Budget Impact Analysis of the EPOCA Telemonitoring System for Elderly Patients in France

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Remote monitoring systems (RMS) have shown promise in improving care coordination and reducing acute care use. The objective of this study is to assess the cost-effectiveness of the EPOCA RMS, implemented within the Vigie-Age framework, compared to standard care (SOC) for older adults with multiple chronic conditions. Methods Using data from the Vigie-Age Article 51 pilot study (722 participants including 408 with long term follow-up), a cost-utility analysis was conducted over a 10-year lifetime horizon. A Markov model with daily cycles simulated transitions across health states: at home, emergency department (ED) visit, hospitalization, and death. Analyses were conducted from both the French National Health Insurance (NHI) and collective perspectives. Direct medical costs, including hospital, outpatient, and intervention costs, were included. Health outcomes were measured in quality-adjusted life years (QALYs). Deterministic and probabilistic sensitivity analyses assessed model robustness. Results EPOCA reduced ED visits by 54% and hospitalizations by 46%, cutting average hospital stay from 55.6 to 30.6 days. Total costs per patient were €29,200 with EPOCA vs. €39,900 for SOC, a €10,700 saving from the societal perspective, and a €7,400 saving from the NHI perspective. EPOCA yielded 0.04 additional QALYs and remained cost-saving even at higher program costs. Sensitivity analyses confirmed the robustness of results. EPOCA had a 90% probability of being dominant and a 95% probability of being cost-effective at a €30,000/QALY threshold. Conclusions EPOCA is a cost-effective strategy for elderly patients at high risk of hospitalization. It reduces healthcare utilization while improving outcomes, supporting its integration into national elderly care pathways and reimbursement by the French NHI. Geriatrics & Gerontology Budget impact analysis Remote patient monitoring Elderly Cost savings Figures Figure 1 Figure 2 Introduction France is undergoing a profound demographic transition marked by a growing elderly population. As of 2024, 10% of the population, equivalent to 7.0 million individuals, are aged 75 or over, and this number is expected to rise to 16% by 2050, representing 12.0 million individuals 1 , 2 . Chronic diseases are highly prevalent among the elderly in France, with 91% of individuals aged 75 and over presenting at least one chronic condition or ongoing treatment. Multimorbidity is also a defining feature of aging: 47% of men and 36% of women aged 75 or older live with two or more chronic diseases, and up to 26% of men and 17% of women in this age group have three or more 3 . Aging also significantly increases the risk of loss of independence. While most seniors remain autonomous until late in life, the share of older adults receiving the French "Allocation Personnalisée d'Autonomie" (APA), a marker of dependency, rises from 2% among 70–74-year-olds to nearly 50% between ages 90 and 94, and three-quarters among those 95 or older 4 . Finally, growing age is accompanied by increased risks of social isolation, particularly among women. Over half of women aged 85 live alone, compared to just 25% of men 4 . These demographic shifts place immense pressure on France’s healthcare infrastructure, which is already strained by shortages of geriatricians and a declining number of general practitioners (GPs). The result is a fragmented and reactive healthcare system, where emergency departments and inpatient services often serve as the default response to complex geriatric needs. Nearly 40% of those aged 80 and above in France are hospitalized annually, with an average duration of approximately 25 days per patient. It is estimated that over 30% of these hospitalizations could have been avoided, with similar figures for emergency department (ED) visits 5 , 6 . These trends underline the urgent need for scalable, home-based care solutions tailored to the evolving needs of an aging, increasingly dependent population. Remote monitoring systems (RMSs) have gained international traction as a promising solution for managing elderly patients with chronic and complex health needs. Existing RMSs vary widely in structure and technology but generally include combinations of wearable sensors, mobile health (mHealth) applications, and care coordination frameworks 7 – 14 . These RMSs are typically multidisciplinary, involving nurses, hospital physicians, geriatricians, and GPs, often with social support services integrated. The majority of these RMS have demonstrated reductions in hospitalizations and emergency visits 9 – 11 , 13 , 14 . Launched in 2019, the Vigie-Age framework is a multidisciplinary hospital-community initiative designed to provide comprehensive, coordinated care for older adults with multiple chronic conditions. Its primary objectives are to enhance quality of life and reduce avoidable hospitalizations through better continuity of care. This framework includes EPOCA, a RMS that is a human-centered with connected telemedicine solution offering secure and continuous home support for complex elderly patients. It is built around a 24/7 telemonitoring platform that enables real-time clinical oversight, rapid response to health deterioration, and seamless coordination among healthcare professionals. The system integrates two core technological components: (1) connected devices, such as a wristband, for transmitting health data or emergency alerts; and (2) a centralized RMS coordination hub staffed by trained nurses and physicians, who engage directly with patients and caregivers when needed. Hospital geriatricians or GPs play a central role in the framework, offering ongoing medical supervision via teleconsultations and tele-expertise, and maintaining active communication with community healthcare teams. In parallel, community-based nurses conduct regular home visits, monitor patient conditions, and deliver essential care services. Vigie-Age has been included in the French “Article 51” experimental framework launched in 2018 to promote innovation in healthcare delivery and financing. Article 51 enables pilot studies of interventions that aim to improve care coordination, efficiency, and patient outcomes through new organizational models and payment structures. These pilots are evaluated for their clinical impact, economic sustainability, and potential for national scale-up, providing valuable data. This study aims to assess the cost-effectiveness of the Vigie-Age framework including the EPOCA RMS compared to standard care, focusing on reductions in hospitalizations, emergency visits, and overall healthcare costs, using real-world data from the article 51 evaluation of the Vigie-Age framework. Methods Data source This cost-effectiveness analysis is primarily based on data from the Vigie-Age Article 51 pilot study. Conducted prospectively between 2022 and 2024 across four hospitals in France, the study enrolled 722 participants. Eligibility criteria included individuals aged 70 years or older with multiple chronic conditions, a history of recent decompensations, and a high risk of further clinical deterioration. The study population was composed of 36.4% men, with a mean age of 87.9 years (standard deviation [SD] = 7.1). Participants experienced an average of 2.0 (SD = 1.4) overnight hospitalizations in the six months preceding study inclusion. Approximately 70% of participants were recruited either during a hospitalization or from a community-based setting, while the remaining 30% were included following an ED visit. The pilot study assessed outcomes related to clinical efficacy (hospitalizations and ED visits), healthcare resource utilization, and associated costs. These outcomes were derived from French National Health Insurance (NHI) reimbursement data and compared between the study follow-up period and a similar period preceding inclusion. Among the 408 participants who received the EPOCA RMS intervention, outcome data were available for 269 individuals with sufficient follow-up, with a mean observation period of 7.5 months. Perspective, Population, Intervention, Comparator This cost-effectiveness evaluation was conducted from two complementary perspectives. The first was a payer perspective, focusing on healthcare expenditures borne by the French National Health Insurance (NHI). The second was a societal perspective, in line with the recommendations of the Haute Autorité de Santé (HAS) 15 , which includes all direct medical costs regardless of the payer. The analysis was conducted on a population