An aging physician workforce, widening gaps in care, and a steady rise in chronic disease – Germany’s healthcare system is under mounting pressure. Few stakeholders feel that strain more directly than the country’s statutory health insurers. Positioned at the intersection of patients, providers, and policymakers, they see where the system falters – and where it could evolve. Their focus is on tangible solutions: scaling digital health, unlocking the promise of precision medicine, and harnessing AI as a catalyst for more efficient care. And they are certain: Securing the future of healthcare in Germany demands a structural reset. Three leading health insurers share where they see the greatest urgency – and the concrete steps they believe can no longer wait.
Introduction: Growing Pressure on the System
Rising costs on the one hand, declining satisfaction on the other: Germany’s healthcare system is in crisis. Healthcare expenditures in Germany have been rising steadily for years. Over the past decade alone, they have increased by more than half. According to the Association of Substitute Health Insurance Funds (vdek), spending is expected to reach a record level of around €341 billion in 2025. OECD data show that approximately 12.7 percent of Germany’s economic output is spent on healthcare services – placing the country in the top three world-wide.
At the same time, satisfaction among those using healthcare services is declining. Surveys conducted by Techniker Krankenkasse indicate that around one in three adults view the German healthcare system critically. The primary reason is a shortage of medical staff, leading to long wait times as well as regional and sector-specific care deficits. Excessive bureaucracy further exacerbates the staffing shortage.
A sustainable solution has yet to emerge. Although the hospital reform initiated in 2024 and other announced structural measures signal political action, many stakeholders remain skeptical. Current forecasts suggest that the shortage of skilled professionals – particularly in nursing – will continue to worsen. “Without fundamental structural reforms, the solidarity-based system risks reaching its limits,” predicts Andrea Galle, Member of the Executive Board at mkk – meine krankenkasse.
Health insurers know these problems all too well – and they know that time is running out. But what could these reforms look like? What role will artificial intelligence, digital health, and precision medicine play? As part of the P.I.L.O.T. Next Level project, funded by the European Regional Development Fund and the State of Schleswig-Holstein, representatives from three health insurance funds were interviewed – and they provided answers.
Avoiding Disease: Prevention as an Investment
On one point, the health insurance representatives agree: prevention must be at the center of any healthcare reform. Instead of merely treating illness, the system must focus on keeping people healthy and preventing disease from developing in the first place. “We need to create incentives so that it becomes more worthwhile for contracting partners to invest in prevention – meaning we pay less for care and therapy and far more for avoiding future interventions,” says Thomas Bott, Regional Director AOK Rhineland/Hamburg.
Value-based healthcare aligns care delivery with the individual needs of patients and moves away from standardized treatment models. It aims to achieve the best possible outcome for each individual, with patients playing a decisive role in determining whether the priority is pain relief, life extension, or disease prevention. Perceived benefit – measured, for example, through patient-reported outcome and experience measures – determines both the quality and reimbursement of services.
Andrea Galle puts it succinctly: prevention is an investment, not a cost driver. “Every disease prevented is better than the best possible treatment,” she emphasizes. Such transformation does not happen overnight. It requires a fundamental cultural shift and a redesign of reimbursement systems. Preventive measures must be systematically integrated into care pathways: identifying risk factors early, offering comprehensive programs, and embedding supportive structures into everyday life. Reimbursement models should reward avoided cases, not case volumes.
Prevention must become a permanent component of standard care – backed by secure funding.
Andrea Galle
Healthy nutrition and sufficient exercise strengthen prevention. But prevention begins even earlier: health literacy must be taught to children. “We definitely need more health literacy among citizens so they live healthier lives and understand how to stay healthy, so they don’t need treatment in the first place,” says Thomas Bott. He calls for stronger health promotion in daycare centers, schools, and vocational training. “Empowering the insured,” as Sören Schmidt-Bodenstein, Head of the TK Regional Office Schleswig-Holstein, describes it. He underscores that insured individuals must be enabled to take responsibility for their own health.
Source: Unsplash+
Digital Healthcare: From Pilot Project to Everyday Practice
Digital health applications – known in Germany as DiGA – can play an important role in treating established conditions. DiGA are medical devices based on digital technologies designed to deliver positive care effects such as symptom relief or therapy support. They are used, for example, for back pain, diabetes, or depression.
In theory, such apps can also support early disease detection or prevention – for instance, by encouraging behavioral changes in cases of emerging obesity or genetic predisposition. However, pure prevention apps are not eligible for reimbursement under the DiGA framework.
