Digital architecture AURA-IKAR for the advancement of healthcare in the CIS countries

Relevance. Digital transformation of healthcare in the CIS countries requires tools that not only collect data but also detect loss of observability, i. e. divergence between administrative registration and independent channels of severe harm. The purpose of the study: to present AURA–IKAR as a digital management protocol with potential for scaling in CIS health systems, perform an internal robustness assessment of the monitoring divergence index, and propose a framework for subsequent cross-country testing with organizational and economic evaluation. Materials and methods. A methodological study with retrospective testing was performed using depersonalized aggregated data from the narcological service of the Kabardino-Balkarian Republic for 2014–2024. The following indicators were calculated: primary registration flow (newly diagnosed dependence syndrome and harmful use), the number of acute toxicological events (non-fatal acute poisonings and deaths), the number of deaths, the monitoring divergence index (ratio of acute toxicological events to primary registration flow) and the severity coefficient (proportion of deaths among acute toxicological events,%). The Mann–Kendall trend test, Theil–Sen slope estimation, Holm correction, correlation analysis and validation of a pre-calibrated threshold on the hold-out window 2022–2024 were applied. Results. Primary registration of dependence syndrome and harmful use decreased from 621 to 227 cases (–63.4%; τ = –0.917; p < 0.001), whereas the number of acute toxicological events increased from 108 to 213 cases. The monitoring divergence index rose from 0.174 to 0.938 (τ = 0.600; p = 0.010) and exceeded the frozen threshold of 0.332 in 2023–2024. The concurrent association between the index and mortality was strong (ρ = 0.895; p < 0.001), while lagged associations were non-significant; the index was therefore confirmed as an operational concurrent, not leading, indicator. A five-step transfer protocol, measurable key performance indicators of the pilot project and a budget-impact framework were proposed without introducing new primary reporting. Conclusion. AURA–IKAR improves observability and reduces managerial delay without replacing clinical judgment or forecasting future case counts. The architecture is prepared for multicenter testing in the national health systems of the CIS countries; readiness for scaling requires confirmation on independent data.