Can AI really outperform a clinician?

Can AI really outperform a clinician?

By definition, artificial intelligence (AI) describes technologies that perceive, synthesise and infer information in a way usually associated with intelligent beings such as humans. Two decades ago, these innovations rarely had the capacity to rival the capabilities of their mortal creators. But, as AI technologies rapidly advance, there’s a growing belief they pose a threat to traditional human roles and responsibilities. 

We’re increasingly seeing AI and data-led innovations stir great change within most modern industries, with professions surrounding customer service, visual art, coding and content writing already experiencing a considerable level of AI-takeover. While their adoption has lagged significantly compared to other sectors, the healthcare space is no exception.  

Now, with transformational AI health innovations such as Microsoft’s BioGPT recently achieving human parity and IBM’s Watson now able to diagnose heart disease at a greater accuracy than a trained cardiologist, people are progressively beginning to wonder: can AI really outperform a clinician? 

The truth is, there isn’t a straightforward answer. There are times where it’s a resounding ‘yes’ and others where ‘no’ is as clear as day. What is for certain is that an AI-led healthcare revolution is upon us, and the world needs both the technology AND the clinicians to work arm-in-arm. 

Read on to dive deeper with IntelliHQ.

AI is increasingly rubbing shoulders with healthcare professionals

The healthcare industry is an essential and endlessly expanding sector of the modern world. As the space rockets into what has been dubbed ‘Health 4.0’ – where care intertwined with AI, machine-learning (ML) and robotic technologies is normalised – a greater understanding around what is possible and what is needed to make it happen has been realised.

This has empowered a new generation of boundary-pushing health-techs already outshining their clinician equivalent in a number of distinct areas. An expanding emphasis on health data has fueled their advancement, with their capabilities only threatening to improve.

AI technology excels in:

  • Big data analysis 

As the volume of collected and shared health data increases, it also becomes increasingly difficult for clinicians, researchers and health innovators to decode health information and make use of it all. Bringing AI onboard to process these large amounts of medical, patient and research data can therefore streamline the data analysis process, make error-free predictions and expose patterns that may have been impossible for a human to detect.

These results can empower more personalised treatment plans, preemptively identify health problems, improve clinical trial design and help map future snapshots of an individual or population’s health.   

  • Diagnostics 

Drawing information from patient medical records, test results and imaging data, AI has been proven to accurately identify and predict diseases and medical outcomes – sometimes more effectively than specialised clinicians. They reduce the potential of human-error by distraction or tiredness and circumvent the limitations of the human eye.

This has been shown with Google AI technology increasingly beating doctors at mammogram scan accuracy and machine-learning solutions matching the capabilities of physicians in cardiovascular risk diagnosis.

  • Repetitive tasks

Both in clinical settings and for back-end admin, AI can automate repetitive or time-consuming tasks to allow clinicians to better allocate time and resources elsewhere. 

On the hospital floor, there are available technologies that can reduce paperwork by accurately transcribing audio during consultations, managing patient medication with timely reminders and deeply analysing medical images such as X-rays and MRIs to accelerate diagnoses. 

In the office, AI can revolutionise appointment scheduling, decrease the need for human-to-human interaction, troubleshoot with patients and ensure billing paperwork is a thing of the past. A fruitful collaboration between Datarwe and KJR even helps map ICU bed availability by predicting patient trajectories from the data of similar patients. 

While AI may outperform a clinician in the above areas, there is an increasing understanding that this is less of a disservice to clinicians and more of a positive opportunity for clinicians to uplift their care or focus their time, intelligence and expertise elsewhere.

AI in healthcare isn’t always the answer

AI technologies lack empathy, intuition, social skills and, usually, opposable thumbs. This means that, even as the capabilities of AI and data-led innovations continue to expand, healthcare clinicians will always play a critical role in patient care in a way machines cannot replicate.  

