Healthcare’s quiet business model revolution: The engineering potential of device-as-a-service

For decades, healthcare has operated on a simple economic model: invest heavily in high-class equipment, utilize it to its fullest extent, and replace it periodically. Whether it was MRI machines, infusion pumps, or patient monitors, the paradigm was consistent—capital expenditure, ownership, and maintenance handled in silos.

That model is now under pressure.

Hospitals and health systems face mounting capital constraints. The industry is navigating device obsolescence from rapid advances in digital health, artificial intelligence, continuous care models, and remote patient monitoring. Meanwhile, we’ve seen a structural shift from ownership to access across industries—from servers to cloud computing, from enterprise software to SaaS, from PCs to device-as-a-service (DaaS). 

For healthcare, a similar directional shift is emerging: from selling medical devices to delivering medical capabilities as a service. This evolution is beginning to crystallize into Medical Device-as-a-Service (MDaaS) and broader Technology-as-a-Service models across healthcare.

The Emergence of Device-as-a-Service in Healthcare

The move towards subscription and service-based healthcare technology presents ample opportunity for growth.

Estimates this high indicate a high likelihood of the industry structural adopting this emerging market, so what is MDaaS, really?

At its core, MDaaS enables healthcare providers to access medical technology through subscription, managed service, or usage-based models. Some modalities, like Radiology and In Vitro Diagnostics, and technologies like Connected Cardiac Implants and Continuous Glucose Monitors are leading the wave of MDaaS innovation. Advancements in these areas paint a clear picture—providers can avoid large upfront investments while gaining access to integrated solutions that bundle hardware, software, maintenance, and upgrades.

MDaaS is becoming increasingly visible across several categories. Beyond cardiac therapy technology, connected patient monitoring solutions increasingly bundle devices, analytics platforms, and clinical services into recurring service offerings. Remote patient monitoring ecosystems deliver wearable devices and home-based monitoring tools through subscription frameworks that support continuous care beyond hospital walls.

MDaaS changes the value proposition. As more healthcare domains incorporate MDaaS into their working realities, the Medtech industry shifts focus. From product delivery to capability delivery. From episodic transactions to continuous engagements. 

The structural challenges making space for growth in MDaaS

MDaas responds to specific inefficiencies that affect every stakeholder in the healthcare industry. Large radiology players in CT, MRI, Xray, and Ultrasound technologies are building digital health platforms with subscription models. Among lab and in vitro diagnostics players, we’re seeing an increase in interoperable, connected platforms to exchange data and price information, all while reducing capital equipment costs.

Cost and capital pressures

Healthcare systems globally are under intense financial strain. Traditional device ownership requires high upfront costs, complex maintenance contracts, and periodic reinvestment cycles. 

MDaaS transforms these costs into predictable operating expenses, providing greater financial agility and enabling organizations to scale more efficiently. Through this transformation, the nature of medical devices’ AMCs and warranty frameworks evolves. Coverage becomes continuous, not term based, and the volatile costs that accompany traditional AMCs are eliminated under a model that shifts accountability from hospitals to vendors. 

Technology obsolescence

Medical devices today are increasingly dependent on software—AI-enabled diagnostics, cloud-connected monitoring, and continuous firmware updates. A device purchased today may be outdated in 3 to 5 years. 

Service-based models enable continuous access to the latest capabilities and built-in upgrade pathways, overcoming the challenge of keeping pace with rapidly changing technologies. 

Healthcare fragmentation

Healthcare is increasingly moving out of hospitals. Medical providers meet their clients in home care environments, ambulatory settings, and through remote monitoring.

MDaaS meets the requirements of these complex and separated environments, providing connected device ecosystems and seamless data flow across environments.

The rise of value-based care

Payment models are shifting toward outcomes. Health systems are being measured on readmission rates, patient experience, and clinical efficiency.

The engineering reality behind MDaaS

While the business model shift is visible, the real transformation is happening beneath the surface—at the engineering level. MDaaS represents a fundamental shift in how healthcare technology is engineered, deployed, and maintained. It is a deep technical stack integration challenge. 

Devices are becoming intelligent edge systems

Historically, many medical devices operated as isolated hardware systems.

Modern devices function as connected endpoints, data generators, and software-defined systems.

Engineers must now expertly design these device ecosystems, bringing together edge computing, real-time data capture, and secure communications.

Connectivity enabling interoperability

The success of any service-based model depends on persistent connectivity. It is mission critical for devices to communicate reliably with cloud environments, hospital systems, clinicians, and patients.

This introduces significant engineering challenges involving interoperability, IoT architecture, and stringent cybersecurity needs.

Internet of Medical Things (IoMT) is now an imperative engineering layer. Reliable connectivity and secure, compliant data exchange is a foundational requirement.

Cloud and platform engineering 

The device orchestration platform is at the center of every MDaaS solution. This platform must handle device onboarding, fleet management, telemetry ingestion, analytics, and billing & subscription logic. 

For every MDaaS deployment, a cloud platform for medical devices is essential. 

Data and AI integration

Continuous connectivity generates massive volumes of data—from lab data, patient health info, and several critical clinical, device-related, and associated data points. This data enables predictive maintenance, clinical insights, and AI-driven decision support.

