New healthcare AI and Machine Learning research conducted by Healthcare IT Today suggests that many industry leaders are serious about adopting healthcare AI and machine learning tools and what’s more, that these technologies are being used as part of mission-critical efforts rather than one-off pilot tests.
At the same time, it highlights the degree to which these solutions are in ferment and being thrown at a huge array of potentially viable targets.
Roughly 53% of respondents said that they were currently using machine learning and AI technologies in their organizations. The list of uses to which they’re putting these technologies is quite extensive, ranging from tentative data management attempts to embedding such tools in their core enterprise applications.
“We’re using basic machine learning to sort through all of the data and turn the data into action,” one respondent said. “We’re sitting on this pile of data and we need to know what the data really means.”
More than one of the survey respondents said that AI and machine learning tech are helping to capture and leverage clinical data. “Our EHR system [allows] some level of AI, where comprehensive and complicated algorithms suggest or default clinical data like orders, problems or interventions,” another respondent reported. Another said that their organization uses machine learning to implement predictive analytics within its EHR platform.
Health leaders answering the survey questions saw many interesting applications of these technologies in the future. One cited the potential for supporting robotic process automation, another suggested that AI-supported smart rooms will emerge as a part of care delivery and several drew attention to its potential for improving radiology practice, including clinical diagnosis.
Meanwhile, areas in which respondents would like to see machine learning and AI data applied over the next five to 10 years were quite varied.
One broad niche many targeted is the enhancement of patient experiences with care. “I’d love to see machine learning and AI really personalize the patient experience much more than it is today,” one health leader wrote. “That includes how we communicate with patients, the treatments a patient receives, the way the patient is diagnosed and how we track a patient after the visit.”
However, there were dozens of other areas respondents would like to see addressed using machine learning and AI address over five to 10 years, including virtual office assistants, clinical decision support, development of new medical treatments, personalized medicine, billing/claims and eligibility checking, treatment pathways and identification of high-risk patients.
When asked how much overall impact machine learning and AI will ultimately have on healthcare, most than 80% said that it will have a significant or very significant impact on healthcare. Another 13% project that it will have a moderate effect. Only 2% expected it to have little or no effect.
Note: For reference, you can find the full list of healthcare AI and Machine Learning survey questions from this survey. The survey respondents came from Healthcare IT Today’s email newsletter and social media.