Software plays a growing role in healthcare – from mobile apps and wearables to tools that support diagnosis using AI. This wave of digital innovation offers real potential to improve care, but it also creates new regulatory pressure. Frequent updates and online distribution make it harder to apply traditional oversight. This underscores the importance of regulatory compliance in healthcare, especially in fast-moving digital domains.
Ensuring patient safety amid rapid innovation requires both regulators and industry leaders to proactively address challenges such as device traceability, cybersecurity risks, and system interoperability.
For healthcare executives, this evolving landscape requires staying agile with compliance strategies while harnessing software’s benefits. These developments highlight the role of regulatory compliance in the healthcare industry in balancing innovation and patient safety.
Highlights:
- Building cross-functional teams combining technology, clinical, and regulatory expertise helps ensure compliance throughout development.
- Robust data governance structures are key to balancing innovation – especially in AI – with regulatory requirements.
- Staying vigilant and proactive in adapting development processes in response to evolving regulations is critical.
- Partnering with experienced firms that navigate the convergence of FHIR interoperability, AI, and healthcare compliance can turn regulatory challenges into strategic strengths. In particular, healthcare data analytics consulting helps organizations align innovation with compliance, ensuring that data strategies support both patient safety and regulatory readiness.
Healthcare compliance regulations for Software as a Medical Device (SaMD)
Software as a Medical Device (SaMD) refers to software intended for medical purposes without being part of a hardware device. In practice, this can include diagnostic smartphone apps, clinical decision support algorithms, or cloud-based health monitoring platforms. Both U.S. and EU regulators classify SaMD as a type of medical device, meaning such software must meet medical device safety and performance requirements equivalent to physical devices. These requirements are essential components of healthcare regulatory compliance when deploying software in clinical settings.
Regulatory Classification in US vs. EU
In the United States, SaMD falls under the same risk-based device classes as traditional hardware – Class I, II, or III, depending on its intended use and risk level. Higher-risk software (e.g. used for critical diagnoses or treatment decisions) will be Class II or III, requiring rigorous FDA review, while lower-risk wellness apps might be Class I or exempt.
In the European Union, the EU Medical Device Regulation (MDR) similarly applies risk classes I, IIa, IIb, or III to software. EU rules (notably MDR Rule 11) tend to up-classify many standalone clinical software: for example, software providing information for diagnosis or therapy is at least Class IIa, with potential elevation to IIb or III if its decisions could seriously deteriorate health or cause death. The upshot is that in both jurisdictions SaMD is regulated on par with medical devices – its risk classification drives the level of scrutiny, documentation, and approvals required.
Compliance Implications: If software is deemed SaMD, it triggers full medical device compliance obligations. Businesses must implement a quality management system and fulfill regulatory controls just as they would for a physical device.
The SaMD designation often lengthens development timelines and adds compliance costs, but it is crucial for market access. Healthcare executives need to plan for these compliance requirements early – allocating resources for documentation, risk assessments, and possibly partner with regulatory experts – to avoid delays in product launch.
Key Regulatory Standards for SaMD
Medical device software teams must navigate several key standards and regulations that establish the “rules of the road” for quality and safety. Adhering to these frameworks is not only a legal requirement in the US/EU markets but also a strategic investment in product reliability and company reputation. Below are some of the primary standards executives should ensure their teams align with as part of their compliance in healthcare data development strategies.
Software Development Life Cycle (SDLC) Regulatory Compliance
It’s not enough to merely check off the boxes for healthcare regulations at the end of development; they need to be part of the software development life cycle (SDLC) from the start. To be compliant, you need a structured SDLC that includes design controls and risk management.
Adding compliance to the SDLC implies that there are quality assurance and regulatory checks at every stage of development.
By embedding these steps, the development team creates the necessary Design History File (DHF) and Technical Documentation as a natural byproduct of development, rather than a scramble at the end.
This proactive strategy lowers the risk of unexpected non-compliance issues that might slow down market entrance or regulatory approvals. For company executives, putting money into a compliant SDLC lowers the chance of costly redesigns or recalls, and it typically speeds up time-to-market since regulatory reviewers can easily see proof of a strong development process. It’s essential to clearly identify the roles and responsibilities for healthcare regulatory compliance at the start of a collaborative or partnered development project. This makes sure that everyone follows the same strategy for development and documentation.
