The scientific evidence for the superiority of neurobiological biomarkers over subjective diagnostic methods is supported by a convincing health economic analysis that highlights the hidden costs of current diagnostic inaccuracy.
The hidden cost burden of incorrect diagnoses
The systematic reliability problems of psychiatric diagnostics lead to enormous, often invisible costs in the healthcare system. If major depression only achieves kappa values of 0.28-0.32, this means that over approximately 70% of diagnostic decisions between different specialists do not match. This unreliability leads to a cascade of costly misdiagnoses. (See: https://gtsg.ch/de/interrater-reliabilitaet-in-der-psychiatrie-quantitative-evidenz-fuer-systematische-diagnostikfehler/)
Patients undergo multiple diagnostic cycles, receive inappropriate medications with significant side effects, and require frequent therapy adjustments. The average delay of 9.5 years until a correct bipolar diagnosis is made not only causes enormous personal suffering, but also massive treatment costs due to ineffective therapies and repeated hospitalizations.
Cost-effectiveness analysis of objective biomarkers
Systematic analysis of the five most common mental illnesses shows impressive cost-effectiveness values for EEG-based biomarker analysis systems. With costs between €6,500 and €18,000 per quality-adjusted life year (QALY) gained, these systems are well below the cost-effectiveness thresholds commonly accepted in Europe. By way of comparison, the British health system NICE uses thresholds between €23,000 and €35,000 per QALY, while other European countries consider values between €20,000 and €80,000 per QALY to be acceptable, depending on the severity of the disease. The EEG-based biomarker analysis systems are therefore at the lower end of this scale – they are not only https://gtsg.ch/de/von-subjektiv-zu-subjektiv-und-objektiv-warum-biomarker-die-psychiatrische-diagnostik-revolutionieren/, but also very attractive from an economic point of view. In other words: The new diagnostic methods represent a worthwhile investment because they help patients significantly and cost the healthcare system less than many other established treatments.
The five-year projection for Europe and North America shows a total investment of €398 billion with total savings of €2.01 trillion, representing a net return on investment of 406 percent. This calculation is based on the gradual implementation of EEG-based biomarker analysis systems for the diagnosis of the five most common psychiatric disorders (major depression, anxiety disorders, bipolar disorders, ADHD, schizophrenia). With a total population of 1.12 billion and a current prevalence of 23 percent, approximately 258 million people are affected. The projection takes into account the documented annual increase in prevalence of 2 percent, based on WHO data (25 percent increase in anxiety and depression due to the COVID-19 pandemic in 2020-2021) and CDC surveys (increase from 25.3 to 27.7 percent in children in 2016-2021). Over the five-year period, prevalence increases from 23 to 24.9 percent, representing an average of 268 million people affected per year.
An average of 240 people per 1,000 inhabitants are diagnosed with these disorders, which corresponds to 1.2 devices per 1,000 inhabitants (device capacity: one system for up to 200 patients per year, two systems for up to 500 patients, three systems for up to 1,000 patients). Per 1,000 inhabitants, the investment amounts to €355,000 with savings of €1.8 million. Per 1,000 patients, the cost-effectiveness is even more pronounced: The investment of €296,518 over five years (of which €46,481 is for hardware, training, and maintenance, and €250,000 is for ongoing diagnostic costs at €250 per patient) leads to savings of €1.5 million and a net profit of €1.2 million. The break-even analysis shows that the investment pays for itself after just 0.99 years – after that, each diagnosed patient generates continuous savings of €1,500 per year through more precise treatment, fewer failed attempts, and reduced hospitalizations.
The total investment includes the acquisition costs of 1.34 million EEG systems (€30,000 per device), training of medical staff (30 percent of the acquisition costs), complete diagnostic costs per patient (€250 including material costs of €23, personnel costs for EEG technicians of €90 and specialists of €80 at hourly rates of €120 and €160, respectively), AI software and data storage €12, analysis systems €30 reduced by economies of scale for 268 million patients annually from €70 for 1,000 patients, and overhead €15), technical infrastructure, and ongoing operating and maintenance costs (5 percent annually) over five years. The projected savings result from reduced misdiagnoses, avoided ineffective treatment attempts, shortened diagnostic odysseys, targeted drug selection, and significantly fewer psychiatric hospitalizations. These figures are based on conservative estimates (30 percent cost reduction with average treatment costs of €5,000 per patient per year) and only take into account direct medical costs, not the enormous indirect savings from improved work productivity and reduced disability benefits. Without the early implementation of biomarker systems, the increasing prevalence alone will cause additional treatment costs of €263 billion over five years.