corresponding to participants enrolled in the Vigie-Age Article 51 pilot study. The EPOCA RMS intervention was compared to standard care (SOC) as typically provided to this high-risk population under current clinical practice. Model Structure Due to the limited follow-up duration in the Vigie-Age Article 51 pilot study, a Markov model was developed to extrapolate the long-term clinical and economic outcomes of the EPOCA intervention over a lifetime horizon, defined as 10 years based on the average age of the target population. The model used daily cycles and incorporated the following health states: Stable condition at home; ED visits; Hospitalization (either scheduled or via emergency visit); Death (all-cause). Transition probabilities for hospitalizations and ED visits were derived from the Vigie-Age Article 51 pilot study. Based on these data, the model assumes that the EPOCA intervention reduces the frequency of both emergency visits and hospitalizations. However, the probability of hospitalization following an emergency visit, as well as the average length of hospital stay, were assumed to be similar between the intervention and control groups. Additionally, the model assumes that participants in the EPOCA arm retain the intervention’s benefits even after exiting the program. This assumption is supported by pilot study findings, which showed comparable rates of hospitalizations and emergency visits during and after participation in the program. The model also accounted for the recruitment setting. Specifically, it was assumed that patients enrolled in the EPOCA intervention during an ED visit would avoid immediate hospitalization, whereas similar patients under standard care could proceed to inpatient admission. Model parameters are detailed in Table 1 . Table 1 Model Parameters Mean CI in PSA/DSA Distribution Source Transition Probabilities Standard of Care Emergency Department Entry (SOC) 22% Not Inc. Art. 51 Monthly Probability of Hospitalization 1.9 1.8-2.0 Normal Art. 51 Monthly Probability of ED Visits 3.5 3.4–3.6 Normal Art. 51 Proportion of Hospitalizations Following ED Visits 71% 64%-79% Béta Art. 51 Length of Stay (days) 7.7 6.2–9.2 Normal Art. 51 EPOCA Emergency Department Entry (EPOCA) 0% Not Inc. Art. 51 Monthly Probability of Hospitalization 1.3 1.2–1.4 Normal Art. 51 Monthly Probability of ED Visits 1.6 1.5–1.7 Normal Art. 51 Proportion of Hospitalizations Following ED Visits 69% 55%-83% Béta Art. 51 Length of Stay (days) 7.3 5.8–8.8 Normal Art. 51 Patient Characteristics Mean Age 87.9 80.8–95.0 Normal Art. 51 Costs VIGIE-AGE Program €2,210 Not Inc. Assumption Hospitalization – EPOCA (per hospitalization) €3,714 €832-€9,557 LogNorm Art. 51 Hospitalization – SOC (per hospitalization) €3,773 €1,056-€8,873 LogNorm Art. 51 Hospitalization Following ED Visit €4,249 €395-€14,057 LogNorm Art. 51 Emergency Department Visits €52 €44-€61 LogNorm 18 , 19 Outpatient Care – EPOCA (per year) €5,820 €4,656-€6,984 Gamma Art. 51 Outpatient Care – SOC (per year) €5,337 €4,270-€6,404 Gamma Art. 51 Utility General Population Aged 75+ 0.8 Not Inc. 20 Hospitalization (Per Day) -0.0013 -0.0016–0.0010 Béta 21 ED: Emergency Department, SOC: Standard of Care; CI: 95% Confidence Interval; PSA: Probabilistic Sensitivity Analysis; DSA: Deterministic Sensitivity Analysis; LogNorm: Log-Normal; Art. 51: Vigi-Age Article 51 pilot study Costs and Utilities The analysis included only direct medical costs, encompassing hospitalizations, ED visits, outpatient care, and the EPOCA intervention. Hospitalization and outpatient costs were derived from average expenditures observed in the Vigie-Age Article 51 pilot study and were stratified by study arm to reflect differences in the type of hospitalizations and intensity of outpatient follow-up. Hospitalization costs were based on production costs (Echelle National des Coûts), which were directly used for the societal perspective. For the payer (NHI) perspective, tariffs were estimated to be 1.27 times lower than production costs, based on observed differences between actual costs and reimbursements 16 , 17 . Similarly, outpatient care costs were based on tariffs. For the NHI perspective, it was assumed, according to reimbursement rules, that 65% of outpatient costs were reimbursed by the NHI, while the full amount was considered under the societal perspective. Costs of ED department visits were estimated using the average cost per visit, calculated from the total annual funding allocated to emergency services in France 18 and the national number of ED visits 19 . From the NHI perspective, costs were applied only to ED visits that did not result in hospitalization, as the latter were considered part of inpatient costs. The cost of the EPOCA intervention was based on the reimbursement tariff used in the Vigie-Age Article 51 pilot study, with a mean cost of €2,210 per participant per year. A higher value of €4,441 was used in sensitivity analyses. This cost was applied at the beginning of each year to the proportion of patients remaining in the program. Program duration was assumed to be 6 months for 59% of participants and 12 months for the remaining 41%, resulting in an average duration of 8.4 months. This was implemented as a probability of continued participation, with an estimated 22% of participants still enrolled at the beginning of year 2. Health utilities were sourced from published literature, using age-adjusted baseline utilities for the general population 20 and applying disutility weights for each day spent hospitalized 21 . Outcomes and Analysis The analysis compared discounted and undiscounted clinical outcomes, including the mean number of hospitalizations per patient, total hospital stay duration, and the mean number of emergency department (ED) visits leading to hospital admissions, between the EPOCA intervention and SOC. Economic outcomes included mean hospitalization costs per patient, ED visit costs, outpatient care costs, and intervention costs. Quality of life outcomes were measured in quality-adjusted life years (QALYs). A cost-utility analysis (CUA) was conducted, with the primary outcome expressed as the incremental cost-effectiveness ratio (ICER), defined as the additional cost per QALY gained with EPOCA compared to SOC. To evaluate the robustness of the model results, both deterministic and probabilistic sensitivity analyses were performed. Deterministic sensitivity analysis (DSA) explored the impact of key parameters, including costs, transition probabilities, and utility values, by varying them within their 95% confidence intervals or by ± 20% when confidence intervals were unavailable. Results were presented using a tornado diagram to identify the most influential parameters. Probabilistic sensitivity analysis (PSA) was conducted using Monte Carlo simulations to simultaneously assess uncertainty across multiple parameters. Probability distributions were assigned to cost inputs, transition probabilities, and utility values. Results are presented using cost-effectiveness acceptability curves (CEACs). Results Results are presented in Table 2 . Table 2 Cost-Effectiveness and Budget Impact Results EPOCA Standard of Care Difference (% reduction) Resource Emergency Department Visits (n) 2.8 6.1 -3.3 (54%) Hospitalization (n) 4.2 7.8 -3.6 (47%) Hospitalization days 30.6 55.6 -25.0 (45%) Undiscounted Costs per Patient (€) Collection Perspective Program 2,850 0 Emergency Department Visits 145 315 -170 (54%) Hospitalization 12,262 23,226 -10,964 (47%) Outpatient 10,277 9,424 853 (-9%) Total 25,535 32,965 -7,430 (23%) NIH Perspective Program 2,850 0 Emergency Department Visits 465 1,008 -543 (54%) Hospitalization 15,573 29,497 -13,924 (47%) Outpatient 10,277 9,424 853 (-9%) Total 29,165 39,929 -10,764 (27%) Cost-Effectiveness Collection Perspective Discounted QALY 1.30 1.26 0.04 Discounted Total Costs (€) 24,683 31,792 -7,108 ICER Dominant Dominated NIH Perspective Discounted QALY 1.30 1.26 0.04 Discounted Total Costs (€) 28,181 38,510 -10,329 ICER Dominant Dominated Over a lifetime horizon, accounting for background mortality, the model estimated an undiscounted average survival of 1.8 years per patient, with an average duration in the EPOCA program of 8.1 months. During this period, patients in the EPOCA arm experienced an average of 2.8 emergency department (ED) visits and 4.2 hospitalizations, compared to 6.1 ED visits and 7.8 hospitalizations in the standard of care (SOC) arm, representing a 54% and 46% reduction, respectively. The decrease in hospitalizations translated into a reduction in the total number of hospital days, from 55.6 days in the SOC arm to 30.6 days in the EPOCA