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Can health insurance data be used to develop AI models capable of predicting cancer? A research team at MHH, in collaboration with an IT company and two health insurance providers, aims to find out. The goals: to identify individual disease risks early, develop strategies for risk communication, and improve healthcare.
In Germany, approximately 518,000 people are newly diagnosed with cancer each year, and the trend is rising. For those affected, the disease is usually associated with significant physical and psychological strain, and it often results in high treatment costs for the healthcare system. Through prevention and early detection, the chances of successful treatment can be increased, and the progression of the disease can be slowed or even halted. At the same time, costs for the healthcare system can be reduced. This is precisely where the ROKAVI project comes in. The acronym ROKAVI stands for Risk Prediction in Oncology: Development of an AI Algorithm, Patient Preferences, and Ethical Implications. Under the leadership of the Institute for Epidemiology, Social Medicine, and Health Systems Research at Hannover Medical School (MHH), AI-based models for the early detection of disease risks are to be developed using health insurance data
Data with Great Potential
The impetus for the project came from the Health Data Use Act (GDNG), which took effect in 2024. It allows statutory health insurance providers to use routine data to inform insured individuals about their individual health risks. A key area of this data-driven health prevention concerns cancer. “We are investigating whether AI-based algorithms for assessing cancer risk can be developed using health insurance data—such as diagnoses, services provided, and sociodemographic information,” explains ROKAVI project leader Prof. Dr. Christian Krauth from the Institute of Epidemiology, Social Medicine, and Health Systems Research at MHH. His team, which includes health scientists Dr. Kathrin Krüger and Viktoria Wiesner as well as statistician Laura Böhme, aims to explore the potential of predictive models that health insurance companies could use to inform their policyholders. One of the project’s partners is the IT company ITSC GmbH, which has several years of experience implementing data-driven projects for statutory health insurance providers. The participating health insurance providers, Pronova BKK and mkk – meine krankenkasse, are making their routine data available to ROKAVI. Together, they have more than 1.3 million insured members. Other partners include the statutory health insurance provider BKK 24 and the Comprehensive Cancer Center Hannover (CCC Hannover).
Comparing Innovative and Traditional Models
In the ROKAVI project, researchers first identify which types of cancer—such as prostate, breast, lung, or colorectal cancer—are particularly well-suited for a predictive model. They then develop a traditional statistical model and an innovative model based on artificial intelligence (AI) for a selected type of cancer. These models will be compared in terms of their predictive accuracy to identify the most suitable one. “One of our hypotheses is that an AI-based algorithm for predicting cancer provides more precise risk assessments than traditional statistical models,” says Professor Krauth.
Ethical Guidelines for the Use of Predictive Models
The second part of the project involves creating an ethical framework for the use of predictive models and developing appropriate risk communication strategies for cancer prediction. To this end, the MHH team is drawing on the expertise of the CCC Hannover. Among other things, the project aims to determine whether, to what extent, and in what form insured individuals wish to receive information about their cancer risk. This is intended to safeguard the insured individuals’ right to informational self-determination. The MHH team is also interviewing representatives of health insurance companies to gather their assessments of the benefits and risks of the developed predictive model. Based on the results, the ROKAVI team will then formulate recommendations for the use of predictive models.
Can positive experiences be applied to Germany?
ROKAVI launched in April and is funded for three years with approximately one million euros from the Innovation Fund of the Joint Federal Committee. In Germany, there is as yet no experience with prediction models based on routine data from health insurance companies. “International studies show that such models support the prevention and early detection of cancer, lead to better patient care, and can also reduce healthcare costs,” says Professor Krauth. He is therefore eager to find out whether this could also apply to Germany.
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Further information can be found here: https://www.mhh.de/en/institute-for-epidemiology/research/research-focus-health-...
For further information, please contact Prof. Dr. Christian Kraut, krauth.christian@mh-hannover.de.
Exploring the potential of AI in the early detection of cancer: Dr. Kathrin Krüger, Viktoria Wiesner ...
Copyright: Karin Kaiser/MHH
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