Ripe for disruption: Artificial intelligence is advancing deeper into healthcare

Ripe for disruption: Artificial intelligence is advancing deeper into healthcare

Skyrocketing costs, closed facilities, capacity issues, staff burnout, staff shortages, lots of chaos – it sounds like a struggling industry – and that industry is healthcare. Can artificial intelligence help solve some of the problems faced by hospitals and healthcare providers? There has been progress on this front – not fast enough, but progress nonetheless.

While interest in AI in healthcare is high, “the level of acculturation of C-level executives is lagging, especially for organizations that would need it the most – pharma, medtech and hospitals,” reports a recent Capgemini report. The problem, the study authors say, is the data. “Improving the course of care and improving the supply of care remain top priorities for organizations”, according to the team of co-authors of the report, led by Charlotte Pierron-Perlès. However, only about a third of healthcare organizations surveyed by Capgemini prioritize the availability of patient information. “We don’t see any major progress from 2021 [the year of the previous study].”

The good news is that many healthcare providers are stepping up their work on AI. “The healthcare industry is now beginning 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 increase 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 of accessing healthcare – that is, better access to care. and meaningful, actionable health data,” continues Ambrozie. “Intelligent situational routing based on the consumer record and consumable analysis of medical record data – which help consumers and patients better manage their health – are the obvious next steps in the journey simply because there is a vast experience from other industries.”

Of course, healthcare is a huge conglomeration of moving parts, which complicates matters. It’s ripe for disruption, especially where AI and automation can fill the gaps in rote and repeatable tasks. “Healthcare is an extremely complex industry and perhaps the most regulated activity in the country,” says Mudit Garg, CEO of Qventus. “The sheer volume of menial and repetitive tasks that are part of patient care does not allow caregivers to perform at the top of their licenses and focus on the most crucial work for patients. AI can simplify many of the these processes.

How does AI continue to evolve to meet patient needs? “Truly understanding a patient’s long-term health needs, not just their transactional care needs, requires analyzing an unimaginable volume of data – genome, demographics, medical history, environmental factors, symptoms and much more. says Ambrozie. “In reality, it is impossible for suppliers to perform this analysis manually. AI and ML are evolving to uniquely produce solutions capable of automatically performing this vast data processing and analysis with the ultimate goal of helping physicians identify safe and personalized treatment pathways for a patient.

The challenges and changes needed to advance AI go well beyond technological considerations. “With the entry of data and AI in health, we are dealing with a profound cultural change, which will not happen overnight”, according to Pierron-Perlès among his co-authors. “Many organizations are developing their own acculturation initiatives to build the data and AI literacy of their resources into engaging formats. AI goes well beyond technical considerations.

There has been a lot of concern that too much AI is dehumanizing healthcare. But, when carefully studied and planned, it may turn out to increase human care. “People, including providers, imagine that AI will be cold and calculating with no regard for patients,” says Garg. “In fact, AI-powered healthcare operations automation frees clinicians and others from menial manual tasks that keep them from focusing their full attention on patient care. While other AI-based products can predict events, the most impactful ones are integrated into workflows to solve problems and drive action from frontline users.

The new dynamics that are emerging in the healthcare system thanks to AI are:

  • Patient-centered: “Not only do stakeholders now have a better understanding of what patients really want, but they also feel better equipped to meet their needs,” said Pierron-Perlès of Capgemini and his co-authors.
  • Smarter capacity utilization. “Provider and hospital capacity is limited and will be increasingly strained with an aging population seeking care,” Ambrozie says. “It is therefore imperative that the use of capacity – whether it is the supplier or facilities such as operating theaters – is optimized to the maximum. Using AI and ML to better forecast demand and optimize resource utilization is something that is gaining momentum across the board. And more care, sooner is better care that saves lives.
  • Opportunities to increase income. “AI-powered care automation helps healthcare systems increase surgical revenue by maximizing operating room utilization through improved scheduling,” suggests Garg. “By automating elements of the discharge process, it also allows hospitals to shorten the average patient stay. At the same time, hospitals are grappling with staff shortages exacerbated by the Covid-19 pandemic. They no longer have the organs to deal with procedural tasks and they must free up their contractors to do the most important work. AI-powered care automation makes this possible.
  • More successful search: “Startups, big pharmas and research organizations are reshaping the R&D landscape,” observes the Capgemini team. “We are seeing more approaches to selecting the most promising drug candidates, sometimes leveraging the quantum. The race for more efficient drug development is generating excitement around revamped processes, new data sources, and value-added use cases that address patient and practitioner pain points.

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