AI is revolutionizing industries everywhere, and healthcare is feeling its impact just as quickly, bringing both new challenges and opportunities for health IT developers. From predictive analytics to AI-powered decision-support tools, AI developers are redefining how healthcare providers make critical decisions and improve patient outcomes. Yet, as innovation accelerates, so does the complexity of delivering safe, secure, and compliant solutions. As a result, ensuring that AI technologies are reliable and trustworthy is essential—not just for meeting regulatory standards, but also for encouraging widespread adoption. When these qualities are in place, they foster confidence among providers, payers, and Electronic Health Record (EHR) developers, creating more opportunities to improve care delivery and streamline operations.
To highlight the importance of trust in healthcare AI, let’s examine the growing concerns around ethical risks and system reliability—and how effective risk management helps developers address these issues while gaining a competitive edge in the market.
Skepticism Impacting AI Acceptance in Healthcare
High-profile incidents of algorithmic bias and evolving discussions towards the validity of AI-based decision support has led to heightened scrutiny towards AI technologies. This growing apprehension is reflected in a 2023 study by Pew Research Center, which found that 60% of Americans are concerned about the potential misuse of AI in critical sectors like healthcare, illustrating the skepticism developers must overcome.
For developers, this statistic underscores a crucial reality: perception of AI risks in healthcare can make or break the adoption of AI solutions. When providers making critical care decisions are apprehensive about the validity of AI-driven decision processes, developers face a steep uphill battle in gaining stakeholder trust. Providers need assurance that AI tools will enhance—not undermine—clinical decision-making, while payers require confidence in the system’s ability to meet operational goals and regulatory standards. If healthcare providers perceive an AI solution as unreliable or unsafe, adoption rates will plummet, no matter how innovative or advanced the technology may be.
To overcome this skepticism and build the trust necessary for adoption, developers must go beyond innovation, demonstrating a proactive commitment to mitigating risks and ensuring transparency. Let’s look at how deliberate, measurable actions—like certifications, validations, and transparent communication—can reinforce confidence and build trust in healthcare AI solutions.
Developing Trust Through Effective Risk Management Strategies
For healthcare AI developers, earning trust requires a steadfast commitment to risk management and transparency. This commitment begins with obtaining independent certifications and accreditations. Publicly sharing these certifications and regularly updating customers on renewals or expansions underscores a developer’s dedication to safety, compliance, and accountability.
Equally important is a commitment to ethical AI practices. Developers should align their development processes with industry guidelines and share updates on system improvements or incident resolutions to demonstrate accountability. Sharing customer success stories and actively engaging in industry discussions showcases a broader dedication to both innovation and the advancement of safe, reliable healthcare AI.
Third-party validation further bolsters credibility. Independent audits and participation in industry-standard programs like FHIR interoperability testing or HL7 validation reflect a proactive effort to meet and exceed regulatory expectations. Developers should prominently feature these validations, along with partnerships with trusted standards bodies and regulators, to instill confidence in stakeholders and healthcare providers.
At the heart of all these efforts lies certification—an unequivocal benchmark of trust and reliability. Independent certifications validate that a developer’s solutions meet rigorous safety, compliance, and performance standards. By prioritizing certifications and prominently showcasing their achievements, healthcare AI developers not only strengthen customer trust but also lay a solid foundation for adaptability, ensuring their solutions remain competitive as regulatory demands evolve.
The Competitive Edge in Prioritizing Certification
Certification and risk management are crucial for developers aiming to enhance their solutions and establish trust. These foundational practices help ensure solutions align with industry standards, stay adaptable to evolving regulations, and earn the confidence of stakeholders. Below are the key benefits developers can achieve by prioritizing risk management validation:
Future-Proofing Your Solution Through Certification
As AI continues to propel healthcare innovation, staying compliant with shifting guidelines has become a critical priority. Furthermore, certification acts as both a benchmark and a roadmap, offering developers a structured framework to demonstrate their commitment to risk management while promoting best practices that could eventually become essential for meeting increasingly complex compliance requirements. Examples of these best practices are:
- Identifying and disclosing known risks.
