Towards more efficient burn care: Identifying factors associated with good quality of life post-burn
|dc.identifier.citation||Finlay, V. and Phillips, M. and Allison, G. and Wood, F. and Ching, D. and Wicaksono, D. and Plowman, S. et al. 2015. Towards more efficient burn care: Identifying factors associated with good quality of life post-burn. Burns. 41 (7): pp. 1397-1404.|
Background: As minor burn patients constitute the vast majority of a developed nation case-mix, streamlining care for this group can promote efficiency from a service-wide perspective. This study tested the hypothesis that a predictive nomogram model that estimates likelihood of good long-term quality of life (QoL) post-burn is a valid way to optimise patient selection and risk management when applying a streamlined model of care. Method: A sample of 224 burn patients managed by the Burn Service of Western Australia who provided both short and long-term outcomes was used to estimate the probability of achieving a good QoL defined as 150 out of a possible 160 points on the Burn Specific Health Scale-Brief (BSHS-B) at least six months from injury. A multivariate logistic regression analysis produced a predictive model provisioned as a nomogram for clinical application. A second, independent cohort of consecutive patients (n = 106) was used to validate the predictive merit of the nomogram. Results and discussion: Male gender (p = 0.02), conservative management (p = 0.03), upper limb burn (p = 0.04) and high BSHS-B score within one month of burn (p < 0.001) were significant predictors of good outcome at six months and beyond. A Receiver Operating Curve (ROC) analysis demonstrated excellent (90%) accuracy overall. At 80% probability of good outcome, the false positive risk was 14%. The nomogram was validated by running a second ROC analysis of the model in an independent cohort. The analysis confirmed high (86%) overall accuracy of the model, the risk of false positive was reduced to 10% at a lower (70%) probability. This affirms the stability of the nomogram model in different patient groups over time. An investigation of the effect of missing data on sample selection determined that a greater proportion of younger patients with smaller TBSA burns were excluded due to loss to follow up. Conclusion: For clinicians managing comparable burn populations, the BSWA burns nomogram is an effective tool to assist the selection of patients to a streamlined care pathway with the aim of improving efficiency of service delivery.
|dc.title||Towards more efficient burn care: Identifying factors associated with good quality of life post-burn|
|curtin.department||School of Physiotherapy and Exercise Science|
|curtin.accessStatus||Fulltext not available|
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