arm. From the societal (collective) perspective, the undiscounted total cost per patient was estimated at €29,200 in the EPOCA arm, compared to €39,900 in the SOC arm. This difference was driven primarily by reductions in hospitalization (€13,900 savings) and ED visit costs (€540 savings), partially offset by an increase of €900 in outpatient care costs. After incorporating the program cost (€2,800), the net savings amounted to €10,800 per patient. Similar cost savings were observed under the NHI perspective, with total savings of €7,400 per patient. These included €11,000 in reduced hospitalization costs, €200 in ED savings, and an €800 increase in outpatient costs, with program costs assumed equal across perspectives. Importantly, EPOCA remained cost-saving even when applying the higher intervention cost of €4,441 used in sensitivity analyses. In terms of health outcomes, the EPOCA arm was associated with 1.30 discounted QALYs compared to 1.26 QALYs in the SOC arm, a gain of 0.04 QALYs, primarily attributable to reduced hospitalizations and associated improvements in quality of life. Discounted total costs were €23,200 for EPOCA and €29,500 for SOC from the collective perspective, yielding net savings of €6,300. Given that EPOCA resulted in both lower costs and improved outcomes, it was considered a dominant strategy compared to SOC. Similar conclusions were observed in the NHI perspective, with €3,900 in total cost savings. EPOCA remained dominant at the higher intervention cost of €4,441 in both perspectives. Deterministic sensitivity analysis (Fig. 1 ) identified the average cost of hospitalization as the most influential parameter in the NHI perspective and the mean age at inclusion, and cost of hospitalization as the most influential parameters in the collective perspective. However, even under lower hospitalization cost scenarios, EPOCA remained cost-saving or cost-neutral confirming the robustness of the model’s conclusions across parameter ranges. Probabilistic sensitivity analysis (Fig. 2 ) further supported these findings. From the collective perspective, EPOCA had a 90% probability of being the dominant strategy and a 95% probability of being cost-effective at a willingness-to-pay threshold of €30,000 per QALY. From the NHI perspective, these probabilities were 80% and 87%, respectively. Discussion This cost-effectiveness analysis shows that the EPOCA RMS significantly reduces avoidable hospitalizations and ED visits in frail, polypathological older adults. Over a modeled lifetime horizon, EPOCA was associated with a 54% reduction in ED visits and a 46% reduction in hospitalizations, resulting in a 25-day decrease in cumulative hospital stay per patient. These reductions led to a cost savings of €10,800 per patient from the collective perspective and €7,400 from the French NHI perspective. Notably, even under conservative assumptions for the program costs and sensitivity analyses, EPOCA remained a dominant strategy, offering better outcomes at lower costs. These results are consistent with the Article 51 pilot study and real-world data from a retrospective observational studies of the EPOCA system 22 . In both hospital-led and GP-led implementations, EPOCA was associated with sharp declines in hospitalizations (− 48% to − 57%), ED visits (− 48% to − 62%), and hospital stay duration (− 49% to − 63%) within just one year of follow-up. International evidence supports the observed outcomes of EPOCA. Similar RMS systems have demonstrated reductions in hospital use, with relative risk reductions up to 57%, 28% in unplanned hospitalizations and 33% in ED visits 7 , 9 – 11 , 13 , 23 . EPOCA appears to achieve higher magnitudes of effect, possibly due to its integration into a comprehensive care coordination model involving both hospital and community actors, including nurses, general practitioners, and geriatricians. Additionally, unlike some RMS systems, which may inadvertently increase ED use due to over-alerting 10 , EPOCA’s design emphasizes triage, anticipatory care, and direct intervention, which could contribute to a true reduction in ED burden. In terms of cost-effectiveness, international evidence also supports the outcomes observed in this study. Previous evaluations of RMS have reported per-patient savings ranging from approximately €1,000 to €2,800 11,24,25 , including program costs, which are on the lower end of €7,400 to €10,800 in net savings estimated in this analysis. These findings have several important implications for health policy. First, EPOCA’s demonstrated effectiveness in both clinical and economic dimensions supporting its integration into national care pathways for older adults. Second, the program’s net savings from the NHI perspective support the case for full reimbursement, particularly in light of demographic aging and increasing chronic disease prevalence. Moreover, EPOCA responds to systemic challenges faced by the French healthcare system: high hospitalization rates among the elderly, under-resourced primary care, and fragmented coordination between community and hospital-based care. By reducing hospital reliance and enabling safe, structured home care, EPOCA contributes directly to system efficiency and sustainability. Despite these promising findings, several limitations must be acknowledged. First, the base data from the Vigie-Age Article 51 pilot study involved limited follow-up, requiring extrapolation through Markov modeling. Although sensitivity analyses confirmed the robustness of results, longer-term data will be necessary to validate projections. Second, there was significant variability in available hospitalization costs, potentially impacting cost estimates. Third, outpatient cost data were partially incomplete, particularly for non-reimbursed services, which may have led to conservative cost assumptions. Finally, while the program likely reduces caregiver burden through improved coordination and reduced crisis care, these effects were not directly measured and warrant further investigation. In conclusion, Vigie-Age including the EPOCA RMS is a cost-effective intervention for managing elderly patients at high risk of hospitalization. It not only reduces acute care utilization but also improves quality-adjusted life expectancy and lowers total healthcare costs. From the NHI perspective, the budget impact is neutral to favorable. Supported by real-world implementation data and consistent with international best practices, EPOCA has strong potential for national scale-up. Embedding such models within France’s elderly care infrastructure could enhance care quality, reduce hospital pressure, and better address the needs of a rapidly aging population. References INSEE (2020) Accessed 03/25/2025. https://www.insee.fr/fr/statistiques/4277619 INSEE, Bilan démographique (2024) Accessed 03/25/2025. https://www.insee.fr/fr/statistiques/8327319 Bagein G, Costemalle V, Deroyon T et al (2022) L’état de santé de la population en France. Vol. 102. 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Telemed J E Health Sep 19(9):652–657. 10.1089/tmj.2012.0244 Kokkonen J, Mustonen P, Heikkilä E et al (2024) Effectiveness of Telemonitoring in Reducing Hospitalization and Associated Costs for Patients With Heart Failure in Finland: Nonrandomized Pre-Post Telemonitoring Study. JMIR Mhealth Uhealth Feb 7:12:e51841. 10.2196/51841 Additional Declarations The authors declare potential competing interests as follows: DT, MD and EC are employees of EPOCA U&I Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6518753","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":447449009,"identity":"5c54d3d9-725e-4391-be4b-0d659481b0d7","order_by":0,"name":"Henri Leleu","email":"data:image/png;base64,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","orcid":"","institution":"Public health expertise, Paris - 75004, France","correspondingAuthor":true,"prefix":"","firstName":"Henri","middleName":"","lastName":"Leleu","suffix":""},{"id":447449010,"identity":"6d2c6791-cbf1-4d9f-958f-1df57bc6133b","order_by":1,"name":"Damien Testa","email":"","orcid":"","institution":"EPOCA U\u0026I, Nanterre - 92000, France","correspondingAuthor":false,"prefix":"","firstName":"Damien","middleName":"","lastName":"Testa","suffix":""},{"id":447449011,"identity":"dc28a1de-e3c5-4a0d-af60-9659203fe169","order_by":2,"name":"Mireille Dutech","email":"","orcid":"","institution":"EPOCA U\u0026I, Nanterre - 92000, France","correspondingAuthor":false,"prefix":"","firstName":"Mireille","middleName":"","lastName":"Dutech","suffix":""},{"id":447449012,"identity":"f84ec62e-cde7-411d-8792-409ce9072c2f","order_by":3,"name":"Elise