Healthcare organizations are ramping up their investments in artificial intelligence in response to the COVID-19 pandemic, according to recent surveys.
But they are not turning to tech giants like Google and Amazon to deploy these technologies.
In an Optum survey of 500 healthcare executives at hospitals, life sciences companies, health plans, and employer organizations, more than half (56%) say they are accelerating or expanding their AI deployment timelines in response to the pandemic. It demonstrates the importance of this business tool during the most stressful times.
Of those who reported being in the late stages of AI deployment, 51% believe they’ll achieve a return on their AI investments faster due to their pandemic response, according to the survey.
The majority of health care organizations (83%) have an AI strategy in place, and another 15% are planning on creating one, Optum found.
Healthcare executives expect to see a return on investment on AI investments in just 3.6 years, down from 4.7 in 2019. More than half (57%) of organizations in late-stage AI deployment believe they’ll see savings in as soon as two years.
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The findings echo those of a recent Deloitte survey of 120 healthcare executives conducted late last year. Nearly three in four health care organizations surveyed expect to increase their AI funding in 2020, with executives citing making processes more efficient as the top outcome they are trying to achieve with AI, Deloitte found.
Healthcare organizations reported their top AI risk concern is the cost of the technologies, cited by a third of respondents, according to the Deloitte report.
The Optum survey found that trust in AI is a significant barrier. When health care executives who had expressed doubt or concern about AI were asked why, 73% selected a lack of transparency in how the data is used or how the technology makes decisions, and 69% selected the role of humans in the decision-making process.
Healthcare sectors have different priorities for AI development, according to Optum's survey. For hospitals, AI is being used primarily to improve reimbursement coding, monitor the Internet of Things (IoT), and accelerate research.
Health plans are looking to use AI to automate administrative processes and detect fraud, waste, and abuse, while life sciences organizations are turning to AI to help identify patients for trials and enable personalized communications.
AI vendors
While healthcare investments in AI are increasing at a fast pace, few organizations have settled on any one AI vendor as their go-forward choice, a recent KLAS Research report found. So far, most organizations use a hodgepodge of solutions to meet their needs.
KLAS examined the recent AI purchase decisions of 47 organizations and found that the top factor driving purchase decisions in healthcare AI is expertise. Organizations are looking for companies with healthcare-specific knowledge as well as machine learning and data science expertise.
AI company Jvion has high visibility and one of the largest client bases based on KLAS data. Potential customers are drawn to Jvion’s technology, expertise, healthcare-specific vectors, and ability to prescriptively suggest interventions to improve patient outcomes, the KLAS report found.
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Other leading AI healthcare vendors that healthcare organizations are working with include DataRobot, KenSci, Health Catalyst, ClosedLoop.ai, and Medial EarlySign. Epic's Cognitive Computing is the most widely adopted electronic health record AI solution and some customers are using HealtheDataLab, Cerner’s machine learning platform.
The demand for healthcare-specific AI expertise is holding some organizations back from partnering with the large tech giants, including Amazon, Google, IBM and Microsoft, the KLAS report found.
"In general, organizations are intrigued by the vendors’ AI technology and expertise but worry about their relative inexperience in healthcare, the fact that their solutions reside in the cloud (an area that healthcare organizations are just getting into), and the burden of integrating the tools into workflows," KLAS wrote.
Of the 47 organizations, two chose to go with Amazon's AI technology and two organizations decided to partner with Microsoft. Of the four, IBM receives the most considerations (eight) but is the only one not actually selected in any of the 47 purchase decisions included in the KLAS research.
Organizations passed on IBM due to skepticism about outcomes as well as concerns about cost and over-marketing, KLAS reported.
Amazon has a solid reputation of being innovative and adaptive but is viewed as lacking a nuanced understanding of healthcare. Additionally, respondents are unclear what Amazon’s healthcare and AI development strategies are, and there is skepticism about Amazon’s ability to integrate operationally.
Google is less well known in healthcare, and respondents feel they would have trouble trusting Google with their data, KLAS found.
Half of respondents who shared perceptions of Microsoft feel the vendor has a strong healthcare AI offering and has more healthcare expertise than the other cross-industry vendors. But some executives report that Microsoft has a tendency to overpromise and underdeliver, KLAS found.