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Accuracy of lung cancer ICD-9-CM codes in Umbria, Napoli 3 Sud and Friuli Venezia Giulia administrative healthcare databases: a diagnostic accuracy study

OBJECTIVES: To assess the accuracy of International Classification of Diseases 9th Revision–Clinical Modification (ICD-9-CM) codes in identifying subjects with lung cancer. DESIGN: A cross-sectional diagnostic accuracy study comparing ICD-9-CM 162.x code (index test) in primary position with medical...

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Autores principales: Montedori, Alessandro, Bidoli, Ettore, Serraino, Diego, Fusco, Mario, Giovannini, Gianni, Casucci, Paola, Franchini, David, Granata, Annalisa, Ciullo, Valerio, Vitale, Maria Francesca, Gobbato, Michele, Chiari, Rita, Cozzolino, Francesco, Orso, Massimiliano, Orlandi, Walter, Abraha, Iosief
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BMJ Publishing Group 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5961589/
https://www.ncbi.nlm.nih.gov/pubmed/29773701
http://dx.doi.org/10.1136/bmjopen-2017-020628
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author Montedori, Alessandro
Bidoli, Ettore
Serraino, Diego
Fusco, Mario
Giovannini, Gianni
Casucci, Paola
Franchini, David
Granata, Annalisa
Ciullo, Valerio
Vitale, Maria Francesca
Gobbato, Michele
Chiari, Rita
Cozzolino, Francesco
Orso, Massimiliano
Orlandi, Walter
Abraha, Iosief
author_facet Montedori, Alessandro
Bidoli, Ettore
Serraino, Diego
Fusco, Mario
Giovannini, Gianni
Casucci, Paola
Franchini, David
Granata, Annalisa
Ciullo, Valerio
Vitale, Maria Francesca
Gobbato, Michele
Chiari, Rita
Cozzolino, Francesco
Orso, Massimiliano
Orlandi, Walter
Abraha, Iosief
author_sort Montedori, Alessandro
collection PubMed
description OBJECTIVES: To assess the accuracy of International Classification of Diseases 9th Revision–Clinical Modification (ICD-9-CM) codes in identifying subjects with lung cancer. DESIGN: A cross-sectional diagnostic accuracy study comparing ICD-9-CM 162.x code (index test) in primary position with medical chart (reference standard). Case ascertainment was based on the presence of a primary nodular lesion in the lung and cytological or histological documentation of cancer from a primary or metastatic site. SETTING: Three operative units: administrative databases from Umbria Region (890 000 residents), ASL Napoli 3 Sud (NA) (1 170 000 residents) and Friuli Venezia Giulia (FVG) Region (1 227 000 residents). PARTICIPANTS: Incident subjects with lung cancer (n=386) diagnosed in primary position between 2012 and 2014 and a population of non-cases (n=280). OUTCOME MEASURES: Sensitivity, specificity and positive predictive value (PPV) for 162.x code. RESULTS: 130 cases and 94 non-cases were randomly selected from each database and the corresponding medical charts were reviewed. Most of the diagnoses for lung cancer were performed in medical departments. True positive rates were high for all the three units. Sensitivity was 99% (95% CI 95% to 100%) for Umbria, 97% (95% CI 91% to 100%) for NA, and 99% (95% CI 95% to 100%) for FVG. The false positive rates were 24%, 37% and 23% for Umbria, NA and FVG, respectively. PPVs were 79% (73% to 83%)%) for Umbria, 58% (53% to 63%)%) for NA and 79% (73% to 84%)%) for FVG. CONCLUSIONS: Case ascertainment for lung cancer based on imaging or endoscopy associated with histological examination yielded an excellent sensitivity in all the three administrative databases. PPV was moderate for Umbria and FVG but lower for NA.