Cabanes","email":"","orcid":"","institution":"EPOCA U\u0026I, Nanterre - 92000, France","correspondingAuthor":false,"prefix":"","firstName":"Elise","middleName":"","lastName":"Cabanes","suffix":""}],"badges":[],"createdAt":"2025-04-24 08:37:35","currentVersionCode":1,"declarations":{"humanSubjects":false,"vertebrateSubjects":false,"conflictsOfInterestStatement":true,"humanSubjectEthicalGuidelines":false,"humanSubjectConsent":false,"humanSubjectClinicalTrial":false,"humanSubjectCaseReport":false,"vertebrateSubjectEthicalGuidelines":false},"doi":"10.21203/rs.3.rs-6518753/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6518753/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":81962485,"identity":"50e15884-9186-4b04-8552-75c17bfb2ca1","added_by":"auto","created_at":"2025-05-05 11:12:35","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":167660,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eDeterministic Sensitivity Analysis Results\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA: Collective Perspective, B: National Health Insurance Perspective; SOC: Standard of Care: ED: Emergency Department\u003c/p\u003e","description":"","filename":"Capturedecran20250424a13.52.31.png","url":"https://assets-eu.researchsquare.com/files/rs-6518753/v1/67968ebcb5aba517a49b4481.png"},{"id":81963563,"identity":"f8fb4622-fd65-4c3e-92bc-977541e34aff","added_by":"auto","created_at":"2025-05-05 11:20:35","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":137019,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eProbabilistic Sensitivity Analysis Results\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA: Collective Perspective, B: National Health Insurance Perspective\u003c/p\u003e","description":"","filename":"Capturedecran20250424a13.54.04.png","url":"https://assets-eu.researchsquare.com/files/rs-6518753/v1/f0d19b8f2e8306b1cba39674.png"},{"id":81965219,"identity":"25418d20-ea8d-4ace-81d0-1fafa30de42e","added_by":"auto","created_at":"2025-05-05 11:28:40","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":924372,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6518753/v1/bce92285-e960-42fb-909e-e67067591bee.pdf"}],"financialInterests":"The authors declare potential competing interests as follows: DT, MD and EC are employees of EPOCA U\u0026I","formattedTitle":"\u003cp\u003eBudget Impact Analysis of the EPOCA Telemonitoring System for Elderly Patients in France\u003c/p\u003e","fulltext":[{"header":"Introduction","content":"\u003cp\u003eFrance is undergoing a profound demographic transition marked by a growing elderly population. As of 2024, 10% of the population, equivalent to 7.0\u0026nbsp;million individuals, are aged 75 or over, and this number is expected to rise to 16% by 2050, representing 12.0\u0026nbsp;million individuals\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e,\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eChronic diseases are highly prevalent among the elderly in France, with 91% of individuals aged 75 and over presenting at least one chronic condition or ongoing treatment. Multimorbidity is also a defining feature of aging: 47% of men and 36% of women aged 75 or older live with two or more chronic diseases, and up to 26% of men and 17% of women in this age group have three or more\u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e. Aging also significantly increases the risk of loss of independence. While most seniors remain autonomous until late in life, the share of older adults receiving the French \"Allocation Personnalis\u0026eacute;e d'Autonomie\" (APA), a marker of dependency, rises from 2% among 70\u0026ndash;74-year-olds to nearly 50% between ages 90 and 94, and three-quarters among those 95 or older\u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u003c/sup\u003e. Finally, growing age is accompanied by increased risks of social isolation, particularly among women. Over half of women aged 85 live alone, compared to just 25% of men\u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eThese demographic shifts place immense pressure on France\u0026rsquo;s healthcare infrastructure, which is already strained by shortages of geriatricians and a declining number of general practitioners (GPs). The result is a fragmented and reactive healthcare system, where emergency departments and inpatient services often serve as the default response to complex geriatric needs. Nearly 40% of those aged 80 and above in France are hospitalized annually, with an average duration of approximately 25 days per patient. It is estimated that over 30% of these hospitalizations could have been avoided, with similar figures for emergency department (ED) visits\u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e,\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u003c/sup\u003e. These trends underline the urgent need for scalable, home-based care solutions tailored to the evolving needs of an aging, increasingly dependent population.\u003c/p\u003e \u003cp\u003eRemote monitoring systems (RMSs) have gained international traction as a promising solution for managing elderly patients with chronic and complex health needs. Existing RMSs vary widely in structure and technology but generally include combinations of wearable sensors, mobile health (mHealth) applications, and care coordination frameworks\u003csup\u003e\u003cspan additionalcitationids=\"CR8 CR9 CR10 CR11 CR12 CR13\" citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u003c/sup\u003e. These RMSs are typically multidisciplinary, involving nurses, hospital physicians, geriatricians, and GPs, often with social support services integrated. The majority of these RMS have demonstrated reductions in hospitalizations and emergency visits\u003csup\u003e\u003cspan additionalcitationids=\"CR10\" citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e,\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e,\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eLaunched in 2019, the Vigie-Age framework is a multidisciplinary hospital-community initiative designed to provide comprehensive, coordinated care for older adults with multiple chronic conditions. Its primary objectives are to enhance quality of life and reduce avoidable hospitalizations through better continuity of care. This framework includes EPOCA, a RMS that is a human-centered with connected telemedicine solution offering secure and continuous home support for complex elderly patients. It is built around a 24/7 telemonitoring platform that enables real-time clinical oversight, rapid response to health deterioration, and seamless coordination among healthcare professionals. The system integrates two core technological components: (1) connected devices, such as a wristband, for transmitting health data or emergency alerts; and (2) a centralized RMS coordination hub staffed by trained nurses and physicians, who engage directly with patients and caregivers when needed. Hospital geriatricians or GPs play a central role in the framework, offering ongoing medical supervision via teleconsultations and tele-expertise, and maintaining active communication with community healthcare teams. In parallel, community-based nurses conduct regular home visits, monitor patient conditions, and deliver essential care services.\u003c/p\u003e \u003cp\u003eVigie-Age has been included in the French \u0026ldquo;Article 51\u0026rdquo; experimental framework launched in 2018 to promote innovation in healthcare delivery and financing. Article 51 enables pilot studies of interventions that aim to improve care coordination, efficiency, and patient outcomes through new organizational models and payment structures. These pilots are evaluated for their clinical impact, economic sustainability, and potential for national scale-up, providing valuable data.\u003c/p\u003e \u003cp\u003e This study aims to assess the cost-effectiveness of the Vigie-Age framework including the EPOCA RMS compared to standard care, focusing on reductions in hospitalizations, emergency visits, and overall healthcare costs, using real-world data from the article 51 evaluation of the Vigie-Age framework.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eData source\u003c/h2\u003e \u003cp\u003eThis cost-effectiveness analysis is primarily based on data from the Vigie-Age Article 51 pilot study. Conducted prospectively between 2022 and 2024 across four hospitals in France, the study enrolled 722 participants. Eligibility criteria included individuals aged 70 years or older with multiple chronic conditions, a history of recent decompensations, and a high risk of further clinical deterioration.