- Clearly documenting intended uses and the target patient populations.
- Detailing risk mitigation strategies, with a focus on addressing validity and bias.
- Demonstrating ongoing monitoring of AI models and the outcomes they generate.
Beyond regulatory readiness, certification also protects developers from ongoing non-compliance fines, which can be particularly severe in healthcare AI due to the sensitive nature of patient data and the high stakes of clinical decision-making. A single instance of algorithmic bias or faulty decision-support recommendations can lead to serious patient harm, triggering regulatory scrutiny, lawsuits, and reputational damage. By addressing these risks during development, certification offers a safeguard against such fallout while promoting long-term adaptability.
As AI adoption grows, stakeholders are increasingly prioritizing technologies that seamlessly integrate into existing workflows while maintaining compliance with regional and international standards. Certified developers are better positioned to meet these expectations, avoiding rework, penalties, and other risks, and confidently delivering solutions that thrive in the healthcare ecosystem of tomorrow.
This alignment with regulatory and compliance standards not only ensures future operational success but also builds the trust and confidence necessary to foster meaningful collaborations with key stakeholders across the healthcare ecosystem. Let’s explore how this commitment to risk management strengthens partnerships and fosters collaboration across the healthcare ecosystem.
Strengthening Partnerships Through Certification
For providers, payers, and EHR partners, certification acts as a visible assurance that an AI solution has undergone rigorous evaluation and adheres to the industry standards for risk management. This trust is essential for fostering strong partnerships, as organizations are more likely to collaborate with developers whose solutions demonstrate proven compliance with industry regulations and best practices.
In particular, the Drummond pDSI-Risk certification is tailored to support partnerships between healthcare AI developers and ASTP/ONC-certified Health IT systems. When EHRs incorporate AI modules developed by external parties, they assume stewardship of those modules and must ensure they meet ASTP/ONC risk management standards to maintain their certification. Partnering with non-compliant developers puts an EHR’s certification at risk. By achieving pDSI-Risk certification, AI developers provide assurance that their solutions meet these stringent standards, fostering stronger, more secure collaborations.
Providers and payers also require trust assurances, often turning to AI governance platforms to verify that risk management is addressed in the AI solutions they select. These platforms leverage governance standards rooted in the NIST AI Risk Management Framework, which underpins ASTP/ONC and pDSI-Risk certification standards, as well as other growing AI governance compliance requirements.
This emphasis on compliance and trust offers a competitive advantage. Certification not only fosters collaboration but also elevates a developer’s brand by signaling a commitment to addressing AI risks in healthcare. Certified solutions are perceived as more reliable and aligned with industry expectations, making them the preferred choice for healthcare stakeholders. In an increasingly crowded AI marketplace, this credibility enhances brand reputation and positions certified developers as leaders in delivering innovative, ethical, and dependable AI solutions.
Partnering with Drummond: Building Trust and Excellence in Healthcare AI Certification
Drummond has long been recognized as a leader in health IT certification and compliance, with a reputation built on decades of delivering trusted, efficient, and effective certification processes. This legacy positions Drummond as a key ally in addressing the anxieties of stakeholders who are apprehensive about the reliability and safety of AI in healthcare. To meet these challenges head-on, Drummond has introduced its pDSI-Risk Certification Program, a comprehensive framework designed to certify AI health IT solutions by addressing critical challenges such as risk mitigation, transparency, and alignment with U.S. federal standards for the use of AI in health IT.
By leveraging Drummond’s proven expertise, developers, including AI and EHR innovators, can confidently demonstrate their commitment to building AI solutions that meet the highest standards of transparency, accountability, and security—effectively addressing the concerns of even the most skeptical stakeholders. The pDSI-Risk Certification Program not only ensures regulatory adherence but also provides a streamlined pathway to certification, empowering developers to build solutions that inspire trust, foster innovation, and position their products as indispensable tools in the healthcare ecosystem.
With Drummond, developers are not just checking a compliance box—they are building trust, accelerating their timelines, and positioning their AI solutions as benchmarks of reliability in a risk-averse healthcare sector.