Most AI healthcare solutions are also dictated by the data they’re fed. This has the potential to undermine their efficacy if its implemented data fails to represent the true heterogeneity of a population. The resultant bias can be outweighed by diversity within the clinician cohort.

Clinicians will always outperform AI in:

  • Patient interaction 

Compassion, understanding and empathy are intrinsic human qualities especially characteristic of a clinician. When it comes to providing considered and comfortable patient care, these values are essential and build from years of refinement in training and on-site. 

  • Emotional support

Healthcare professionals are trained to provide emotional support and naturally outstretch guidance, advice, empathy and strength during difficult times. With ill-health an inherent part of clinical environments, emotional support and connection is essential to improving quality of life for patients and their families. 

  • Physical examinations

Hands-on physical examinations and surgeries require the human ability to observe, assess and listen to a patient’s body in real-time. They’re also reliant on the capacity of the examiner to troubleshoot or realign care at a moments notice. AI is not yet capable of replicating these essential components of healthcare.

Reflecting on the clinical reliance of resonant human qualities and skills, AI technologies are clearly not replacing medical professionals in clinical settings anytime soon. However, they can undoubtedly help them provide ever higher quality care.

Together, man and machine can revolutionise the healthcare space 

Zooming out to analyse the modern healthcare space, there’s been a problematic reality that’s become more and more realised in recent years: healthcare is struggling to serve the true needs of clinicians and patients. Wealthy countries with ageing populations are seeing the demand for care reach unprecedented levels, while developing regions are failing to secure enough skilled clinicians to serve their growing populations.

This shortfall comes at a massive financial and health expense. In fact, almost 10% of all deaths within the USA are accounted for by misdiagnosis and human-error. There is a clear gap that AI technologies can fill, and the USD$15.4 billion invested in the healthcare AI industry in 2022 shows that the health sector is keen to get a move on.

Dr. Eric Topol, author of the award-winning book: Deep Medicine: How Artificial Intelligence Can Make Healthcare Human Again noted recently in an interview with TIME magazine that not only can AI tighten a worldwide care gap, it can genuinely augment the roles of healthcare works in an enduringly positive way.   

“Using technology to enhance humanity is the ultimate objective here,” says Dr. Topol. “For doctors… all of the data about a person [can be] assimilated and analysed, scans and slides read. That liberates doctors from keyboards so they can look patients in the eye.”

He expands on the powerful convergence of human and artificial intelligence in a paper named High-performance medicine by noting its impact on three levels of the medical space:

  • Clinicians: “rapid, accurate image interpretation”
  • Health systems: “improved workflow and the potential for reduced medical errors”
  • Patients: “enables processing of own data to promote health”

For this machine-accelerated health revolution to be truly realised, however, an industry-wide skill gap needs to be bridged. 

Specialised training leading an industry shift

Hands-on training is crucial for those within clinical settings to confidently amalgamate their capabilities with those of AI technology. It requires a deep exploration of their benefits and risks, as well as their ethical considerations. This is to take place at governance level through to the clinician level.

IntelliHQ’s AI in Healthcare Training Program opens the AI conversation with healthcare practitioners, analysts, researchers and leaders. Through specialised training in analytics andAI  application on and for EMR, the future-focused initiative works to build confidence at the frontline of an AI-complimented healthcare reality.

Dr. Stephanie Chaousis, the General Manager of IntelliHQ, says ground-level training such as the IntelliHQ’s is key to transforming the healthcare sector into one that can enduringly serve the world’s healthcare challenges.

“The courses were developed to balance everything from the basics and challenges of data science, ethical considerations and AI myth-busting, to the behind-the-scenes of data processing in AI technology,” says Dr. Chaousis. “Participants don’t just sit and learn, they put their learning into action. 

“We’re building trust and actionable knowledge through cross-disciplinary understanding for an incredible future of healthcare”.

Together, let’s lead a safer, brighter and more prosperous healthcare industry today – for tomorrow.


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Together, let’s lead the future of healthcare. Reach out to the IntelliHQ team today.

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