Anatoly Panov*
MD, PhD, Associate Professor of the Department of Healthcare Administration, Rostov State Medical University, Russia.
lefrostovsky [at] gmail.com
Abstract
The evolutionary nosological shift toward severe non-oncological pathology (over 85% of the contingent) and the increasing technological apparatus-dependence of patients caused a systemic crisis of the traditional station-centric model of palliative care. The study evaluated the medical-organizational efficiency of transitioning to a proactive patronage model aimed at overcoming the palliative gap and staffing shortages. The authors conducted a retrospective analysis of a continuous sample of 548 inpatient treatment cases and 1433 outpatient patronage cases between 2023 and 2025. The researchers performed statistical processing of primary register data using Pearson’s chi-square test and Student’s t-test (p < 0.05). The analysis revealed that the extensive expansion of the mobile team fleet from 2 to 5 provided a 2.49-fold increase in the volume of outpatient care, reaching 4634 visits per year. The frequency of patronage increased from 3.8 to 9.2 visits per patient, which allowed for the timely initiation of nutritional and respiratory support at home. The intensification of the outpatient sector determined a significant optimization of high-cost intensive care bed resources: while the number of treated patients grew by 35.2%, the average length of stay significantly decreased by 18.4 days to 32.4 days (t = 4.12, p < 0.001). The hospital mortality rate stabilized at 11.16% compared to 14.46% in the baseline period (chi^2 = 0.90, p > 0.05), confirming the safety of increasing bed turnover. The authors proved that the development of the patronage service acted as a critical compensatory mechanism, which allowed neutralizing the inpatient staffing deficit (17%) and eliminating the phenomenon of social blocking of intensive care beds. The identified mathematical patterns confirmed the necessity of implementing a regional digital ecosystem to transition from reactive management to predictive resource analytics.
Keywords: palliative, patronage, efficiency, resources, digitalization