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The business case for AI in healthcare

February 05, 2024
Artificial Intelligence

AI is a foundational technology, so its use cases span everything from administration to patient care to supply chain management to population health, and more. Where you have a lot of data (almost everywhere in healthcare) there will be opportunities for intelligent automation using AI. Some of the initial use cases that have seen some adoption include assistance in reading radiology scans, administrative workflows such as prior authorization and coding, operational use cases in hospitals, intensive care clinical use cases, patient engagement, and more. Each one of these use cases can have significant economic benefits for health systems. For example, the radiology use cases are very strong as the technology will serve as an immediate screener for critical findings on radiology scans and can alert the medical team to immediately check the images to confirm the presence of abnormalities and intervene in a timely manner. This can potentially improve patient outcomes, improve the workflow of the clinicians, and be used to attract more patients with conditions like stroke, trauma, and the critically ill.

I personally believe that the initial use cases that can have significant business benefits are the administrative and operational use cases. Although some may not get as excited about these use cases, I think they are an excellent way to get started. They are lower risk and if the data is not as ready or if technology is not fully mature, they can still provide benefits and not risk any clinical harm to the patients. Also, given the serious shortage of resources and the burned-out staff, helping them with documentation, coding, prior authorization workflows, generating patient communication material and referral letters, etc would be of great value. Revenue cycle management is a critical function for health systems and improving it using AI is within reach. Given the improvement in natural language processing using the large language models that underpin generative AI, these administrative and operational use cases can start to provide benefits in a reasonable amount of time. For executives who want to get started with AI and are trying to decide how and with what use case, they represent an excellent and safe place to start.

It is important to establish clear criteria for evaluating the potential use cases and the specific companies under consideration. In AI Doctor, I lay out guidelines for executives as they evaluate AI solutions. These guidelines assess the potential economic impact of the use case, availability of the needed data, workflow implications, potential for insurance reimbursement, total cost of ownership, governance requirements, complexity of implementation, the product’s track record with similar customers, level of evidence for the product to date, and more. Although this type of assessment may require cross-functional teams from the organization, as well as potential help from consultants and contractors, it will pay huge dividends when the right use cases are prioritized, and the organization gains clear benefits from its investments.

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