This article is based on a market research summary originally published on GlobeNewswire covering the global healthcare cloud computing market outlook through 2023.
Market Overview
The global healthcare cloud computing market was projected to expand at a compound annual growth rate (CAGR) of 25.1% between 2018 and 2023. Several converging forces are behind this momentum: the explosion of clinical data, mounting pressure to reduce IT capital expenditure, regulatory pushes toward interoperability, and the maturation of hyperscale cloud platforms offered by providers such as AWS, Microsoft Azure, and Google Cloud.
At its core, cloud computing in healthcare means shifting from owned infrastructure and licensed on-premises software toward services delivered by external providers. Capital expenses become operational ones. Owned data centers give way to elastic, usage-based infrastructure. Software maintenance responsibilities move from internal IT teams to cloud vendors and their partner ecosystems.
What Is Driving Cloud Adoption in Healthcare?
Healthcare generates enormous and growing volumes of data — from electronic health records (EHRs) and medical imaging to telehealth sessions and patient-generated data from remote monitoring devices. Managing this data efficiently at scale is increasingly beyond the practical reach of on-premises data centers for many organizations.
- Big Data demands: Digital health systems are transforming healthcare into a Big Data environment. Telehealth platforms and consumer-facing remote monitoring devices continuously generate data streams that require scalable storage and processing capabilities that cloud infrastructure is well positioned to provide.
- Cost efficiency: By leveraging shared cloud infrastructure, healthcare providers can reduce capital spending on servers, storage, and networking hardware while gaining the ability to scale capacity up or down based on actual workload.
- SaaS relief for clinical staff: Software-as-a-Service (SaaS) delivery models remove time-consuming patch management, version upgrades, and maintenance tasks from clinical and IT staff, letting them focus on patient care and strategic initiatives.
- Emerging technology enablement: Cloud platforms lower the barrier to deploying artificial intelligence, machine learning, blockchain, and advanced analytics — technologies that would otherwise require significant on-premises compute investment.
- Interoperability: Cloud-based architectures make it easier to build and consume APIs that connect disparate healthcare systems, moving the industry closer to genuine data interoperability across providers, payers, and patients.
Key Challenges Healthcare Organizations Face
Despite the compelling value proposition, cloud adoption in healthcare is not without friction. Organizations that underestimate these challenges risk failed migrations, unexpected costs, and compliance exposure.
- IT talent gap: Cloud infrastructure requires specialized skills — cloud architects, security engineers, DevOps practitioners — that are in short supply across the healthcare sector. Many provider organizations struggle to recruit and retain staff capable of managing a cloud environment at the required level of rigor.
- Cost management complexity: Usage-based pricing models can produce higher-than-anticipated bills if workloads are not carefully sized and governed. Data egress fees, storage tiering, and licensing overlaps are common sources of budget overruns during and after migration.
- Data migration complexity: Moving large volumes of clinical data — particularly legacy imaging archives and structured EHR data — from on-premises systems to cloud storage requires thorough planning, validation, and often extended parallel-run periods.
- Security and privacy requirements: Healthcare data is subject to strict regulatory frameworks (including HIPAA in the United States). Cloud configurations must be carefully architected and continuously audited to ensure encryption, access controls, audit logging, and Business Associate Agreement (BAA) compliance are maintained.
- Vendor selection: Choosing the right cloud platform and the right mix of specialized healthcare ISV partners within that platform’s ecosystem is a complex decision with long-term consequences for integration, scalability, and total cost of ownership.
The Healthcare Cloud Ecosystem: Beyond the Hyperscalers
While AWS, Microsoft Azure, and Google Cloud attract the most media attention, the practical value of cloud in healthcare is often delivered through the specialized partner ecosystems those platforms have cultivated. Independent software vendors (ISVs), system integrators, and healthcare-specific SaaS providers build solutions on top of hyperscale infrastructure, addressing use cases such as:
- Clinical data warehousing and analytics
- Medical imaging storage and AI-assisted reading (imaging informatics)
- Population health management (PHM)
- Real-world data aggregation and outcomes research
- Health data continuity and longitudinal patient records
- Telemedicine platform delivery
These specialized vendors layer healthcare-specific workflows, compliance tooling, and clinical context on top of general-purpose cloud primitives, making cloud adoption more practical for provider organizations that lack deep cloud engineering expertise internally.
