Lithuania

Dementia detection in Lithuania is based on targeted assessment in primary care, not mass screening. The LT-GPCOG demonstrated effectiveness similar to the MMSE and supports early identification during routine care. When results are abnormal, patients are generally referred to specialists or Memory Clinics for comprehensive diagnostic work-up.

CT and MRI are available in public and private hospitals, but public access is limited by scanner capacity and waiting lists. MRI is most accessible in Vilnius and Kaunas, while PET is less commonly used and mainly oriented toward oncology rather than routine dementia care.

There is no national guidance for routine Alzheimer’s genetic testing in Lithuania. Genetic panels are generally limited to research settings, private funding, or foreign arrangements, especially for atypical cases.

Lithuanian national policy does not specify routine use of CSF biomarkers (Aβ, total tau, phosphorylated tau) or blood-based markers. However, centres such as the VUHSK Memory Clinic use CSF selectively for complex cases, with biomarker innovation largely driven by research.

Lithuania does not operate a formal national memory-clinic network, but specialist dementia care is anchored in tertiary university hospitals, most prominently VUHSK through its Center for Alzheimer’s Disease and Other Dementias. The centre provides standardised multidisciplinary assessment, follow-up, and pharmacological management, and serves as the country’s main hub for clinical research and international trials, shaping diagnostic and treatment practices nationwide.

Additional specialist capacity exists at Kaunas Clinics and other university-affiliated hospitals, while municipal mental-health centres contribute outpatient psychiatric and psychosocial services, particularly for behavioural and psychological symptoms of dementia (BPSD).2 However, access to specialist dementia expertise remains geographically uneven.

Palliative care is formally covered under the NHIF and delivered by multidisciplinary teams across inpatient wards, outpatient clinics, and limited home-based services. In practice, dementia-specific palliative pathways are not separately defined, and long-term care (LTC) and palliative integration remains an implementation challenge, especially as demand grows with population ageing. Capacity constraints in community nursing, social work, and specialised dementia palliative care mean that families often shoulder significant care responsibilities before late-stage institutionalisation.

Under Lithuania’s universal compulsory health insurance system insured residents are entitled to receive medically necessary health care services without direct charges when these are provided by institutions contracted with the territorial health insurance funds. For people living with dementia, this includes GP care, specialist consultations, inpatient and outpatient treatment, nursing, rehabilitation, and palliative care, subject to standard referral pathways. Services delivered within the contracted public system are financed from the NHIF, while access to care outside this framework, such as private consultations or diagnostics used to bypass waiting lists, must be paid out-of-pocket by people living with dementia or families.Services or medicines obtained through private consultations, off-list brands, or private dispensing are paid entirely out-of-pocket. As with diagnostics, some people use private services to accelerate access but return to the public system for ongoing reimbursed treatment.

Lithuania’s long-term care system remains in transition from an institutional-centric model toward home and community-based care, with dementia posing particular challenges. Formal, dementia-specific cash benefits or allowances for informal care partners are limited, and structured respite or training programs are not uniformly available nationwide. A notable policy development since 2020 is the state’s assumption of pension and unemployment social insurance contributions for carers of people living with dementia formally assessed as needing permanent care, provided the caregiver lacks insured income, an important protection against long-term social exclusion.

Despite this, European Union and OECD reviews consistently highlight gaps in carer support, workforce availability, and coordination between health and social services. The reliance on family care remains high, and expansion of community nursing, day services, respite care, and carer training is widely recognised as a priority for sustainable dementia care in Lithuania.

Lithuania currently has no dementia-specific national strategy or action plan in force. Policy development in this area has instead been driven largely by civil society and academic actors, most notably Dementia Lithuania, in partnership with universities and clinicians. Since 2021, these stakeholders have led the “Towards a Dementia Strategy: Situation Analysis and Public Awareness” initiative, which consolidated evidence on public awareness, service gaps, and recommendations for dementia strategy development. This process resulted in the Ministry of Health convening a national Dementia Working Group in 2022, tasked with preparing policy recommendations covering prevention, diagnosis, care pathways, and carer support. While this marked an important institutional recognition of dementia as a policy issue, the outputs have not yet been formalised into binding national policy or financing commitments.
At the European Union level, Lithuania joined the JADE Health Joint Action in 2025, aligning the country with a multi-state framework focused on dementia prevention, early diagnosis, health literacy, and integrated, person-centred care. Participation in JADE Health strengthens Lithuania’s technical capacity and policy alignment with European Union standards, but, as in other member states, its domestic impact will depend on whether pilot activities and recommendations are embedded in national regulations, budgets, and workforce planning.

Work toward a national dementia strategy remains ongoing but non-finalised, with NGO and Ministry of Health work streams continuing in parallel with broader ageing and long-term care (LTC) reforms. Lithuania is actively engaged in OECD and WHO Europe technical cooperation addressing population ageing, social care financing, and workforce sustainability. These reforms have the potential to indirectly strengthen dementia care, particularly through expanded home- and community-based services, improved care coordination, and professionalisation of care roles.

However, dementia remains subsumed within wider ageing and disability frameworks, rather than treated as a distinct policy domain. Whether upcoming reforms translate into tangible improvements for people living with dementia will depend on explicit inclusion of dementia-specific service standards, referral pathways, carer entitlements, and monitoring indicators within these broader strategies.

Lithuanian research teams have been particularly active in advancing clinic-friendly, low-cost diagnostic approaches designed to complement conventional cognitive testing in settings where time, specialist availability, or access to advanced biomarkers is limited. Research emerging from the VUHSK Memory Clinic has examined a range of non-invasive sensory and cognitive markers, including olfactory memory testing, colour and visual memory tasks, visuospatial processing assessments, and time-estimation paradigms, that are relatively quick to administer and sensitive to early or atypical cognitive change.Although still in the academic stage, these methods are intended not as stand-alone diagnostics, but as screening or differential tools that may help clinicians distinguish neurodegenerative patterns from ageing or comorbidity-related cognitive impairment, particularly in early disease stages.

In parallel, Kaunas University of Technology (KTU) and collaborating academic centres have focused on AI–driven MRI analytics, developing machine-learning models capable of identifying Alzheimer’s disease patterns and predicting progression trajectories using routinely acquired structural imaging. In controlled research datasets, these models have demonstrated high diagnostic and prognostic accuracy, underscoring their potential to enhance interpretation of MRI scans without requiring new imaging infrastructure. Current research priorities have shifted toward external validation, dataset generalizability, and integration into clinical workflows, including clinician-friendly decision-support interfaces.