\u003c/p\u003e \u003cp\u003eThe study population was composed of 36.4% men, with a mean age of 87.9 years (standard deviation [SD]\u0026thinsp;=\u0026thinsp;7.1). Participants experienced an average of 2.0 (SD\u0026thinsp;=\u0026thinsp;1.4) overnight hospitalizations in the six months preceding study inclusion. Approximately 70% of participants were recruited either during a hospitalization or from a community-based setting, while the remaining 30% were included following an ED visit.\u003c/p\u003e \u003cp\u003eThe pilot study assessed outcomes related to clinical efficacy (hospitalizations and ED visits), healthcare resource utilization, and associated costs. These outcomes were derived from French National Health Insurance (NHI) reimbursement data and compared between the study follow-up period and a similar period preceding inclusion. Among the 408 participants who received the EPOCA RMS intervention, outcome data were available for 269 individuals with sufficient follow-up, with a mean observation period of 7.5 months.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003ePerspective, Population, Intervention, Comparator\u003c/h3\u003e\n\u003cp\u003eThis cost-effectiveness evaluation was conducted from two complementary perspectives. The first was a payer perspective, focusing on healthcare expenditures borne by the French National Health Insurance (NHI). The second was a societal perspective, in line with the recommendations of the Haute Autorit\u0026eacute; de Sant\u0026eacute; (HAS)\u003csup\u003e\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u003c/sup\u003e, which includes all direct medical costs regardless of the payer.\u003c/p\u003e \u003cp\u003eThe analysis was conducted on a population corresponding to participants enrolled in the Vigie-Age Article 51 pilot study. The EPOCA RMS intervention was compared to standard care (SOC) as typically provided to this high-risk population under current clinical practice.\u003c/p\u003e\n\u003ch3\u003eModel Structure\u003c/h3\u003e\n\u003cp\u003eDue to the limited follow-up duration in the Vigie-Age Article 51 pilot study, a Markov model was developed to extrapolate the long-term clinical and economic outcomes of the EPOCA intervention over a lifetime horizon, defined as 10 years based on the average age of the target population. The model used daily cycles and incorporated the following health states:\u003c/p\u003e \u003cp\u003e \u003cul\u003e \u003cli\u003e \u003cp\u003eStable condition at home;\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eED visits;\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eHospitalization (either scheduled or via emergency visit);\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eDeath (all-cause).\u003c/p\u003e \u003c/li\u003e \u003c/ul\u003e \u003c/p\u003e \u003cp\u003eTransition probabilities for hospitalizations and ED visits were derived from the Vigie-Age Article 51 pilot study. Based on these data, the model assumes that the EPOCA intervention reduces the frequency of both emergency visits and hospitalizations. However, the probability of hospitalization following an emergency visit, as well as the average length of hospital stay, were assumed to be similar between the intervention and control groups.\u003c/p\u003e \u003cp\u003eAdditionally, the model assumes that participants in the EPOCA arm retain the intervention\u0026rsquo;s benefits even after exiting the program. This assumption is supported by pilot study findings, which showed comparable rates of hospitalizations and emergency visits during and after participation in the program.\u003c/p\u003e \u003cp\u003eThe model also accounted for the recruitment setting. Specifically, it was assumed that patients enrolled in the EPOCA intervention during an ED visit would avoid immediate hospitalization, whereas similar patients under standard care could proceed to inpatient admission.\u003c/p\u003e \u003cp\u003eModel parameters are detailed in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eModel Parameters\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMean\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCI in PSA/DSA\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eDistribution\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eSource\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eTransition Probabilities\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003eStandard of Care\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEmergency Department Entry (SOC)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e22%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNot Inc.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eArt. 51\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMonthly Probability of Hospitalization\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.8-2.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNormal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eArt. 51\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMonthly Probability of ED Visits\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.4\u0026ndash;3.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNormal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eArt. 51\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eProportion of Hospitalizations Following ED Visits\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e71%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e64%-79%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eB\u0026eacute;ta\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eArt. 51\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLength of Stay (days)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6.2\u0026ndash;9.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNormal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eArt. 51\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003eEPOCA\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEmergency Department Entry (EPOCA)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNot Inc.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eArt. 51\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMonthly Probability of Hospitalization\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.2\u0026ndash;1.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNormal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eArt. 51\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMonthly Probability of ED Visits\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.5\u0026ndash;1.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNormal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eArt. 51\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eProportion of Hospitalizations Following ED Visits\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e69%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e55%-83%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eB\u0026eacute;ta\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eArt. 51\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLength of Stay (days)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5.8\u0026ndash;8.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNormal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eArt. 51\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePatient Characteristics\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMean Age\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e87.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e80.8\u0026ndash;95.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNormal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eArt. 51\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCosts\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVIGIE-AGE Program\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026euro;2,210\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNot Inc.