Dasamal Tharanga Fernando1, Janneke Berecki-Gisolf2, Stuart Newstead2, Zahid Ansari3. 1. Monash University Accident Research Centre, Monash University, Clayton Campus, 21 Alliance Lane, Clayton, 3800, Victoria, Australia. tara.fernando@monash.edu. 2. Monash University Accident Research Centre, Monash University, Clayton Campus, 21 Alliance Lane, Clayton, 3800, Victoria, Australia. 3. Victorian Agency for Health Information, 50 Lonsdale Street, Melbourne, Victoria, 3000, Australia.
Abstract
BACKGROUND: Existing comorbidity measures predict mortality among general patient populations. Due to the lack of outcome specific and patient-group specific measures, the existing indices are also applied to non-mortality outcomes in injury epidemiology. This study derived indices to capture the association between comorbidity, and burden and readmission outcomes for injury populations. METHODS: Injury-related hospital admissions data from July 2012 to June 2014 (161,334 patients) for the state of Victoria, Australia were analyzed. Various multivariable regression models were run and results used to derive both binary and weighted indices that quantify the association between comorbidities and length of stay (LOS), hospital costs and readmissions. The new and existing indices were validated internally among patient subgroups, and externally using data from the states of New South Wales and Western Australia. RESULTS: Twenty-four comorbidities were significantly associated with overnight stay, twenty-seven with LOS, twenty-eight with costs, ten with all-cause and eleven with non-planned 30-day readmissions. The number of and types of comorbidities, and their relative impact were different to the associations established with the existing Charlson Comorbidity Index (CCI) and Elixhauser Comorbidity Measure (ECM). The new indices performed equally well to the long-listed ECM and in certain instances outperformed the CCI. CONCLUSIONS: The more parsimonious, up to date, outcome and patient-specific indices presented in this study are better suited for use in present injury epidemiology. Their use can be trialed by hospital administrations in resource allocation models and patient classification models in clinical settings.
BACKGROUND: Existing comorbidity measures predict mortality among general patient populations. Due to the lack of outcome specific and patient-group specific measures, the existing indices are also applied to non-mortality outcomes in injury epidemiology. This study derived indices to capture the association between comorbidity, and burden and readmission outcomes for injury populations. METHODS: Injury-related hospital admissions data from July 2012 to June 2014 (161,334 patients) for the state of Victoria, Australia were analyzed. Various multivariable regression models were run and results used to derive both binary and weighted indices that quantify the association between comorbidities and length of stay (LOS), hospital costs and readmissions. The new and existing indices were validated internally among patient subgroups, and externally using data from the states of New South Wales and Western Australia. RESULTS: Twenty-four comorbidities were significantly associated with overnight stay, twenty-seven with LOS, twenty-eight with costs, ten with all-cause and eleven with non-planned 30-day readmissions. The number of and types of comorbidities, and their relative impact were different to the associations established with the existing Charlson Comorbidity Index (CCI) and Elixhauser Comorbidity Measure (ECM). The new indices performed equally well to the long-listed ECM and in certain instances outperformed the CCI. CONCLUSIONS: The more parsimonious, up to date, outcome and patient-specific indices presented in this study are better suited for use in present injury epidemiology. Their use can be trialed by hospital administrations in resource allocation models and patient classification models in clinical settings.
Authors: Grant V Bochicchio; Manjari Joshi; Kelly Bochicchio; Diane Shih; W Meyer; Thomas M Scalea Journal: World J Surg Date: 2006-01 Impact factor: 3.352
Authors: Lynne Moore; André Lavoie; Natalie Le Sage; Eric Bergeron; Marcel Emond; Moishe Liberman; Belkacem Abdous Journal: Ann Emerg Med Date: 2008-02-20 Impact factor: 5.721