Using a decision-analysis model for 1,000 Ukrainian PTSD patients, the study estimates MDMA-assisted group therapy with supplemental individual sessions would cost US$1.1m, avert 19.2 deaths, gain 717 QALYs, have an ICER of US$1,537/QALY and produce net societal savings of US$2.6m, with scaled 50% coverage over 10 years potentially saving ~48,000 lives, 1.5 million QALYs and US$5.6bn. These results indicate MAT is likely to be cost‑effective or cost‑saving and could substantially improve population health, supporting its inclusion in Ukraine’s PTSD treatment strategy.
The war in Ukraine has led to widespread trauma, with 6.4 million people suffering from severe, chronic posttraumatic stress disorder (PTSD). This study evaluates the cost‐effectiveness and societal impact of implementing modified group MDMA‐assisted therapy (MAT), with supplemental individual therapy for PTSD treatment in Ukraine. Using a decision analysis model, we estimated clinical benefits, costs, and cost‐effectiveness of MAT for 1000 PTSD patients in Ukraine. The model incorporates PTSD severity, mortality rates, healthcare costs, productivity effects, and caregiver costs. We analyzed outcomes from healthcare payer and societal perspectives over 1‐, 3‐, and 5‐year horizons, projecting scaled‐up impacts for 25%, 50%, and 75% of eligible patients over 10 years. Assuming 3 years of MAT efficacy, treating 1000 patients would cost $1.1 million, avert 19.2 deaths and gain 717 quality‐adjusted life years (QALYs). From a healthcare payer's perspective, MAT is cost‐effective with an incremental cost‐effectiveness ratio of $1537 per QALY gained and a net monetary benefit of $2843. From a partial societal perspective, MAT generates net savings of $2.6 million. Scaled to 50% of eligible patients over 10 years, MAT could save 48,000 lives and gain 1.5 million QALYs, with net societal savings of $5.6 billion. Making MAT available for PTSD treatment in Ukraine is likely to be cost‐effective or cost‐saving, while substantially improving health outcomes. These findings support consideration of MAT as part of Ukraine's strategy to address widespread mental health needs.
Papers cited by this study that are also in Blossom
Agrawal, M., Richards, B. D., Richards, W. A. et al. · Cancer (2023)
Anderson, B. T., Danforth, A. L., Daroff, R. et al. · EClinicalMedicine (2020)
Avancena, A. L. V., Kahn, J. G., Marseille, E. · Clinical Drug Investigation (2022)
Marseille, E., Kahn, J. G., Yazar-Klosinski, B. et al. · PLOS ONE (2020)
Marseille and colleagues frame the study within the substantial mental health burden created by Russia's military aggression against Ukraine, noting large numbers of civilians exposed to trauma and high estimated prevalence of PTSD and complex PTSD. Earlier research and health-system experience suggest existing pharmacological and psychotherapeutic options are frequently inadequate: roughly half of PTSD patients fail to achieve meaningful improvement with standard care. The authors cite Phase 3 trial results showing marked efficacy for MDMA-assisted therapy (MAT) in individual formats and argue that adapting MAT to a group format may be necessary in Ukraine because of severe shortages of trained mental health professionals. This study updates a previously published decision-analytic Markov model to evaluate the costs, health outcomes, and broader societal effects of a modified group-based MAT protocol with supplemental individual sessions in a Ukrainian setting. The investigators model outcomes for a notional cohort of 1,000 PTSD patients, report results from healthcare payer and limited societal perspectives over 1-, 3-, and 5-year horizons, and project scaled-up impacts if 25%, 50% or 75% of eligible civilians receive MAT over a 10-year roll-out. Key outcomes include per-patient MAT costs, quality-adjusted life years (QALYs) gained, premature deaths averted, net costs or savings, and net monetary benefit (NMB).
