BETA
This is a BETA experience. You may opt-out by clicking here
Edit Story

Ripe For Disruption: Artificial Intelligence Advances Deeper Into Healthcare

Following

Spiraling costs, closed facilities, capacity issues, staff burnout, staff shortages, lots of chaos — sounds like an ailing industry — and that industry is healthcare. Can artificial intelligence help mend some of the problems faced by hospitals and healthcare providers? There has been progress on that front — not fast enough, but progress nonetheless.

While interest in healthcare AI is high, “the level of acculturation of C-level executives is lagging, especially for organizations that would need it the most — pharmas, medtechs and hospitals,” a recent Capgemini report relates. The problem, the study’s authors relate, is data. “Enhancing the patient care pathway and improving care delivery remain on the top of the organizations’ agendas,” according to the report’s team of coauthors, led by Charlotte Pierron-Perlès. However, only about a third of healthcare organizations surveyed by Capgemini prioritize the availability of patient information. “We do not see major progress from 2021 [the year of the previous study].”

The good news is that many healthcare providers are stepping up their AI work. “The healthcare industry is now starting to implement AI and machine learning solutions at increased scale and sophistication,” says Tony Ambrozie, CIO at Baptist Health South Florida. “AI and machine learning will augment their ability to make sense of the vast amounts of data available.”

Where opportunities abound “is in using AI and ML to improve the patient experience around access to healthcare – that is, improved access to care and meaningful and actionable health data,” Ambrozie continues. ‘Intelligent situational routing based on the consumer record and consumable analysis of medical records data - that help consumers and patients manage their health better - are the obvious next steps in the journey simply because there is ample experience from other industries.”

Of course, healthcare is a huge agglomeration of moving parts, making things complicated. It is ripe for disruption, especially where AI and automation can fill in gaps for rote and repeatable tasks. "Healthcare is an enormously complex sector and possibly the most-regulated business in the country,” says Mudit Garg, CEO of Qventus. “The sheer volume of menial, repetitive tasks that are part of caring for patients doesn’t allow caregivers to perform at the top of their licenses and focus on the work that is most crucial for patients. AI can simplify many of those processes."

How is AI continuing the evolve to meet patient needs? “Truly understanding a patient’s long-term health needs - not just their transactional care needs — requires analyzing an unimaginably large volume of data – genome, demographic data, medical history, environmental factors, symptoms, and much more,” says Ambrozie. “Realistically, it’s impossible for providers to perform this analysis manually. AI and ML is evolving to uniquely produce solutions that can automatically perform this vast data processing and analysis with the ultimate goal of aiding physicians in identifying safe, personalized treatment pathways for a patient.”

The challenges and changes needed to advance AI go well beyond technology considerations. “With data and AI entering in healthcare, we are dealing with an in-depth cultural change, that will not happen overnight,” according to Pierron-Perlès at her co-authors. “Many organizations are developing their own acculturation initiatives to develop the data and AI literacy of their resources in formats that are appealing. AI goes far beyond technical considerations.”

There has been great concern about too much AI de-humanizing healthcare. But, once carefully considered and planned, may prove to augment human care. “People, including providers, imagine AI will be cold and calculating without consideration for patients,” says Garg. “Actually, AI-powered automation for healthcare operations frees clinicians and others from the menial, manual tasks that prevent them from focusing all their attention on patient care. While other AI-based products can predict events, the most impactful are incorporated into workflows in order to resolve issues and drive action by frontline users.”

New dynamics emerging in the healthcare system thanks to AI include the following:

  • Greater patient centricity: “Not only that stakeholders now have a better understanding of what patients really want, but they also feel better equipped to address their needs,” Capgemini’s Pierron-Perlès and her co-authors state.
  • More intelligent leveraging of capacity. “Provider and hospital capacity is limited and will come under increasing strain with an aging population looking for care,” says Ambrozie. “It is therefore imperative that the capacity — whether provider or facilities such as OR rooms — utilization is optimized to the maximum. Using AI and ML to forecast demand better and optimize resource utilization is something that is gaining traction across the board. And more care and sooner is better care that saves lives.”
  • Opportunities to increase revenues. “AI-powered care automation helps healthcare systems increase surgical revenue by maximizing the usage of operating rooms through improved scheduling,” Garg suggests. “By automating elements of the discharge process, it also allows hospitals to shorten the average patient stay. At the same time, hospitals are struggling with a staffing shortage exacerbated by the Covid-19 pandemic. They no longer have the bodies to throw at procedural tasks and they need to free their providers to do the most important work. AI-powered care automation makes this possible.”
  • More fruitful research: “Startups, big pharmas and research organizations are reshaping the panorama of R&D,” the Capgemini team observes. “We see more approaches to downselect the most promising drug candidates, sometimes leveraging quantum. The race for a more efficient drug development generates excitement around revisited processes, new data sources and value adding use cases addressing patient and practitioners’ pain points.”

Follow me on Twitter