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eAssumption\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHospitalization \u0026ndash; EPOCA (per hospitalization)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026euro;3,714\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026euro;832-\u0026euro;9,557\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eLogNorm\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eArt. 51\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHospitalization \u0026ndash; SOC (per hospitalization)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026euro;3,773\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026euro;1,056-\u0026euro;8,873\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eLogNorm\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eArt. 51\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHospitalization Following ED Visit\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026euro;4,249\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026euro;395-\u0026euro;14,057\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eLogNorm\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eArt. 51\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEmergency Department Visits\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026euro;52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026euro;44-\u0026euro;61\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eLogNorm\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003csup\u003e\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u003c/sup\u003e,\u003csup\u003e\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOutpatient Care \u0026ndash; EPOCA (per year)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026euro;5,820\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026euro;4,656-\u0026euro;6,984\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eGamma\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eArt. 51\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOutpatient Care \u0026ndash; SOC (per year)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026euro;5,337\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026euro;4,270-\u0026euro;6,404\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eGamma\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eArt. 51\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eUtility\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGeneral Population Aged 75+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNot Inc.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003csup\u003e\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHospitalization (Per Day)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.0013\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.0016\u0026ndash;0.0010\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eB\u0026eacute;ta\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003csup\u003e\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003eED: Emergency Department, SOC: Standard of Care; CI: 95% Confidence Interval; PSA: Probabilistic Sensitivity Analysis; DSA: Deterministic Sensitivity Analysis; LogNorm: Log-Normal; Art. 51: Vigi-Age Article 51 pilot study\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e\n\u003ch3\u003eCosts and Utilities\u003c/h3\u003e\n\u003cp\u003eThe analysis included only direct medical costs, encompassing hospitalizations, ED visits, outpatient care, and the EPOCA intervention. Hospitalization and outpatient costs were derived from average expenditures observed in the Vigie-Age Article 51 pilot study and were stratified by study arm to reflect differences in the type of hospitalizations and intensity of outpatient follow-up.\u003c/p\u003e \u003cp\u003eHospitalization costs were based on production costs (Echelle National des Co\u0026ucirc;ts), which were directly used for the societal perspective. For the payer (NHI) perspective, tariffs were estimated to be 1.27 times lower than production costs, based on observed differences between actual costs and reimbursements\u003csup\u003e\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e,\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u003c/sup\u003e. Similarly, outpatient care costs were based on tariffs. For the NHI perspective, it was assumed, according to reimbursement rules, that 65% of outpatient costs were reimbursed by the NHI, while the full amount was considered under the societal perspective.\u003c/p\u003e \u003cp\u003eCosts of ED department visits were estimated using the average cost per visit, calculated from the total annual funding allocated to emergency services in France\u003csup\u003e\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u003c/sup\u003e and the national number of ED visits\u003csup\u003e\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u003c/sup\u003e. From the NHI perspective, costs were applied only to ED visits that did not result in hospitalization, as the latter were considered part of inpatient costs.\u003c/p\u003e \u003cp\u003eThe cost of the EPOCA intervention was based on the reimbursement tariff used in the Vigie-Age Article 51 pilot study, with a mean cost of \u0026euro;2,210 per participant per year. A higher value of \u0026euro;4,441 was used in sensitivity analyses. This cost was applied at the beginning of each year to the proportion of patients remaining in the program. Program duration was assumed to be 6 months for 59% of participants and 12 months for the remaining 41%, resulting in an average duration of 8.4 months. This was implemented as a probability of continued participation, with an estimated 22% of participants still enrolled at the beginning of year 2.\u003c/p\u003e \u003cp\u003eHealth utilities were sourced from published literature, using age-adjusted baseline utilities for the general population\u003csup\u003e\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u003c/sup\u003e and applying disutility weights for each day spent hospitalized\u003csup\u003e\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\n\u003ch3\u003eOutcomes and Analysis\u003c/h3\u003e\n\u003cp\u003eThe analysis compared discounted and undiscounted clinical outcomes, including the mean number of hospitalizations per patient, total hospital stay duration, and the mean number of emergency department (ED) visits leading to hospital admissions, between the EPOCA intervention and SOC. Economic outcomes included mean hospitalization costs per patient, ED visit costs, outpatient care costs, and intervention costs. Quality of life outcomes were measured in quality-adjusted life years (QALYs).\u003c/p\u003e \u003cp\u003eA cost-utility analysis (CUA) was conducted, with the primary outcome expressed as the incremental cost-effectiveness ratio (ICER), defined as the additional cost per QALY gained with EPOCA compared to SOC.\u003c/p\u003e \u003cp\u003eTo evaluate the robustness of the model results, both deterministic and probabilistic sensitivity analyses were performed. Deterministic sensitivity analysis (DSA) explored the impact of key parameters, including costs, transition probabilities, and utility values, by varying them within their 95% confidence intervals or by \u0026plusmn;\u0026thinsp;20% when confidence intervals were unavailable. Results were presented using a tornado diagram to identify the most influential parameters.\u003c/p\u003e \u003cp\u003eProbabilistic sensitivity analysis (PSA) was conducted using Monte Carlo simulations to simultaneously assess uncertainty across multiple parameters. Probability distributions were assigned to cost inputs, transition probabilities, and utility values. Results are presented using cost-effectiveness acceptability curves (CEACs).\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003eResults are presented in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eCost-Effectiveness and Budget Impact Results\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eEPOCA\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eStandard of Care\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eDifference (% reduction)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eResource\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEmergency Department Visits (n)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-3.3 (54%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHospitalization (n)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-3.6 (47%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHospitalization days\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e30.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e55.