The analysis uses an annual-cycle Markov model that categorises patients into five PTSD severity states (asymptomatic, mild, moderate, severe, extreme) and follows transitions through these health states until death. The model’s severity distribution at baseline mirrors that observed in 90 participants from a Phase 3 randomised trial; treatment effectiveness is represented as the observed shift in severity distribution from pre- to post-treatment in that trial measured about eight weeks after the final MDMA session. Mortality rates by severity were taken from published sources and scaled to Ukraine using age-specific background mortality as a referent. Health state utilities were derived from EQ-5D-5L data collected in the Phase 3 trial and converted to utility weights for QALY calculation. Costs and QALYs are discounted at 3% per year. Costing used a micro-costing approach based on Ukrainian compensation rates, local costs for screening/laboratory tests, and an estimate for MDMA acquisition costs; a 10% overhead addition was applied to variable costs. Excess healthcare costs associated with PTSD were estimated by regressing per-patient PTSD costs in a 2020 European systematic review on country per-capita health spending and applying the result to Ukraine’s adjusted per-capita spending for 2022. Productivity and caregiver costs were included in the two limited societal perspectives, and a third societal perspective additionally incorporated economic losses from premature mortality. The base-case assumes MAT efficacy persists for 3 years; results are also reported for 1- and 5-year efficacy durations. The modified treatment protocol costed for Ukraine departs from the MAPS Phase 3 individual format and combines group and individual elements to expand capacity. Each patient receives six 60-minute preparatory sessions (three individual, three group), three group-based MDMA dosing sessions (groups of six patients with two therapists), and 12 integration sessions (three group, one individual after each MDMA session), totalling 21 therapy sessions. The model excludes military personnel and assumes scale-up scenarios in which 25%, 50% or 75% of eligible civilians are treated, with 10% of the target population served each year over a 10-year period; incident PTSD cases and implementation-period mortality were not modelled. Sensitivity analyses (univariate and multivariate stochastic) were conducted using @RISK software, and a Ukraine-specific willingness-to-pay (WTP) threshold was estimated at $5,501 per QALY by scaling thresholds from other countries using GDP ratios.
Base-case findings for a cohort of 1,000 patients, assuming 3 years of MAT benefit, indicate net discounted healthcare payer costs of $1.1 million, 717 QALYs gained, and 19.2 premature deaths averted. Under a WTP of $5,501 per QALY, the healthcare payer analysis produced a net monetary benefit (NMB) of $2,843 and an incremental cost-effectiveness ratio (ICER) of $1,537 per QALY in the 3-year scenario. Extending the assumed duration of benefit to 5 years improved cost-effectiveness (NMB $5,716; ICER $595), whereas assuming benefit lasted only 1 year yielded an NMB near zero and an ICER of $5,261 per QALY, which just meets the estimated WTP threshold. When productivity gains and reductions in caregiver costs were included (limited societal perspective), the analysis showed MAT could generate net savings. The authors report societal savings of $2.6 million per 1,000 patients assuming 3 years of benefit; in those broader perspectives MAT in many scenarios was the dominant option (both less costly and more effective). For scaled-up implementation, the model projects that treating 50% of eligible civilians over 10 years could save about 48,000 lives, gain roughly 1.5 million QALYs, and deliver net societal savings on the order of $5.6 billion (reported as a central estimate). Sensitivity analyses identified the cost of MAT and estimates of productivity and caregiver effects for severe PTSD as the most influential inputs. For the 1,000-patient analysis (perspectives including productivity), multivariate stochastic analysis produced a 90% confidence interval for NMB of roughly $3.6–$6.1 million (payer plus productivity) and $5.2–$8.0 million (including premature mortality losses). For the 10-year, 50% uptake scaled scenario, multivariate analyses yielded wide ranges: estimated net costs varied from -$4.3 billion (net savings) to $0.3 billion (90% CI); estimated net savings ranged approximately $3.0–$8.4 billion in multivariate runs. Estimated undiscounted lives saved over 10 years varied from 15,000 to 88,000 (90% CI). Finally, probabilistic results indicated MAT exceeds a 50% probability of being cost-effective at WTP values above about $1,500 per QALY, and approaches near-certain cost-effectiveness by $2,500 per QALY for the base-case perspective; the two broader societal perspectives reach near-certain cost-effectiveness at much lower WTP levels.
