68% of health system execs plan deeper AI investments to meet strategic goals
During the inaugural HIMSS State of Healthcare digital event on Tuesday, Thomas Kiesau, director digital health leader at the Chartis Group, offered some useful benchmarking for hospitals health systems wondering how their IT investments digital maturity compare to their peers.
The Chartis Group surveyed 226 health system executives nationwide at hospitals health systems of all shapes sizes. They were asked their perspectives on digital health, artificial intelligence machine learning – about the financial health of their respective organizations.
The health system execs had generally positive sentiments about digital health. Most agreed with the sentiments, said Kiesau: “It should be integrated into the care model. It will advance care over the long term. It can create a competitive advantage. It can help close care disparities. Across the board what we saw from our respondents was that they believe those relatively strongly.”
As for some of the commonly-held negative perceptions associated with digital health – that it’s “separate from care delivery; it doesn’t have clear ROI; that it’s not suitable for certain populations” – most respondents didn’t agree, he said.
“This is a positive affirmation about the future of digital health [I] believe that it shows there’s an opportunity that our health system executives see, that they don’t buy into the hype the negative perceptions associated with it.”
Asked about the greatest barriers to digital health adoption, meanwhile, 59% cited regulatory reimbursement issues 42% mentioned clinician buy-in. Only 18% listed technology issues.
Chartis also asked health system executives to describe their digital health efforts to date, elicited “a wide range of responses,” said Kiesau.
“We asked, are these system-wide coordinated? Are they targeted, high-impact? Are there a bunch of pilots but not really clear rollout plans? All the way down to ‘we really haven’t started.’
“What’s notable is that almost everyone has started, whether because of COVID-19 or something they’d already initiated. But 52% of the programs have not progressed beyond the pilot stages.”
As for the priorities strategic imperatives these digital health efforts are aimed at, “patient access is the number one priority for over a third of the health systems,” said Kiesau, “with 70% of the respondents putting it as a top three priority.” Another major goal, of course, is cost reduction, with about 60 percent of execs putting it in their top three.
“You can only improve what you measure,” said Kiesau. “So we also asked our survey respondents to respond to the initiatives they’re currently operating are they being tracked monitored?
“Interestingly, 60% say they are tracking them at a system-wide, real-time progress level, another 30% are saying they’re tracking them with quarterly updates, but regularly consistently tracking progress. Forty percent are in various stages of centrally tracked, but not effectively managed or monitored – or not monitored at all. What this says is, if you are not managing monitoring your digital progress, you’re behind.”
To the question “Do you have a digital health officer today?” Only about a third of respondents said yes. However, “more than a third said they don’t have one today, but they plan to hire one in the next one to two or five-plus years,” said Kiesau. “They recognize the need.”
AI investments on the rise
To the question of AI machine learning, the Chartis Group report suggests that it’s still in the early going at most health systems, with 70% of the respondents yet to establish any sort of strategic artificial intelligence programs.
But when asked whether their investments in AI will change in the future to help achieve strategic goals, “we saw a pretty strong endorsement that it’s going to need to increase,” said Kiesau.
Thirty-eight percent of execs predict a marginal increase in AI investment in the years ahead, “a full 30% say it needs to increase significantly,” he said. “Collectively, nearly 70% of the respondents identified artificial intelligence machine learning as an area that would need to receive greater investment to be able to achieve their future enterprise goals.”
Chartis asked execs about an array of AI ML use cases: insurance, cybersecurity, fraud prevention, dosage error detection, supply chain, voice-assisted charting, registration, remote patient monitoring, referrals, imaging labs, consumer-facing chatbots, surgical robots, clinical trials, care planning, triage, diagnosis more.
There was widespread agreement that artificial intelligence applications can help with all of them.
“Every single category, people saw it as a viable candidate,” said Kiesau. “But there was a notable difference between those that received the highest scores – operational use cases such as insurance cybersecurity – while the clinical interventions, things like care planning, care triage diagnosis, came in much lower. There’s a general belief in AI machine learning its value, but also a general recognition that it’s not fully understood.
“There’s positive perceptions around AI – that it could increase new job capabilities,” he said. “This could focus workload. This could make our people do better, reduce health care disparities reduce cost. But at the same time, there are negative perceptions that it could also cause job losses. It could create some level of risk when we’ve got artificial intelligence guiding more decisions.”
But even with some uncertainty about just what AI ML can accomplish practically – even with most initiatives still in a relatively nascent state – majorities of executives “realize it’s an area they need to invest in,” said Kiesau, “even if it’s just to address the operational use cases or to address the cost pressures they see coming.”