Transforming Healthcare innovation Through Technology
The healthcare sector is undergoing a profound digital transformation. From AI-powered diagnostics to telemedicine platforms and robotics, software innovation now drives the evolution of patient care, data management, and medical research.
Behind every breakthrough lies extensive research and experimentation, precisely the kind of activity the U.S. Research and Development (R&D) Tax Credit was designed to reward. Under IRC §41(d), companies that develop or improve software, algorithms, or digital systems to overcome technological challenges can recover a portion of their qualified expenses.
Let’s explore how healthcare innovation technology initiatives, from EHR integration to virtual reality, align with the IRS’s four-part test for qualified research.
Eliminating Technical Uncertainty
Healthcare technology developers often encounter significant uncertainty in determining whether, and how, a desired software capability can be achieved. These uncertainties are technological in nature and arise from real-world constraints such as security, interoperability, and system performance.
Examples include:
- Determining whether electronic health record (EHR) software can be enhanced to handle complex data sets securely and efficiently.
- Developing machine learning algorithms to improve diagnostic accuracy or treatment prediction.
- Creating interoperability solutions that enable seamless communication between diverse healthcare systems and devices.
- Designing cybersecurity frameworks that meet evolving HIPAA and FDA data protection requirements.
- Integrating medical devices and wearables with real-time data collection tools.
Each of these efforts involves uncertainty about technical feasibility, design methodology, or performance outcomes, qualifying them for the R&D tax credit.
Engaging in a Process of Experimentation
To resolve these uncertainties, healthcare software teams follow a structured process of experimentation, testing alternative approaches, analyzing results, and refining code or system architecture.
Qualified experimentation often includes:
- Prototyping and iterative testing of new EHR or telemedicine features to assess scalability and usability.
- Algorithm training and validation using clinical or imaging datasets to refine predictive models.
- Simulating data exchange protocols to evaluate interoperability and latency across healthcare systems.
- Stress testing and penetration testing to ensure data security and compliance.
- Pilot deployment and performance benchmarking to optimize robotic systems, mHealth applications, or AR/VR training tools.
This experimental framework, involving design, testing, evaluation, and refinement, directly satisfies the IRS’s definition of a process of experimentation under §41(d)(1)(C).
Grounded in the Hard Sciences
Software R&D in healthcare is deeply technological in nature, drawing upon the principles of computer science, data engineering, artificial intelligence, cybersecurity, and biomedical informatics.
Examples include:
- Applying machine learning and natural language processing to extract and analyze unstructured medical data.
- Leveraging cloud computing and distributed systems to enhance data access and storage scalability.
- Using cryptographic and blockchain principles to secure protected health information.
- Applying robotics and control systems engineering in surgical automation or rehabilitation assistance.
- Integrating signal processing and human-computer interaction principles into medical imaging or AR/VR applications.
These disciplines form the scientific foundation required for R&D qualification, ensuring that eligible software development activities are “technological in nature” as defined by the IRS.
Creating New or Improved Products, Processes, or Software Systems
The ultimate objective of healthcare software R&D is to produce new or improved digital tools that enhance functionality, performance, or reliability. Common qualifying developments include:
- Software Development: Building or improving EHR platforms, telemedicine systems, or diagnostic analytics software.
- Data Analysis & Algorithms: Developing AI, predictive analytics, and NLP models to improve patient outcomes or streamline workflows.
- Interoperability Solutions: Creating APIs and data standards to enable seamless integration across health networks.
- Cybersecurity Solutions: Designing secure access control, encryption, and threat-detection systems for sensitive medical data.
- Medical Device Integration: Connecting hardware (e.g., imaging tools, wearables) with EHR systems for real-time monitoring.
- Health Applications: Developing mobile apps for patient engagement, health tracking, or remote monitoring.
- Healthcare Robotics: Researching automation and robotics for surgical assistance, eldercare, and rehabilitation.
- Clinical Trials Management Systems: Streamlining the collection, management, and analysis of trial data.
- Health Information Exchange (HIE): Creating secure platforms for cross-institutional patient data sharing.
- Virtual & Augmented Reality: Designing immersive training, simulation, and pain-management applications for healthcare professionals and patients.
Each represents a measurable improvement in software capability or healthcare delivery, fully meeting the IRS “business component” requirement under §41(d)(2)(B).
Empowering Healthcare Innovation Through the R&D Tax Credit
Modern healthcare innovation is powered by code, data, and design. But behind every algorithm and application lies the same scientific rigor that defines traditional R&D. The R&D Tax Credit recognizes this, allowing companies to reinvest recovered funds into advancing the technologies that shape the future of medicine.
Eligible expenditures typically include:
- Wages of software developers, engineers, data scientists, and cybersecurity experts;
- Supplies used in development and testing environments;
- Contract research or third-party development expenses.
Maintaining detailed documentation, including technical specifications, version histories, and testing records, is key to substantiating claims and ensuring compliance.
Driving the Future of Digital Health
The healthcare technology ecosystem continues to expand, blending medicine, data, and software engineering into powerful new tools for care delivery and medical research. The R&D Tax Credit is more than a financial incentive; it’s a catalyst for innovation that enables health tech pioneers to build smarter, safer, and more connected systems.
At Leyton, our experts help healthcare technology companies identify and document qualifying research, ensuring that their digital breakthroughs translate into tangible financial returns. From AI-driven analytics to interoperable health networks, we ensure that your innovation earns the recognition and the rewards it deserves.