Marseille and colleagues interpret their modelling as indicating that introducing a group-adapted MAT protocol in Ukraine would likely be highly cost-effective from a healthcare payer perspective and cost-saving from a limited societal perspective, while producing substantial public health gains. They emphasise that a group-based MAT format reduces per-patient clinician time and thereby increases treatment capacity—an important consideration given Ukraine’s shortage of mental health professionals. The authors situate their findings alongside earlier Phase 3 trial evidence showing strong clinical efficacy for MDMA-assisted therapy in individual formats and cost-effectiveness studies from higher-income settings, arguing that a modified group format can preserve many economic and health advantages while improving scalability. The investigators acknowledge several important limitations. Key model inputs—PTSD mortality risks, severity distribution, and MAT efficacy—largely derive from U.S. data, including a single Phase 3 trial that used individual rather than group therapy; direct evidence for group MAT efficacy is limited. Ukrainian patient populations may differ in trauma type, demographics, and cultural factors in ways that could affect real-world effectiveness. The analysis excludes military personnel, omits incident PTSD cases during the 10-year implementation window, and does not capture many wider societal effects (for example, reduced domestic violence, accidents, or criminal justice involvement). The authors note that productivity benefits from reduced disability were not fully captured, implying their estimates may be conservative with respect to total societal benefit. Finally, they flag implementation challenges—training providers and integrating MAT into existing services—that would need to be addressed if policymakers were to pursue adoption. On policy and research implications, the authors contend the economic and public-health case for MAT in Ukraine is compelling and robust across plausible scenarios, but call for implementation-oriented research to assess real-world effectiveness, feasibility of group delivery, workforce training needs, and context-specific outcomes in the Ukrainian setting.
The study concludes that making MDMA-assisted therapy available for PTSD in Ukraine would probably be cost-effective from the healthcare payer perspective and cost-saving when broader societal impacts are considered, while producing large gains in QALYs and averting substantial numbers of premature deaths. Marseille and colleagues recommend that policymakers consider MAT as part of a comprehensive mental health response, while recognising the need for further research on implementation and outcomes specific to Ukraine and for addressing workforce and service-integration challenges.
The military aggression of Russia against Ukraine has had serious consequences for the mental health of Ukrainians. Numerous studies have documented the detrimental effects of the war on the psychological state of Ukrainian military personnel, civilian combatants, and the general population, with a significant proportion exhibiting symptoms of depression, anxiety and posttraumatic stress disorder (PTSD). It is estimated that around nine million people will suffer from mental health disorders due to Russia's invasion, and around two million will suffer from severe mental health disorders. The war in Ukraine has exposed millions of individuals to traumatic experiences and severe stress, elevating the risk of developing PTSD and other mental health disorders, thereby requiring targeted therapeutic interventions. The significant prevalence of Complex PTSD (CPTSD) and PTSD combined with baroacoustic and other types of brain trauma, underscores the need for interventions specifically addressing PTSD. See Supporting Information: Appendix S1 for details on Ukraine's demographics and the prevalence of PTSD. The majority of treatments utilized in PTSD are nonspecific to the condition and only target select symptoms. Current therapeutic models have been found to be inadequate in addressing the complex needs of individuals affected by the conflict. Over 50% of patients don't respond to the treatment or only experience a mild and often temporary improvement. The need for effective and tailored PTSD interventions is dire. Furthermore, PTSD is a condition often co-occurring with multiple comorbidities, both psychological and physical. Patients suffering from PTSD are at an increased risk for thinking about, attempting, and dying by suicide). In the United States 17 veterans die by suicide every day due inability to remediate their mental health with the therapy options available today (Veterans Administration 2023). Recovery from or improvement in symptoms of PTSD leads to reductions in suicidality and mortalityExisting pharmacological and psychotherapeutic treatments are often only partially effective, with nearly half of PTSD patients failing to achieve significant improvement through standard therapies. The need for more effective treatments is widely acknowledged. Phase 3 clinical trial results demonstrated that after treatment, 67% of MDMA recipients no longer met the criteria for PTSD, compared to 32% of placebo recipients. Addressing mental health in Ukraine is both a humanitarian necessity and an economic imperative. The population's mental wellbeing directly impacts the country's recovery and resilience. Mental health disorders create substantial economic costs through reduced productivity, increased healthcare expenses, and strain on social services. Thus, efficacious treatments that can alleviate the illness serve not only to patient's benefit, but also yield savings to the country's healthcare and social support systems. MDMA-assisted therapy (MAT) has shown advantages over existing treatments in both clinical efficacy and costeffectiveness. US studies indicate that MAT treatment at $11,537 per patient, would generate discounted net healthcare savings of $9.8 million over 5 years per 1000 patients treated assuming 5 years duration of benefit. It would also generate 1158 quality-adjusted years (QALYs), and avert 14.2 premature deaths. These results are based on the treatment format utilized in Phase 3 MAT clinical trial sponsored by the Multidisciplinary Association for Psychedelic Studies (MAPS): Two therapists following a single patient for three MDMA dosing sessions and 12 nondrug therapy sessions. Another recent cost-effectiveness analysis of the same therapistintensive MAPS phase 3 trial regimen also showed favorable cost-effectiveness. However, given Ukraine's severe shortage of mental health professionals and widespread trauma, the treatment model needs modification to serve more patients. A group therapy format has been proposed as a solution to increase treatment capacity. In the Unoted States, group MDMA therapy for veterans has been shown to reduce clinician costs by 50.9% thus nearly doubling the capacity of scarce trained clinicians. This article explores the costs and benefits of making MDMAassisted group therapy available to eligible civilians in Ukraine.
