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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. [ABSTRACT FROM AUTHOR]

Background: National cancer policies identify the improvement of care coordination as a priority to improve the delivery of health services for people with cancer. Identification of the current barriers to effective cancer care coordination is needed to drive service improvement. Methods: A qualitative study was undertaken in which semi-structured individual interviews and focus groups were conducted with those best placed to identify issues; patients who had been treated for a range of cancers and their carers as well as health professionals involved in providing cancer care. Data collection continued until saturation of concepts was reached. A grounded theory influenced approach was used to explore the participants' experiences and views of cancer care coordination. Results: Overall, 20 patients, four carers and 29 health professionals participated. Barriers to cancer care coordination related to six aspects of care namely, recognising health professional roles and responsibilities, implementing comprehensive multidisciplinary team meetings, transitioning of care: falling through the cracks, inadequate communication between specialist and primary care, inequitable access to health services and managing scarce resources. Conclusions: This study has identified a number of barriers to coordination of cancer care. Development and evaluation of interventions based on these findings is now required. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Background Traumatic spinal cord injury is a devastating condition impacting adversely on the health and wellbeing, functioning and independence, social participation and quality of life of the injured person. In Australia, there are approximately 15 new cases per million population per year; economic burden estimates suggest 2 billion dollars annually. For optimal patient outcomes expert consensus recommends expeditious transfer ("<24 hours of injury") to a specialist Spinal Cord Injury Unit, where there is an interdisciplinary team equipped to provide comprehensive care for the many and complex issues associated with traumatic spinal cord injury. No study of this patient population has been undertaken, that assessed the extent to which care received reflected clinical guidelines, or examined the patient journey and outcomes in relation to this. The aims of this study are to describe the nature and timing of events occurring before commencement of specialist care, and to quantify the association between these events and patient outcomes. Methods and design The proposed observational study will recruit a prospective cohort over two years, identified at participating sites across two Australian states; Victoria and New South Wales. Included participants will be aged 16 years and older and diagnosed with a traumatic spinal cord injury. Detailed data will be collected from the point of injury through acute care and subacute rehabilitation, discharge from hospital and community reintegration. Items will include date, time, location and external cause of injury; ambulance response, assessments and management; all episodes of hospital care including assessments, vital signs, diagnoses and treatment, inter-hospital transfers, surgical interventions and their timing, lengths of stay and complications. Telephone follow-up of survivors will be conducted at 6, 12 and 24 months. Discussion There is limited population level data on the effect of delayed commencement of specialist care (>24hours) in a Spinal Cord Injury Unit. Examining current health service and clinical intervention pathways in this Australian population-based sample, in relation to their outcomes, will provide an understanding of factors associated with patient flow, resource utilisation and cost, and patient and family quality of life. Barriers to streamlined effective early-care pathways and facilitators of optimal treatment for these patients will be identified. [ABSTRACT FROM AUTHOR]