Once the foundation is in place, senior living and post-acute care organizations can move on to optimizing care, which involves determining how to use data analytics and connected care. This is where the organization should begin to consider how it would like to use AI and machine learning, virtual care, sensors, wearables and smart home technologies. The organization should begin to find integration opportunities that optimize workflows and make them more efficient.
This process involves assessing how the organization is managing its IT and whether it has the right workflows and processes in place. Automating on top of ineffective processes won’t solve any problems. It’s important to identify where workflows and processes are breaking down, make the necessary changes, and then maximize systems and applications already in place before implementing automation solutions. Optimizing existing systems also helps with cost reduction, as the organization may be paying for an application that it isn’t using to the fullest potential.
However, it’s important for organizations to remember that optimization isn’t something that happens in six months or a year. It must be a well-thought-out strategy and could easily span three to five years. There are several steps that must occur organizationally and financially; modernization and innovation are not cheap, but they are worth it.
Best Practices for AI Implementation in Senior Care
Once an organization’s IT environment is modernized and optimized, it can turn its attention to AI solutions. It’s important to start by considering where AI would be most effective.
A common way healthcare organizations approach AI implementation is to start with back-office operations before moving to a care setting. Don’t try to boil the ocean; rather, start with smaller use cases and work up to the big picture.
If AI is being used in a care setting to analyze data to support clinical decision-making, then it’s crucial that the data is accurate. That also means ensuring that strong data governance is in place so the data being pulled into the AI algorithm is of high quality. There’s an old saying that junk in is junk out, so quality and accuracy are paramount.
Using AI in a clinical setting is most effective when there’s a specific use case in mind. Does the organization want to use it for a certain diagnosis?
EXPLORE: How can AI and automation transform processes for senior care providers?
How Can Senior Care Organizations Benefit from Tech Partnership?
Our priority at CDW is continuing to assist senior living and post-acute care organizations in making the best technology choices and plans the future. It shouldn’t be a one-size-fits-all approach.
For many organizations, AI, remote monitoring and other technologies are still new, and many organizations still operate a lot like they did 15 or 20 years ago. From our standpoint at CDW, we focus on helping organizations transition in a way that works for their unique situation. We start with core IT and foundational needs, especially as this relates to infrastructure, security and data. Once those areas are modernized, with good procedures and governance in place, we can move on to enhancing operational and clinical workflows.
This article is part of HealthTech’s MonITor blog series. Keep this page bookmarked for our coverage of the 2024 LeadingAge Annual Meeting, taking place Oct. 27-30 in Nashville, Tenn. Follow us on the social platform X at @HealthTechMag and join the conversation at #LeadingAge24.
