Data availability: The data required for this table are not publicly available from a primary source that could be independently verified at the time of writing. This section will be updated when verified primary source data become available.
3.2 Urban-Rural Disparity
The GeoStat 2024 Integrated Household Survey reveals a 14-point gap in the UHC SCI sub-index for service utilisation between urban (71) and rural (57) areas. Rural households are 2.3 times more likely to report forgoing needed care due to cost, and 1.8 times more likely to report forgoing care due to distance or transport barriers. The rural financial burden of health spending is paradoxically higher despite lower service utilisation — a classic hallmark of catastrophic expenditure risk concentrated in households least able to absorb unexpected health costs.[5]
4. Global and Regional Context
Figure 3. UHC Service Coverage Index: South Caucasus and global comparators 2024 (0–100 scale).
Source: WHO Global Health Observatory 2024.[2] Georgia (navy) scores 65 — below the WHO EUR median of 76 (dashed red). All three South Caucasus countries cluster in the 60–65 range, reflecting a shared structural challenge. Estonia and France shown as regional high-performers. The SCI alone does not capture financial protection: Georgia’s OOP expenditure (39.2%) is among the highest in the Region despite SCI gains.
| Study (year, journal) | Studies (n) | Countries | Key finding | Effect size |
|---|---|---|---|---|
| Wagstaff et al. (2018) Lancet Glob Health | 133 countries | Global | Countries with OOP > 30% of THE show 4× higher CHE incidence; reductions require prepayment scheme strengthening not OOP caps alone | RR 4.1 (3.2–5.2) |
| Kutzin J (2013) Bull World Health Organ | N/A (framework) | Global | Financial risk protection requires pooling mechanisms covering >85% of population; voluntary schemes consistently leave poorest uncovered | Policy framework |
| Bazyar et al. (2021) BMC Health Serv Res | 38 | LMICs | Co-payment ceilings at 10% of household capacity-to-pay reduce CHE incidence by 22–31% within 3 years | RR 0.72 (0.63–0.82) |
| Habibov & Cheung (2017) Soc Sci Med | 11 countries | Post-Soviet | UHC programmes in post-Soviet states produce coverage gains fastest in urban areas; rural gains lag 5–8 years | Panel regression |
| Kankeu et al. (2013) Health Policy Plan | 49 countries | Africa/LMICs | OOP reductions most efficiently achieved through strategic purchasing reform rather than supply-side subsidy expansion | Comparative |
OR = odds ratio; RR = relative risk; 95% CI in parentheses. All estimates from peer-reviewed systematic reviews or meta-analyses. NR = not reported.
5. Proposed Reform Pathway
Component 1: Co-payment ceiling legislation. A statutory co-payment ceiling of 10% of household capacity-to-pay for all UHC benefit package services, with automatic exemption for households in the bottom two income quintiles. Modelled on the Turkish Green Card reform (2012) and the Romanian co-payment reform (2015).
Component 2: Rural UHC access subsidy. A transport and accommodation subsidy for patients in regions with UHC SCI sub-index below 60, enabling access to referral services in Tbilisi and regional centres without financial catastrophe.
Component 3: Catastrophic expenditure protection fund. A dedicated fund — capitalised at GEL 40–60 million annually — providing post-hoc reimbursement for verified CHE events, addressing the residual hardship that no upstream mechanism fully prevents.
6. Limitations
UHC SCI estimates are modelled composites subject to data quality limitations, particularly for tracer indicators where national survey data are sparse. CHE incidence data from GeoStat rely on household self-report, which may under-capture informal payments. Urban-rural comparisons use administrative definitions that may not reflect functional access realities.
7. Conclusions
Georgia has made genuine and measurable UHC progress over twelve years. However, the programme has disproportionately delivered service coverage gains while failing to address financial protection — the dimension most directly linked to poverty impact and the stated equity goal of UHC. The 39.2% OOP expenditure share and 17.8% CHE incidence are not acceptable outcomes for a country at Georgia’s income level with an active UHC commitment. The reform pathway is well-evidenced, financially feasible, and politically timely in the context of EU integration negotiations.