We updated a previously-published decision analysis model to evaluate the clinical benefits, costs, net medical expenses, and gains in productivity for a theoretical group of 1000 patients receiving MAT. This group mirrors the PTSD severity distribution seen in 90 patients who participated in a Lycos-funded, randomized, placebo-controlled, multi-site phase 3 study from November 2018 to May 2020). Our Markov model categorizes patients into PTSD severity levels (asymptomatic, mild, moderate, severe, or extreme) and tracks their progression through these states. Treatment effectiveness is measured by changes in severity distribution between trial start and end. Estimates of mortality rates and medical costs across different PTSD severities were taken from published literature, and health state values were derived from EQ-5D-DL questionnaires filled out by trial participants. The Markov model runs on an annual basis until death, and discounts costs and quality-adjusted life years (QALYs) annually by 3%. Findings are displayed over three time frames, 1, 3, and 5 years. These represent alternative assumptions regarding the duration of MAT efficacy. All cost projections are based on figures from the most recent year available, and the main model inputs are detailed in Table. As described below, the cost of delivering MAT was estimated based on Ukrainian compensation rates, Ukrainian cost for other inputs such as screening and lab tests, and the likely cost of the MDMA itself. We also modeled the excess healthcare
• Given the widespread trauma suffered by the Ukrainian people as a result of Russia's invasion, effective and costeffective treatments for PTSD should be considered by the Ukrainian healthcare system. • Based on a decision model, MDMA-assisted therapy (MAT) shows remarkable cost-effectiveness in Ukraine's context: treating 1000 PTSD patients costs $1.1 million but prevents 19.2 deaths and gains 717 quality-adjusted life years, generating net societal savings of $2.6 million over 3 years. • At scale, implementing MAT for 50% of eligible Ukrainian civilians with PTSD could save 48,000 lives and generate 1.5 million quality-adjusted life years over a decade, with potential societal savings of $5.6 billionmaking it both a humanitarian and economic imperative. care costs, productivity effects, caregiver costs and the costs of early mortality due to PTSD based on a comparison with estimates available in other countries adjusted for differences in per capita healthcare spending and relative wage rates. These estimates were used to calculate the cost-effectiveness of MAT assuming, (1) Healthcare payer's perspective including estimated changes in healthcare costs; (2) limited societal perspective that adds productivity gains and reductions in caregiver costs to changes in healthcare costs; and, (3) same as 2, but with the addition of the economic gains from reduced premature PTSD-related mortality. To project scaled implementation, we modeled scenarios where 25%, 50%, or 75% of eligible patients access treatment. We conducted sensitivity analyses using @RISK® software (Palisade Corporation, v8.1.1) to test both individual variables and combined uncertainties. We also constructed a scenario in which two paid peer assistants are added to the therapeutic team and reported associated net cost and savings.
We report the following outcomes: Per-patient cost of MAT; premature deaths averted; QALYs gained; net costs (or savings) using the healthcare payer's perspective; and using two limited societal perspectives: one that includes productivity effects and caregiver costs; and a second that incudes, in addition, the economic loss due to premature mortality. Cost effectiveness is portrayed as Net Monetary Benefit (NMB). NMB is a measure of cost-effectiveness calculated as incremental benefit multiplied by Willingness to Pay (WTP), minus incremental cost. WTP is the threshold cost per unit of health gained below which an option is considered cost-effective. Compared with the incremental cost-effectiveness ratio (ICER), the NMB has the advantage of putting cost and benefits on a common monetary metric. This method is particularly useful for the current study in which some of our results indicate that MAT generates both net health benefits and net savings. In these circumstances the incremental cost effectiveness ratio is uninterpretable. We therefore include NMB as the primary measure of cost-effectiveness. We also report the ICER in those cases when MAT is not the dominant option.
