Literature DB >> 28395889

Identification of Acute Decompensated Heart Failure Hospitalizations Using Administrative Data.

Hans Huang1, Matthew Turner1, Srihari Raju2, Jon Reich1, Sarah Leatherman3, Katherine Armstrong3, Patricia Woods3, Ryan E Ferguson4, Louis D Fiore4, Frank A Lederle5.   

Abstract

Hospitalization for acute decompensated heart failure (ADHF) is an important outcome in clinical trials and heart failure registries; however, the optimal strategy to identify these hospitalizations using International Classification of Diseases, Ninth Revision (ICD-9) codes is uncertain. We sought to identify diagnostic codes that improve ascertainment of ADHF hospitalizations. Heart failure-related ICD-9 principal discharge codes were used to identify 2,202 hospitalizations within the Minneapolis Veterans Affairs Medical Center from 2009 to 2014. Two independent reviewers adjudicated 447 of these hospitalizations to determine the accuracy of each code. We then applied our findings to an unadjusted nationwide sample containing the same ICD-9 codes of interest, from which overall positive predictive value (PPV), sensitivity, and accuracy were calculated. Use of 428.x alone resulted in a PPV of 91.3% (95% confidence interval [CI] 91.0 to 91.7), sensitivity of 97.5% (95% CI 97.3 to 97.6), and accuracy of 89.7% (95% CI 89.4 to 90.0). Combining 428.x with 402.x1, 404.x1, 415, and 518.4 resulted in improved sensitivity (99.2%; 95% CI 99.0 to 99.3) and accuracy (90.7%; 95% CI 90.4 to 91.1) while maintaining a PPV of 91.1% (95% CI 90.7 to 91.4). Excluding chronic heart failure codes (428.22, 428.32, and 428.42) from the proposed strategy resulted in an improvement of PPV to 92.3% (95% CI 92.0 to 92.6), although sensitivity and accuracy decreased to 96.6% (95% CI 96.3 to 96.8) and 90.0% (95% CI 89.6 to 90.3), respectively. In conclusion, a combination of codes including 428.x, 402.x1, 404.x1, 415, and 518.4 improves sensitivity and overall accuracy in ascertaining ADHF events compared with 428.x alone. This strategy could be further improved by manual adjudication of chronic heart failure codes.
Copyright © 2017 Elsevier Inc. All rights reserved.

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Year:  2017        PMID: 28395889     DOI: 10.1016/j.amjcard.2017.03.007

Source DB:  PubMed          Journal:  Am J Cardiol        ISSN: 0002-9149            Impact factor:   2.778


  4 in total

1.  Differential Associations of Chronic Inflammatory Diseases With Incident Heart Failure.

Authors:  Sameer Prasada; Adovich Rivera; Arvind Nishtala; Anna E Pawlowski; Arjun Sinha; Joshua D Bundy; Simran A Chadha; Faraz S Ahmad; Sadiya S Khan; Chad Achenbach; Frank J Palella; Rosalind Ramsey-Goldman; Yvonne C Lee; Jonathan I Silverberg; Babafemi O Taiwo; Sanjiv J Shah; Donald M Lloyd-Jones; Matthew J Feinstein
Journal:  JACC Heart Fail       Date:  2020-04-08       Impact factor: 12.035

2.  Which ICD-9-CM codes should be used for bronchiolitis research?

Authors:  Paul Walsh; Stephen J Rothenberg
Journal:  BMC Med Res Methodol       Date:  2018-11-22       Impact factor: 4.615

3.  Investigating changes in disease activity as a mediator of cardiovascular risk reduction with methotrexate use in rheumatoid arthritis.

Authors:  Tate M Johnson; Harlan R Sayles; Joshua F Baker; Michael D George; Punyasha Roul; Cheng Zheng; Brian Sauer; Katherine P Liao; Daniel R Anderson; Ted R Mikuls; Bryant R England
Journal:  Ann Rheum Dis       Date:  2021-05-28       Impact factor: 19.103

4.  Long-Term Trajectories of Left Ventricular Ejection Fraction in Patients With Chronic Inflammatory Diseases and Heart Failure: An Analysis of Electronic Health Records.

Authors:  Adovich S Rivera; Arjun Sinha; Faraz S Ahmad; Edward Thorp; Jane E Wilcox; Donald M Lloyd-Jones; Matthew J Feinstein
Journal:  Circ Heart Fail       Date:  2021-08-10       Impact factor: 10.447

  4 in total

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