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Open Access Research article

Comparison of measures of comorbidity for predicting disability 12-months post-injury

Belinda J Gabbe124*, James E Harrison3, Ronan A Lyons4, Elton R Edwards156, Peter A Cameron126 and On behalf of the Victorian Orthopaedic Trauma Outcomes Registry

Author affiliations

1 Department of Epidemiology and Preventive Medicine, Monash University, The Alfred Centre, 99 Commercial Rd, Melbourne, Victoria, 3004, Australia

2 National Trauma Research Institute, The Alfred Hospital, Melbourne, Australia

3 Research Centre for Injury Studies, Flinders University, Adelaide, Australia

4 College of Medicine, Swansea University, Swansea, United Kingdom

5 Department of Orthopaedic Surgery, The Alfred, Melbourne, Australia

6 Emergency and Trauma Centre, The Alfred Hospital, Melbourne, Australia

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Citation and License

BMC Health Services Research 2013, 13:30  doi:10.1186/1472-6963-13-30

Published: 26 January 2013

Abstract

Background

Understanding the factors that impact on disability is necessary to inform trauma care and enable adequate risk adjustment for benchmarking and monitoring. A key consideration is how to adjust for pre-existing conditions when assessing injury outcomes, and whether the inclusion of comorbidity is needed in addition to adjustment for age. This study compared different approaches to modelling the impact of comorbidity, collected as part of the routine hospital episode data, on disability outcomes following orthopaedic injury.

Methods

12-month Glasgow Outcome Scale – Extended (GOS-E) outcomes for 13,519 survivors to discharge were drawn from the Victorian Orthopaedic Trauma Outcomes Registry, a prospective cohort study of admitted orthopaedic injury patients. ICD-10-AM comorbidity codes were mapped to four comorbidity indices. Cases with a GOS-E score of 7–8 were considered “recovered”. A split dataset approach was used with cases randomly assigned to development or test datasets. Logistic regression models were fitted with “recovery” as the outcome and the performance of the models based on each comorbidity index (adjusted for injury and age) measured using calibration (Hosmer-Lemshow (H-L) statistics and calibration curves) and discrimination (Area under the Receiver Operating Characteristic (AUC)) statistics.

Results

All comorbidity indices improved model fit over models with age and injuries sustained alone. None of the models demonstrated acceptable model calibration (H-L statistic p < 0.05 for all models). There was little difference between the discrimination of the indices for predicting recovery: Charlson Comorbidity Index (AUC 0.70, 95% CI: 0.68, 0.71); number of ICD-10 chapters represented (AUC 0.70, 95% CI: 0.69, 0.72); number of six frequent chronic conditions represented (AUC 0.70, 95% CI: 0.69, 0.71); and the Functional Comorbidity Index (AUC 0.69, 95% CI: 0.68, 0.71).

Conclusions

The presence of ICD-10 recorded comorbid conditions is an important predictor of long term functional outcome following orthopaedic injury and adjustment for comorbidity is indicated when assessing risk-adjusted functional outcomes over time or across jurisdictions.

Keywords:
Orthopaedic injury; Comorbidity; Disability outcomes; Prediction