Key standards in Healthcare SDLC
There are also particular requirements for medical software development and use, in addition to general quality and risk standards. These provide software teams clear instructions on how to follow the regulations and fulfill the expectations of regulatory bodies.
- IEC 62304 – Medical Device Software Life Cycle Processes: IEC 62304 is the primary international standard that defines the software development life cycle for medical device software. It specifies a framework of processes and objectives needed to safely design and maintain software, covering everything from initial planning and requirements through coding, verification, release, and maintenance. Notably, IEC 62304 introduces software safety classes (A, B, C) based on risk, which determine the level of rigor required in development and testing.
Regulatory bodies in both the EU and US highly encourage or expect compliance with IEC 62304 for SaMD and software in devices, as it provides confidence that the software has been engineered with patient safety in mind.
- IEC 62366 – Usability Engineering for Medical Devices: IEC 62366 focuses on the human factors engineering aspect of medical devices, including software UIs. This international standard provides a structured process for manufacturers to analyze, specify, develop, and evaluate the usability of a medical device’s user interface with regard to safety. In practical terms, IEC 62366 guides teams to study how users interact with the software, identify use-related hazards or potential user errors, and iterate the design to mitigate those risks. Following this standard is crucial in preventing “use errors” – mistakes not from device failure, but from confusion or misuse – which can just as seriously endanger patients.
Read also:
Read the case studyRegulators place high importance on usability (for example, FDA human factors guidance aligns with IEC 62366 principles), and the FDA has formally recognized IEC 62366 as a consensus standard. This means a manufacturer can submit a Declaration of Conformity to IEC 62366 to partly satisfy FDA premarket review requirements, streamlining the approval process.
To follow healthcare compliance regulations, you need to find a balance between following the guidelines and making plans for your organization. The difficult aspect for leaders is getting developers, regulators, and partners to work together on these requirements. Those who succeed not only get to market sooner, but they also healthcare data regulatory compliance bodies, healthcare providers, and patients. Ultimately, this fosters greater market credibility and long-term financial sustainability.
Regulatory Compliance with AI in Healthcare
AI is becoming a bigger part of patient care, from diagnostic algorithms to virtual health aides. This is expected to lead to better results and more efficient treatment. The FDA has approved more than 690 AI-powered medical devices for use in the United States alone. This shows how quickly these technologies are being used in healthcare. As organisations engage in AI healthcare solutions development, they must not only innovate—but also prepare for increased scrutiny from regulators. Authorities want to make sure that AI systems are safe, useful, and reliable when used in real-world care situations.
AI applications can assist, automate, and improve many medical processes, but they also come with additional risks that need to be controlled by regulations. So far, authorities in the U.S. and the EU have mostly looked at healthcare AI through the lens of current medical device frameworks, classifying software as a medical device and putting it under the same rules. While this approach is suitable for many AI solutions, it introduces significant challenges.
Traditional regulations didn’t take into account AI’s unique capacity to change its algorithms based on fresh data over time, which might mean that it evolves faster than the initial approval requirements. Because of this, the vast majority agree that the present restrictions may not be enough for powerful, self-driving AI. In response, policymakers are changing guidelines and making new regulations just for AI.
The EU is moving away from voluntary recommendations and toward a full Artificial Intelligence Act that would set strict rules for AI in important areas like healthcare, such as how to manage risks, regulate data, be open, and have human supervision. This shift reinforces the need for interoperability and compliance in healthcare when adopting AI at scale.
Meanwhile, U.S. authorities are working on their regulations to encourage responsible AI innovation while protecting patients. For example, the FDA is developing new guidelines for AI-driven devices, and the Office of the National Coordinator for Health IT (ONC) is making new standards. There is even talk of unifying transatlantic approaches; a combined EU-US project is looking at an AI code of conduct to make standards more consistent. Healthcare CEOs need to be able to navigate regulations while employing AI in patient care since the landscape is always changing. Regulators have a clear goal: to make sure that AI can bring about big changes in healthcare without putting patient safety, data integrity, or ethical norms at risk.