The model used trial outcomes around 8 weeks after the last MDMA session, comparing the active treatment group's pre and posttreatment states without assuming any treatment change for the control. It reflects the intervention's impact by showing the shift in severity distribution, with patient severity categories and their accompanying mortality rates and utilities maintained from trial end without additional change during the analyses period. Details are provided elsewhere).
The MAPS phase 3 trial on which the present study's efficacy estimate is based, consisted of the following protocol: After initial assessments and three nondrug therapy sessions, participants were given placebo or MDMA in each of three treatment sessions, followed by three psychotherapy integration sessions after each (a total of nine integration sessions). Trained professionals conducted the therapy with a ratio of two therapists to one study participant for each drug-and nondrug session. Details are provided elsewhere. Considering the acute shortage of therapists, the introduction of group therapy for MDMA is being pursued in Ukraine. We therefore costed a modified version of this protocol that is organized around three MDMA sessions, and includes a mix of individual and group therapy sessions with a combined total of 21 sessions. Individual therapy sessions consist of one therapist and one patient; and group sessions consist of two therapists and six patients. MDMA treatment regimen consists of the following: Each patient receives six 60-min preparatory sessions before any MDMA session, three individual and three group sessions. The three MDMA sessions that follow are in the group format. Each of these MDMA sessions is followed by four integration sessions, three in group format and one individual session for a total of 12 integration sessions. See Table.
We used a standard micro-costing approach to estimate the variable cost of delivering MAT per patient served. Each of the elements of the therapy were quantified and assigned a cost. For example, clinician costs are the product of the compensation rate including fringe benefits of each clinician multiplied by the number of hours of each clinician required to deliver the therapy and summed across all clinicians and therapy sessions. In addition, we assessed the cost of screening and testing, and the MDMA itself (Maryna Mormul 2023). We then added 10% to the cost of all of the variable cost elements mentioned above to reflect the incremental MAT-related overhead and administration. See Supporting Information: Appendix S1 for details on the estimation of overhead costs.
We estimated the base-case excess healthcare costs of PTSD using a 2020 systematic review of European countries (von der. Adjusting for inflation, we developed a linear regression model with per-patient PTSD costs as the dependent variable and country per capita healthcare spending as the independent variable. Ukraine's 2020 per capita healthcare spending of $945 (international dollars) was adjusted to $1181 for 2022. Applying the regression model yielded $5304 (international dollars) in excess PTSD costs, equivalent to UAH 14,828 or $507 in 2022 USD at market exchange rates. We assigned this cost to severe PTSD, with costs for other severities adjusted proportionally. Posttreatment costs were assumed to decrease by 20% annually over 5 years, consistent with prior analyses. See detailed explanation in Supporting Information: Appendix and Appendix Figure.
Using the age-specific background mortality rate in Ukraine as a referent (World Health Organization 2024) we set the relative mortality risks at 1.0, 1.74, 2.05, 2.51, and 2.76 for asymptomatic, mild, moderate, severe, and extreme PTSD, respectively. The base-case analysis projects costs and health consequences to 3 years. We also report results at 1 and 5 years.
Health State Utility Values. The EQ-5D-5L (EuroQol) questionnaire was administered to the Phase 3 trial participants, and scores were converted to utilities as used in QALY assessments according to the methods outlined in a 2019 study designed specifically to convert EQ-5D-5L scores utility measures. Adverse events associated with the trial were transient and are not reflected in the current analysis).
Due and 75% of the eligible civilian population in Ukraine. These treatment targets are based on previous modeling studies on the costs and benefits of scaling up mental health treatment services. For simplicity, we assumed that 10% of the target population would be served in each of 10 years. We did not include estimates of incident cases of PTSD, or of mortality over the 10-year implementation period.
