Improved wound management at lower costs: A sensible goal for Australia

Chronic wounds cost the Australian health system at least US$2·85 billion per year. Wound care services in Australia involve a complex mix of treatment options, health care sectors and funding mechanisms. It is clear that implementation of evidence-based wound care coincides with large health improvements and cost savings, yet the majority of Australians with chronic wounds do not receive evidence-based treatment. High initial treatment costs, inadequate reimbursement, poor financial incentives to invest in optimal care and limitations in clinical skills are major barriers to the adoption of evidence-based wound care. Enhanced education and appropriate financial incentives in primary care will improve uptake of evidence-based practice. Secondary-level wound specialty clinics to fill referral gaps in the community, boosted by appropriate credentialing, will improve access to specialist care. In order to secure funding for better services in a competitive environment, evidence of cost-effectiveness is required. Future effort to generate evidence on the cost-effectiveness of wound management interventions should provide evidence that decision makers find easy to interpret. If this happens, and it will require a large effort of health services research, it could be used to inform future policy and decision-making activities, reduce health care costs and improve patient outcomes.

Characterization of anomalous relaxation using the time-fractional Bloch equation and multiple echo T2 *-weighted magnetic resonance imaging at 7T

PURPOSE To study the utility of fractional calculus in modeling gradient-recalled echo MRI signal decay in the normal human brain. METHODS We solved analytically the extended time-fractional Bloch equations resulting in five model parameters, namely, the amplitude, relaxation rate, order of the time-fractional derivative, frequency shift, and constant offset. Voxel-level temporal fitting of the MRI signal was performed using the classical monoexponential model, a previously developed anomalous relaxation model, and using our extended time-fractional relaxation model. Nine brain regions segmented from multiple echo gradient-recalled echo 7 Tesla MRI data acquired from five participants were then used to investigate the characteristics of the extended time-fractional model parameters. RESULTS We found that the extended time-fractional model is able to fit the experimental data with smaller mean squared error than the classical monoexponential relaxation model and the anomalous relaxation model, which do not account for frequency shift. CONCLUSIONS We were able to fit multiple echo time MRI data with high accuracy using the developed model. Parameters of the model likely capture information on microstructural and susceptibility-induced changes in the human brain.

Correcting for bias when estimating the cost of hospital-acquired infection : an analysis of lower respiratory tract infections in non-surgical patients

Hospital acquired infections (HAI) are costly but many are avoidable. Evaluating prevention programmes requires data on their costs and benefits. Estimating the actual costs of HAI (a measure of the cost savings due to prevention) is difficult as HAI changes cost by extending patient length of stay, yet, length of stay is a major risk factor for HAI. This endogeneity bias can confound attempts to measure accurately the cost of HAI. We propose a two-stage instrumental variables estimation strategy that explicitly controls for the endogeneity between risk of HAI and length of stay. We find that a 10% reduction in ex ante risk of HAI results in an expected savings of £693 ($US 984).