Navigating the future of healthcare: AI, technology, and medico-legal considerations

June 16, 2024
healthcaretoday, APHM, Zubin J Daruwalla, health tech, artificial intelligence, AI, big data analytics, patient centricity, healthcare, connected care, medico-legal, predictive care,
​​In the rapidly evolving landscape of healthcare, the intersection of artificial intelligence (AI), innovative technologies, and medico-legal implications is creating a complex yet promising future. Dr Zubin J Daruwalla (pix), APAC Health Industries Leader at PwC Singapore, recently addressed these critical topics at the Association of Private Hospitals, Malaysia (APHM)’s 30th International Healthcare Conference and Exhibition.

The perils of relying on technology
Years ago, in the UK, a controversial figure advised people to consult Google instead of visiting the emergency department. This approach led to tragic consequences, such as a case where a mother, relying on online information, failed to recognize her child's rash as a symptom of meningitis. The child, unfortunately, passed away. This incident starkly illustrates the potential dangers of over-reliance on technology without proper medical guidance.

Similar stories have emerged, including the rise and fall of Babylon Health. Initially celebrated for its AI outperforming human doctors in clinical exams, Babylon ultimately faced bankruptcy due to multiple issues within its model. Despite predictions in 2019 that AI would become mainstream in healthcare, the reality has been more complex and challenging.

The new health economy
Dr Zubin describes the "new health economy" as a global health ecosystem where new entrants—ranging from startups to established corporations—are bringing fresh perspectives and technologies into healthcare. These players are leveraging new business models, financing mechanisms, and healthcare delivery methods to transform care.

However, as we embrace these advancements, it remains crucial to prioritize patients. Key considerations include privacy, accessibility, affordability, quality care, accountability, and technology integration. The new ecosystem is characterized by three main attributes:
  • Predictive: Utilizing real-time data on patients' vital signs, lifestyle behaviors, and social factors to anticipate health issues.
  • Preventative: Enhanced predictive capabilities enable proactive measures, such as tracking the spread of diseases like COVID-19 through smartphone apps.
  • Participatory: With 5G technology, patients become active participants in their healthcare, making informed decisions and engaging more deeply with their health outcomes.

Global healthcare trends
Globally, healthcare is witnessing significant trends such as AI and intelligent automation, big data analytics, and a focus on patient-centricity. These shifts include:
  • Transitioning from healthcare to health, emphasizing preventative care.
  • Moving from hospital-based to home and community-based care.
  • Shifting from fee-for-service models to value-based care, where outcomes determine compensation.
In this new paradigm, patients have more control over their healthcare choices, armed with vast amounts of information—both accurate and misleading.

Understanding AI and its components
Artificial intelligence encompasses techniques that enable computers to mimic human intelligence through logic, decision trees, and machine learning (ML), including deep learning. Key components include:
  • Machine learning: Techniques that allow machines to improve tasks with experience, including deep learning.
  • Neural networks: Models inspired by biological neural networks in animal brains, comprising interconnected nodes called artificial neurons.
  • Deep learning: Algorithms that enable software to perform tasks like speech and image recognition by training multilayered neural networks with extensive data.
  • Generative AI: AI capable of generating text, images, videos, or other data using generative models.
  • Large language models: These models can recognize, summarize, translate, predict, and generate vast datasets.

The convergence of healthcare, health tech, and pharma is leading to connected care, where devices link patients directly to providers, enhancing convenience, quality, and personalization.

Medico-legal considerations in AI adoption
The integration of AI in healthcare presents both opportunities and risks. Benefits include improved administrative efficiency, predictive care, medical imaging, diagnostics, and drug discovery. However, the risks are multifaceted and must be carefully managed.

Risks can be categorized into data-related, model-related, and user-related risks. A comprehensive risk assessment framework should include:
  • Risk and threat analysis: Identifying potential risks and threats.
  • Impact analysis: Assessing the potential impact of identified risks.
  • Mitigation measures: Implementing strategies to mitigate these risks.
Organizations and governments must develop policies to ensure the safe and reliable adoption of AI systems. This involves identifying and managing risks, assessing their impact, and employing effective mitigation strategies.

The evolution of technology in healthcare
Technological evolution over the past two decades has been astounding. From cumbersome computers to portable devices, and now to cutting-edge innovations like digital contact lenses and real-time blood parameter bots, the pace of change is unprecedented. Despite fears of AI surpassing human capabilities, technology is intended to complement, not replace, clinical practices.

Dr Zubin emphasizes that technology should augment clinical practices, not replace them. While AI has become a buzzword, the greatest challenge remains clinical adoption. The question of responsibility in autonomous systems—whether it lies with the practitioner, manufacturer, healthcare facility, or technician—remains a gray area.

Ensuring patient-centric care
As we integrate AI into healthcare, maintaining the standard of care is paramount. Whether AI is used to replace or complement clinical processes, the onus remains on clinicians to ensure patient safety and quality of care. This includes securing informed consent and validating the clinical efficacy of AI solutions.

The liability regime varies depending on whether AI is classified as a medical product or service. Product liability applies when hardware or software is involved, while clinicians must ensure that the standard of care is not compromised. Even in automated processes, responsibility ultimately falls on the provider to mitigate risks and uphold care standards.

The role of technology in enhancing healthcare delivery
Digital transformation, including AI adoption, has significantly benefited healthcare delivery. It has improved emergency flow, reduced hospital stays, optimized operating theatres, and enhanced outpatient and labor management. However, the human touch—compassion, empathy, and personalized care—remains irreplaceable.

Embracing technology responsibly
The future of healthcare lies in the responsible integration of technology. AI and other innovations should complement clinical practices, not replace them. Ensuring patient-centric care, maintaining high standards, and addressing medico-legal implications are crucial as we navigate this evolving landscape.

As we move forward, the key is to embrace technology while retaining the human elements that are fundamental to healthcare. The convergence of technology and medicine promises a future where care is more predictive, preventative, and participatory—benefiting both patients and providers. The challenge lies in balancing these advancements with the ethical, legal, and human considerations that define quality healthcare.

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