To our knowledge, Ukraine has no guidelines regarding the range of acceptable cost-effectiveness thresholds for its healthcare investments. We therefore estimated a cost-effectiveness threshold for Ukraine based on the ratio of per capita GDP between Ukraine and the average thresholds for U.S., and selected European and Asian countries with known thresholds. These thresholds were provided by a targeted literature review conducted in 2020. This approach yielded a cost-effectiveness threshold for Ukraine of $5501. See details in Supporting Information: Appendix Table.
Tabledisplays the results of our analysis for three different analytic horizons 5, 3, and 1 year and from three analytic perspectives: (1) Healthcare payer's perspective; (2) healthcare perspective plus a limited societal perspective that adds productivity gains and reduction in caregiver costs; and, (3) same as 2, but with the addition of the economic gains from reduced premature mortality. Also presented in this section are the results of projected scaled-up access to MAT.
Assuming 3 years of MAT benefit, the Ministry of Health and other healthcare payers would assume net discounted costs of $1.1 million for every 1000 patients receiving MAT. In addition, 717 QALYS would be gained and 19.2 deaths would be averted. Assuming a WTP of $5501 per QALY, MAT should be considered cost-effective in this scenario with an NMB of $2843 and an ICER of $1537. Applying the more favorable assumption of 5 years duration of MAT benefit, yields an NMB of $5,716 and an ICER of $595. Assuming that benefits cease after 1 year, the NMB approximates zero, the ICER is $5261 per QALY, and MAT in this scenario just crosses the threshold for cost-effectiveness, given a WTP of $5501 per QALY. See Table. From this perspective, Ukrainian society saves $2.6 million per 1,000 patients receiving MAT assuming 3 years of benefit. It is the dominant option with an NMB of $6571, and remains dominant assuming only 1 year of benefit (NMB, $1350). Abbreviation: QALYs, quality-adjusted life years. a Undiscounted b MDMA-AT is less costly and yields more QALYs; no cost-effectiveness ratio calculated c Incremental cost-effectiveness ratio (ICER)
We performed both univariate and multivariate stochastic sensitivity analysis to document the likely range of costeffectiveness outcome as conveyed by NMB for each of the three analytic perspectives. For this set of sensitivity analyses we assumed 3 years of MAT efficacy.
The univariate sensitivity analysis in Figure(below) shows the relative impact of the top 10 variables by order of greatest effect on NMB. The cost of MAT has the greatest effect on NMB which ranges from a low of $2.4 million per 1,000 patients assuming the high end of the range of MAT cost as shown in Table, and a high of $3.3 million assuming the low end of the MAT cost range. The variable with the greatest influence is the estimated variation in productivity effects combined with caregiver costs for those affected by severe PTSD. For 1000 patients the NMB of MAT ranged between $4.1 million and $5.7 million given low and high estimates for the value of this input, respectively. The second most influential variable is the cost of MAT for which the NMB varied between $4.4 million and $5.4 million. See Figure. Figuredisplays the result of multivariate sensitivity analysis for the NMB for 1000 MAT patients assuming the healthcare payer's perspective, plus productivity effects and caregiver costs. The 90% confidence interval for the NMB is $3.6-$6.1 million.
Effects, Caregiver Costs and Loss Due to Premature Mortality (Perspective #3) In univariate sensitivity analysis, productivity and caregiver costs associated with severe PTSD had the most influence on NMB, $5.8-$7.4 million, followed by the economic loss due to premature mortality, $5.9-$7.3 million. See Figure. In multivariate sensitivity analysis, net monetary benefit had a 90% CI of $5.2-$8.0 million. See Figure.
This set of sensitivity analyses assumes that 50% of eligible PTSD patients receive MAT over 10 years. Results are presented from each of the three analytic perspectives and assume 3 years of MAT efficacy.
