Artificial intelligence (AI) has the potential to revolutionize healthcare provider organizations’ value-based care journeys by improving quality performance and accuracy in risk adjustment. This can ultimately lead to better health outcomes and financial results.
Despite the significant benefits AI can offer, many healthcare C-suite executives remain cautious and skeptical about investing in AI tools. While AI has shown promise in operational and administrative areas, there are still challenges to overcome on the clinical side, where patient lives are at stake. Securing buy-in from organizational leaders continues to be a hurdle.
Dr. Michael S. Barr, president and founder of Medis, a healthcare consulting firm, has developed a four-step communication framework called SBAR – Situation, Background, Assessment, and Recommendation – based on his experience in engaging C-suites on AI initiatives. This framework aims to address concerns and instill confidence in AI investments by focusing on delivering a strong return on investment (ROI).
Common obstacles that healthcare executives face when considering AI investments include questions about clinician adoption, ease of use, data quality, privacy, security, and alignment with organizational needs. The primary concern often revolves around the financial ROI that an AI system can deliver. Demonstrating a data-driven ROI estimate, including conservative scenarios, is crucial in gaining C-suite support for AI initiatives.
The SBAR model, originally used in the military and healthcare settings, provides a structured approach to effectively communicate the benefits of AI systems to C-level executives. By addressing each step – Situation, Background, Assessment, and Recommendation – with a focus on ROI and data-driven insights, healthcare leaders can make a compelling case for AI investments.
In the Situation stage, organizations can highlight the inefficiencies in current risk adjustment and quality performance processes, supported by data illustrating the financial impact. The Background stage expands on these issues, addressing concerns about AI accuracy, reliability, and compatibility with existing systems.
The Assessment stage outlines the capabilities and benefits of an AI system, along with quantifiable predictions of its impact on the organization. The Recommendation stage proposes a specific course of action, such as piloting an AI system, with SMART goals (Specific, Measurable, Attainable, Relevant, Time-based) to guide implementation.
By combining a logical, data-driven approach with a flexible communication model, healthcare leaders can build confidence in AI investments using the SBAR framework. Tailoring the presentation to address the C-suite’s priorities and concerns, such as risk adjustment or quality performance, can further strengthen the case for AI adoption.
In conclusion, the SBAR-based approach offers a structured and effective way to demonstrate the value of AI to healthcare executives. With the right communication strategy and a focus on delivering a strong ROI, organizations can successfully navigate the path to AI implementation in healthcare.
