AI-driven precision healthcare is here – what you need to know

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Dr. Anmol Kapoor, founder of CardiAI and BioAro, is an expert in precision healthcare, artificial intelligence and blockchain technologies. He has filed more than 70 patents in areas ranging from AI and genomics to quantum sciences and digital health. Through his work, he aims to transform modern healthcare through personalized, precision-based approaches.

We spoke with Kapoor recently to tap his expertise and gain a deeper understanding of these emerging areas of care innovation. We discussed AI-driven genomic analysis, explored where there are strategic opportunities for the C-suite in precision medicine and discussed how distributed ledger technology can enhance data security and trust in health systems pursuing genomics.

He also discussed how multi-omic integration can offer a competitive advantage for those health systems – and described how clinical and C-suite leaders should be navigating ethical and regulatory challenges as AI-powered precision medicine becomes more common.

Q. How does artificial intelligence help with genomic analysis, and how can it offer a strategic opportunity for hospitals and health systems to enhance patient outcomes and operational efficiency?

A. AI-driven genomics and precision medicine offer hospitals and health systems a significant opportunity to enhance their services and improve employee wellness. By using genomic and microbiome data, C-suite executives can implement targeted workplace wellness programs.

These initiatives can include screening and monitoring employees to identify predispositions to cardiovascular, metabolic or mental health disorders. Personalized health plans incorporating lifestyle and nutrition changes can help reduce lost man-hours and promote overall wellness. Additionally, mental health support can be strengthened by identifying at-risk individuals and providing access to counseling and stress management programs.

The microbiome, comprising the microorganisms within our bodies, plays a vital role in both physical and mental health. The gut-brain axis illustrates how gut health impacts mental wellbeing.

By monitoring patients and employees, health systems can develop dietary interventions to reduce stress, anxiety and depression while enhancing productivity. These interventions can lead to improved energy levels and overall workforce health.

AI-based guidance is particularly beneficial in high-stress industries like airlines and mining, where attention to detail and long working hours are common. AI tools can analyze data from employees to optimize job suitability, determine optimal work hours, and suggest appropriate break times and job rotations.

This approach minimizes burnout and boosts overall productivity. Machine learning-driven predictive analytics can develop models to assess how workplace environments, stress levels and genetic predispositions influence health and productivity.

Additionally, wearable health technology integrated with AI can continuously monitor health metrics like heart rate and stress levels in real time, providing valuable insights to refine workplace conditions and ensure employee wellbeing.

Q. Why do you believe blockchain is an ideal technology to deal with securing sensitive genomic information?

A. Blockchain technology provides an irreversible and non-editable robust framework, making it highly effective for protecting genomic and multi-omics data. Once data is recorded, it cannot be altered or deleted, safeguarding against unauthorized changes. By using encryption and decentralized identifiers, genomic data remains confidential even if accessed without permission.

Additionally, blockchain can efficiently handle large amounts of genomic data, ensuring the network stays fast and reliable as data volumes grow.

Smart contracts can provide individuals ownership and control over their genomic data, which they can grant or revoke, in real time. This creates a transparent audit trail for every data access, increasing accountability.

The secure exchange of health records among healthcare providers and researchers using blockchain not only supports a more connected healthcare ecosystem but also protects individual privacy. It can also be helpful to maintain continued regulatory compliance.

Q. You suggest integrating genomics, proteomics and metabolomics using AI can create a competitive advantage for health systems. Please elaborate.

A. AI-based integration of multi-omics data facilitates personalized medicine, enabling precise and personalized management of patients with minimal adverse effects.

AI algorithms can help identify biomarkers, which can be used for early disease detection and risk prediction through use of predictive analytics, making healthcare proactive and less reactive.

It also helps accelerate research and development to identify new biological pathways and mechanisms of disease that lead to innovative therapies and enhanced clinical decision-making support for healthcare providers.

Q. As hospitals and health systems adopt AI-driven genomic technologies, C-suite executives must address ethical, regulatory and legal challenges. How should leadership ensure ethical data use, patient consent and compliance with evolving regulations?

A. Ethical challenges faced by hospitals and healthcare providers primarily emanate from patient privacy and consent, with a high potential for misuse and breaches. Bias in AI/ML-models and complex AI-algorithm design can raise concerns about transparency and accountability.

C-suite executives, both within and outside a healthcare organization, should create a culture of transparency and ethical data use, focusing on patient and employee interests. This can be achieved through creation of ethical review boards and involving members of the general public in policy decision-making processes.

Technological advancements often outpace regulations, making it difficult to navigate the regulatory challenges around use of AI-driven genomic data. Proactive compliance with HIPAA, PIPEDA and GDPR, and regular audits and assessments of data handling practices, is needed.

Clear guidelines for AI applications in healthcare are also crucial and training staff on compliance and data protection standards can enhance the organization’s ability to effectively navigate the regulatory landscape.

Follow Bill’s HIT coverage on LinkedIn: Bill Siwicki
Email him: [email protected]
Healthcare IT News is a HIMSS Media publication

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