Search

Antimicrobial resistance (AMR) is a global pandemic, however, estimating its burden is a complex process. As a result, many countries rely on global estimates to infer burden within their own setting. With a growing number of recent publications quantifying AMR burden in Australia, and an expansion of surveillance programs, enumerating AMR mortality for Australia is feasible. We aimed to leverage existing published data to assess methodological factors contributing to the considerable variation in AMR-related mortality and provide two reliable estimates of AMR mortality in Australia. This is a necessary step towards generating meaningful measures of AMR burden in Australia. What is known about the topic? Antimicrobial resistance is a significant global health threat, but estimating the burden of disease is complicated by data challenges. What does this paper add? This paper highlights progress in estimating the number of people dying from antimicrobial resistance in Australia and highlights the importance of rigorous antimicrobial resistance mortality estimates in Australia to assess burden of disease. What are the implications for practitioners? Practitioners should use only rigorous estimates of burden of disease to inform actions on reducing the threat of antimicrobial resistance. [ABSTRACT FROM AUTHOR]

Identifying potentially fraudulent or wasteful medical insurance claims can be difficult due to the large amounts of data and human effort involved. We applied unsupervised machine learning to construct interpretable models which rank variations in medical provider claiming behaviour in the domain of unilateral joint replacement surgery, using data from the Australian Medicare Benefits Schedule. For each of three surgical procedures reference models of claims for each procedure were constructed and compared analytically to models of individual provider claims. Providers were ranked using a score based on fees for typical claims made in addition to those in the reference model. Evaluation of the results indicated that the top-ranked providers were likely to be unusual in their claiming patterns, with typical claims from outlying providers adding up to 192% to the cost of a procedure. The method is efficient, generalizable to other procedures and, being interpretable, integrates well into existing workflows.

Many studies have stressed the importance of psychosocial determinants of health such as food insecurity, housing instability, and education level, as important drivers of health outcomes. Western Health developed a set of nine screening questions (the Western 9) based on psychosocial measures to profile patients enrolled in the HealthLinks Chronic Care initiative. An aggregate score was then converted into a Low, Medium and High risk profiles. The aim of the study was to see if the Western 9 questions added additional discriminative power to existing risk of readmission algorithms. Results show that the inclusion of the risk profiles significantly improved model fit and calibration compared to a baseline risk model. Suggestions for further refinement include developing weighted indices for the Western 9 to improve model fit.