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Procedure-based severity index for inpatients: development and validation using administrative database
BACKGROUND: Risk adjustment is important in studies using administrative databases. Although utilization of diagnostic and therapeutic procedures can represent patient severity, the usability of procedure records in risk adjustment is not well-documented. Therefore, we aimed to develop and validate...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2015
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4495704/ https://www.ncbi.nlm.nih.gov/pubmed/26152112 http://dx.doi.org/10.1186/s12913-015-0889-x |
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author | Yamana, Hayato Matsui, Hiroki Fushimi, Kiyohide Yasunaga, Hideo |
author_facet | Yamana, Hayato Matsui, Hiroki Fushimi, Kiyohide Yasunaga, Hideo |
author_sort | Yamana, Hayato |
collection | PubMed |
description | BACKGROUND: Risk adjustment is important in studies using administrative databases. Although utilization of diagnostic and therapeutic procedures can represent patient severity, the usability of procedure records in risk adjustment is not well-documented. Therefore, we aimed to develop and validate a severity index calculable from procedure records. METHODS: Using the Japanese nationwide Diagnosis Procedure Combination database of acute-care hospitals, we identified patients discharged between 1 April 2012 and 31 March 2013 with an admission-precipitating diagnosis of acute myocardial infarction, congestive heart failure, acute cerebrovascular disease, gastrointestinal hemorrhage, pneumonia, or septicemia. Subjects were randomly assigned to the derivation cohort or the validation cohort. In the derivation cohort, we used multivariable logistic regression analysis to identify procedures performed on admission day which were significantly associated with in-hospital death, and a point corresponding to regression coefficient was assigned to each procedure. An index was then calculated in the validation cohort as sum of points for performed procedures, and performance of mortality-predicting model using the index and other patient characteristics was evaluated. RESULTS: Of the 539 385 hospitalizations included, 270 054 and 269 331 were assigned to the derivation and validation cohorts, respectively. Nineteen significant procedures were identified from the derivation cohort with points ranging from −3 to 23, producing a severity index with possible range of −13 to 69. In the validation cohort, c-statistic of mortality-predicting model was 0.767 (95 % confidence interval: 0.764–0.770). The ω-statistic representing contribution of the index relative to other variables was 1.09 (95 % confidence interval: 1.03–1.17). CONCLUSIONS: Procedure-based severity index predicted mortality well, suggesting that procedure records in administrative database are useful for risk adjustment. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12913-015-0889-x) contains supplementary material, which is available to authorized users. |
format | Online Article Text |
id | pubmed-4495704 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2015 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-44957042015-07-09 Procedure-based severity index for inpatients: development and validation using administrative database Yamana, Hayato Matsui, Hiroki Fushimi, Kiyohide Yasunaga, Hideo BMC Health Serv Res Research Article BACKGROUND: Risk adjustment is important in studies using administrative databases. Although utilization of diagnostic and therapeutic procedures can represent patient severity, the usability of procedure records in risk adjustment is not well-documented. Therefore, we aimed to develop and validate a severity index calculable from procedure records. METHODS: Using the Japanese nationwide Diagnosis Procedure Combination database of acute-care hospitals, we identified patients discharged between 1 April 2012 and 31 March 2013 with an admission-precipitating diagnosis of acute myocardial infarction, congestive heart failure, acute cerebrovascular disease, gastrointestinal hemorrhage, pneumonia, or septicemia. Subjects were randomly assigned to the derivation cohort or the validation cohort. In the derivation cohort, we used multivariable logistic regression analysis to identify procedures performed on admission day which were significantly associated with in-hospital death, and a point corresponding to regression coefficient was assigned to each procedure. An index was then calculated in the validation cohort as sum of points for performed procedures, and performance of mortality-predicting model using the index and other patient characteristics was evaluated. RESULTS: Of the 539 385 hospitalizations included, 270 054 and 269 331 were assigned to the derivation and validation cohorts, respectively. Nineteen significant procedures were identified from the derivation cohort with points ranging from −3 to 23, producing a severity index with possible range of −13 to 69. In the validation cohort, c-statistic of mortality-predicting model was 0.767 (95 % confidence interval: 0.764–0.770). The ω-statistic representing contribution of the index relative to other variables was 1.09 (95 % confidence interval: 1.03–1.17). CONCLUSIONS: Procedure-based severity index predicted mortality well, suggesting that procedure records in administrative database are useful for risk adjustment. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12913-015-0889-x) contains supplementary material, which is available to authorized users. BioMed Central 2015-07-08 /pmc/articles/PMC4495704/ /pubmed/26152112 http://dx.doi.org/10.1186/s12913-015-0889-x Text en © Yamana et al. 2015 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. |
spellingShingle | Research Article Yamana, Hayato Matsui, Hiroki Fushimi, Kiyohide Yasunaga, Hideo Procedure-based severity index for inpatients: development and validation using administrative database |
title | Procedure-based severity index for inpatients: development and validation using administrative database |
title_full | Procedure-based severity index for inpatients: development and validation using administrative database |
title_fullStr | Procedure-based severity index for inpatients: development and validation using administrative database |
title_full_unstemmed | Procedure-based severity index for inpatients: development and validation using administrative database |
title_short | Procedure-based severity index for inpatients: development and validation using administrative database |
title_sort | procedure-based severity index for inpatients: development and validation using administrative database |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4495704/ https://www.ncbi.nlm.nih.gov/pubmed/26152112 http://dx.doi.org/10.1186/s12913-015-0889-x |
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