How AI is Disrupting Healthcare across the Patient Journey

By Jillian Robertson

Artificial intelligence (AI) — its potential applications, repercussions and cascading effects — has been making headlines across a wide variety of sectors, including healthcare and pharma. And as the world looks to strengthen healthcare systems in the wake of the global COVID-19 pandemic, it’s clear AI could serve as a disruptive force. Keeping up with the evolution and use cases of AI is now a critical part of how global and public health practitioners should think about potential solutions for patient care.

AI touches nearly every aspect of the patient journey and treatment cycle, from research and development through continued care, and understanding the promise and peril of its use is essential. One way AI could enhance the patient experience includes increasing the speed of drug discovery and development, leading to faster solutions to positively impact public health. That could mean increasing the speed of vaccine development or developing new solutions to address the global obesity epidemic, a rapidly growing space that could save healthcare systems billions if addressed properly.

Another area of potential impact for AI is software as a medical device and digital therapeutics as a whole, using technology to change the existing model of reliance on in-office visits and testing to something more agile. We got a taste of this during the pandemic, with the accelerated rollout and adoption of telemedicine. And in terms of digital therapeutics, there is potential for AI-based software solutions to help improve daily life for patients as well.

But as digital and AI-driven solutions accelerate, it’s vital to address equitable access and work to close digital divides in rural and under-resourced communities.

Trends we’re monitoring

Here are three AI trends we’re watching in the health and pharma space.

  • Self-diagnosis and self-care — What happens when consumers go from WebMD to ChatGPT to try to self-diagnose? Because AI tools are so readily available, people are already using them to attempt to diagnose their own medical conditions. Although this presents its own set of risks, with the right resources, mobile technology can help patients be their own best advocate.
  • Preventative care via chatbot — Overwhelmed health systems may turn to chatbots as a form of telemedicine, aggregating answers and triaging common issues, not unlike less sophisticated chatbots already do in non-healthcare contexts. Patient history and wearable data could be more easily synthesized and analyzed to identify early warning signs for diseases. This has the potential to make care delivery easier in under-resourced communities, collapsing the gap in access, especially in rural communities.
  • Patient privacy in public health — What are the implications of using AI in the highly-regulated healthcare setting and how will patient privacy be preserved (or threatened)? Health Insurance Portability and Accountability Act (HIPAA) calls for the deidentification of personal health data in any circumstance — but algorithms require extremely large sets of real patient data to learn. How can public health practitioners use AI to synthesize large amounts of information to gauge community health more quickly and accurately, while avoiding the pitfalls of inaccurate information?

As AI technology and its uses continue to rapidly evolve, these potential use cases for global and public health applications generate more questions than answers. But if properly applied, the possibilities for AI are enormous. Add to that, they could have real impact on patient health — reaching underserved communities, empowering more preventative health measures and giving healthcare practitioners powerful tools to use when tackling the multifaceted and nuanced challenges of patient diagnosis and treatment.

Jillian Robertson


Account Director, Digital & Healthcare

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