Large healthcare organizations are slated to invest an average of $32.4M per organization in AI over the next 5 years, found a recent survey, and of the 500 healthcare leaders surveyed, 91 percent are confident they will see an ROI on their AI investment in the next 3 to 4 years.

That’s according to a recent commentary by longtime tech stakeholder Cheong Ang in CIO.  But to be successful, Ang says, healthcare execs need to understand how AI may be added into the current IT mix, whether by being included in an existing application or integrated with applications in a workflow. 

One promising development Ang points to are EHR vendors who are striving to innovate by adding AI in their applications. Using voice assistants for documentation, and Natural Language Processing (NLP) to summarize free-text notes are two of the examples. 

He quotes Epic's Seth Hain, R&D Division Manager for Analytics and Machine Learning, who noted, “We want to help tailor the system to pick out the most interesting information available, as well as the tasks they’re most likely to want to perform and place them at the user’s fingertips. That will allow the clinician to spend more time with the patient.”

Another positive AI development Ang cites comes involves the Westchester Center Health Network (WMCHealth), which is adding AI to an existing workflow by using both its EHR’s risk model and a third-party vendor’s predictive model to prioritize discharged patients for readmission-reduction efforts. 

Yet another another example of applying AI in a healthcare workflow is Beth Israel Deaconess Medical Center’s use of TensorFlow on Amazon SageMaker to scan pre-surgical document packages to identify and insert consent forms into the corresponding electronic medical records. The tool delivers a notification to the EHR, if the consent form is missing, to trigger the follow-up workflow action.

In short, says Ang, “a balanced, three-pronged strategy will enable a healthcare organization to minimize risk of disruption where necessary, but not limit its ability to innovate to its current workflows or existing applications. Gearing up the organization with capabilities, and practice to allow ‘AI to encapsulate the workflows’ is ultimately an opportunity to gain a sustainable competitive advantage in an era that sees continued pressure from bountiful consumer choices, profit margin pinches, and assumptions of risk in the patients’ long-term wellbeing.”