đ Global Health Is Becoming More Expensive â From the USA to the Pacific, FMTVDMÂŽ FRONTIER Transforms Healthcare Systems
- Richard M Fleming, PhD, MD, JD

- 3 days ago
- 7 min read
Global health systems are spending more while getting less: rising budgets, persistently high late-stage disease burden, and diagnostic variability that drives unnecessary care and missed opportunities for prevention.
FMTVDMÂŽ FRONTIER is a patented platform for absolute calibration and quantification of regional blood flow and metabolism in PET/SPECT that replaces subjective imaging with reproducible measures. By shifting systems from âseeingâ to measuring, it reduces waste, improves early detection, and unlocks large fiscal and health returns across income levels.
â ď¸ The problem: spending blind, outcomes stalled
Late-stage detection fuels high-cost hospitalizations, prolonged therapies, and poor functional outcomes.
Subjective interpretation and inter-reader variability create inconsistent care pathways and avoidable procedures.
Non-reproducible imaging prevents pooled learning, slows clinical progress, and fragments policy decisions.
Escalating costs without proportional gains leave governments paying more per health outcome, threatening sustainability and equity.
"A pragmatic credo: countries that measure can manage resources and improve outcomes; those that guess will continue to spend inefficiently."
--- Dr. Richard M. Fleming, PhD, MD, JD
đŹ The solution: measurable medicine at scale
FMTVDMÂŽ FRONTIER delivers core capabilities that realign incentives and outcomes:
Early detection before symptoms through calibrated, quantified perfusion and metabolism.
Standardized interpretation across nations via absolute calibration and harmonized metrics.
Real-time therapy monitoring to optimize treatment duration and intensity.
A.I.2 - supported health planning built on calibrated, comparable data rather than proxies.
Reduced spending and improved survival driven by fewer advanced interventions and better-targeted care.
Mechanically, earlier detection plus reproducible monitoring reduces advanced therapies, shortens hospital stays, compresses morbidity, and improves longevity.
đ Economic model and regional impact
Conservative global model (transparent assumptions): baseline global health spend US$10.0T; business-as-usual growth 5% annually; with broad FMTVDMÂŽ adoption conservative growth reduces to 3% annually; time horizon 10 years.
Result: year-10 spending difference â US$2.85T; cumulative 10-year savings â US$14.0T under conservative assumptions. With broader, realistic adoption and integrated prevention, modeled regional impacts approach US$16â16.5T cumulative savings over 10 years.
Representative regional case study table:
1) The current global picture â hard numbers
Global health spending surged during the pandemic and remains massive: estimates put global health spending near US$9.8â10.0 trillion (about 10% of world GDP) in recent years.
National examples: the United States spent roughly US$4.9 trillion on health in 2023 (âUS$14,570 per person), with growth of ~7â8% in 2023.
Wide international variation: per-capita health spending ranges from under US$1,500 to over US$12,000 depending on country; OECD averages and peer comparisons show many nations spending much less per person but facing similar outcomes challenges.
Disease burden driving costs: noncommunicable diseases (NCDs) â especially cancers, cardiovascular disease, diabetes, chronic respiratory disease â create a massive economic burden. Recent analyses estimate the global economic burden of cancers and related NCDs in the trillions of dollars across coming decades.
(Sources: WHO Global Spending on Health reports & database, World Economic Forum / Our World in Data, Health Affairs / CMS, OECD country comparisons, peer-reviewed economic burden studies.)

