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ICD-10-AM codes for cirrhosis and related complications: key performance considerations for population and healthcare studies

OBJECTIVE: The utility of International Classification of Diseases (ICD) codes relies on the accuracy of clinical reporting and administrative coding, which may be influenced by country-specific codes and coding rules. This study explores the accuracy and limitations of the Australian Modification of...

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Autores principales: Hayward, Kelly L, Johnson, Amy L, Mckillen, Benjamin J, Burke, Niall T, Bansal, Vikas, Horsfall, Leigh U, Hartel, Gunter, Moser, Chris, Powell, Elizabeth E, Valery, Patricia C
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BMJ Publishing Group 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7500192/
https://www.ncbi.nlm.nih.gov/pubmed/32943463
http://dx.doi.org/10.1136/bmjgast-2020-000485
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author Hayward, Kelly L
Johnson, Amy L
Mckillen, Benjamin J
Burke, Niall T
Bansal, Vikas
Horsfall, Leigh U
Hartel, Gunter
Moser, Chris
Powell, Elizabeth E
Valery, Patricia C
author_facet Hayward, Kelly L
Johnson, Amy L
Mckillen, Benjamin J
Burke, Niall T
Bansal, Vikas
Horsfall, Leigh U
Hartel, Gunter
Moser, Chris
Powell, Elizabeth E
Valery, Patricia C
author_sort Hayward, Kelly L
collection PubMed
description OBJECTIVE: The utility of International Classification of Diseases (ICD) codes relies on the accuracy of clinical reporting and administrative coding, which may be influenced by country-specific codes and coding rules. This study explores the accuracy and limitations of the Australian Modification of the 10th revision of ICD (ICD-10-AM) to detect the presence of cirrhosis and a subset of key complications for the purpose of future large-scale epidemiological research and healthcare studies. DESIGN/METHOD: ICD-10-AM codes in a random sample of 540 admitted patient encounters at a major Australian tertiary hospital were compared with data abstracted from patients’ medical records by four blinded clinicians. Accuracy of individual codes and grouped combinations was determined by calculating sensitivity, positive predictive value (PPV), negative predictive value and Cohen’s kappa coefficient (κ). RESULTS: The PPVs for ‘grouped cirrhosis’ codes (0.96), hepatocellular carcinoma (0.97) ascites (0.97) and ‘grouped varices’ (0.95) were good (κ all >0.60). However, codes under-detected the prevalence of cirrhosis, ascites and varices (sensitivity 81.4%, 61.9% and 61.3%, respectively). Overall accuracy was lower for spontaneous bacterial peritonitis (‘grouped’ PPV 0.75; κ 0.73) and the poorest for encephalopathy (‘grouped’ PPV 0.55; κ 0.21). To optimise detection of cirrhosis-related encounters, an ICD-10-AM code algorithm was constructed and validated in an independent cohort of 116 patients with known cirrhosis. CONCLUSION: Multiple ICD-10-AM codes should be considered when using administrative databases to study the burden of cirrhosis and its complications in Australia, to avoid underestimation of the prevalence, morbidity, mortality and related resource utilisation from this burgeoning chronic disease.
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spelling pubmed-75001922020-10-05 ICD-10-AM codes for cirrhosis and related complications: key performance considerations for population and healthcare studies Hayward, Kelly L Johnson, Amy L Mckillen, Benjamin J Burke, Niall T Bansal, Vikas Horsfall, Leigh U Hartel, Gunter Moser, Chris Powell, Elizabeth E Valery, Patricia C BMJ Open Gastroenterol Epidemiology OBJECTIVE: The utility of International Classification of Diseases (ICD) codes relies on the accuracy of clinical reporting and administrative coding, which may be influenced by country-specific codes and coding rules. This study explores the accuracy and limitations of the Australian Modification of the 10th revision of ICD (ICD-10-AM) to detect the presence of cirrhosis and a subset of key complications for the purpose of future large-scale epidemiological research and healthcare studies. DESIGN/METHOD: ICD-10-AM codes in a random sample of 540 admitted patient encounters at a major Australian tertiary hospital were compared with data abstracted from patients’ medical records by four blinded clinicians. Accuracy of individual codes and grouped combinations was determined by calculating sensitivity, positive predictive value (PPV), negative predictive value and Cohen’s kappa coefficient (κ). RESULTS: The PPVs for ‘grouped cirrhosis’ codes (0.96), hepatocellular carcinoma (0.97) ascites (0.97) and ‘grouped varices’ (0.95) were good (κ all >0.60). However, codes under-detected the prevalence of cirrhosis, ascites and varices (sensitivity 81.4%, 61.9% and 61.3%, respectively). Overall accuracy was lower for spontaneous bacterial peritonitis (‘grouped’ PPV 0.75; κ 0.73) and the poorest for encephalopathy (‘grouped’ PPV 0.55; κ 0.21). To optimise detection of cirrhosis-related encounters, an ICD-10-AM code algorithm was constructed and validated in an independent cohort of 116 patients with known cirrhosis. CONCLUSION: Multiple ICD-10-AM codes should be considered when using administrative databases to study the burden of cirrhosis and its complications in Australia, to avoid underestimation of the prevalence, morbidity, mortality and related resource utilisation from this burgeoning chronic disease. BMJ Publishing Group 2020-09-17 /pmc/articles/PMC7500192/ /pubmed/32943463 http://dx.doi.org/10.1136/bmjgast-2020-000485 Text en © Author(s) (or their employer(s)) 2020. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ. http://creativecommons.org/licenses/by-nc/4.0/ http://creativecommons.org/licenses/by-nc/4.0/This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/.
spellingShingle Epidemiology
Hayward, Kelly L
Johnson, Amy L
Mckillen, Benjamin J
Burke, Niall T
Bansal, Vikas
Horsfall, Leigh U
Hartel, Gunter
Moser, Chris
Powell, Elizabeth E
Valery, Patricia C
ICD-10-AM codes for cirrhosis and related complications: key performance considerations for population and healthcare studies
title ICD-10-AM codes for cirrhosis and related complications: key performance considerations for population and healthcare studies
title_full ICD-10-AM codes for cirrhosis and related complications: key performance considerations for population and healthcare studies
title_fullStr ICD-10-AM codes for cirrhosis and related complications: key performance considerations for population and healthcare studies
title_full_unstemmed ICD-10-AM codes for cirrhosis and related complications: key performance considerations for population and healthcare studies
title_short ICD-10-AM codes for cirrhosis and related complications: key performance considerations for population and healthcare studies
title_sort icd-10-am codes for cirrhosis and related complications: key performance considerations for population and healthcare studies
topic Epidemiology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7500192/
https://www.ncbi.nlm.nih.gov/pubmed/32943463
http://dx.doi.org/10.1136/bmjgast-2020-000485
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