Reimagine healthcare through human and AI collaboration

The evolving and growing importance of artificial intelligence (AI) as a fundamental technology changing healthcare forever has been a constantly tracked trend in course of the past three year's Digital Health Technology Vision reports. This year's trend explores how leaders are fostering human-AI collaboration at the frontline. Healthcare organisations have plugged AI and other tech tools into existing workflows, focusing on automation and execution. Consider how AI systems are powering chatbots that help health providers screen and triage patients, or how they are enabling the rapid reconfiguration of supply chains impacted by COVID-19.1 AI has helped to eliminate rote work for clinicians. But simply using AI to make an organisation run faster and cheaper is limiting its impact. Instead, AI can become an agent of change, transforming not just how organisations do work—but also what they actually do.

AI offers a unique advantage that has helped startups disrupt decades-old incumbents: the technology doesn't approach a problem based on years of experience or inherent human biases. It hasn't yet learned what not to try. This blank slate offers fertile ground for transformation in healthcare.

69%

of healthcare organisations are piloting or adopting AI

Designing for AI

In this new era where physical distance has become a requirement, not a preference, AI can help treat people at home. Smartphones equipped with sensors can continuously monitor a variety of health issues, including respiratory conditions. Algorithms identify and classify the severity of coughs or flag breathing irregularities so that care providers can intervene when issues arise, no matter where the person is when they arise.2 Human-AI collaboration is playing a role in the race to find a COVID-19 vaccine. Insilico Medicine, a Hong Kong-based biotech company, has repurposed its AI platform to help expedite the development of a COVID-19 drug, using machine learning to speed up the drug discovery process.3

Payers and providers can look at any care model or process and ask, "what am I trying to accomplish, and how can AI make it better or easier?" There is ample opportunity in the back office where there is heavy burden that machines could minimise. Cogito shows this potential in practice. This AI solution analyses voice signals in phone conversations to help call center agents infuse empathy in every conversation. Imagine how that real-time emotional intelligence could help hospital customer service agents, patient navigators and others to have better interactions.

Skills for a blended workforce

To tap into the unique strengths of AI, healthcare organisations will rely on people's ability to steward, direct and refine the technology. Accenture conducted research into the possibilities for humans to train AI for medical coding, seeing if the medical knowledge of humans would improve the system's performance at identifying links.

We established a process and training so that medical coders could train the AI, giving AI a front seat to knowledge generation—which allowed it to learn better, thus making it a better tool for coders. The coders learned to think like data scientists and the AI learned to think like coders. We learned that human-machine collaboration, along with embedding AI in the process and feedback loop, enabled explainable, more trustworthy results.4

This is just one example of work potentially being carried out and shared differently. When machines take on simple tasks, people can work at a higher cognitive level—but not around the clock. Healthcare enterprises must look at the new skills needed to enable fluid interactions between human and machines, and the workforce models needed to support these new forms of collaboration.

Only 39% of healthcare organisations report that they have inclusive design or human-centric design principles in place to support human-machine collaboration.

No touch triage

Partners HealthCare created the AI-based COVID-19 Screener to help assess whether patients should be evaluated for COVID-19. A simple chat interface asks a series of questions to help with pre-hospital triage. The system can screen high numbers of patients rapidly to alleviate burden on the organisation's hotline and reduce the number of patients visiting facilities in person for assessment.5

What can healthcare leaders do next?

Collaborate, don't just automate

Healthcare leaders should find more collaborative use cases and build the capabilities needed for AI.

Context matters

Prioritising explainability will help IT leaders in healthcare to ensure that people understand AI.

Reimagine what you do

Providers and payers that facilitate human-machine collaboration today will be able to reimagine every aspect of their organisation.

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Kaveh Safavi

Senior Managing Director – Consulting, Global Health


Brian Kalis

Managing Director – Strategy, Health

MORE ON THIS TOPIC

Digital Health Tech Vision 2019
Avoiding a capacity crisis using workforce data
AI: Injecting intelligence into healthcare

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