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Validation of the multivariable In-hospital Mortality for PulmonAry embolism using Claims daTa (IMPACT) prediction rule within an all-payer inpatient administrative claims database
OBJECTIVE: To validate the In-hospital Mortality for PulmonAry embolism using Claims daTa (IMPACT) prediction rule, in a database consisting only of inpatient claims. DESIGN: Retrospective claims database analysis. SETTING: The 2012 Healthcare Cost and Utilization Project National Inpatient Sample....
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BMJ Publishing Group
2015
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4636647/ https://www.ncbi.nlm.nih.gov/pubmed/26510731 http://dx.doi.org/10.1136/bmjopen-2015-009251 |
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author | Coleman, Craig I Kohn, Christine G Crivera, Concetta Schein, Jeffrey R Peacock, W Frank |
author_facet | Coleman, Craig I Kohn, Christine G Crivera, Concetta Schein, Jeffrey R Peacock, W Frank |
author_sort | Coleman, Craig I |
collection | PubMed |
description | OBJECTIVE: To validate the In-hospital Mortality for PulmonAry embolism using Claims daTa (IMPACT) prediction rule, in a database consisting only of inpatient claims. DESIGN: Retrospective claims database analysis. SETTING: The 2012 Healthcare Cost and Utilization Project National Inpatient Sample. PARTICIPANTS: Pulmonary embolism (PE) admissions were identified by an International Classification of Diseases, ninth edition (ICD-9) code either in the primary position or secondary position when accompanied by a primary code for a PE complication. The multivariable IMPACT rule, which includes age and 11 comorbidities, was used to estimate patients’ probability of in-hospital mortality and classify them as low or higher risk (≤1.5% deemed low risk). PRIMARY AND SECONDARY OUTCOME MEASURES: The rule's sensitivity, specificity, positive and negative predictive values (PPV and NPV) and area under the receiver operating characteristic curve statistic for predicting in-hospital mortality with accompanying 95% CIs. RESULTS: A total of 34 108 admissions for PE were included, with a 3.4% in-hospital case-fatality rate. IMPACT classified 11 025 (32.3%) patients as low risk, and low risk patients had lower in-hospital mortality (OR, 0.17, 95% CI 0.13 to 0.21), shorter length of stay (−1.2 days, p<0.001) and lower total treatment costs (−$3074, p<0.001) than patients classified as higher risk. IMPACT had a sensitivity of 92.4%, 95% CI 90.7 to 93.8 and specificity of 33.2%, 95% CI 32.7 to 33.7 for classifying mortality risk. It had a high NPV (>99%), low PPV (4.6%) and an AUC of 0.74, 95% CI 0.73 to 0.76. CONCLUSIONS: The IMPACT rule appeared valid when used in this all payer, inpatient only administrative claims database. Its high sensitivity and NPV suggest the probability of in-hospital death in those classified as low risk by IMPACT was minimal. |
format | Online Article Text |
id | pubmed-4636647 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2015 |
publisher | BMJ Publishing Group |
record_format | MEDLINE/PubMed |
spelling | pubmed-46366472015-11-13 Validation of the multivariable In-hospital Mortality for PulmonAry embolism using Claims daTa (IMPACT) prediction rule within an all-payer inpatient administrative claims database Coleman, Craig I Kohn, Christine G Crivera, Concetta Schein, Jeffrey R Peacock, W Frank BMJ Open Haematology (Incl Blood Transfusion) OBJECTIVE: To validate the In-hospital Mortality for PulmonAry embolism using Claims daTa (IMPACT) prediction rule, in a database consisting only of inpatient claims. DESIGN: Retrospective claims database analysis. SETTING: The 2012 Healthcare Cost and Utilization Project National Inpatient Sample. PARTICIPANTS: Pulmonary embolism (PE) admissions were identified by an International Classification of Diseases, ninth edition (ICD-9) code either in the primary position or secondary position when accompanied by a primary code for a PE complication. The multivariable IMPACT rule, which includes age and 11 comorbidities, was used to estimate patients’ probability of in-hospital mortality and classify them as low or higher risk (≤1.5% deemed low risk). PRIMARY AND SECONDARY OUTCOME MEASURES: The rule's sensitivity, specificity, positive and negative predictive values (PPV and NPV) and area under the receiver operating characteristic curve statistic for predicting in-hospital mortality with accompanying 95% CIs. RESULTS: A total of 34 108 admissions for PE were included, with a 3.4% in-hospital case-fatality rate. IMPACT classified 11 025 (32.3%) patients as low risk, and low risk patients had lower in-hospital mortality (OR, 0.17, 95% CI 0.13 to 0.21), shorter length of stay (−1.2 days, p<0.001) and lower total treatment costs (−$3074, p<0.001) than patients classified as higher risk. IMPACT had a sensitivity of 92.4%, 95% CI 90.7 to 93.8 and specificity of 33.2%, 95% CI 32.7 to 33.7 for classifying mortality risk. It had a high NPV (>99%), low PPV (4.6%) and an AUC of 0.74, 95% CI 0.73 to 0.76. CONCLUSIONS: The IMPACT rule appeared valid when used in this all payer, inpatient only administrative claims database. Its high sensitivity and NPV suggest the probability of in-hospital death in those classified as low risk by IMPACT was minimal. BMJ Publishing Group 2015-10-28 /pmc/articles/PMC4636647/ /pubmed/26510731 http://dx.doi.org/10.1136/bmjopen-2015-009251 Text en Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/ 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 | Haematology (Incl Blood Transfusion) Coleman, Craig I Kohn, Christine G Crivera, Concetta Schein, Jeffrey R Peacock, W Frank Validation of the multivariable In-hospital Mortality for PulmonAry embolism using Claims daTa (IMPACT) prediction rule within an all-payer inpatient administrative claims database |
title | Validation of the multivariable In-hospital Mortality for PulmonAry embolism using Claims daTa (IMPACT) prediction rule within an all-payer inpatient administrative claims database |
title_full | Validation of the multivariable In-hospital Mortality for PulmonAry embolism using Claims daTa (IMPACT) prediction rule within an all-payer inpatient administrative claims database |
title_fullStr | Validation of the multivariable In-hospital Mortality for PulmonAry embolism using Claims daTa (IMPACT) prediction rule within an all-payer inpatient administrative claims database |
title_full_unstemmed | Validation of the multivariable In-hospital Mortality for PulmonAry embolism using Claims daTa (IMPACT) prediction rule within an all-payer inpatient administrative claims database |
title_short | Validation of the multivariable In-hospital Mortality for PulmonAry embolism using Claims daTa (IMPACT) prediction rule within an all-payer inpatient administrative claims database |
title_sort | validation of the multivariable in-hospital mortality for pulmonary embolism using claims data (impact) prediction rule within an all-payer inpatient administrative claims database |
topic | Haematology (Incl Blood Transfusion) |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4636647/ https://www.ncbi.nlm.nih.gov/pubmed/26510731 http://dx.doi.org/10.1136/bmjopen-2015-009251 |
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