Virtual Visit Vitals: Build vs Buy for Health Systems

The infrastructure of virtual care has matured past video conferencing. For health systems, the pressing architecture challenge is no longer how to see the patient remotely, but how to extract clinical-grade physiological data during that encounter without mailing out hardware. As remote photoplethysmography (rPPG) and camera-based vital sign technologies transition from academic concepts to enterprise-ready tools, health system Chief Information Officers (CIOs) and clinical informatics teams face a classic technology crossroad. They must evaluate the virtual visit vitals build vs buy decision carefully. They must decide whether to engineer a custom integration using available rPPG libraries or partner with an enterprise vendor for a turnkey solution. This architecture decision dictates The initial capital expenditure. The long-term operational viability of the virtual care program.

"The transition to virtual-first care models shifts the IT procurement conversation from simple video capacity to clinical data depth. Deciding whether to build or buy that capability fundamentally alters a health system's total cost of ownership." - Kevin B. Mahoney, Frontiers of Health Services Management, 2024.

The virtual visit vitals build vs buy decision

When analyzing the virtual visit vitals build vs buy scenarios, procurement teams must look beyond the initial software development costs. The allure of building an in-house camera-based vitals capture platform is rooted in the idea of having total control over the intellectual property, a perfectly tailored user interface, and the avoidance of recurring vendor subscription fees. For a health system with a large, sophisticated IT department, keeping technology proprietary can seem like a strategic advantage.

However, building medical-grade software inside a health system demands specialized engineering resources that are rarely native to hospital IT departments. Creating a robust remote vital signs module requires deep expertise in computer vision, complex signal processing, and continuous machine learning algorithm training across diverse patient demographics. The algorithms must account for minute variations in skin tone, ambient lighting, and unpredictable patient movement during a live video call.

If a health system decides to build, it also assumes the massive burden of clinical validation and ongoing regulatory compliance. The total cost of ownership for an internal build compounds rapidly when factoring in the continuous maintenance required. Smartphone operating systems update annually, browser standards shift, and new mobile device camera hardware is released constantly. An in-house algorithm that works flawlessly on an iPhone today might break on an Android device tomorrow unless a dedicated team of developers is actively maintaining the code base.

Conversely, purchasing an enterprise-grade virtual care vital signs platform offloads the technical risk and the relentless maintenance burden to a dedicated vendor. A purchased solution is generally deployed in a fraction of the time, often arriving with established EHR integrations and rigorous clinical validation studies already completed. The trade-off is a recurring operational expense, typically structured as a Software-as-a-Service (SaaS) subscription, and a reliance on a third party's product roadmap. But for clinical informatics teams, buying shifts the organizational focus from managing a complex software development lifecycle to designing the clinical workflows that actually utilize the new vital signs data to improve patient outcomes.

| Decision Factor | Build In-House | Buy Vendor Solution | | :--- | :--- | :--- | | Upfront Capital Cost | High (Engineering, testing, and validation) | Low to Medium (Implementation fees) | | Deployment Timeline | 18 to 36 months | 3 to 6 months | | Maintenance Burden | High (Continuous updates, bug fixes, OS compatibility) | Low (Managed by the vendor) | | EHR Integration | Custom development required | Standardized HL7/FHIR APIs included | | Clinical Validation | Health system assumes full responsibility | Vendor provides existing validation data | | Long-Term Economics | Highly variable, dependent on internal resources | Predictable subscription model (SaaS) |

Core architecture and implementation requirements

The decision to integrate camera-based vitals requires a clear understanding of the technical pipeline involved. Whether a health system chooses to build or buy, the resulting platform must successfully execute a rigorous set of functions without disrupting the provider-patient conversation:

• Capture consistent video frames securely through the patient's existing mobile device, tablet, or desktop computer camera.
• Process the minute changes in light absorption on the patient's face to extract the raw photoplethysmogram signal.
• Translate the raw signal into discrete, accurate vital signs such as heart rate, respiratory rate, and estimated blood pressure.
• Transmit the structured data seamlessly into the electronic health record (EHR) before the provider finalizes the clinical note.
• Ensure the entire data pipeline operates within strict HIPAA compliance, without ever storing raw video footage on local devices or cloud servers.
• Maintain high availability and low latency so that the vitals capture does not degrade the quality of the concurrent video and audio streams.

The hidden costs of in-house development

Health system IT budgets often focus heavily on the capital expenditure required to launch a new initiative. In a build scenario, the initial phase involves hiring specialized software engineers, data scientists, and UI/UX designers. Yet, the true financial strain of building a virtual vitals platform emerges post-launch.

Maintaining a custom telemedicine feature requires a permanent allocation of resources. Security patching, server maintenance, and troubleshooting interoperability issues with the EHR drain IT budgets. Furthermore, health systems must continuously monitor the algorithm for accuracy drift. When vendors release new solutions, they spread these continuous maintenance costs across dozens or hundreds of health system clients. A hospital building its own solution bears 100 percent of the ongoing total cost of ownership.

Industry applications and clinical workflows

Choosing the right procurement path depends heavily on how the health system intends to deploy the technology across its various service lines.