Regulatory compliance HTI-1 in the US
In the United States, one of the most significant recent regulatory updates for healthcare AI comes from the Office of the National Coordinator for Health IT (ONC). In 2023, ONC released the Health Data, Technology, and Interoperability: Certification Program Updates, Algorithm Transparency, and Information Sharing (HTI-1) Final Rule, which directly addresses AI usage in certified health software. HTI-1 introduces transparency requirements for artificial intelligence and other predictive algorithms embedded in electronic health records (EHRs) and clinical decision support tools , reinforcing the importance of regulatory compliance in healthcare when adopting AI-driven solutions.
For any health IT product to earn or maintain ONC certification (which is used by over 96% of U.S. hospitals), developers must now disclose key information about their AI models. This includes details like what data the algorithm was trained on, its intended purpose, and performance characteristics directly supporting healthcare data regulatory compliance efforts. The goal is to give frontline clinicians a consistent, baseline set of information about each algorithm they rely on for patient care.
Compliance with HTI-1 means that healthcare software vendors using AI must build algorithmic transparency into their products by design. For example, if an EHR includes a machine learning risk predictor (say for sepsis or readmission), the vendor will need to provide end-users access to documentation or a “nutrition label” for that model – detailing how it works and any known limitations or biases. Organizations implementing such systems should be prepared for additional paperwork and governance processes to gather and review these disclosures from their vendors, maintaining regulatory compliance in healthcare industry standards.
Over the next couple of years, healthcare providers will likely see new information windows or dashboards in their clinical software, revealing facts about the AI suggestions that previously might have been “black box.” This push for transparency doesn’t occur in isolation; HTI-1 is part of a broader strategy to improve data interoperability and compliance in healthcare. Alongside the AI provisions, the rule upgrades data standards (adopting USCDI v3 as a new baseline for data interoperability) to ensure more complete and high-quality data exchange USCDI v3 expands the range of standardized patient data (including social determinants of health, health status, etc.), which in turn can improve the quality of data feeding AI algorithms.
Robust interoperability frameworks like HL7 FHIR are essential to meeting these new requirements by enabling standardized, structured data exchange between systems. Solutions such as our Kodjin FHIR Server provide scalable, FHIR-native infrastructure that helps organizations implement USCDI v3, manage AI-ready data, and maintain compliance with evolving regulatory frameworks like HTI-1. By leveraging modern FHIR-based platforms, healthcare organizations can streamline certification, enhance data transparency, and ensure their systems are future-ready for regulatory and AI-driven innovations.
In the long run, this transparency is poised to increase provider and patient trust in AI-supported healthcare, but in the short run, it requires proactive adaptation and possibly updates or upgrades to certified systems.
The Path Forward in Healthcare Software Regulation
The quickly changing regulations for healthcare software provide both challenges and opportunities for companies who work in this field. As we’ve seen, the rules in the US and EU are getting more complex to deal with the special requirements of SaMD, AI-based healthcare solutions, and data management procedures, all of which fall under evolving healthcare compliance regulations.
There are a few main themes emerging:
| Main Regulatory Themes for Healthcare Software Regulation | |
| Compliance should be a part of every step of development | Regulatory compliance is no longer something that can be put off until later; it needs to be a part of the whole software development lifecycle. Companies that include quality management systems, risk assessments, and regulatory requirements from the very beginning of development may save money on redesigns and get their products to market faster. |
| Bringing together AI and medical device rules | As AI becomes increasingly common in healthcare, regulatory agencies are changing the rules that are already in place and adopting new ones just for AI. The FDA’s approach to AI-powered devices and the EU’s Artificial Intelligence Act show that there is a trend toward more thorough supervision, ensuring regulatory compliance in healthcare industry standards that strike a balance between patient safety and innovation. |
| Data is the basis of compliance | The quality, control, and interoperability of healthcare data are important for both following the rules and using AI effectively. To fulfill transparency standards and show that AI systems are safe and effective, a strong data fabric that makes sure data is standardized and well-managed is becoming more and more important. |
| Transparency as a rule of law | New regulations, such as ONC’s HTI-1 rule, show the growing significance of healthcare regulatory compliance and the need for transparency in healthcare software. To earn the trust of regulators, healthcare providers, and patients, businesses need to be ready to write down and share information about their algorithms, data practices, and development processes. |
Healthcare leaders and development teams need to take a strategic approach to navigating this complicated regulatory environment. This means making sure that compliance initiatives are in line with company goals. This means:
- Putting money into quality management systems that meet standards like 21 CFR 820, IEC 62304, and ISO 13485;
- Creating teams that bring together people with technological, clinical, and regulatory knowledge;
- Setting up strong data governance systems that help both AI innovation and compliance in healthcare data development;
- Keeping an eye on changing rules and proactively changing how development is done.
