Assessing measures of comorbidity and functional status for risk adjustment to compare hospital performance for colorectal cancer surgery: a retrospective data-linkage study

BMC Medical Informatics and Decision Making

Research Article

Jane M Young¹  Tim Badgery-Parker¹  Timothy A Dobbins²  David C Currow³ 

[1] Cancer Epidemiology and Services Research, Sydney School of Public Health, University of Sydney, Sydney, NSW, Australia;Cancer Institute NSW, Sydney, NSW, Australia;Surgical Outcomes Research Centre (SOuRCe), Sydney Local Health District, Royal Prince Alfred Hospital, Sydney, NSW, Australia;Cancer Epidemiology and Services Research, Sydney School of Public Health, University of Sydney, Sydney, NSW, Australia;National Centre for Epidemiology and Population Health, Research School of Population Health, Australian National University, Canberra, ACT, Australia;Cancer Institute NSW, Sydney, NSW, Australia;

关键词: Risk adjustment;    Comorbidity;    Surgical outcomes;    Administrative data;    Charlson comorbidity index;    ECOG performance status;    ASA score;   

DOI  :  10.1186/s12911-015-0175-1

 received in 2014-10-09, accepted in 2015-06-26,  发布年份 2015

来源: Springer

【 摘 要 】

BackgroundComparing outcomes between hospitals requires consideration of patient factors that could account for any observed differences. Adjusting for comorbid conditions is common when studying outcomes following cancer surgery, and a commonly used measure is the Charlson comorbidity index. Other measures of patient health include the ECOG performance status and the ASA physical status score. This study aimed to ascertain how frequently ECOG and ASA scores are recorded in population-based administrative data collections in New South Wales, Australia and to assess the contribution each makes in addition to the Charlson comorbidity index in risk adjustment models for comparative assessment of colorectal cancer surgery outcomes between hospitals.MethodsWe used linked administrative data to identify 6964 patients receiving surgery for colorectal cancer in 2007 and 2008. We summarised the frequency of missing data for Charlson comorbidity index, ECOG and ASA scores, and compared patient characteristics between those with and without these measures. The performance of ASA and ECOG in risk adjustment models that also included Charlson index was assessed for three binary outcomes: 12-month mortality, extended length of stay and 28-day readmission. Patient outcomes were compared between hospital peer groups using multilevel logistic regression analysis.ResultsThe Charlson comorbidity index could be derived for all patients, ASA score was recorded for 78 % of patients and ECOG performance status recorded for only 24 % of eligible patients. Including ASA or ECOG improved the predictive ability of models, but there was no consistently best combination. The addition of ASA or ECOG did not substantially change parameter estimates for hospital peer group after adjusting for Charlson comorbidity index.ConclusionsWhile predictive ability of regression models is maximised by inclusion of one or both of ASA score and ECOG performance status, there is little to be gained by adding ASA or ECOG to models containing the Charlson comorbidity index to address confounding. The Charlson comorbidity index has good performance and is an appropriate measure to use in risk adjustment to compare outcomes between hospitals.

【 授权许可】

Unknown   
© Dobbins et al. 2015. This article is published under license to BioMed Central Ltd. 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.