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-25.0 (45%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eUndiscounted Costs per Patient (\u0026euro;)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003eCollection Perspective\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eProgram\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2,850\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEmergency Department Visits\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e145\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e315\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-170 (54%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHospitalization\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e12,262\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e23,226\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-10,964 (47%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOutpatient\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10,277\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9,424\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e853 (-9%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e25,535\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e32,965\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-7,430 (23%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003eNIH Perspective\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eProgram\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2,850\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEmergency Department Visits\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e465\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1,008\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-543 (54%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHospitalization\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e15,573\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e29,497\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-13,924 (47%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOutpatient\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10,277\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9,424\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e853 (-9%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e29,165\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e39,929\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-10,764 (27%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCost-Effectiveness\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003eCollection Perspective\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDiscounted QALY\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.04\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDiscounted Total Costs (\u0026euro;)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e24,683\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e31,792\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-7,108\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eICER\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDominant\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eDominated\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003eNIH Perspective\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDiscounted QALY\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.04\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDiscounted Total Costs (\u0026euro;)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e28,181\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e38,510\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-10,329\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eICER\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDominant\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eDominated\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eOver a lifetime horizon, accounting for background mortality, the model estimated an undiscounted average survival of 1.8 years per patient, with an average duration in the EPOCA program of 8.1 months. During this period, patients in the EPOCA arm experienced an average of 2.8 emergency department (ED) visits and 4.2 hospitalizations, compared to 6.1 ED visits and 7.8 hospitalizations in the standard of care (SOC) arm, representing a 54% and 46% reduction, respectively. The decrease in hospitalizations translated into a reduction in the total number of hospital days, from 55.6 days in the SOC arm to 30.6 days in the EPOCA arm.\u003c/p\u003e \u003cp\u003eFrom the societal (collective) perspective, the undiscounted total cost per patient was estimated at \u0026euro;29,200 in the EPOCA arm, compared to \u0026euro;39,900 in the SOC arm. This difference was driven primarily by reductions in hospitalization (\u0026euro;13,900 savings) and ED visit costs (\u0026euro;540 savings), partially offset by an increase of \u0026euro;900 in outpatient care costs. After incorporating the program cost (\u0026euro;2,800), the net savings amounted to \u0026euro;10,800 per patient. Similar cost savings were observed under the NHI perspective, with total savings of \u0026euro;7,400 per patient. These included \u0026euro;11,000 in reduced hospitalization costs, \u0026euro;200 in ED savings, and an \u0026euro;800 increase in outpatient costs, with program costs assumed equal across perspectives. Importantly, EPOCA remained cost-saving even when applying the higher intervention cost of \u0026euro;4,441 used in sensitivity analyses.\u003c/p\u003e \u003cp\u003eIn terms of health outcomes, the EPOCA arm was associated with 1.30 discounted QALYs compared to 1.26 QALYs in the SOC arm, a gain of 0.04 QALYs, primarily attributable to reduced hospitalizations and associated improvements in quality of life. Discounted total costs were \u0026euro;23,200 for EPOCA and \u0026euro;29,500 for SOC from the collective perspective, yielding net savings of \u0026euro;6,300. Given that EPOCA resulted in both lower costs and improved outcomes, it was considered a dominant strategy compared to SOC. Similar conclusions were observed in the NHI perspective, with \u0026euro;3,900 in total cost savings. EPOCA remained dominant at the higher intervention cost of \u0026euro;4,441 in both perspectives.\u003c/p\u003e \u003cp\u003eDeterministic sensitivity analysis (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e) identified the average cost of hospitalization as the most influential parameter in the NHI perspective and the mean age at inclusion, and cost of hospitalization as the most influential parameters in the collective perspective. However, even under lower hospitalization cost scenarios, EPOCA remained cost-saving or cost-neutral confirming the robustness of the model\u0026rsquo;s conclusions across parameter ranges.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eProbabilistic sensitivity analysis (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e) further supported these findings. From the collective perspective, EPOCA had a 90% probability of being the dominant strategy and a 95% probability of being cost-effective at a willingness-to-pay threshold of \u0026euro;30,000 per QALY. From the NHI perspective, these probabilities were 80% and 87%, respectively.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis cost-effectiveness analysis shows that the EPOCA RMS significantly reduces avoidable hospitalizations and ED visits in frail, polypathological older adults. Over a modeled lifetime horizon, EPOCA was associated with a 54% reduction in ED visits and a 46% reduction in hospitalizations, resulting in a 25-day decrease in cumulative hospital stay per patient. These reductions led to a cost savings of \u0026euro;10,800 per patient from the collective perspective and \u0026euro;7,400 from the French NHI perspective. Notably, even under conservative assumptions for the program costs and sensitivity analyses, EPOCA remained a dominant strategy, offering better outcomes at lower costs.\u003c/p\u003e \u003cp\u003eThese results are consistent with the Article 51 pilot study and real-world data from a retrospective observational studies of the EPOCA system\u003csup\u003e\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u003c/sup\u003e. In both hospital-led and GP-led implementations, EPOCA was associated with sharp declines in hospitalizations (\u0026minus;\u0026thinsp;48% to \u0026minus;\u0026thinsp;57%), ED visits (\u0026minus;\u0026thinsp;48% to \u0026minus;\u0026thinsp;62%), and hospital stay duration (\u0026minus;\u0026thinsp;49% to \u0026minus;\u0026thinsp;63%) within just one year of follow-up.\u003c/p\u003e \u003cp\u003eInternational evidence supports the observed outcomes of EPOCA. Similar RMS systems have demonstrated reductions in hospital use, with relative risk reductions up to 57%, 28% in unplanned hospitalizations and 33% in ED visits\u003csup\u003e\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e,\u003cspan additionalcitationids=\"CR10\" citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e,\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e,\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u003c/sup\u003e. EPOCA appears to achieve higher magnitudes of effect, possibly due to its integration into a comprehensive care coordination model involving both hospital and community actors, including nurses, general practitioners, and geriatricians. Additionally, unlike some RMS systems, which may inadvertently increase ED use due to over-alerting\u003csup\u003e\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u003c/sup\u003e, EPOCA\u0026rsquo;s design emphasizes triage, anticipatory care, and direct intervention, which could contribute to a true reduction in ED burden. In terms of cost-effectiveness, international evidence also supports the outcomes observed in this study. Previous evaluations of RMS have reported per-patient savings ranging from approximately \u0026euro;1,000 to \u0026euro;2,800\u003csup\u003e11,24,25\u003c/sup\u003e, including program costs, which are on the lower end of \u0026euro;7,400 to \u0026euro;10,800 in net savings estimated in this analysis.