{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,11,2]],"date-time":"2026-11-02T17:03:31Z","timestamp":1793639011717,"version":"4.5.1"},"reference-count":50,"publisher":"Ovid Technologies (Wolters Kluwer Health)","issue":"2","content-domain":{"domain":["www.ahajournals.org"],"crossmark-restriction":true},"short-container-title":["Circ: Cardiovascular Quality and Outcomes"],"published-print":{"date-parts":[[2023,2]]},"abstract":"<jats:sec>\n                    <jats:title>Background:<\/jats:title>\n                    <jats:p>Heart failure (HF) is a leading cause of hospitalization in older adults. Medicare data have been used to assess HF outcomes. However, the validity of ICD-10 diagnosis codes (used since 2015) to identify acute HF hospitalization or distinguish reduced (heart failure with reduced ejection fraction) versus preserved ejection fraction (HFpEF) is unknown in Medicare data.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods:<\/jats:title>\n                    <jats:p>Using Medicare data (2015\u20132017), we randomly sampled 200 HF hospitalizations with ICD-10 diagnosis codes for HF in the first\/second claim position in a 1:1:2 ratio for systolic HF (I50.2), diastolic HF (I50.3), and other HF (I50.X). The primary gold standards included recorded HF diagnosis by a treating physician for HF hospitalization, ejection fraction (EF)\u226450 for heart failure with reduced ejection fraction, and EF&gt;50 for HFpEF. If the quantitative EF was not present, then qualitative descriptions of EF were used for heart failure with reduced ejection fraction\/HFpEF gold standards. Multiple secondary gold standards were also tested. Gold standard data were extracted from medical records using standardized forms and adjudicated by cardiology fellows\/staff. We calculated positive predictive values with 95% CIs.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results:<\/jats:title>\n                    <jats:p>The 200-chart validation sample included 50 systolic, 50 diastolic, 47 combined dysfunction, and 53 unspecified HF patients. The positive predictive values of acute HF hospitalization was 98% [95% CI, 95\u2013100] for first-position ICD-10 HF diagnosis and 66% [95% CI, 58\u201374] for first\/second-position diagnosis. Quantitative EF was available for \u226580% of patients with systolic, diastolic, or combined dysfunction ICD-10 codes. The positive predictive value of systolic HF codes was 90% [95% CI, 82\u201398] for EFs\u226450% and 72% [95% CI, 60\u201385] for EFs\u226440%. The positive predictive value was 92% [95% CI, 85\u2013100] for HFpEF for EFs&gt;50%. The ICD-10 codes for combined or unspecified HF poorly predicted heart failure with reduced ejection fraction or HFpEF.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions:<\/jats:title>\n                    <jats:p>ICD-10 principal diagnosis identified acute HF hospitalization with a high positive predictive value. Systolic and diastolic ICD-10 diagnoses reliably identified heart failure with reduced ejection fraction and HFpEF when EF 50% was used as the cutoff.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1161\/circoutcomes.122.009078","type":"journal-article","created":{"date-parts":[[2023,1,23]],"date-time":"2023-01-23T05:00:45Z","timestamp":1674450045000},"update-policy":"https:\/\/doi.org\/10.1161\/crossmarkpolicy","source":"Crossref","is-referenced-by-count":117,"title":["Validity of International Classification of Diseases (ICD)-10 Diagnosis Codes for Identification of Acute Heart Failure Hospitalization and Heart Failure with Reduced Versus Preserved Ejection Fraction in a National Medicare Sample"],"prefix":"10.1161","volume":"16","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-1221-4028","authenticated-orcid":true,"given":"Benjamin A.","family":"Bates","sequence":"first","affiliation":[{"name":"Center for Pharmacoepidemiology and Treatment Science, Institute for Health, 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