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spelling pubmed-59615892018-05-30 Accuracy of lung cancer ICD-9-CM codes in Umbria, Napoli 3 Sud and Friuli Venezia Giulia administrative healthcare databases: a diagnostic accuracy study Montedori, Alessandro Bidoli, Ettore Serraino, Diego Fusco, Mario Giovannini, Gianni Casucci, Paola Franchini, David Granata, Annalisa Ciullo, Valerio Vitale, Maria Francesca Gobbato, Michele Chiari, Rita Cozzolino, Francesco Orso, Massimiliano Orlandi, Walter Abraha, Iosief BMJ Open Research Methods OBJECTIVES: To assess the accuracy of International Classification of Diseases 9th Revision–Clinical Modification (ICD-9-CM) codes in identifying subjects with lung cancer. DESIGN: A cross-sectional diagnostic accuracy study comparing ICD-9-CM 162.x code (index test) in primary position with medical chart (reference standard). Case ascertainment was based on the presence of a primary nodular lesion in the lung and cytological or histological documentation of cancer from a primary or metastatic site. SETTING: Three operative units: administrative databases from Umbria Region (890 000 residents), ASL Napoli 3 Sud (NA) (1 170 000 residents) and Friuli Venezia Giulia (FVG) Region (1 227 000 residents). PARTICIPANTS: Incident subjects with lung cancer (n=386) diagnosed in primary position between 2012 and 2014 and a population of non-cases (n=280). OUTCOME MEASURES: Sensitivity, specificity and positive predictive value (PPV) for 162.x code. RESULTS: 130 cases and 94 non-cases were randomly selected from each database and the corresponding medical charts were reviewed. Most of the diagnoses for lung cancer were performed in medical departments. True positive rates were high for all the three units. Sensitivity was 99% (95% CI 95% to 100%) for Umbria, 97% (95% CI 91% to 100%) for NA, and 99% (95% CI 95% to 100%) for FVG. The false positive rates were 24%, 37% and 23% for Umbria, NA and FVG, respectively. PPVs were 79% (73% to 83%)%) for Umbria, 58% (53% to 63%)%) for NA and 79% (73% to 84%)%) for FVG. CONCLUSIONS: Case ascertainment for lung cancer based on imaging or endoscopy associated with histological examination yielded an excellent sensitivity in all the three administrative databases. PPV was moderate for Umbria and FVG but lower for NA. BMJ Publishing Group 2018-05-17 /pmc/articles/PMC5961589/ /pubmed/29773701 http://dx.doi.org/10.1136/bmjopen-2017-020628 Text en © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2018. All rights reserved. No commercial use is permitted unless otherwise expressly granted. 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 and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/
spellingShingle Research Methods
Montedori, Alessandro
Bidoli, Ettore
Serraino, Diego
Fusco, Mario
Giovannini, Gianni
Casucci, Paola
Franchini, David
Granata, Annalisa
Ciullo, Valerio
Vitale, Maria Francesca
Gobbato, Michele
Chiari, Rita
Cozzolino, Francesco
Orso, Massimiliano
Orlandi, Walter
Abraha, Iosief
Accuracy of lung cancer ICD-9-CM codes in Umbria, Napoli 3 Sud and Friuli Venezia Giulia administrative healthcare databases: a diagnostic accuracy study
title Accuracy of lung cancer ICD-9-CM codes in Umbria, Napoli 3 Sud and Friuli Venezia Giulia administrative healthcare databases: a diagnostic accuracy study
title_full Accuracy of lung cancer ICD-9-CM codes in Umbria, Napoli 3 Sud and Friuli Venezia Giulia administrative healthcare databases: a diagnostic accuracy study
title_fullStr Accuracy of lung cancer ICD-9-CM codes in Umbria, Napoli 3 Sud and Friuli Venezia Giulia administrative healthcare databases: a diagnostic accuracy study
title_full_unstemmed Accuracy of lung cancer ICD-9-CM codes in Umbria, Napoli 3 Sud and Friuli Venezia Giulia administrative healthcare databases: a diagnostic accuracy study
title_short Accuracy of lung cancer ICD-9-CM codes in Umbria, Napoli 3 Sud and Friuli Venezia Giulia administrative healthcare databases: a diagnostic accuracy study
title_sort accuracy of lung cancer icd-9-cm codes in umbria, napoli 3 sud and friuli venezia giulia administrative healthcare databases: a diagnostic accuracy study
topic Research Methods
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5961589/
https://www.ncbi.nlm.nih.gov/pubmed/29773701
http://dx.doi.org/10.1136/bmjopen-2017-020628
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