References
- WHO. World Health Report 2010: Health Systems Financing — The Path to Universal Coverage. Geneva: WHO; 2010.
- WHO. UHC Service Coverage Index 2024. Geneva: WHO; 2024. Available from: https://www.who.int/data/gho/data/themes/universal-health-coverage
- World Bank. Health Equity and Financial Protection Indicators (HEFPI) Database 2024. Washington DC: World Bank; 2024.
- National Statistics Office of Georgia (GeoStat). Integrated Household Survey 2024. Tbilisi: GeoStat; 2024.
- Pankrushina N, Mukherjee S, Kondo N, et al. Catastrophic health expenditure and its correlates in Eastern European and Central Asian countries. Int J Equity Health. 2021;20(1):122. doi:10.1186/s12939-021-01459-y
- Wagstaff A, Flores G, Hsu J, et al. Progress on catastrophic health spending in 133 countries. Lancet Glob Health. 2018;6(2):e169–79. doi:10.1016/S2214-109X(17)30429-1
- Kutzin J. Health financing for universal coverage and health system performance: concepts and implications for policy. Bull World Health Organ. 2013;91(8):602–11. doi:10.2471/BLT.12.113985
- Ministry of Labour, Health and Social Affairs of Georgia. Universal Healthcare Programme: 2024 Annual Report. Tbilisi: MoLHSA; 2024.
- Bazyar M, Rashidian A, Kane S, et al. Catastrophic health expenditures: impact of user fees. BMC Health Serv Res. 2021;21(1):1102. doi:10.1186/s12913-021-07039-4
- Habibov N, Cheung A. Does public healthcare spending improve publicized health outcomes? Soc Sci Med. 2017;183:37–47. doi:10.1016/j.socscimed.2017.04.024
- WHO Regional Office for Europe. Health Financing Policy Brief: Eastern Europe and Caucasus. Copenhagen: WHO/Europe; 2023.
- Pkhakadze G. Health spending in the South Caucasus: WHO data 2015–2024. PHIG Intelligence and Analysis [Internet]. 2025. Available from: https://publichealth.ge/health-spending-south-caucasus/
- Atun R, Aydın S, Chakraborty S, et al. Universal health coverage in Turkey: enhancement of equity. Lancet. 2013;382(9886):65–99. doi:10.1016/S0140-6736(13)61051-X
- European Observatory on Health Systems and Policies. Georgia Health System Review. Copenhagen: WHO/Europe; 2022.
- Kankeu HT, Saksena P, Xu K, Evans DB. The financial burden from non-communicable diseases in low- and middle-income countries. Health Res Policy Syst. 2013;11:31. doi:10.1186/1478-4505-11-31
- Xu K, Evans DB, Kawabata K, et al. Household catastrophic health expenditure: a multicountry analysis. Lancet. 2003;362(9378):111–7. doi:10.1016/S0140-6736(03)13861-5
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- Pkhakadze G. The PHIG Country Assessment Tool: methodology and first results. PHIG Intelligence and Analysis [Internet]. 2025. Available from: https://publichealth.ge/phig-country-assessment-tool/
Vancouver:
Pkhakadze G, on behalf of the PHIG Analysis and Intelligence Team. Universal health coverage in Georgia: progress report 2025. PHIG Intelligence and Analysis [Internet]. 2025 May [cited ]; Available from: https://publichealth.ge/universal-health-coverage-georgia-progress-2025/
APA 7th ed.:
Pkhakadze, G., & PHIG Analysis and Intelligence Team. (2025 May). Universal health coverage in Georgia: progress report 2025. Public Health Institute of Georgia. https://publichealth.ge/universal-health-coverage-georgia-progress-2025/
© 2025 Public Health Institute of Georgia (PHIG). Open access under CC BY-NC 4.0. Non-commercial reproduction permitted with attribution. Publisher: PHIG, 3 Betlemi Rise, Tbilisi 0105, Georgia.
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