Revolutionising digital health care – the impact of AI

Suchitra Kataria MBBS, MD, MBA
Founder and CEO – Mélange Communications Pte Ltd, Singapore

Technological revolution in healthcare

In a traditional doctor-patient relationship, we have a recent entrant – technology, especially over a decade, making waves and shaking things in many ways.  Medicine has always been deeply rooted in data-driven, evidence-based science. But, technology or digitization has enabled data capture at a more granular level and from myriad sources, which were unthinkable a few decades back. The most significant transformation has been the quest to digitize patient data and distill the data for all purposes to enhance the quality of care and improve patient outcomes. Healthcare data in all forms and sources is the combustion fuel for digital engines to run and function smoothly and forge ahead.

Digitization of patient data: a paradigm shift

The in-clinic and hospitalized patient records are maintained and updated through electronic health records (EHR), telemedicine providing remote care, sensors sensing alarming signs and alerting, clinical decision support systems (CDSS) helping clinicians in real-time decision-making through artificial intelligence (AI), and large language model (LLM) providing clinical summary or diagnostic prompts, virtual reality (VR) for rehabilitation or mental conditioning are some of the transformative changes appending healthcare system’s digital transformation overhaul. Digital adoption is at the level of all stakeholders – clinicians, patients, and the healthcare system;. However, the degree varies from different geographies; the same digitization enables things to be replicated, transmitted, and scaled up at a far lower cost. The digital charge is taking on and shaking up traditional doctor-patient interactions from diagnosis, treatment, rehabilitation, and complication limitation. For example, the granularity and availability of digital data are helping provide vital clues to make the diagnosis by using computer vision and feeding radiological images into deep learning (ML/DL) AI models, which busy radiologists may miss.

AI’s inroads into healthcare: present and future

AI’s journey to impact the healthcare system has just begun. We are in the infantile stage of developing, adopting, validating, and applying AI for various applications. The algorithms must be trained on diverse datasets and tested for applicability to vast patient groups across different geographies. The outcomes may be good in the testing phase. Still, when confronted with different pragmatic situations in the clinic, the performance of AI may not meet expectations or match the exact performance benchmark. However, the potential and opportunities provided by AI to transform medical education, diagnosis, care quality, and patient management are immense. There have been several prophecies that predict AI will replace doctors in the near future. AI has an assistive role to play, but replacing clinicians is far-fetched. No algorithms can replace the human experience, empathy, and expertise honed daily, year after year. 

Further Reading:

  1. Topol EJ. The creative destruction of medicine : how the digital revolution will create better health care. New York: Basic Books, Cop; 2013.
  2. Topol EJ. The patient will see you now : the future of medicine is in your hands. New York: Basic Books; 2016.
  3. Topol EJ. Deep Medicine : How Artificial Intelligence Can Make Healthcare Human Again. New York: Basic Books; 2019.