In univariate sensitivity analyses on net costs over 10 years the most influential variable was the cost of MAT ($1.3-$3.4 billion, followed by the number of eligible patients and the discount rate. See Appendix Figure. In multivariate sensitivity analysis the estimated net costs varied from a $1.3 billion to $3.5 billion, (90% CI). See Supporting Information: Appendix Figure. The estimates of the undiscounted lives saved over 10 years is driven by the relative risk of mortality with PTSD and by the number of medically eligible civilians. See Supporting Information: Appendix Figure. Given the uncertainty in these estimates, the number of lives saved varies from 15,000 to 88,000 (90% CI). See Supporting Information: Appendix Figure. In univariate sensitivity analyses the most influential variable affecting net savings was the cost of MAT (savings of $1.0-$3.0 billion), and the second most influential variable was the discount rate (savings of $1.8-$2.2 billion). See Supporting Information: Appendix Figure. In multivariate sensitivity analysis the estimated net costs varied from -$4.3 billion (savings) to $0.3 billion (90% CI). See Supporting Information: Appendix Figure. In univariate sensitivity analyses of net savings the most influential variable were the losses due to premature mortality (-$7.3 to -4.2 billion); followed by the cost of MAT (-$6.6 to -4.6 billion) and the discount rate (-$6.5 to -4.9 billion). See Appendix Figure. In multivariate sensitivity analysis the estimated net savings varied from $3.0 to $8.4 billion (90% CI). See Supporting Information: Appendix Figure.
Since no Ukraine-specific estimates were available, we calculated an approximate willingness to pay for a QALY by inferences from other countries. Our estimate, $5501 per QALY gained, is thus subject to significant uncertainty. We therefore calculated the likelihood of MAT being cost-effective at lower levels of WTP assuming 3 years of efficacy. Using the cost-effectiveness results from 20,000 multivariate simulations, We found that MAT cost-effectiveness exceeds 50% at any willingness to pay above about $1500 per QALY. At $2500 per QALY, the probability of MAT being cost-effective approaches 100%. See Figure. For perspectives #2 and #3 the likelihood of MAT being costeffective approaches 100% at $500 per QALY for perspective #2 and $0 per QALY for prospective #3 (figures not shown).
The war in Ukraine has significantly affected its citizens' mental health. It has also exposed weaknesses in the national mental healthcare system and highlighting the urgent need for enhanced services and resources to meet rising demandsMost trials of MAT to date utilized an individual therapy format in which two therapists are aiding a single patient through their therapeutic journey. The shortage of healthcare professionals makes this therapy approach unsuitable for Ukraine. Group therapy formats are being explored as a tool that could expand access to MAT and other psychedelic-assisted therapies. The adoption of group therapy for a portion of the MDMA treatment protocol both reduces overall per-patient costs, and allow more patients to be treated for a given number of trained clinicians and is thus favored in Ukraine. The economics of a group therapy protocol for MAT analyzed in the context of a trial in the United States found that it could roughly double the number of patients treated for a given number of clinicians. The latter point is particularly relevant if MAT is to be made available at a meaningful scale given the demands on limited mental health personnel.
Several limitations should be considered when interpreting our results. We relied on U.S. data for PTSD mortality rates, severity distribution, and MAT efficacy due to lack of Ukraine-specific data. Our efficacy estimates come from a single Phase 3 trial that did not include group therapy, though early evidence suggests group therapy may also be effective. Patient profiles in Ukraine likely differ from U.S. trial participants in PTSD etiology, demographics, and cultural factors, which could affect MAT efficacy in ways we cannot predict. We excluded military personnel from our analysis since they represent a small portion of the MAT-eligible population, and those with severe treatment-resistant PTSD often transition to civilian status. Our analysis captures productivity gains from averted premature mortality but does not account for gains from reduced PTSD disability. We also omitted other significant societal impacts including reduced domestic violence, accidents, and criminal justice involvement. These omissions suggest that our analysis underestimates the total societal benefits and cost-effectiveness of MAT in Ukraine.
This analysis demonstrates that making MDMA-assisted therapy available for PTSD treatment in Ukraine would likely be highly cost-effective or cost-saving while generating substantial health benefits. Even under conservative assumptions considering only healthcare costs, MAT meets typical cost-effectiveness thresholds. Including broader societal impacts such as improved productivity and reduced caregiver burden strengthens the economic case further, projecting net cost savings. The potential scale of impact is significant. Treating half of eligible patients could save tens of thousands of lives, generate over 1.5 million QALYs, and save billions in societal costs over a decade. These projections remain robust across various plausible scenarios and assumptions. While implementation would require addressing challenges in provider training and integration with existing mental health services, the economic and public health rationale for including MAT in Ukraine's mental health strategy is compelling. Future research should focus on implementation approaches and outcomes specific to the Ukrainian context. Given the scale of Ukraine's mental health crisis and the limitations of current PTSD treatments, policymakers have strong evidence-based reasons to consider MAT as part of a comprehensive mental health response.
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