Benjamin A Bates, Ehimare Akhabue, Meghan M Nahass, Abhigyan Mukherjee, Emily Hiltner, Joanna Rock, Brandon Wilton, Garima Mittal, Aayush Visaria, Melanie Rua, Poonam Gandhi, Chintan V Dave, Soko Setoguchi
{"title":"国际疾病分类(ICD)-10诊断代码在国家医疗保险样本中识别急性心力衰竭住院和射血分数降低与保留的心力衰竭的有效性","authors":"Benjamin A Bates, Ehimare Akhabue, Meghan M Nahass, Abhigyan Mukherjee, Emily Hiltner, Joanna Rock, Brandon Wilton, Garima Mittal, Aayush Visaria, Melanie Rua, Poonam Gandhi, Chintan V Dave, Soko Setoguchi","doi":"10.1161/CIRCOUTCOMES.122.009078","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>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.</p><p><strong>Methods: </strong>Using Medicare data (2015-2017), 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)≤50 for heart failure with reduced ejection fraction, and EF>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.</p><p><strong>Results: </strong>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, 95-100] for first-position ICD-10 HF diagnosis and 66% [95% CI, 58-74] for first/second-position diagnosis. Quantitative EF was available for ≥80% of patients with systolic, diastolic, or combined dysfunction ICD-10 codes. The positive predictive value of systolic HF codes was 90% [95% CI, 82-98] for EFs≤50% and 72% [95% CI, 60-85] for EFs≤40%. The positive predictive value was 92% [95% CI, 85-100] for HFpEF for EFs>50%. The ICD-10 codes for combined or unspecified HF poorly predicted heart failure with reduced ejection fraction or HFpEF.</p><p><strong>Conclusions: </strong>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.</p>","PeriodicalId":10301,"journal":{"name":"Circulation. Cardiovascular Quality and Outcomes","volume":"16 2","pages":"e009078"},"PeriodicalIF":6.9000,"publicationDate":"2023-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"9","resultStr":"{\"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.\",\"authors\":\"Benjamin A Bates, Ehimare Akhabue, Meghan M Nahass, Abhigyan Mukherjee, Emily Hiltner, Joanna Rock, Brandon Wilton, Garima Mittal, Aayush Visaria, Melanie Rua, Poonam Gandhi, Chintan V Dave, Soko Setoguchi\",\"doi\":\"10.1161/CIRCOUTCOMES.122.009078\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Background: </strong>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.</p><p><strong>Methods: </strong>Using Medicare data (2015-2017), 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)≤50 for heart failure with reduced ejection fraction, and EF>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.</p><p><strong>Results: </strong>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, 95-100] for first-position ICD-10 HF diagnosis and 66% [95% CI, 58-74] for first/second-position diagnosis. Quantitative EF was available for ≥80% of patients with systolic, diastolic, or combined dysfunction ICD-10 codes. The positive predictive value of systolic HF codes was 90% [95% CI, 82-98] for EFs≤50% and 72% [95% CI, 60-85] for EFs≤40%. The positive predictive value was 92% [95% CI, 85-100] for HFpEF for EFs>50%. The ICD-10 codes for combined or unspecified HF poorly predicted heart failure with reduced ejection fraction or HFpEF.</p><p><strong>Conclusions: </strong>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.</p>\",\"PeriodicalId\":10301,\"journal\":{\"name\":\"Circulation. Cardiovascular Quality and Outcomes\",\"volume\":\"16 2\",\"pages\":\"e009078\"},\"PeriodicalIF\":6.9000,\"publicationDate\":\"2023-02-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"9\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Circulation. Cardiovascular Quality and Outcomes\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1161/CIRCOUTCOMES.122.009078\",\"RegionNum\":2,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Circulation. Cardiovascular Quality and Outcomes","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1161/CIRCOUTCOMES.122.009078","RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
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.
Background: 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.
Methods: Using Medicare data (2015-2017), 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)≤50 for heart failure with reduced ejection fraction, and EF>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.
Results: 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, 95-100] for first-position ICD-10 HF diagnosis and 66% [95% CI, 58-74] for first/second-position diagnosis. Quantitative EF was available for ≥80% of patients with systolic, diastolic, or combined dysfunction ICD-10 codes. The positive predictive value of systolic HF codes was 90% [95% CI, 82-98] for EFs≤50% and 72% [95% CI, 60-85] for EFs≤40%. The positive predictive value was 92% [95% CI, 85-100] for HFpEF for EFs>50%. The ICD-10 codes for combined or unspecified HF poorly predicted heart failure with reduced ejection fraction or HFpEF.
Conclusions: 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.
期刊介绍:
Circulation: Cardiovascular Quality and Outcomes, an American Heart Association journal, publishes articles related to improving cardiovascular health and health care. Content includes original research, reviews, and case studies relevant to clinical decision-making and healthcare policy. The online-only journal is dedicated to furthering the mission of promoting safe, effective, efficient, equitable, timely, and patient-centered care. Through its articles and contributions, the journal equips you with the knowledge you need to improve clinical care and population health, and allows you to engage in scholarly activities of consequence to the health of the public. Circulation: Cardiovascular Quality and Outcomes considers the following types of articles: Original Research Articles, Data Reports, Methods Papers, Cardiovascular Perspectives, Care Innovations, Novel Statistical Methods, Policy Briefs, Data Visualizations, and Caregiver or Patient Viewpoints.