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Risk Adjustment for Smoking Identified through Tobacco Use Diagnoses in Hospital Data: A Validation Study
Adjustment for the differing risk profiles of patients is essential to the use of administrative hospital data for epidemiological research. Smoking is an important factor to include in such adjustments, but the accuracy of the diagnostic codes denoting smoking in hospital records is unknown. The ai...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2014
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3988140/ https://www.ncbi.nlm.nih.gov/pubmed/24736621 http://dx.doi.org/10.1371/journal.pone.0095029 |
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author | Havard, Alys Jorm, Louisa R. Lujic, Sanja |
author_facet | Havard, Alys Jorm, Louisa R. Lujic, Sanja |
author_sort | Havard, Alys |
collection | PubMed |
description | Adjustment for the differing risk profiles of patients is essential to the use of administrative hospital data for epidemiological research. Smoking is an important factor to include in such adjustments, but the accuracy of the diagnostic codes denoting smoking in hospital records is unknown. The aims of this study were to measure the validity of current smoking and ever smoked status identified from diagnoses in hospital records using a range of algorithms, relative to self-reported smoking status; and to examine whether the misclassification of smoking identified through hospital data is differential or non-differential with respect to common exposures and outcomes. Data from the baseline questionnaire of the 45 and Up Study, completed by 267,153 residents of New South Wales (NSW), Australia, aged 45 years and older, were linked to the NSW Admitted Patient Data Collection. Patients who had been admitted to hospital for an overnight stay between 1 July 2005 and the date of completion of the questionnaire (1 January 2006 to 2 March 2009) were included. Smokers were identified by applying a range of algorithms to hospital admission histories, and compared against self-reported smoking in the questionnaire (‘gold standard’). Sensitivities for current smoking ranged from 59% to 84%, while specificities were 94% to 98%. Sensitivities for ever smoked ranged from 45% to 74% and specificities were 93% to 97%. For the majority of algorithms, sensitivities and/or specificities differed significantly according to principal diagnosis, number of comorbidities, socioeconomic status, residential remoteness, Indigenous status, 28 day readmission and 365 day mortality. The identification of smoking through diagnoses in hospital data results in differential misclassification. Risk adjustment based on smoking identified from these data will yield potentially misleading results. Systematic capture of information about smoking in hospital records using a mandatory item would increase the utility of administrative data for epidemiological research. |
format | Online Article Text |
id | pubmed-3988140 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2014 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-39881402014-04-21 Risk Adjustment for Smoking Identified through Tobacco Use Diagnoses in Hospital Data: A Validation Study Havard, Alys Jorm, Louisa R. Lujic, Sanja PLoS One Research Article Adjustment for the differing risk profiles of patients is essential to the use of administrative hospital data for epidemiological research. Smoking is an important factor to include in such adjustments, but the accuracy of the diagnostic codes denoting smoking in hospital records is unknown. The aims of this study were to measure the validity of current smoking and ever smoked status identified from diagnoses in hospital records using a range of algorithms, relative to self-reported smoking status; and to examine whether the misclassification of smoking identified through hospital data is differential or non-differential with respect to common exposures and outcomes. Data from the baseline questionnaire of the 45 and Up Study, completed by 267,153 residents of New South Wales (NSW), Australia, aged 45 years and older, were linked to the NSW Admitted Patient Data Collection. Patients who had been admitted to hospital for an overnight stay between 1 July 2005 and the date of completion of the questionnaire (1 January 2006 to 2 March 2009) were included. Smokers were identified by applying a range of algorithms to hospital admission histories, and compared against self-reported smoking in the questionnaire (‘gold standard’). Sensitivities for current smoking ranged from 59% to 84%, while specificities were 94% to 98%. Sensitivities for ever smoked ranged from 45% to 74% and specificities were 93% to 97%. For the majority of algorithms, sensitivities and/or specificities differed significantly according to principal diagnosis, number of comorbidities, socioeconomic status, residential remoteness, Indigenous status, 28 day readmission and 365 day mortality. The identification of smoking through diagnoses in hospital data results in differential misclassification. Risk adjustment based on smoking identified from these data will yield potentially misleading results. Systematic capture of information about smoking in hospital records using a mandatory item would increase the utility of administrative data for epidemiological research. Public Library of Science 2014-04-15 /pmc/articles/PMC3988140/ /pubmed/24736621 http://dx.doi.org/10.1371/journal.pone.0095029 Text en © 2014 Havard et al http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited. |
spellingShingle | Research Article Havard, Alys Jorm, Louisa R. Lujic, Sanja Risk Adjustment for Smoking Identified through Tobacco Use Diagnoses in Hospital Data: A Validation Study |
title | Risk Adjustment for Smoking Identified through Tobacco Use Diagnoses in Hospital Data: A Validation Study |
title_full | Risk Adjustment for Smoking Identified through Tobacco Use Diagnoses in Hospital Data: A Validation Study |
title_fullStr | Risk Adjustment for Smoking Identified through Tobacco Use Diagnoses in Hospital Data: A Validation Study |
title_full_unstemmed | Risk Adjustment for Smoking Identified through Tobacco Use Diagnoses in Hospital Data: A Validation Study |
title_short | Risk Adjustment for Smoking Identified through Tobacco Use Diagnoses in Hospital Data: A Validation Study |
title_sort | risk adjustment for smoking identified through tobacco use diagnoses in hospital data: a validation study |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3988140/ https://www.ncbi.nlm.nih.gov/pubmed/24736621 http://dx.doi.org/10.1371/journal.pone.0095029 |
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