According to the health insurers, Germany’s healthcare system is lagging behind in practical implementation. In 2024, 400,000 DiGA prescriptions were issued. Yet they are often poorly integrated into medical care pathways and rarely embedded in a consistent treatment concept. “Despite political initiatives and legal frameworks, there is still a lack of comprehensive structures, interoperable systems, and consistent integration of digital solutions into everyday care,” says Andrea Galle. In her view, the biggest hurdle for insurers is integrating DiGA into a holistic digital concept that combines effectiveness and cost-efficiency.
Health apps and digital services should be readily available to everyone on their smartphones – from AI-powered symptom checks to online appointment booking and treatment, all the way to medication ordering.
Sören Schmidt-Bodenstein
However, physicians remain skeptical. They receive no feedback on user behavior, which raises doubts about effectiveness. Thomas Bott advises manufacturers: “Involve providers and patients from the very beginning – the people who will ultimately use the product.” After all, DiGA must be more than clinically effective. To succeed, they must integrate into existing care pathways and deliver real added value.
DiGA must consistently address specific needs and close a gap that can realistically be covered by an app.
Thomas Bott
Another point of criticism concerns the rising costs of digital health applications. Under the so-called “fast-track” procedure of the Federal Institute for Drugs and Medical Devices (BfArM), applications can initially be listed in the DiGA directory with an evaluation concept but without full proof of benefit. The goal is to bring innovation into care more quickly and allow manufacturers to further develop applications based on real-world use. Since January 1, 2026, mandatory application-accompanying outcome measurement (AbEM) has also increased transparency: manufacturers must submit anonymized data on usage duration, patient satisfaction, and health status, and BfArM publishes the results in the DiGA directory. However, insurers criticize that DiGA must be reimbursed from the moment they are listed – even if their effectiveness cannot ultimately be demonstrated.
Precision Medicine: Close to the Patient
Targeted cancer therapies enabled by genetic testing or gene injections for spinal muscular atrophy: within just ten years, precision medicine has ushered in a new era of healthcare in Europe. What initially revolutionized oncology is now expanding into more and more medical fields.
Precision medicine refers to a modern medical approach in which diagnostics, prevention, and treatment are systematically tailored to the biological and real-world characteristics of specific patient groups.
At its core is the systematic use of molecular information – such as genomic data, biomarker profiles, or tumor characteristics – supplemented by environmental and lifestyle factors to better characterize diseases and treat them in a targeted manner. Precision medicine aims to provide the right intervention for a clearly defined patient group at the right time and in the appropriate dosage, thereby increasing effectiveness, limiting side effects, and avoiding unnecessary therapies.
Health insurers see significant opportunities in this approach. While patients benefit most, the system also gains. Targeted use of precision medicine conserves resources by avoiding lengthy diagnostic processes or therapies with limited prospects of success. Precision medicine also opens doors in prevention. “Diseases can be detected earlier or even prevented through individualized risk assessments,” explains Sören Schmidt-Bodenstein. A major advantage for patients and insurers alike. Nevertheless, barriers remain. Andrea Galle cites fragmented processes, insufficient data interoperability, and complex approval pathways.
Health insurers therefore see great potential in precision medicine – but also room for improvement. The decisive factor remains: individualized approaches must substantiate their added value with robust evidence. Only then can equity in care and cost-efficiency be secured in the long term.
Precision medicine can only unlock its full potential when knowledge, technologies, structures, and stakeholders work together effectively.
Sören Schmidt-Bodenstein
AI: New Advisor in the Background
Artificial intelligence (AI) detects cancer cells, suggests therapy options, intervenes in complications, and optimizes hospital bed utilization. As in many other industries, AI has entered the healthcare sector – with a broad range of applications.
Artificial intelligence in healthcare refers to digital systems that learn from data and perform tasks that previously required medical or nursing judgment – such as recognizing patterns, predicting risks, or recommending treatment steps. The goal is to make care more precise, efficient, and manageable without replacing the responsibility of healthcare professionals.
For health insurers, process optimization is the primary focus. In administration, AI can take over routine tasks that previously consumed significant time, including claims approval, appointment coordination, or fraud detection. In day-to-day operations, AI is already being used in customer service and communication with insured members.
AI can also provide valuable support in prevention. It helps individuals identify diseases and risks early and receive appropriate recommendations for prevention or treatment. In an age of information overload, well-designed AI could strengthen health literacy by helping people find reliable information, Thomas Bott believes.
