Afternoon Forum | Optimising Provider Cost Comparisons with Machine Learning-Driven Risk Adjustment

Optimising Provider Cost Comparisons with Machine Learning-Driven Risk Adjustment 

Medical inflation at unsustainable levels is a global concern, prompting insurers to adopt more targeted approaches to claims management. Both locally and internationally, there is growing interest and stricter governance from health insurers and regulators regarding claims and provider management. However, one of the biggest challenges in detecting inappropriate claims and comparing claims across providers is accounting for the wide range of events, services, and patient risks that influence overall claims experience. Insurers are increasingly turning to A.I.-driven solutions for more targeted claims management, especially when addressing the disparity of claims costs at the provider level. This involves using advanced A.I. techniques to identify hospitals or doctors that consistently drive higher than average claims and limiting insurer exposure through mechanisms like customer steerage incentives (e.g. panels) or negotiated payment arrangements. Communicating cost disparities to providers can also be difficult, especially if the conclusions are not backed by robust, peer-reviewed, and well-recognized analytical methods.

In this presentation, we will introduce a methodology that leverages clinical groupers and machine learning models to adjust for key drivers of claims variation. The aim is to enable like-for-like comparisons of event costs across providers. We will explore the approach used to create benchmarks, the metrics considered, and how these support claims comparison and anomaly detection. This technical discussion assumes a foundational understanding of health claims and machine learning technologies.

SPEAKER

Yuan Wei | Analytics Development Lead | Amplify Health

Yuan Wei is the Analytics Development Lead for Provider Management at Amplify Health. With 12 years of experience in healthcare before transitioning into the health insurance industry. Yuan specialises in biostatistics, health economics, and worked with health authorities across Asia on analytical projects related to drug discovery, clinical research, real-world evidence generation and health technology assessments.

At Amplify Health, Yuan is responsible for developing data-driven profiling tools for alternative provider arrangements and overseeing discount monitoring solutions. She holds a degree in actuarial science and risk management, a Master’s degree in biostatistics and a Master’s degree in economic evaluation of health technology. 

FEES

• Complimentary to members
• $30 for non-members

ADDITIONAL DETAILS

• Zoom dial-in link will be shared 1 day before the session.

Registration closing on Thursday, 5 Dec 2024, 12pm .