Artificial intelligence, to name just one key use case, can help transform healthcare provider organizations’ value-based care journeys by enhancing quality performance and risk adjustment accuracy – ultimately driving better health and financial outcomes.
If huge potential doesn’t convince health system C-level execs to open the purse strings for AI tools, some other convincing might be needed. Because, when it comes to buying into AI investments, many healthcare C-suites today still remain a bit cautious, and skeptical of the hype.
AI has proven itself in some use cases on the operational and administrative side of things, but there’s still lots of ground to cover – and crucial questions to answer – on the clinical side, where lives are at stake. And many organizational leaders are still skeptical. And securing their buy-in remains a challenge.
Dr. Michael S. Barr is president and founder of Medis, a veteran-owned healthcare consulting firm. He has a lot of experience talking with C-suites about AI. And he uses a four-step communication framework from the military for overcoming the challenge, a framework called SBAR – Situation, Background, Assessment and Recommendation.
Barr is a board-certified internist. He was previously executive vice president at the National Committee for Quality Assurance and senior vice president of medical practice at the American College of Physicians. He currently serves on the medical advisory board at Navina, an AI platform for clinicians and care teams.
We spoke with Barr to discuss C-suite buy-in to AI and leveraging his SBAR framework to help healthcare leaders instill confidence that an AI investment will deliver a strong ROI.
Q. What are common obstacles healthcare C-suite executives hit when it comes to approving AI investments?
A. There are a variety of common concerns among healthcare C-suite executives that can make them hesitant to implement an AI system, such as questions about how widely clinicians will use the system; its ease of use; data quality, privacy and security; and how effectively it will meet the needs of clinicians, patients and the healthcare organization.
But if we look at the big picture, the overarching obstacle tends to be concern about the financial return on investment the system will provide, which will be affected by all those factors. That’s not to suggest they aren’t prioritizing high-quality patient outcomes: C-level executives generally agree that to achieve those outcomes in a scalable and sustainable way, a system must also deliver a strong ROI.
For AI advocates, preparing and adequately addressing ROI in your presentations is imperative. It can make a tremendous difference when trying to get the C-suite on board with an AI system. Showing a robust and data-driven ROI estimate will help alleviate their specific concerns.
This means presenting not just an optimistic scenario but also conservative estimates showing that even in less ideal scenarios, the system will still offer them a sufficiently high ROI.
The focus on ROI is an essential part of each one of the four steps in the process that I recommend. Keeping that in mind can help you perform each step successfully.
Q. You have a four-step process for overcoming these obstacles. Before you talk about the process, please describe how you came about the idea for the process and the ideas for the solutions.
A. The SBAR model is an approach to communication that originated in the military but is often used in healthcare settings. It can be very useful for conveying critical information efficiently, especially in challenging circumstances. It is also highly adaptable to a wide variety of situations.
In my work with healthcare organizations looking to adopt an AI system, I often see what a challenge it can be to get C-level executives on board. And given my own healthcare and military background, it seemed natural to me to adapt the SBAR model to help physicians and other healthcare professionals – many of whom are familiar with the model – make the case for AI systems to the C-suite.
But there’s more to the approach that I suggest than just following the SBAR model. In adapting the model to get buy-in from healthcare executives, I added some more specific suggestions that can be particularly helpful.
Perhaps most important, I recommend making sure the way you address each of SBAR’s four steps speaks to the C-suite’s concerns, especially ROI – and that it does so in a data-focused way, without hype or exaggeration.
Q. So, what is the four-step process? Please explain it for C-suite and other IT leaders.
A. The short answer is that the four steps are Situation, Background, Assessment and Recommendation. However, to make the model effective for the purpose of getting buy-in from healthcare executives, it’s important to consider each step in more depth.
The first of those stages, situation, is where you introduce the problem you want an AI system to address. Here, it’s important to identify issues that will resonate with the C-suite.
For healthcare organizations engaged in value-based care, that will mean describing the inefficiency of current approaches to risk adjustment (especially HCC coding) and quality performance (including steps intended to achieve high Medicare Star Ratings).
And to drive those points home for your C-level audience, you’ll want to present data showing what a financial burden those factors are for your organization.
The second stage, background, builds on that foundation by providing additional details, including both hard data and an explanation of qualitative problems with the status quo. That involves describing things like limitations of the technology your organization currently uses, ways your organization has tried to make improvements with limited success, and the costs of your current approaches to HCC coding and quality performance.
This also is a great opportunity to preemptively address common concerns about AI, such as questions about its accuracy, reliability, transparency and compatibility with your existing platforms, as well as the extent to which clinicians will actually use it once it’s purchased and deployed.
The last two stages are where you shift from focusing mostly on the past and the status quo to discussing how AI can improve that situation. In the third stage, assessment, you’ll want to describe how a given AI system would work and what it would accomplish – laying out its capabilities, use cases and benefits, as well as specific and quantifiable predictions of the benefits it will offer your organization.
And in the fourth stage, recommendation, you’ll want to suggest exactly what course of action you want your organization to undertake, such as a pilot of an AI system.
Throughout these last two stages, the key is balancing specificity with clarity and simplicity in a way that instills confidence. There’s a good chance that your audience will include executives without a clinical background, so it’s best to avoid jargon and terminology less familiar to them.
And when you define the objectives of your recommended course of action, it’s important to make sure they’re SMART goals: Specific, Measurable, Attainable, Relevant and Time-based.
Q. How exactly will this process instill confidence in healthcare leaders that AI investments will deliver a strong ROI?
A. What makes this approach to communication such an effective way to address healthcare executives is that it combines a logical, efficient and flexible communication model with a factual, data-driven and ROI-focused communication style.
The SBAR structure helps methodically make the case for an AI system to the organization’s C-suite, providing a framework to build an argument leading from a problem or a series of problems to a recommended solution. Meanwhile, the communication style I suggest helps convey that information in a matter-of-fact way designed to build confidence.
It’s also important to keep in mind this is a malleable framework, not a one-size-fits-all template. One major benefit it offers is that you can and should adapt it to meet your needs, to reflect your healthcare organization’s realities, and to address your C-suite’s priorities.
For example, risk adjustment – especially HCC coding – and quality performance are both areas in which many healthcare organizations have serious and expensive difficulties stemming from the shift toward value-based care. But is your organization’s executive leadership equally concerned with both issues, or is one a more pressing issue than the other for them?
If possible, I recommend fine-tuning your presentation to reflect factors like that.
No less important, a major reason this SBAR-based approach is such an effective way to make the case for AI to a healthcare C-suite is the simple fact that the case already is so well-founded. Before investing in an AI system, C-level executives want to be confident it will provide an ROI that justifies its purchase.
There is AI-driven tech out there today that is hugely effective, that offers healthcare organizations a remarkable ROI, and that can help them adapt to the realities of value-based care.
In that sense, the facts really speak for themselves; your job is just to get your audience’s attention, keep that attention, present those facts clearly, and show how they justify a recommended course of action. And in my experience, this model can make a real difference in helping you do that successfully.
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