Specific savings potential by disorder
In ADHD, EEG-based biomarker analysis systems enable an increase in coverage from 40 to 80 percent of the population with a diagnostic accuracy of 90 percent. This leads to a 25 percent improvement in academic performance and a 38 percent reduction in accident rates, generating significant societal savings.
Pharmacogenetics in depression also shows high cost-effectiveness with ICER values of €25,280-35,430 per QALY. By reducing adverse effects by 30 percent and improving remission rates by 25 percent, costly drug trials are avoided and treatment time is shortened.
In bipolar disorders, regular measurement of specific biomarkers in the blood (nerve growth factors and inflammation levels) enables significantly better early detection of critical phases. This leads to a 42 percent reduction in hospitalizations during manic episodes and a 78 percent improvement in mood stability. The savings from avoided hospital stays exceed the costs of regular laboratory tests many times over.
The reality of implementation: surmountable barriers
The introduction of biomarker systems into clinical routine presents three key challenges, which can, however, be overcome with proven strategies.
First: Uncertain reimbursement. Many medical institutions are hesitant to invest because it is unclear whether and to what extent health insurance companies will reimburse the diagnostic services. This applies to both the purchase costs of the devices and the ongoing diagnostic costs of $250 per patient. Smaller practices and clinics without large budget reserves are particularly dependent on clear billing guidelines.
Second: Complex technical integration. The new EEG-based biomarker analysis systems must be integrated into the existing IT infrastructure—in particular, electronic patient records, laboratory systems, and billing software. This integration requires standardized data interfaces, compatible software versions, and often proprietary connections to various systems. During the transition phase, physicians often have to work with both paper and electronic systems in parallel, which slows down the workflow and reduces acceptance.
Third: Intensive training requirements. EEG technicians need an average of 45 minutes per patient to perform the examination correctly, and specialists need an additional 30 minutes for diagnosis and interpretation using AI-supported analysis systems. These new skills must be taught systematically while regular clinical work continues.
However, successful solution strategies have been documented: University hospitals and academic medical centers are particularly successful pioneers in the implementation of new diagnostic procedures. Their research infrastructure, technical expertise, and financial resources enable them to overcome the teething problems of new systems and develop best practices that smaller institutions can then adopt. Systematic reviews show that over 70 percent of implementation projects involving so-called “champions” – experienced users who act as multipliers and mentors – are successful, while projects without such key individuals fail significantly more often. Transparent communication of treatment successes, for example through case conferences and comparisons of diagnostic accuracy before and after the introduction of biomarkers, significantly increases acceptance and long-term use. These documented success factors have been included in the cost calculations and show that realistic, step-by-step implementation in clinical practice can be successful.
Break-even analysis and development over time
The break-even analysis shows impressive results: EEG-based biomarker analysis systems pay for themselves after just 0.99 years – in other words, practically within the first twelve months. With system costs averaging €30,000 per device and fully calculated diagnostic costs of €250 per patient (including €23 for materials, personnel costs of €170, software of €12, analysis systems of €30, and overheads of €15), the systems quickly generate corresponding savings through more precise diagnostics, avoided mistreatment, and reduced hospitalizations. Per 1,000 patients, the total investment over five years is €296,518, while the savings reach €1.5 million – a net profit of €1.2 million. After the first year, each diagnosed patient continuously generates savings of €1,500 per year.
