Lives depend on research access and reform in the health data space, yet the Government says it will start reform in other sectors, says CMCRC Health Research Analyst Cassie Quilty on Flying Blind website, a joint collaboration between CMCRC and Research Australia.Instead of starting in the health sector, government says implementation “will begin in the banking,
PhD Health Market Quality candidate Arif Khan has been published in the International Journal of Medical Informatics alongside one of the co-authors, CMCRC HMQ senior research scientist and PhD mentor Dr Uma Srinivasan. Their research has uncovered how using and analysing 1.4 million electronic medical records from almost 1 million de-identified patients can help determine when
Congratulations to CMCRC Senior Health Economist and Analyst Dr Kathy Tannous for being selected as a finalist in the Western Sydney University Research Impact Competition. Dr Tannous has also been recently involved in the Flying Blind Blog, which is an initiative of CMCRC and written in collaboration with Research Australia. Dr Tannous’s case study in Flying Blind
The healthcare sector deals with large volumes of electronic data related to patient services. This article describes two novel applications that leverage big data to detect fraud, abuse, waste, and errors in health insurance claims, thus reducing recurrent losses and facilitating enhanced patient care. The results indicate that claim anomalies detected using these applications help
Srinivasan, U. “Anomalies Detection in Healthcare Services” Using several practical examples of cost and quality-of-care outliers, the author presents a framework to detect outliers and anomalies in healthcare services. Author(s): Srinivasan, U. View Paper
The healthcare sector deals with large volumes of electronic data related to patient services. This article describes two novel applications that leverage big data to detect fraud, abuse, waste, and errors in health insurance claims, thus reducing recurrent losses and facilitating enhanced patient care. The results indicate that claim anomalies detected using these applications help
Fei Wang, Uma Srinivasan, Shahadat Uddin, and Sanjay Chawla. “Application of network analysis on healthcare”. In Advances in Social Networks Analysis and Mining (ASONAM), 2013 IEEE/ACM International Conference on IEEE, 2014. The healthcare sector holds large amounts of semantically rich electronic data generated and used by different sections of the health care community. Data analytic
Fei Wang, Sanjay Chawla, and Wei Liu. “Tikhonov or lasso regularization: Which is better and when. In Tools with Artificial Intelligence” (ICTAI), 2013 IEEE 25th International Conference on, pages 795–802. IEEE, 2013. It is well known that supervised learning problems with ℓ1 (Lasso) and ℓ2 (Tikhonov or Ridge) regularizers will result in very different solutions. For example,
Sanjay Chawla, Federico Girosi, Fei Wang “Data Science and the Policy Completion Problem” The link between policy analysis and data science is more delicate than it may appear. A new policy, by definition, will change the underlying data generating model, rendering classification or supervised learning inapplicable. Perhaps eliciting causal relations from observational data is the
Governments as well as health and accident compensation insurers are grappling to improve health outcomes while keeping spiraling costs under control. These seemingly irreconcilable goals require a careful balance of policy to help stem the tide of ever increasing costs in the health industry. Dr Uma Srinivasan CMC Insurance Solutions CMC Lead Scientist Keywords: Health insurance,