Integration with provider systems, as well as payer systems, are comercially crucial aspects of this process, directly affecting provider revenue management and healthcare costs for patients. Integrating data and AI also introduces added complexity, requiring engineering expertise and deep domain knowledge for data normalization across devices, auditability, and regulatory compliance.

Security and compliance engineering

Healthcare is one of the world’s most regulated industries. MDaaS models must meet HIPAA standards (US), GDPR standards (EU), FDA / CE validation requirements, cybersecurity mandates, and a wide range of additional regional standards. 

Cyber security and data privacy are increasingly imperative engineering considerations for the digital health platforms that interconnect wearables, tracking devices, and medical device systems. As interconnected and interoperable systems become clinical standards, FHIR and HL7 considerations are especially significant. 

Engineers must design with compliance in mind from the beginning, ensuring end-to-end encryption, secure firmware updates, and traceability of system changes. 

Systems integration is the hardest MDaaS problem

The most difficult task for MDaaS solutions is integrating devices into real clinical workflows. Healthcare organizations operate on heterogenous systems, in multi-vendor environments, and with legacy infrastructure. MDaaS must seamlessly integrate into EHR systems, hospital IT workflows, and existing clinical processes. 

Software led updates delivered through cloud applications or OTA bring significant competitive advantages, and MDaaS systems need to be designed to accommodate these capabilities.

This is a systems engineering challenge at scale, and where MDaaS initiatives are ultimately tested. 

A collaborative approach for an ecosystem-level challenge

Medical device manufacturers and OEMs are at the center of the MDaaS transformation, but they face a wide range of structural constraints. Historically, OEMs have excelled at hardware design and innovation, manufacturing, and regulatory compliance. They are not built for cloud platforms, large-scale software engineering, or digital ecosystem integration. 

OEM organizations are often fragmented between hardware teams, software teams, and service teams. To meet the requirements of MDaaS, an OEM would need to cross-functionally integrate engineering across all layers. As the pace of digital innovation accelerated beyond traditional engineering cycles, it falls out of scope for an OEM to deliver these solutions in an ecosystem that’s already incredibly complex. 

As healthcare providers increasingly shift to MDaaS, capital and operating expenditure management has become a critical KPI. MDaaS fundamentally shifts the way hospitals and researchers work to reduce capital investments and optimize operational costs, and the business model changes for OEMs as well. However, OEMs lack the end-to-end engineering capabilities across hardware, software, and digital technologies. 

Engineering services firms can play several critical roles:

Enabling device connectivity:

Engineering partners can retrofit legacy devices with connectivity, design next-gen connected systems, and implement secure IoT architectures. 

At Quest Global, we bring a wide range of expertise and experience in cloud development, SMART edge devices, and IoT-based connectivity, offering comprehensive services for device interoperability, compliance, and cyber security. 

Building the MDaaS platform layer:

OEMs need subscription infrastructure, device orchestration platforms, and remote diagnostics systems. Engineering firms can build reusable platforms, scalable architectures, and multi-device ecosystems.

Systems integration across the healthcare stack:

Engineering partners can fill in the largest white space for OEMs entering MDaaS, integrating devices with hospital IT systems, enabling interoperability across vendors, and creating unified data pipelines.

Verification, validation, and compliance:

As devices become software-driven, validation becomes exponentially more complex. Engineering firms can provide automated validation frameworks, regulatory documentation, and cybersecurity compliance.

Quest Global’s deep expertise in global compliance standards can be enabled with a range of services, from data-led documentation to CSV and test process automation with AI.

Engineering the “experience layer”:

The future of healthcare is experiences—seamless patient journeys, optimized clinician workflows, and outcome-driven systems.

Engineering firms can design end-to-end solutions, integrate analytics and AI, and enable real-time decision-making.

Quest Global delivers better customer experiences and user experiences, offering AI-led analytics, data visualization, user training services, and automation with AI, bringing OEMs critical cost savings.

For engineering firms, the opportunity is a strategic repositioning from staff augmentation and component-level engineering to platform engineering, system orchestration, and outcome enablement. 

The healthcare technology stack is evolving:

Layer 5 → Clinical outcomes (value-based care)

Layer 4 → Digital workflows & care pathways

Layer 3 → DaaS orchestration platforms

Layer 2 → Connected medical devices

Layer 1 → Hardware engineering

The real shift: outcome ownership

Healthcare isn’t just adopting a new pricing model. It’s undergoing the same structural shift we’ve seen in every industry. By moving to MDaaS, the device is no longer the product. The platform becomes the product, and the experience—the outcome—becomes the differentiator.

Providers see their total cost of ownership reduced. Real world data makes payments and insurance a smoother process with less guesswork and clearer outcomes. Costs are reduced across the board—OEMs no longer have to grapple with lifecycle management for each individual asset, and treatment expenses are reduced for patients.

Medtech players are still grappling with how to sell smarter devices, but a more important question they should be investigating is how they can deliver continuous care capabilities. It’s a shift that requires connected systems, platforms, and lifecycle engineering, moving beyond single product delivery models. 

This is where the real gap lives—not in scale, but positioning. The next wave of value in healthcare will be captured by providers who enable OEMs and integrate systems across the stack, seamlessly orchestrating between device, data, workflow, and experience.

For companies like Quest Global, the question is not whether to participate, but where to play. When engineering firms move up the stack, they’ll define the next era of healthcare, where value is not measured by devices sold, but outcomes enabled.