For decades, health tech leaders have faced a recurring question: should we build our own tools or buy proven solutions?
On paper, building in-house can appear cost-effective and customizable. In practice, however, the story often unfolds differently, especially in healthcare, where interoperability, regulatory compliance, and usability at the point of care are essential.
Some developers believe that AI will make it easier to build clinical intelligence capabilities internally. However, relying on AI without a clinically validated foundation can create misleading shortcuts, resulting in tools that lack the accuracy, evidence-based structure, and real-world context needed for safe clinical use. Instead of simplifying development, this approach often amplifies technical debt and risk.
The Hidden Cost of Building from Scratch
When organizations decide to build their own clinical intelligence, documentation, or quality measure tools, they are taking on more than just an engineering project. They are committing to ongoing clinical knowledge management that involves maintaining content libraries, mappings, terminology updates, and evolving standards such as Fast Healthcare Interoperability Resources (FHIR), United States Core Data for Interoperability (USCDI), and electronic Clinical Quality Measures (eCQMs).
Many teams may get part of the way there, but the maintenance tail is long and constantly changing. If the original architect leaves, the institutional knowledge often goes with them, and suddenly, maintenance costs spiral while consistency and accuracy degrade. Even vendors that specialize in informatics struggle to keep up with evolving requirements for coding, billing, and reporting. For provider organizations or mid-market electronic health records (EHRs), that burden can quickly become unsustainable.
The Risk of Reinventing the Wrong Wheel
Healthcare data structures were primarily designed to support billing and interoperability, rather than clinician usability. Attempting to build new tools on top of these legacy foundations can perpetuate inefficiencies rather than solve them.
Recently, some organizations have turned to large language models (LLMs) or generic AI tools as a shortcut. While these technologies have potential, they are not grounded in the evidence-based, clinically validated data graphs required for safe and accurate decision support. Without deep clinical mappings and a rigorously maintained knowledge base, AI-driven tools risk introducing more complexity and potential errors into already overburdened workflows.
Buying for Speed, Scale, and Sustainability
At the same time, choosing to buy a proven solution does not mean giving up control. Instead, leveraging proven tools accelerates innovation by building on a stronger foundation that integrates into existing systems with less risk and fewer resources.
By choosing an established partner, teams can:
- Shorten time to market by using existing, standards-based architectures
- Reduce total cost of ownership through maintained mappings and updates
- Improve interoperability with bi-directional FHIR and terminology support
- Enhance clinician satisfaction with usable, intuitive interfaces
- Future-proof technology against evolving compliance and reporting mandates
The right solution should integrate seamlessly into existing EHRs and applications, converting existing data into more usable, structured, and interoperable forms. This reduces long-term maintenance burdens while improving return on investment.
Why Quippe Delivers a Smarter “Buy”
Medicomp’s Quippe® was designed precisely for this challenge. Backed by 45 years of clinical knowledge engineering, Quippe delivers clinical intelligence that bridges the gap between structured data and clinical usability at the point of care and across the care continuum.
At its core is an evidence-based Clinical Knowledge Graph spanning all specialties and domains of medicine, including the clinically validated MEDCIN™ terminology with more than 400,000 concepts, 10 million mappings between standards and terminologies, over 100 million diagnostic relevancy links, and 15,000 genomic markers and diagnostic links for phenotype identification. This is a foundation no organization or other AI solution could easily replicate or maintain on its own.
Quippe enables EHRs and health tech solutions to integrate easily through a cloud-ready, stateless application programming interface (API) that supports web, desktop, and mobile platforms. It dynamically surfaces clinically relevant information, automates quality measure reporting and Hierarchical Condition Category (HCC) and Risk Adjustment Factor (RAF) scoring, delivers bidirectional interoperability through FHIR, Consolidated Clinical Document Architecture (C-CDA), and USCDI support, and validates coding is both accurate and complete. With its library of prebuilt templates, wizards, and workflows, Quippe allows partners to deploy quickly and confidently.
The Smarter Way Forward
When development teams are stretched thin, the fastest route to better outcomes is not AI shortcuts or reinventing the wheel, but instead partnering with those who have already built, refined, and validated it.
With Quippe, organizations can focus on innovation and care delivery rather than the endless task of maintaining clinical mappings, terminologies, and quality measure rules. Building may seem less expensive upfront, but buying a proven, extensible platform like Quippe delivers smarter, faster, and more sustainable value at the point of care and beyond.
To learn more about how Medicomp’s Quippe suite helps accelerate deployment, reduce costs, and improve care delivery visit medicomp.com or contact our team today.