\u003c/p\u003e \u003cp\u003eThese findings have several important implications for health policy. First, EPOCA\u0026rsquo;s demonstrated effectiveness in both clinical and economic dimensions supporting its integration into national care pathways for older adults. Second, the program\u0026rsquo;s net savings from the NHI perspective support the case for full reimbursement, particularly in light of demographic aging and increasing chronic disease prevalence. Moreover, EPOCA responds to systemic challenges faced by the French healthcare system: high hospitalization rates among the elderly, under-resourced primary care, and fragmented coordination between community and hospital-based care. By reducing hospital reliance and enabling safe, structured home care, EPOCA contributes directly to system efficiency and sustainability.\u003c/p\u003e \u003cp\u003eDespite these promising findings, several limitations must be acknowledged. First, the base data from the Vigie-Age Article 51 pilot study involved limited follow-up, requiring extrapolation through Markov modeling. Although sensitivity analyses confirmed the robustness of results, longer-term data will be necessary to validate projections. Second, there was significant variability in available hospitalization costs, potentially impacting cost estimates. Third, outpatient cost data were partially incomplete, particularly for non-reimbursed services, which may have led to conservative cost assumptions. Finally, while the program likely reduces caregiver burden through improved coordination and reduced crisis care, these effects were not directly measured and warrant further investigation.\u003c/p\u003e \u003cp\u003eIn conclusion, Vigie-Age including the EPOCA RMS is a cost-effective intervention for managing elderly patients at high risk of hospitalization. It not only reduces acute care utilization but also improves quality-adjusted life expectancy and lowers total healthcare costs. From the NHI perspective, the budget impact is neutral to favorable. Supported by real-world implementation data and consistent with international best practices, EPOCA has strong potential for national scale-up. Embedding such models within France\u0026rsquo;s elderly care infrastructure could enhance care quality, reduce hospital pressure, and better address the needs of a rapidly aging population.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eINSEE (2020) Accessed 03/25/2025. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.insee.fr/fr/statistiques/4277619\u003c/span\u003e\u003cspan address=\"https://www.insee.fr/fr/statistiques/4277619\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eINSEE, Bilan d\u0026eacute;mographique (2024) Accessed 03/25/2025. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.insee.fr/fr/statistiques/8327319\u003c/span\u003e\u003cspan address=\"https://www.insee.fr/fr/statistiques/8327319\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBagein G, Costemalle V, Deroyon T et al (2022) \u003cem\u003eL\u0026rsquo;\u0026eacute;tat de sant\u0026eacute; de la population en France.\u003c/em\u003e Vol. 102. \u003cem\u003eLes dossiers de la DREES\u003c/em\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eINSEE Personnes \u0026acirc;g\u0026eacute;es d\u0026eacute;pendantes. 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(2020) :115. \u003cem\u003eMethodological Guidance\u003c/em\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eATIH Etudes nationales de co\u0026ucirc;ts sanitaires. 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J Med Internet Res Dec 15(12):e400. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.2196/jmir.7677\u003c/span\u003e\u003cspan address=\"10.2196/jmir.7677\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDe San Miguel K, Smith J, Lewin G (2013) Telehealth remote monitoring for community-dwelling older adults with chronic obstructive pulmonary disease. Telemed J E Health Sep 19(9):652\u0026ndash;657. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1089/tmj.2012.0244\u003c/span\u003e\u003cspan address=\"10.1089/tmj.2012.0244\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKokkonen J, Mustonen P, Heikkil\u0026auml; E et al (2024) Effectiveness of Telemonitoring in Reducing Hospitalization and Associated Costs for Patients With Heart Failure in Finland: Nonrandomized Pre-Post Telemonitoring Study. JMIR Mhealth Uhealth Feb 7:12:e51841. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.2196/51841\u003c/span\u003e\u003cspan address=\"10.2196/51841\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Budget impact analysis, Remote patient monitoring, Elderly, Cost savings","lastPublishedDoi":"10.21203/rs.3.rs-6518753/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6518753/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cb\u003eBackground\u003c/b\u003e\u003c/p\u003e \u003cp\u003eFrance\u0026rsquo;s aging population faces high rates of chronic illness, multimorbidity, and avoidable hospitalizations, placing pressure on an already strained healthcare system. Remote monitoring systems (RMS) have shown promise in improving care coordination and reducing acute care use. The objective of this study is to assess the cost-effectiveness of the EPOCA RMS, implemented within the Vigie-Age framework, compared to standard care (SOC) for older adults with multiple chronic conditions.\u003c/p\u003e\u003cp\u003e\u003cb\u003eMethods\u003c/b\u003e\u003c/p\u003e \u003cp\u003eUsing data from the Vigie-Age Article 51 pilot study (722 participants including 408 with long term follow-up), a cost-utility analysis was conducted over a 10-year lifetime horizon. A Markov model with daily cycles simulated transitions across health states: at home, emergency department (ED) visit, hospitalization, and death. Analyses were conducted from both the French National Health Insurance (NHI) and collective perspectives. Direct medical costs, including hospital, outpatient, and intervention costs, were included. Health outcomes were measured in quality-adjusted life years (QALYs). Deterministic and probabilistic sensitivity analyses assessed model robustness.\u003c/p\u003e\u003cp\u003e\u003cb\u003eResults\u003c/b\u003e\u003c/p\u003e \u003cp\u003eEPOCA reduced ED visits by 54% and hospitalizations by 46%, cutting average hospital stay from 55.6 to 30.6 days. Total costs per patient were \u0026euro;29,200 with EPOCA vs. \u0026euro;39,900 for SOC, a \u0026euro;10,700 saving from the societal perspective, and a \u0026euro;7,400 saving from the NHI perspective. EPOCA yielded 0.04 additional QALYs and remained cost-saving even at higher program costs. Sensitivity analyses confirmed the robustness of results. EPOCA had a 90% probability of being dominant and a 95% probability of being cost-effective at a \u0026euro;30,000/QALY threshold.\u003c/p\u003e\u003cp\u003e\u003cb\u003eConclusions\u003c/b\u003e\u003c/p\u003e \u003cp\u003eEPOCA is a cost-effective strategy for elderly patients at high risk of hospitalization. It reduces healthcare utilization while improving outcomes, supporting its integration into national elderly care pathways and reimbursement by the French NHI.\u003c/p\u003e","manuscriptTitle":"Budget Impact Analysis of the EPOCA Telemonitoring System for Elderly Patients in France","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-05-05 11:12:31","doi":"10.21203/rs.3.rs-6518753/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"7ca2cde6-7269-49c2-8267-aa9a88c10344","owner":[],"postedDate":"May 5th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":47614867,"name":"Geriatrics \u0026 Gerontology"}],"tags":[],"updatedAt":"2025-05-05T11:12:31+00:00","versionOfRecord":[],"versionCreatedAt":"2025-05-05 11:12:31","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-6518753","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6518753","identity":"rs-6518753","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}