Convergence with Emerging Technologies
One of the more consequential aspects of healthcare cloud maturation is its role as an accelerant for adjacent technologies:
- Artificial Intelligence and Machine Learning: Cloud platforms provide the GPU compute, managed ML services, and large-scale data pipelines needed to train and serve AI models for clinical decision support, image analysis, and predictive risk scoring.
- Blockchain: Distributed ledger approaches to health data consent management, supply chain integrity, and credential verification are being prototyped on cloud infrastructure, though production adoption remains early-stage.
- Advanced Analytics: Cloud-native data warehouses and lakehouse architectures enable health systems to run population-level analytics across previously siloed datasets without the cost of building dedicated on-premises analytical infrastructure.
- 5G Networks: The rollout of 5G wireless connectivity is expected to increase the volume and velocity of data flowing from remote monitoring devices and telehealth endpoints into cloud-based processing pipelines, amplifying both the opportunity and the infrastructure demands described above.
- Multi-cloud Strategies: Organizations are increasingly distributing workloads across more than one cloud provider to avoid vendor lock-in, optimize cost, and meet data residency requirements — adding governance complexity but increasing resilience.
Medical Imaging: A Significant Cloud Use Case
Medical imaging represents one of the largest and most data-intensive workloads in healthcare. PACS (Picture Archiving and Communication Systems) archives grow continuously, and AI-assisted diagnostic tools require both large-scale training datasets and low-latency inference infrastructure. Cloud storage and compute address both problems simultaneously — providing elastic capacity for archive growth and managed ML services for deploying imaging AI models — making imaging informatics one of the leading near-term cloud growth opportunities in the sector.
Five Key Growth Opportunities
The market research summarized here identified five primary areas where cloud adoption is expected to generate the most significant near-term growth within healthcare:
- Imaging Informatics: Cloud-hosted PACS, vendor-neutral archives (VNAs), and AI-powered image analysis tools.
- Population Health Management (PHM): Aggregating multi-source patient data to identify at-risk populations and coordinate proactive care interventions at scale.
- Real-World Data and Analytics: Generating clinical evidence and commercial insights from EHR data, claims data, and patient-reported outcomes outside of traditional controlled trials.
- Health Data Continuity: Ensuring patients’ longitudinal health records are accessible across care settings and episodes, supported by cloud-based interoperability platforms.
- Telemedicine: Delivering synchronous and asynchronous virtual care through cloud-hosted video, messaging, and remote monitoring platforms — a category that has accelerated significantly since this forecast was originally published.
Competitive Landscape
The competitive structure of the healthcare cloud market spans three tiers: the hyperscale infrastructure providers (AWS, Azure, Google Cloud), the major enterprise technology vendors and systems integrators that build healthcare solutions on those platforms, and a large, fragmented set of specialized healthcare ISVs targeting specific clinical or operational workflows. Vendor selection criteria in healthcare weight compliance capabilities, security posture, integration with existing EHR systems, and the depth of the provider’s healthcare partner ecosystem heavily — not just raw compute price or performance.
Notable M&A activity has reshaped parts of the landscape — the research highlighted IBM’s acquisition of Red Hat as a significant development affecting hybrid cloud strategy options for enterprise healthcare organizations.
Key Takeaways for Healthcare IT Decision-Makers
- Cloud is not a binary decision — hybrid and multi-cloud architectures are increasingly the practical reality for large health systems.
- The partner ecosystem surrounding a cloud provider often matters as much as the platform itself when selecting a cloud strategy for clinical workloads.
- Data migration planning, cloud cost governance, and security configuration reviews are critical pre-migration investments, not afterthoughts.
- Imaging, PHM, telemedicine, and real-world analytics represent the clearest near-term ROI opportunities for cloud investment in clinical settings.
- The cloud’s greatest long-term impact in healthcare may be its role in enabling new care delivery ecosystems — connecting providers, payers, life sciences companies, and patients around shared, interoperable data platforms.
Source: Market research summary originally distributed via GlobeNewswire (2020). Figures and forecasts reflect analysis conducted prior to February 2020.