Analysis of Worsening Heart Failure Events in an Integrated Health Care System.

BACKGROUND: There is growing interest to disentangle worsening heart failure (WHF) from location of care and move away from hospitalization as a surrogate for acuity. OBJECTIVES: The purpose of this study was to describe the incidence of WHF events across the care continuum from ambulatory encounters to hospitalizations. METHODS: We studied calendar year cohorts of adults with diagnosed heart failure (HF) from 2010-2019 within a large, integrated health care delivery system. Electronic health record (EHR) data were accessed for outpatient encounters, emergency department (ED) visits/observation stays, and hospitalizations. WHF was defined as ≥1 symptom, ≥2 objective findings including ≥1 sign, and ≥1 change in HF-related therapy. Symptoms and signs were ascertained using natural language processing. RESULTS: We identified 103,138 eligible individuals with mean age 73.6 ± 13.7 years, 47.5% women, and mean left ventricular ejection fraction of 51.4% ± 13.7%. There were 1,136,750 unique encounters including 743,039 (65.4%) outpatient encounters, 224,670 (19.8%) ED visits/observation stays, and 169,041 (14.9%) hospitalizations. A total of 126,008 WHF episodes were identified, including 34,758 (27.6%) outpatient encounters, 28,301 (22.5%) ED visits/observation stays, and 62,949 (50.0%) hospitalizations. The annual incidence (events per 100 person-years) of WHF increased from 25 to 33 during the study period primarily caused by outpatient encounters (7 to 10) and ED visits/observation stays (4 to 7). The 30-day rate of hospitalizations for WHF ranged from 8.2% for outpatient encounters to 12.4% for hospitalizations. CONCLUSIONS: ED visits/observation stays and outpatient encounters account for approximately one-half of WHF events, are driving the underlying growth in HF morbidity, and portend a poor short-term prognosis.

A Natural Language Processing-Based Approach for Identifying Hospitalizations for Worsening Heart Failure Within an Integrated Health Care Delivery System.

Importance: The current understanding of epidemiological mechanisms and temporal trends in hospitalizations for worsening heart failure (WHF) is based on claims and national reporting databases. However, these data sources are inherently limited by the accuracy and completeness of diagnostic coding and/or voluntary reporting. Objective: To assess the overall burden of and temporal trends in the rate of hospitalizations for WHF. Design, Setting, and Participants: This cohort study, performed from January 1, 2010, to December 31, 2019, used electronic health record (EHR) data from a large integrated health care delivery system. Exposures: Calendar year trends. Main Outcomes and Measures: Hospitalizations for WHF (ie, excluding observation stays) were defined as 1 symptom or more, 2 objective findings or more including 1 sign or more, and 2 doses or more of intravenous loop diuretics and/or new hemodialysis or continuous kidney replacement therapy. Symptoms and signs were identified using natural language processing (NLP) algorithms applied to EHR data. Results: The study population was composed of 118 002 eligible patients experiencing 287 992 unique hospitalizations (mean [SD] age, 75.6 [13.1] years; 147 203 [51.1%] male; 1655 [0.6%] American Indian or Alaska Native, 28 451 [9.9%] Asian or Pacific Islander, 34 903 [12.1%] Black, 23 452 [8.1%] multiracial, 175 840 [61.1%] White, and 23 691 [8.2%] unknown), including 65 357 with a principal discharge diagnosis and 222 635 with a secondary discharge diagnosis of HF. The study population included 59 868 patients (20.8%) with HF with a reduced ejection fraction (HFrEF) (<40%), 33 361 (11.6%) with HF with a midrange EF (HFmrEF) (40%-49%), 142 347 (49.4%) with HF with a preserved EF (HFpEF) (≥50%), and 52 416 (18.2%) with unknown EF. A total of 58 042 admissions (88.8%) with a primary discharge diagnosis of HF and 62 764 admissions (28.2%) with a secondary discharge diagnosis of HF met the prespecified diagnostic criteria for WHF. Overall, hospitalizations for WHF identified on NLP-based algorithms increased from 5.2 to 7.6 per 100 hospitalizations per year during the study period. Subgroup analyses found an increase in hospitalizations for WHF based on NLP from 1.5 to 1.9 per 100 hospitalizations for HFrEF, from 0.6 to 1.0 per 100 hospitalizations for HFmrEF, and from 2.6 to 3.9 per 100 hospitalizations for HFpEF. Conclusions and Relevance: The findings of this cohort study suggest that the burden of hospitalizations for WHF may be more than double that previously estimated using only principal discharge diagnosis. There has been a gradual increase in the rate of hospitalizations for WHF with a more noticeable increase observed for HFpEF.