Design of Scalable Cloud Architectures for Healthcare IT Modernization Integrating Data Protection, Access Control and Continuous Compliance Monitoring

Healthcare cloud modernization requires capacity elasticity without compromising confidentiality, identity governance, or continuous evidence of regulatory safeguards. This study develops a layered cloud architecture and a four-dimensional nonlinear dynamical model coupling normalized resource load (R), security exposure (S), access-control effectiveness (A), and compliance performance (C). Five dimensionless parameters represent workload, scaling responsiveness, protection, adaptive access, and monitoring. Reproduced equilibrium and time-integration experiments from the supplied research outline quantify their interactions. At the baseline (L, k, p, a, m) = (0.65, 1.00, 0.80, 0.85, 0.80), the supplied equilibrium is approximately (0.713, 0.254, 0.881, 0.892). Raising k from 0.80 to 1.30 at L = 0.95 reduces equilibrium utilization from 1.410 to 0.813; increasing protection p from 0.45 to 1.20 at a = 0.85 decreases exposure from 0.378 to 0.184. At L = 0.95, increasing monitoring m from 0.40 to 1.20 increases the compliance index from 0.750 to 0.900. Periodic workload perturbations produce larger forced utilization oscillations as amplitude and forcing period rise in the examined domain. The numerical study provides design sensitivities and a reproducible stability-analysis framework, but does not constitute empirical clinical deployment validation or verified AUTO-07p bifurcation results. The principal contribution is a transparent joint capacity–security–compliance evaluation framework for healthcare cloud planning.