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.

Timeline and sessions for 1st cohort of Learning Exchange

Open

e-Learning Course structure as envisioned in Feb 2025

Open

Partner: Amref Health Africa

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.

Trainers

• Simona Dobre: is a researcher with an academic background in automatic control and computer science, with a strong interest in modeling across multidisciplinary domains, including health, aerospace, and defense. Since 2018, she has focused on Artificial Intelligence, founding her company, DevAIs . She has consulted on projects such as openIMIS , which supports health financing systems, and the BRCCH Alex team, where she contributed to the development of a digital health assistant for pediatric asthma in
  Romania. Passionate about applying her expertise across various fields, she believes that all work should be guided by responsibility and ethics.

• Tim Ohlenburg: is currently a consultant in digital social protection and a PhD candidate in the Computer Science Department of University College London, working on proxy means testing, which is a type of AI system He has been documenting AI policy developments in publications of GIZ, the Asian Development Bank and the World Bank, and given online and in person workshops and seminar sessions on the topic. Before going back to university, he mainly worked as a development economist, including as an ODI Fellow at Sierra Leone's finance ministry and as Country Economist for the International Growth Centre based at the Bank of Uganda

Country cases

During the transfer workshop in Nairobi / Kenya (17-19 March 2025) all country delegations presented on the background, opportunities and challenges for AI in their specific context.

• Kenya

  • Dr. Kuhora Samuel, Social Health Authority, Head, Benefits Design and Claims Management, Kenya

  • Mr. David Dawe, Social Health Authority, Claims and Management Department, Kenya

• Tanzania

  • Mr. Rashid Amour, National Health Insurance Fund (NHIF), Tanzania (mainland)

  • Mr. Hafidh Abubakar Ali, Zanzibar Health Service Fund (ZHSF), Tanzania (Zanzibar)

  • Ms. Msahna Rahma, GIZ Tanzania, Technical Advisor (bilat. health program) Tanzania (mainland)

• Ghana

  • Mr. Annor-Darkwah Joe, National Health Insurance Authority (NHIA), Deputy Director, MIS Business, Systems & IT Projects, Ghana

  • Mr. Theophilus, Owusu-Ansah, National Health Insurance Authority (NHIA), Deputy Director and Head of the NHIA Claims Processing Center (CPC), Ghana

• Nigeria

  • Ms. Buba Rasheeda, Kaduna State Contributory Health Management Authority (KADCHMA), Principal Programme Analyst / Head of ICT, Nigeria (Kaduna State)

  • Dr. Kurfi Abubakar M; Head of Policy, Planning and International Collaboration Division Nigeria (national level), National Health Insurance Authority, Nigeria

• Nepal

  • Mr. Tinkari Suresh Singh, Health Insurance Board (HIB), Senior IT Officer Nepal

  • Dr. Mr Koju, Roshan, Social Security Fund (SSF), IT Director Nepal

  • Mr. Sapkota, Purushottam, GIZ Nepal, Technical Advisor (bilat. health program S2HSS II), Nepal

• Cambodia

  • Ms. Sok Sina, National Social Security Fund (NSSF), Deputy Head of Office for Treatment and Healthcare Services, Cambodia

  • Ms. Tek Thida, National Social Security Fund (NSSF), Deputy Director of IT Department Cambodia

  • Mr Sem Sopheak, National Payment Certification Agency as part of National Social Security Fund (NPCA)

  • Mr. Chun Senchheang, GIZ Cambodia, ICT and Digitalization Advisor to the Improving Social Protection and Health, Cambodia