To drive successful adoption and deployment of AI technologies, and ultimately desired outcomes, it is critical to have a partnership in which customers and vendors are working collaboratively. Healthcare organizations and vendors alike must share their responsibilities to divide and conquer the work. Through our research, KLAS has discovered several best practices for both providers and vendors, which we broke down in our recent Healthcare AI 2019 report. I’ve chosen a few to discuss below.
What Healthcare Organizations Can Do
For healthcare providers and their organizations, the success or failure of an AI tool can really come down to change management and operations.
- Embed AI in the workflow
These organizations frequently face information and tool overload. New tools are often perceived as extra hoops to jump through. If done right, AI tools should fit within their users’ regular routines and make their jobs easier.
One CIO recommends spending time observing clinician workflows to make sure AI tools fit: “Any CTO, CIO, or CDO should be sensitive to clinicians’ workloads. I watched what different types of clinicians do on a daily basis with each patient and found places in the workflow where we could insert predictive models in the reports. That way, the tool is part of a normal daily routine and is not going to disrupt that at all. The clinician doesn’t have to run another report or print anything out; it’s going to show up inside the EMR with this extra information they didn’t have before.”
- Take ownership
Leadership needs to play a big role to get staff engaged. The report didn’t focus much on having a clinician champion to drive changes in workflow, because while this bottom-up approach can be useful, the top-down approach seems to be more effective with AI. For a project to be successful, leadership must have buy-in from the start so they can socialize the idea across different departments.
Leadership then needs to report back on any progress and successes. This provides validation to staff members that they’re hitting the right marks.
What Vendors Can Do
For healthcare organizations to be successful with their AI solutions, they need vendors that do much more than deliver a high-quality, technologically capable product. The best practices below were reported by vendors’ most successful AI customers.
- Deliver comprehensive services. This is critical, especially considering that both the adoption cycle of AI in healthcare and the maturity model for clients are still in early stages. Customers cannot simply purchase tools or technology and be expected to achieve success without proper guidance and support from their vendor. That would be like handing future homeowners blueprints and materials and wishing them luck on building their new houses.
A director of data sciences outlined a vendor’s approach: “We have both a dedicated account manager and a dedicated client-facing data scientist, so it’s basically like we bought the AI tool. We got the software, but then we also got a free data scientist along with it. The vendor came in heavy with the training. They sent us to an all-day course to make sure we were familiar with the tool and all the settings in the tool. We’ve built a model, but it’s not exactly performing the way we want. We just call up the vendor, and they’re right there.”
Vendors that offer comprehensive services demonstrate to customers that client success is their ultimate goal. I cannot emphasize enough how important it is to implement these services during the early-adoption phase. For vendors who haven’t yet done so, it’s definitely something to consider.
- Be a humble, active partner. Being transparent going into the project, and being responsive to constructive feedback, will go a long way in terms of creating a strong partnership between vendors and their customers. The market is still young, and healthcare AI vendors are learning as they go.
One CIO described the partnership between a vendor and a healthcare organization as follows: “Our vendor is always ready to work with us. They are listening, they are acting, and they are timely. They are always willing to jump on the next plane to meet with us. It takes a lot to create something. More importantly, when I brought my clinicians to the table, it’s an exact science for them to make them believers. It is kudos to them and the physician that they brought on board, and my team that worked with them of course, but we still have variable results.”
To learn more about the other best practices we found, please read the full report. It has been an incredible journey to watch this market evolve and progress. We’re excited to see what AI technology will bring to the healthcare space in the near future.