosted decision tree ensemble models to predict 1-year hospitalizations, emergency department visits/observation stays, and outpatient encounters for WHF and all-cause death within each LVEF category: HF with reduced ejection fraction (EF) (LVEF <40%), HF with mildly reduced EF (LVEF 40%-49%), and HF with preserved EF (LVEF ≥50%). Model discrimination was evaluated using area under the curve and calibration using mean squared error. We identified 338 426 adults with HF: 61 045 (18.0%) had HF with reduced EF, 49 618 (14.7%) had HF with mildly reduced EF, and 227 763 (67.3%) had HF with preserved EF. The 1-year risks of any WHF event and death were, respectively, 22.3% and 13.0% for HF with reduced EF, 17.0% and 10.1% for HF with mildly reduced EF, and 16.3% and 10.3% for HF with preserved EF. The WHF model displayed an area under the curve of 0.76 and mean squared error of 0.13, whereas the model for death displayed an area under the curve of 0.83 and mean squared error of 0.076. Performance and predictors were similar across WHF encounter types and LVEF categories. Conclusions We developed risk prediction models for 1-year WHF events and death across the LVEF spectrum using structured and unstructured electronic health record data and observed no substantial differences in model performance or predictors except for death, despite differences in underlying HF cause.

Association Between Participation in a Heart Failure Telemonitoring Program and Health Care Utilization and Death Within an Integrated Health Care Delivery System.

BACKGROUND: The clinical usefulness of remote telemonitoring to reduce postdischarge health care use and death in adults with heart failure (HF) remains controversial. METHODS AND RESULTS: Within a large integrated health care delivery system, we matched patients enrolled in a postdischarge telemonitoring intervention from 2015 to 2019 to patients not receiving telemonitoring at up to a 1:4 ratio on age, sex, and calipers of a propensity score. Primary outcomes were readmissions for worsening HF and all-cause death within 30, 90, and 365 days of the index discharge; secondary outcomes were all-cause readmissions and any outpatient diuretic dose adjustments. We matched 726 patients receiving telemonitoring to 1985 controls not receiving telemonitoring, with a mean age of 75 ± 11 years and 45% female. Patients receiving telemonitoring did not have a significant reduction in worsening HF hospitalizations (adjusted rate ratio [aRR] 0.95, 95% confidence interval [CI] 0.68-1.33), all-cause death (adjusted hazard ratio 0.60, 95% CI 0.33-1.08), or all-cause hospitalization (aRR 0.82, 95% CI 0.65-1.05) at 30 days, but did have an increase in outpatient diuretic dose adjustments (aRR 1.84, 95% CI 1.44-2.36). All associations were similar at 90 and 365 days postdischarge. CONCLUSIONS: A postdischarge HF telemonitoring intervention was associated with more diuretic dose adjustments but was not significantly associated with HF-related morbidity and mortality.