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The top three artificial intelligence challenges facing hospitals

Seventy-seven percent of respondents ranked budget or financial challenges among their top three challenges related to AI.
By Intel
09:24 AM
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Healthcare providers are interested in increasing the role of artificial intelligence in their organizations in the near term, according to a recent HIMSS Analytics survey, sponsored by Intel. Fifty-seven percent of providers plan to leverage AI in their financial departments within the next two years; and 52 percent plan to leverage AI initiatives in clinical departments within the next two years.[1]

However, the implementation of AI initiatives also comes with challenges, according to respondents. Respondents — who included business leaders, IT leaders, IT professionals and clinical staff — identified three primary challenges for organizations seeking to leverage AI initiatives. Those challenges, in order of significance, were: budgets/financial resources, lack of technical expertise, and lack of infrastructure.

Budgets identified as No. 1 challenge

Fifty-seven percent of respondents ranked ‘budget or financial challenges’ as their No. 1 challenge related to AI. Seventy-seven percent of respondents ranked budget or financial challenges among their top three challenges related to AI. The IT director of one 500-plus bed organization said, “The funding is an issue, because dollars are hard to come by, and sometimes it's hard to show a return on investment with something like this. Funding is sort of pivotal, because that's what drives the ability from a technology perspective and from a resource perspective.”

More than one provider mentioned the long-term nature of the ROI related to AI initiatives as a specific financial challenge. The CIO of one intermediate-size provider (251 to 500 beds) explained: "Our senior executives want to see results. Our board of directors want to see results. But when you're doing research and discovery on new technologies, it takes time before you start to see tangible results. ... When you buy a new MRI machine, you start seeing patients; it starts generating billings and revenues, the ROI is tangible. Investing in AI is not as immediately tangible. It's going to take multiple years until you start to see the results. So you have to keep reminding the people that are making the decisions and allocating the funds that that's the case." 

Lack of technical expertise also an issue

While only 11 percent of respondents ranked “lack of technical expertise/human capital” as their No. 1 challenge, 68 percent ranked lack of technical expertise/human capital among their top three challenges. The manager of IT at a 500-plus bed provider said: “Right now, we lack data scientists to actually get in there and be the brains and set a lot of this [AI] up. As a result of our limited resources, we are in a position where we're relying on vendors to provide some of that for us, but it’s definitely something we want to bring in-house, long-term.”

The survey showed providers are taking varying approaches to solve their shortage of in-house expertise related to AI. Forty-two percent of respondents intend to reallocate and train existing resources; 41 percent plan to outsource human capital needs related to AI. Only 21 percent plan to hire to fill new roles. Nearly one-quarter (24 percent) reported they were uncertain as to how they would approach challenges related to staffing expertise needed to support AI. 

Existing technology infrastructure inadequate

Only 5 percent of respondents ranked “lack of necessary infrastructure” as their No. 1 challenge. However, more than half of respondents (51 percent) ranked lack of necessary infrastructure as among their top three challenges related to AI. The manager of IT at a 500-plus bed organization said, “I think in the next two years we have a lot of work to do on the infrastructure side and getting our heads around how do we make this work, [because] AI is going to be a pretty important piece of the puzzle.”

In response to technology infrastructure challenges, 45 percent of respondents said they would ‘”do what we can with the systems we have in place.” One-third (34 percent) said they would outsource, using third-party solutions, such as SaaS or an off-premise data center. One of five (20 percent) said they would reinvest in scalable infrastructure.

In spite of the challenges, providers are moving ahead with plans to “future proof” their organizations with respect to AI initiatives. The medical director of one 500-plus bed provider said, “Within two years, [we will] have identified an overall strategy for AI, identified specific use cases, and have begun to implement the infrastructure to accomplish our overall strategy.” He added, “[AI] currently has a minimal impact [on our organization]. However, [AI] may hold the key to the future of informatics in healthcare.”

Access more information from this sponsor here: How AI/Cognitive Computing Fits into the Healthcare Picture.


[1] “Future Proofing Healthcare: Artificial Intelligence,” conducted by HIMSS Analytics on behalf of Intel, September 2017.

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