Navina Insights on Ethical AI Implementation in Healthcare

Ronen Lavi, CEO and Co-Founder of Navina sat down with Healthcare Digital to discuss ethical AI implementation in healthcare

Physician-first AI platform \was founded in 2018 to help healthcare organisations succeed in value-based care. Founder and CEO Ronen Lavi's career spans over two decades in the Israel Defense Forces (IDF), where he was notably recognised for establishing and leading the AI Lab of the renowned military intelligence unit. 

Under his leadership, the AI Lab collaborated with leading tech companies and academic institutions to develop cross-functional platforms that provide insight into areas challenged by diverse and complex data. His contributions in this field were acknowledged in 2018 when he received the prestigious National Security Award. Since then, Lavi has been channelling his expertise of leveraging complex, multi-modal data for real-time decision making into solving the most complex data challenges in primary care, with a broader vision of revolutionising the healthcare sector with AI.  

Lavi shares his expert insight with Healthcare Digital about ethical AI implementation.

What emerging technologies in Health IT are currently shaping the landscape, and how do they contribute to improved patient outcomes and healthcare delivery?

Artificial intelligence (AI) was undoubtedly the top tech trend of 2023, and its nascent impact on healthcare is sure to be one of the key developments of 2024. Empowering healthcare with AI is not just a technical upgrade; it represents a paradigm shift, with significant potential to revolutionise healthcare delivery. 

The timing is auspicious: the current healthcare landscape is at a pivotal inflection point, with value-based care models on the rise, growing interoperability, and an influx of new sources of patient health data. These changes hold immense potential for bridging clinical information gaps and aligning provider incentives with the true value of care.

In 2024, AI will make a significant impact in two areas. The first is the automation of routine tasks and workflows, for instance by using ambient AI scribes or solutions that automate the prior authorization. Automation can be especially helpful in mitigating the effect of staff shortages and reducing physician burnout. By streamlining administrative processes and reducing the time spent on data entry and retrieval, healthcare professionals can focus more on direct patient care. This not only improves efficiency but also enhances the quality of patient-provider interactions.

The second trend we should pay attention to is the increased use of AI to enhance and augment clinical processes by engaging deeply with actual patient data. AI-assisted radiology analysis is one prominent use case. Predictive analytics for early intervention and preventive care are another exciting opportunity. By analysing vast amounts of data, including patient history, lab results and genetic information, these tools can help identify patients at risk of chronic diseases or complications early. This early intervention approach facilitates preventive care measures, potentially reducing hospital readmissions and improving long-term health outcomes.

What should be trending in health IT that’s not?

In 2024, as clinicians grow increasingly sophisticated when it comes to AI, the need for explainable and responsible AI is sure to emerge as a key trend. Doctors and the organisations they work for will seek responsible AI solutions that provide evidence-based and explainable recommendations.

As the focus shifts towards responsible AI, healthcare leaders seeking to incorporate innovative AI technologies into their organisations’ clinical workflows will need to be aware of how these tools work. Many solutions cannot provide tailored recommendations for care for individual patients, as they are based on millions of data points with no specific emphasis on the individual. Their lack of personalised focus and explainability due to their ‘black box’ nature underscores the need for solutions that can make sense of specific patient data and generate evidence-based insights for clinicians, granting them the final word in their decision-making.

What health IT trend has you concerned? What can be done about it and what’s the impact if we do nothing?

While AI-powered healthcare solutions are indeed trending, and it’s difficult to argue with AI’s potential to transform healthcare, its long-term success is dependent on its adoption by hundreds of thousands of very busy doctors. Getting AI tools in the hands of those who need them most – physicians at the point of care – is an uphill battle. Adapting to paradigm shifts is never easy, and overburdened physicians have every reason to be resistant to new solutions. Generic ‘black box’ solutions that lack evidence-backed explainability particularly risk alienating clinical teams and turning them off AI altogether.

Given the adoption challenge, even the most forward-thinking organizations might be tempted to focus on AI-powered analytics and other backoffice solutions, leaving much of AI’s potential untapped: fragmented patient data will continue to overwhelm providers, creating chaos instead of being used to improve care and health outcomes. Responsible, evidence-backed AI solutions designed with physicians’ needs in mind will go a long way towards mitigating this challenge.

What health IT trend are not enough people talking about that they should be?

The ethics of AI in healthcare is garnering increasing attention but is still not as central in the discourse as it should be. This aspect of healthcare technology poses numerous challenges and considerations that are critical to the responsible and beneficial implementation of AI in this sensitive field. The need for transparency and explainability of AI systems is a leading ethical concern. A lack of transparency can erode trust and accountability, which are crucial in healthcare settings.

One primary ethical concern is the risk of inherent biases in AI algorithms, often as a result of training AI systems on datasets that do not adequately represent the full diversity of patient populations. This can lead to AI tools that perpetuate existing healthcare disparities, leading to unequal treatment and outcomes for various demographic groups, particularly minorities. To counter this, it is essential to employ diverse and inclusive data sets in training AI models and to establish mechanisms for the continuous monitoring and correction of biases in AI outputs.

It is incumbent on all players at the nexus of healthcare and technology to be guided by both the age-old ethics at the heart of the physician-patient relationship, as well as the latest technological developments that can help offset structural biases and other concerns. 

Which health IT trend has you most excited and why is it exciting?

AI’s ability to make sense of chaotic, multi-source patient data, and to turn it into actionable insights for clinicians is especially exciting. This empowers physicians to make better informed decisions, and focus more on patient-centric care, rather than getting bogged down by data management and administrative tasks. As AI grows ever-more sophisticated, the impact on both physicians and their patients will be profound. 

The continuing development of generative AI will allow for intuitive, conversational interfaces where clinicians can interact naturally, using the specific language and nuances of their discipline. And as data sets and algorithms expand and evolve, we will see robust AI solutions that can help predict patient outcomes, anticipate future health trends, and personalise care. This not only has the potential to revolutionise healthcare delivery but also significantly improve patient outcomes and reduce healthcare costs.

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