Hybrid Cloud iPaaS for Healthcare Digital Transformation: Bridging On-Premises and Cloud-Based Health Information Systems
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Hybrid Cloud iPaaS for Healthcare Digital Transformation: Bridging On-Premises and Cloud-Based Health Information Systems
Arjun Warrier
Delivery Project Manager
Warrier.arjun@gmail.com
Abstract- Healthcare organizations are contending with a rapidly evolving ecosystem of electronic health records, imaging repositories, laboratory information systems, patient apps, and analytics platforms that must interoperate securely and reliably across organizational and network boundaries. Integration Platform as a Service (iPaaS) has emerged as a practical foundation for unifying heterogeneous, standards-driven health information systems while enabling transformation at the speed demanded by clinical and business stakeholders. However, many providers and payers remain anchored to mission-critical on-premises systems even as they adopt cloud services to scale analytics, enable mobile access, and comply with interoperability mandates. This paper proposes and evaluates a hybrid cloud iPaaS architecture tailored for healthcare digital transformation initiatives. The architecture combines on-premises integration runtimes with managed cloud integration services, bound together by a control plane that provides policy-driven routing, event streaming, secrets management, observability, and zero-trust access. The research focuses on hybrid integration strategies that preserve local data residency and low-latency clinical workflows while unlocking cloud elasticity for bursty workloads, de-identified research data processing, and cross-enterprise data exchange based on HL7 v2, C-CDA, and HL7 FHIR R4 [1], reinforced by SMART on FHIR authorization flows [16], [17] and Bulk Data specifications for population-scale queries [18]. We frame the problem through regulatory, architectural, and operational lenses, referencing HIPAA and 42 CFR Part 2 protections [7], [40], and incorporating NIST guidance on zero-trust and control baselines [5], [6]. Methodologically, we design a reference blueprint and quantify outcomes via a mixed approach: discrete-event workload simulation, architecture decision records mapped to security controls, and an empirical multi-quarter program analysis using real-world baselines and synthetic workloads calibrated to published adoption patterns for APIs and event streaming [13], [15], [31]. Results indicate that a staged hybrid deployment that uses a strangler-fig migration pattern for legacy interfaces, event-driven microservices with service-mesh isolation, and automated CI/CD across on-prem and cloud reduces integration delivery lead time by roughly 50% and achieves a modeled cost optimization of approximately $20 million over three years at the scale of a 10-hospital integrated delivery network. The cost signal arises from decommissioning proprietary interface engines, consolidating message transformation logic on a shared platform, right-sizing runtimes elastically, and shifting non-PHI test and analytics workloads to the cloud while maintaining PHI processing on-premises. We discuss threats to validity, including vendor lock-in, data gravity, and organizational readiness; and we outline governance guardrails based on DAMA-DMBOK, HITRUST CSF mapping, and NIST SP 800-207 policy enforcement at the connector, message, and identity tiers [19], [25], [5]. The paper contributes a reproducible methodology, a security-aligned reference architecture, and migration patterns that reconcile clinical safety, regulatory compliance, and the agility needed for digital front-door experiences, clinical decision support, and population health analytics. The findings suggest that healthcare organizations can accelerate digital transformation without sacrificing safety and compliance by adopting a hybrid cloud iPaaS strategy that is anchored in open standards, zero-trust identity, and event-centric design.
Keywords: Hybrid cloud; iPaaS; healthcare interoperability; HL7 FHIR; SMART on FHIR; HIPAA; Zero Trust; event streaming; service mesh; strangler pattern; data residency; Bulk FHIR; DICOMweb; governance; cost optimization
DOI: 10.55041/ISJEM00123