In this climate, the businesses that do well will be the ones who don’t see following the rules as a burden, but as a chance to stand out by being safe, high-quality, and trustworthy. Healthcare software developers may not only get into the market but also create trust with healthcare practitioners and help patients get well by following regulatory best practices.
The regulations on healthcare software will definitely change as it continues to change how patients are cared for, from hospitals to home monitoring. Companies that plan forward will help shape these rules by joining industry groups, getting involved with regulators, and making a commitment to ethical innovation. In the future, healthcare software regulation won’t simply be about following the rules that are already in place. It will also be about working together to create frameworks that safeguard patients while allowing digital health innovation to reach its full potential.
To succeed in this dynamic environment, organizations need experienced partners who understand the intersection of interoperability, AI, and healthcare compliance. Edenlab helps companies navigate the complexities of regulatory requirements, build secure and standards-compliant solutions, and accelerate time-to-market. Our team combines deep expertise in FHIR, data software development, and healthcare data governance to turn regulatory challenges into strategic advantages.
Want to simplify compliance and drive faster, safer healthcare data projects?
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FAQ
How can I ensure my healthcare data partner is HIPAA-compliant?
To ensure your healthcare data partner is HIPAA-compliant, start by requesting documentation of their HIPAA policies, recent risk assessments, and evidence of employee training on privacy and security practices. Confirm they sign a Business Associate Agreement (BAA), which legally binds them to HIPAA standards.
Evaluate their technical safeguards – such as encryption, access controls, and audit logging – as well as their processes for breach notification and incident response. You may also want to conduct a due diligence review or third-party audit to verify their compliance posture before sharing any protected health information (PHI).
How do you automate compliance processes?
Automating compliance processes in healthcare typically involves leveraging specialized software that monitors systems for policy violations, enforces access controls, manages documentation, and generates audit trails automatically. Tools such as compliance management platforms can track regulatory changes, schedule regular risk assessments, and alert staff about required actions or expired credentials.
Automation can extend to continuous monitoring of data access and security configurations, ensuring deviations from standard practices are detected and addressed promptly. Integrating these tools into your IT workflows reduces manual effort, streamlines reporting, and helps maintain up-to-date, auditable records for regulatory reviews.
What is the biggest threat to the security of healthcare data?
The biggest threat to the security of healthcare data remains unauthorized access, most commonly through phishing attacks, compromised credentials, or insider misuse. Healthcare organizations are frequent targets for cybercriminals because electronic health records contain highly valuable personal and financial information. Ongoing vigilance, strong identity management, and robust staff education are critical to minimizing this risk.
What healthcare compliance practices to watch in 2025?
In 2025, healthcare compliance will increasingly focus on transparency and traceability for AI-driven systems, expanded privacy regulations around patient-generated and wearable data, and stricter enforcement of third-party risk management.
Regulatory bodies are expected to push for explainability in clinical algorithms, require evidence of bias mitigation, and mandate continuous post-market monitoring for AI solutions. Additionally, compliance programs will need to adapt to evolving international data transfer standards and demonstrate proactive management of cloud and vendor security. Organizations that integrate automated monitoring, real-time policy updates, and comprehensive incident response into their compliance strategies will be best positioned to navigate this rapidly changing environment.
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