2) Why increasing spending hasnât reliably translated to proportional health gains
Much spending is reactive (late-stage care, expensive hospitalizations, high-cost pharmaceuticals), not preventive.
Diagnostic limitations (qualitative imaging, variable interpretation, non-standardized metrics) lead to missed early disease windows and inefficient therapy choices.
Fragmented data and non-harmonized imaging standards impair rapid learning and population-level prevention programs.
The result: rising costs with only incremental improvements in many outcome metrics (life expectancy stagnation in some countries, persistent NCD mortality, large gaps in disability-free life years).
(These patterns are visible in cross-country data and WHO analysis showing that pandemic-era spending spikes were not always sustained in per-capita government health budgets; rising costs remain concentrated in hospitalization, drugs, and specialized care.)
3) How FMTVDMÂŽ FRONTIER changes the economics â mechanisms
FMTVDMÂŽ FRONTIER is designed to alter the drivers of cost and poor outcomes:
Early detection (quantified perfusion + metabolism): catches disease before costly late-stage care is needed.
Absolute quantification and reproducibility: reduces inter-reader variability and avoids unnecessary or ineffective treatments.
Data-driven screening & resource allocation: targets population screening where it most reduces morbidity and cost.
Standardized calibrated measures: enable cross-center comparability, pooled research, and faster clinical learning.
Mechanistically, earlier detection + better monitoring â fewer advanced therapies, fewer complications, shorter hospital stays, and better long-term functional outcomes.
4) A conservative global savings model (transparent assumptions)
Below is a simple, conservative modeled scenario to make the cost impact concrete. We show two plausible trajectories for global health spending starting from a US$10.0 trillion baseline (round number consistent with recent WHO/WEF figures).
Assumptions (transparent):
Baseline global health spend = US$10.0 trillion today (rounded).
âBusiness as usualâ annual growth = 5.0% (reflecting continued cost pressures, aging, tech costs).
With FMTVDMÂŽ adoption at scale, we model a conservative reduced growth = 3.0% annually (reflecting efficiency gains from earlier detection, treatment optimization, and fewer late-stage costs).
Time horizon = 10 years.
Results (arithmetically exact):
Annual spending after 10 years at 5% growth:
10.0T Ă (1.05)^10 = â US$16.29 trillion per year.
Annual spending after 10 years at 3% growth:
 10.0T Ă (1.03)^10 = â US$13.44 trillion per year.
Annual difference in year 10: â US$2.85 trillion (16.29T â 13.44T).
Cumulative 10-year savings (sum of year-by-year differences) â US$14.0 trillion over the decade under these assumptions.
(Calculation note: figures are compound-growth calculations.)
Interpretation: even conservative efficiency of a couple percentage points in annual growth results in trillions of dollars of global savings over a decade â money that can be reinvested in prevention, primary care, social determinants, or economic development.
5) How those savings translate to better health, not just smaller bills
Money saved is useful â but the key is value: more healthy years per dollar. FMTVDMÂŽ can deliver value in multiple ways:
Fewer late-stage interventions: expensive surgeries, extended chemo regimens, ICU stays decrease â freeing capacity.
Improved quality of life: earlier, less invasive treatments preserve function and reduce disability.
Longevity gains through prevention: catching progressive disease earlier reduces mortality and years lived with disability.
Stronger productivity and GDP effects: healthier populations are more economically productive; reduced disability lowers social welfare costs.
For context, long-range economic analyses of NCDs and cancer place the economic burden of these diseases in the tens of trillions over coming decades â preventing even a modest share of advanced disease yields enormous economic and human returns.
6) Realistic scenarios â conservative & optimistic
Conservative scenario: Partial national rollout reduces advanced-stage treatment volume by 10% and slows per-capita spending growth by ~2 percentage points (e.g., 5% â 3%).
Result: multi-trillion dollar savings globally in 10 years (see model above) and measurable reductions in late-stage mortality/morbidity.
Optimistic scenario: Widespread global adoption, integrated with A.I.2 analytics and prevention programs, reduces advanced-stage care by 25â40% and slows spending growth by 3â4 percentage points across many countries.
Outcome: very large cumulative savings, substantial compression of morbidity, and measurable increases in healthy life expectancy.
(These are modeling scenarios for planning, not promises â actual results depend on deployment scale, adherence, local costs, and health-system integration.)
7) Why governments and payers should view FMTVDMÂŽ as an investment, not an expense
Deployment requires upfront capital for scanners, software, training and calibration â but the payback comes from prevented high-cost events, better therapy targeting, and reduced waste.
The SNS (Select Nation Status)/pilot-to-scale pathway supported by FMTVDMÂŽ can concentrate early ROI in pilot regions, demonstrate savings, then scale nationally.
The real metric: cost per healthy life year gained (value-based); FMTVDMÂŽ improves that ratio by increasing diagnostic precision and reducing unnecessary interventions.
8) Practical next steps for policy makers & health systems
Pilot FMTVDMÂŽ in a defined national or regional program (e.g., cancer screening + therapy monitoring) with pre-specified economic and clinical endpoints.
Collect harmonized, calibrated data (FMTVDM quantitative metrics + outcomes) to demonstrate real-world effect and refine deployment.
Scale with value-based payment arrangements so savings and quality gains benefit providers, payers, and patients.
Invest saved resources into primary care, prevention, and social determinants to multiply health gains.
đď¸ Pathway to impact: Select Nation Status (SNS) and policy steps
Pilot with pre-specified endpoints â launch targeted national or regional pilots (e.g., oncology screening + therapy monitoring) to demonstrate clinical and economic ROI.
Create Select Nation frameworks â countries adopting FMTVDMÂŽ become Select Nations with exclusive calibration centers, training/certification, and diplomatic recognition for measurable medicine.
Mandate harmonized metrics â require calibrated FMTVDM quantitative measures in procurement and reimbursement to enable pooled research and fair comparison.
Safeguard A.I.2 deployment â integrate A.I.2 only after domain-specific validation with clinician oversight to prevent hallucinations, miscalibration, and wasteful follow-ups.
Adopt value-based payment models â align incentives so providers and payers share savings and quality improvements.
Reinvest savings â channel demonstrated savings into primary care, prevention, and social determinants to multiply health returns.
Conclusion
Global health spending is large and rising; continued reliance on subjective, non-reproducible diagnostics perpetuates waste and suboptimal outcomes.
FMTVDMÂŽ FRONTIER converts imaging into an absolute, calibrated data source that enables early detection, consistent monitoring, and evidence-driven policy. Even conservative adoption scenarios show multi-trillion-dollar global savings over a decade; with committed pilots, harmonized standards, and validated A.I.2 integration, nations can secure fiscal sustainability, improved survival, and unified, resilient health systems. Deploying quantified diagnostics and theranostics is an investment in measured health sovereignty, not an optional expense.
Sources and Key References (representative):
WHO â Global spending on health: Emerging from the pandemic (Global Health Expenditure Report 2024).
World Bank Health Expenditure Database (2024).
World Economic Forum / Our World in Data â global spending ~US$9.8T (2021â2022 baseline).
Health Affairs / CMS national health expenditure reports â U.S. spending â US$4.9T (2023).
OECD â per-capita comparisons and OECD averages; OECD Health Statistics (2024).
Fleming RM. FMTVDM FRONTIER â The Standard for a Calibrated, Quantifiable Medical World (2024).
Chen S. et al. (2023) â estimates of the global economic cost of cancers and disease burden studies.





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