High-volume primary care triage

In primary care, the speed and efficiency of data acquisition are critical. Virtual waiting rooms equipped with camera-based vitals capture can process physiological data before the physician even joins the call. If a health system builds this internally, the engineering team must ensure the interface is entirely frictionless for patients who may not be technologically savvy. Vendor solutions typically have the advantage of processing millions of patient encounters, resulting in highly refined, intuitive user experiences that minimize patient drop-off and frustration during the crucial triage phase.

Chronic disease management

Managing chronic conditions like hypertension, diabetes, and heart failure remotely relies on consistent, longitudinal data. The virtual care platform must be reliable enough to capture trends over time accurately. When evaluating the virtual visit vitals build vs buy equation for chronic care, the cost of algorithm drift must be considered. In-house algorithms might perform well at launch but can quickly degrade in accuracy as new consumer devices enter the market. Enterprise vendors dedicate entire engineering teams to updating their signal processing libraries to maintain clinical-grade accuracy across the latest iOS and Android releases.

Behavioral health integration

Behavioral health providers increasingly use physiological data, such as heart rate variability (HRV) and resting heart rate, as objective markers of stress and anxiety. Deploying vitals capture in behavioral health requires a subtle, unobtrusive software footprint that does not distract the patient from the therapeutic conversation. Buying a specialized vendor platform often grants immediate access to these advanced metrics without requiring a health system to fund years of specialized behavioral informatics research.

Current research and evidence

The complexities of digital health procurement and architecture are well documented in recent medical informatics literature. An August 2023 study published in "Applied Clinical Informatics" by Barry Saver, Jenna Marquard, and colleagues examined the persistent challenges health systems face when developing consumer-facing digital health interventions. The researchers noted that "buy or build" decisions frequently underestimate the long-term resource drain of maintaining custom software in a rapidly shifting consumer technology environment. The study highlighted that internal builds often struggle to keep pace with the usability standards set by commercial technology companies.

Furthermore, research into remote photoplethysmography confirms that achieving high accuracy requires vast, diverse training datasets. Algorithms trained solely on a regional health system's localized patient population risk exhibiting demographic bias, particularly regarding skin melanin levels and varying facial structures. Commercial vendors typically aggregate training data on a global scale to ensure their computer vision models remain equitable and clinically accurate across all patient populations. When health systems build internally, acquiring a sufficiently diverse dataset to train their algorithms safely represents a massive, often unanticipated, capital and operational expense.

The future of virtual care vitals capture

As virtual care matures from a supplementary service into a primary avenue for healthcare delivery, the expectation for clinical depth during remote visits will only increase. Providers will no longer accept virtual visits that lack the foundational objective data they rely on in physical clinics. Consequently, the technology enabling camera-based vitals will shift from a novel innovation to a mandatory commodity infrastructure requirement.

The future of this space will likely see a sharp decline in the number of health systems attempting to build these complex signal processing engines from scratch. Just as hospitals eventually stopped building their own electronic health records in favor of enterprise platforms like Epic and Cerner, the vitals capture layer will consolidate around specialized, interoperable vendor solutions. CIOs will increasingly prioritize interoperability, cloud security, and proven clinical validation over the perceived advantages of owning proprietary software.

The focus for clinical informatics teams will shift away from the mechanics of data capture and toward maximizing the clinical utility of the captured data. By partnering with specialized vendors, health systems can deploy their internal IT resources toward building advanced predictive analytics models and personalized care pathways that actually use the physiological data to prevent hospital readmissions and improve overall population health.

Frequently asked questions

What is remote photoplethysmography (rPPG)? Remote photoplethysmography (rPPG) is a contactless technology that uses a standard digital camera to detect minute changes in light absorption on the skin's surface, corresponding to blood flow. This allows for the extraction of physiological vital signs, such as heart rate and respiratory rate, without physical wearables.

Why is it difficult for a health system to build an rPPG solution internally? Building an rPPG solution requires specialized expertise in computer vision, signal processing, and continuous machine learning model training. Additionally, maintaining the software to ensure compatibility with thousands of different consumer mobile devices, browser updates, and operating systems represents a massive ongoing engineering burden.

How does buying a vendor solution affect total cost of ownership? While buying a vendor solution introduces recurring subscription or licensing fees, it generally lowers the overall total cost of ownership by eliminating the massive upfront capital required for specialized engineering, clinical validation, and regulatory compliance. It also offloads the continuous maintenance, security patching, and infrastructure hosting costs to the vendor.

Can purchased vitals capture platforms integrate with our existing EHR? Yes. Enterprise-grade camera vitals platforms are explicitly designed with interoperability in mind. They typically use standardized healthcare APIs, such as FHIR and HL7, to securely transmit the captured physiological data directly into the patient's chart within the EHR, ensuring a seamless provider workflow that does not require double documentation.

Deciding how to architect the clinical data layer of your telehealth program is a defining moment for modern health systems. Circadify is addressing this space by providing seamless, EHR-integrated vitals capture that eliminates the heavy lifting of in-house development while delivering the objective physiological data your clinicians require. If your clinical informatics team is evaluating the total cost of ownership for scaling remote patient assessment, explore our health system demo and see how our clinical workflows operate in real time at circadify.com/solutions/telehealth.