Data-Driven Analytics – Modeling Changes to Compensation (Part 6)
Healthcare leadership using data-driven guidance can expertly strive to align provider compensation – often the most significant expense for a practice – with the organization’s core objectives. Providing physicians with up-to-date information regarding their current performance and projected compensation is one of the best ways to ensure transparent communication and motivate change. With the variety of plans and calculation parameters in play today, being able to accurately model proposed physician compensation plans with ease and flexibility is now a critical task.
This timely webinar discusses how to implement a strategic analytics plan to develop consistency in automating, calculating, and modeling physician compensation plans. We’ll share data-driven methodologies and tactics that nurture a trust-centric culture, essential for ensuring physician buy-in. We’ll also explore how to effectively communicate not only current and projected compensation but also actionable insights a provider can take to maximize their performance going forward. You’ll discover the key role data-driven analytics play in modeling and adapting compensation structures.
What You’ll Learn:
• How to project and align physician compensation with critical practice initiatives
• Methods to provide physicians and management with relevant, timely data
• Tactics that foster productivity while emphasizing evolving strategic objectives
• Strategies for mitigating mistrust and dissatisfaction when introducing changes to compensation plans
Who Should Attend:
Healthcare executives, financial officers, HR professionals, and anyone focused on understanding the intricacies of physician compensation in the contemporary, data-driven era will find this webinar invaluable.
Join us on November 29, 2023, at 1 PM Eastern Time. As we conclude our series, we’ll delve into the intricate nature of physician compensation metrics and emphasize how the insights from Parts 1-5 are instrumental for organizations aspiring to adopt best practices in a data-driven environment.
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