AI in Health Insurance (Learning exchange with Amref)

Background

In the realm of health insurance, the evolution from traditional Business Intelligence (BI) to Artificial Intelligence (AI) marks a transformative leap. AI can be incredibly useful in health insurance due to its ability to process large amounts of data quickly and detect patterns that humans might miss, which is of critical importance especially in claims in adjudication and fraud control. Automated processing of claims by extracting information from medical records and medical guidelines or policy rules help with real time decision support and anomaly detection for identifying fraud. Further, due to pattern recognition and machine learning, AI could be used in predictive analytics, natural language processing (NLP) and workflow optimization due to the ability to prioritize high risk claims. Some health insurance agencies have already started to benefit from implementation of AI to streamline claims processing, improve accuracy in adjudication, and enhance fraud detection capabilities, ultimately leading to cost savings, improved efficiency, and better protection against fraudulent activities. However, there are emerging learnings to be considered in implementation regarding data governance, standardization & quality, regulatory compliance, continuous learning, data privacy, security and ethical concerns.

Description

For the benefit of policy makers and practitioners working in the space of health insurance, Amref and GIZ are developing an open-source e-learning course that covers both the use and implementation considerations for AI in health insurance. To begin with the focus would be claims adjudication and fraud control. As the course is targeted at policy makers and practitioners, Amref and GIZ are envisioning to develop course material based on practical realities, the country needs and emerging learnings from the country experience. Aligned with the vision, a learning exchange taking advantage of countries experience with AI in health insurance processes is conducted, providing a safe space for exchanging their current practices, with the following learning objectives. Represented countries are Ghana, Nigeria, Kenya, Tanzania, Nepal and Cambodia.

Learning Agenda

• Understand the use of AI for health insurance processes in various countries, especially methods deployed in claims adjudication and fraud control including implementation considerations and emerging learnings from country implementation experience. As countries are at various stages of using AI, this enables cross- ideation and learning from country experience.

• Gain insights from countries on applicability and implementation considerations on innovative developments with relation to AI methods and tools available for claims adjudication and fraud control.

Partner: Amref Health Network

Amref is the largest Africa-based international health development organisation currently implementing over 150 programs in 35 countries and directly impacting about 12 million people.