The phased implementation strategy enables step-by-step investments with immediate returns and takes into account the documented annual prevalence increase of 2 percent for the five most common psychiatric disorders (major depression, anxiety disorders, bipolar disorders, ADHD, schizophrenia). Tier 1 implementations in years 1-2 focus on the best-validated systems for ADHD and depression with high patient numbers (combined prevalence of approximately 27.5 percent) and the fastest returns. These disorders benefit particularly from objective diagnostics, as misdiagnoses and ineffective medication trials are particularly common and costly in these cases. Tier 2 implementations in years 2-4 expand to bipolar disorder (2.6 percent prevalence) and schizophrenia (1 percent prevalence) with longer payback periods due to lower case numbers, but higher overall savings per patient through avoided hospitalizations. This phased strategy minimizes financial risks, enables learning effects from Tier 1 implementations, and addresses the increasing prevalence, which without intervention would cause additional treatment costs of €263 billion over five years in Europe and North America.
Societal perspective: Beyond direct costs
The analysis primarily considers direct medical costs, but underestimates the enormous indirect societal savings. Improved diagnostic accuracy leads to increased work productivity, reduced work disability, and reduced disability benefits. For ADHD alone, a 25 percent improvement in academic performance leads to substantial long-term income gains and reduced social costs.
The psychosocial costs of diagnostic odysseys—loss of trust in the healthcare system, secondary depression due to unsuccessful treatment attempts, and family stress—are difficult to quantify in monetary analyses, but are of enormous social relevance.
CONCLUSION: The economic necessity of objective diagnostics
The health economic evidence is clear: EEG-based biomarker analysis systems represent a highly cost-effective investment. With costs between €6,500 and €18,000 per quality-adjusted life year (QALY) gained, these systems are well below the European cost-effectiveness thresholds. By way of comparison, the British NICE accepts values of up to €35,000 per QALY, while other European countries accept up to €80,000 depending on the severity of the disease. The five-year projection for Europe and North America shows savings of €2.01 trillion on a total investment of €398 billion – a return on investment of 406 percent.
The cost-effectiveness is particularly evident in the rapid amortization: the break-even point is reached after just 0.99 years. Per 1,000 patients, this means that an investment of €296,518 over five years leads to savings of €1.5 million and a net profit of €1.2 million. After the first year, each diagnosed patient continuously generates savings of 1,500 euros per year through more precise treatment, avoided medication trials, and significantly reduced hospitalizations. These rapid returns significantly reduce investment risks and make the phased implementation strategy financially attractive.
The medical necessity of objective biomarkers is underscored by the weaknesses of current diagnostics: In major depression, various professionals achieve only kappa values of 0.28 to 0.32 for diagnostic agreement—scientifically classified as “weak agreement.” Even for the most common psychiatric disorders, the values are below 0.6, which is considered only “moderate agreement.” This diagnostic uncertainty leads to delayed correct diagnoses, ineffective treatment attempts, and significant patient suffering. The average delay in receiving a correct bipolar diagnosis is 9.5 years—almost a decade in which patients suffer from mistreatment and the healthcare system incurs high costs without therapeutic benefit.
The urgency of objective diagnostics is reinforced by epidemiological trends: the prevalence of the five most common psychiatric disorders is documented to be increasing by 2 percent annually. The WHO reports a 25 percent increase in anxiety and depression due to the COVID-19 pandemic, and CDC data show an increase from 25.3 to 27.7 percent among children between 2016 and 2021. Without the early implementation of biomarker systems, this increasing prevalence will cause additional treatment costs of €263 billion in Europe and North America over the next five years alone.
The central question is therefore no longer whether objective biomarkers should be implemented, but how quickly this can be done. The economic evidence is overwhelming: investments in objective diagnostic systems pay for themselves within a year, relieve the healthcare system of trillions of euros, and fundamentally improve the quality of care for millions of patients. Every year without systematic implementation means continued diagnostic uncertainty, avoidable mistreatment, and rising costs, while the number of patients continues to grow. The scientific, medical, and economic evidence speaks for itself: the time for objective psychiatric diagnostics is now.
Biomarker Workshop 2025: From Scientific Evidence to Economic Reality
December 11, 2025 | Zurich (hybrid)
Learn how scientific superiority translates into economic advantages and why biomarker implementation represents an investment in the future of psychiatry.
Registration: https://gtsg.ch/de/biomarker-workshop-2025-2/
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