However, insurance representatives also want health insurers themselves to act more proactively in prevention. “AI-supported analysis of healthcare data can help identify at-risk patients early and deploy preventive measures more precisely – or simply improve the quality of our services,” explains Andrea Galle. For example, mkk uses AI to detect the risk of long-term care dependency at an early stage and offer targeted support to those affected. According to Galle, such approaches are well received by insured members.
Techniker Krankenkasse advocates a similar model: AI-supported analysis of billing data to identify risks early and provide individualized support. So far, however, data protection concerns have limited broader automated analysis.
But what about reimbursement for AI-supported services such as risk analysis or clinical decision support? First, a clear patient-relevant benefit must be demonstrated. Thomas Bott takes a pragmatic view: “Safety and data protection must be ensured, as must demonstrable benefit. Then AI-supported services can be reimbursed.”
Data at the core
Data form the backbone of the modern healthcare industry. Without high-quality data – defined by accuracy, completeness, consistency, and timeliness – resources remain underutilized and risks such as misdiagnosis persist. Data quality directly determines the effectiveness of AI: only complete and standardized datasets enable precise models, for example for risk prediction. Inconsistent or flawed datasets lead to failure – much like human assessors. Initiatives such as the European Health Data Space therefore promote standardized, high-quality data as the foundation for trustworthy AI.
With the introduction of Section 25b of the German Social Code Book V (SGB V) under the 2024 Health Data Use Act, health insurers can now, for the first time, analyze existing insured member data in a targeted manner. This supports the identification of individual health risks, for example in rare diseases, vaccination gaps, or overdue preventive screenings. Such analyses strengthen prevention and can close care gaps at an early stage. However, the law remains narrowly defined: data use is limited to five specified use cases. In Andrea Galle’s view, this represents a missed opportunity to unlock broader possibilities.
In the end, it is not a lack of data protection that costs lives, but the unused potential when – out of legitimate yet excessive data protection barriers – we forgo insights that could prevent disease or save lives.
Andrea Galle
Techniker Krankenkasse also aims to offer its insured members recommendations that enable effective health management and improved prevention. In its view, insured individuals should decide for themselves which data they wish to share. However, appropriate regulatory frameworks are required. Data protection and health protection must be continuously balanced in their development. “We advocate for better integration of existing health data and their analysis with the help of AI. This can significantly improve the quality of care,” emphasizes Sören Schmidt-Bodenstein.
From TK’s perspective, the electronic patient record (ePA) could play a key role. Health insurers should be able to integrate individualized services into the ePA together with physicians, hospitals, and other providers. This would allow new approaches to be tested more quickly while giving insured members access to a wide range of services. However, this requires structured and complete data within the ePA. Sören Schmidt-Bodenstein therefore advocates for targeted consolidation of existing health data – supported by AI. Health insurers also demand timely data availability. Currently, it can take months before data reach insurers.
Data protection remains important but must not prevent people from benefiting from modern treatment options.
Sören Schmidt-Bodenstein
In anonymized form, patient data could also contribute to the development of new medications and be used by pharmaceutical companies.
Looking ahead: what must change
Health insurance representatives see clear areas for action and offer concrete proposals for advancing the healthcare system. Prevention ranks first: they unanimously call for a shift from a treatment-focused model to one centered on prevention.
Additionally, Thomas Bott emphasizes the stringent development of the workforce: policymakers and industry must systematically build expertise, for example through improved training pathways for physicians and nursing professionals. Digital solutions such as AI and big data offer additional leverage. “The potential of digitalization must be consistently harnessed,” says Sören Schmidt-Bodenstein. This includes not only process optimization but also data-driven risk analysis.
Better use of existing data is also high on insurers’ wish lists. The electronic patient record (ePA) could serve as a central platform for secure and transparent data exchange – a prerequisite for seamless care. This also requires clear standards, for example defining maximum wait times for patient appointments.
Closer cooperation among all stakeholders is equally essential. AOK is already working in project groups with pharmaceutical companies, physicians, the Association of Statutory Health Insurance Physicians, and other insurance representatives. The goal is to develop treatment guidelines for specific patient groups. Andrea Galle advises health insurers, research institutions, and manufacturers to jointly design innovation projects from the outset. This would help establish new approaches more quickly and effectively. Such partnerships could strengthen the resilience of the healthcare system as a whole and drive innovation forward.
Text: Uta Mommert
Cover image: Unsplash+
