Driving Adoption in HealthTech: The Role of Human-AI Interaction

Working in health technology, it’s easy to get excited about the groundbreaking potential of AI in healthcare. From AI-driven diagnostics that uncover early indicators of disease to wearables that empower patients to monitor their own health, we’re seeing developments that could redefine the patient experience. But beyond the impressive capabilities of AI lies something equally important: the way humans interact with this technology. In a world where digital tools are increasingly intuitive, Human-AI Interaction (HAI) should be treated with as much care as the algorithms driving these tools.

HAI: The Often Overlooked Element in AI Systems

HAI refers to how humans engage with, interact with, and provide input to AI-driven systems. In healthcare, this means developing AI tools that are not only highly effective but also intuitive and seamlessly integrated into the day-to-day lives of patients and clinicians. When it comes to healthcare, an AI application isn’t just “another tool.” It’s something that has to fit naturally into a clinician’s workflow or a patient’s routine, and any friction there could mean the difference between regular use and abandonment.

The Changing Landscape of HAI

As technology becomes more deeply embedded in daily life, users’ expectations have shifted accordingly. Consider how Apple’s careful design choices in haptics and gestures have turned certain swipes, taps, and clicks into second nature. As these interactions become the new standard, users have come to expect seamless and frictionless experiences across all digital platforms.

This applies to healthcare just as much as to consumer tech. Patients and clinicians alike need AI tools that work effortlessly, giving them access to valuable insights without requiring them to think too hard about how they’re using the tool. According to a 2022 HIMSS report, over 70% of users expect the same intuitive experience from health technology as they get with consumer apps, underscoring a need for health tech companies to prioritise HAI in their designs

Leading Examples of HAI in HealthTech

Some AI health technologies today are making impressive strides in balancing powerful capabilities with engaging and intuitive interfaces. Here are a few notable examples:

• Gamified AI Applications: Certain mental health apps, such as Woebot Health and thymia, use conversational AI with gamified interactions. This approach makes the experience more interactive and less clinical, which encourages consistent use. By focusing on the human element, these applications provide users with an approachable way to manage their mental health while collecting valuable data.

• Passive Monitoring through Wearables: Wearables like the ŌURA Ring are at the forefront of passive monitoring, tracking metrics like sleep, activity, and heart rate without users needing to take any action. The global wearable technology market is projected to grow at a compound annual growth rate (CAGR) of 18.1% through 2030, reaching £175 billion by the end of the decade. This growth reflects the rising demand for health insights delivered passively, enabling early intervention and empowering patient autonomy in ways previously not possible.

• Video Analysis: Advances in AI can now detect signs of mental health challenges through speech and video analysis, examining facial expressions and vocal patterns for early indicators. Early mental health intervention is crucial, and by integrating these tools into everyday devices, the potential for timely support expands .

These examples how focusing on HAI can shape patient and clinician engagement, promoting regular use and enabling insights that support better health outcomes.

The Importance of HAI: Why It Matters

In my view, HAI plays a vital role in health technology adoption, as a well-designed interaction framework brings several key benefits:

• Encouraging Adoption and Consistency: Easy-to-use health technologies are more likely to be consistently used. A 2023 Deloitte study showed that health apps with simple, intuitive designs achieved 30% higher retention rates, underscoring the importance of user experience in long-term engagement .

• Reducing Bias: Wed HAI can reduce conscious and unconscious biases that affect assessments and diagnoses. Research shows that patients’ knowledge of being observed can influence their responses, which can skew mental health evaluations. Tools that passively collect data can provide more objective assessments, helping clinicians make unbiased decisions .

• Empowering Patient Autonomy: Monitoring and personalised insights allow patients to take control of their health and become more active participants in their care. This kind of empowerment aligns with the NHS’s goals for patient autonomy and preventative healthcare, creating pathways to healthier lives without additional burden on healthcare providers.

The Road Ahead: What the Future Holds for HAI in Healthcare

Looking forward, I expect that HAI will only become more essential. Here’s how I envision this evolution:

• More Comprehensive HAI Design in AI Tools: The best AI health tech of the future will prioritise not only technical capability but also intuitive, accessible design. It’s possible we’ll see the rise of AI “super apps” that combine passive monitoring, gamified assessments, and voice or gesture interfaces in one seamless experience, giving patients and clinicians a single, cohesive point of interaction.

• Integration with National He alth Systems: Once these tools achieve regulatory approval - and subsequently the credibility they need for institutional buy-in -they could be integrated with national healthcare systems, pulling in individual medical and medication histories to create comprehensive, context-aware assessments. This level of integration could open doors to AI-powered preventative care at scale, personalised for each patient and grounded in a unified system.

Conclusion

Human-AI Interaction is not a nice-to-have; it’s essential to realising the full potential of AI in healthcare. AI tools that are thoughtfully designed, intuitive, and engaging drive better adoption, improve patient outcomes, and ultimately make a greater impact. As HAI principles evolve, we move closer to a future where healthcare technology is more accessible, integrated, and centred on the human experience. By prioritising HAI, we’re setting the stage for AI to empower patients and healthcare professionals alike.

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