Clarify’s core philosophy is that, in order to drive improvement and push towards value, clinicians must be central to the journey. Most clinical physician performance assessment approaches traditionally used by health systems to reduce cost and improve provider performance measures have failed to drive impact. This is due to a combination of outdated healthcare information, lack of robust case-mix-adjustment, black box benchmarking methods, static pdf-based reporting with no ability to test or validate the underlying healthcare analytics, and generic healthcare metrics that do not deliver practice-specific, actionable provider performance insights. As a result, myths and flawed orthodoxies about the futility of provider performance analytics have emerged that are diametrically opposed to the lessons on how analytics can drive success learned from other industries. When clinicians feel like the complexity of their patients’ care journeys are not reflected in the benchmarks provided, they ignore provider performance reports lacking a properly case-mix-adjusted or a poorly explained benchmark. Consequently, many administrators are of the opinion that clinicians are averse to change and that reporting alone will not influence behavior. Meanwhile, other industries have made massive leaps forward in delighting their customers with new business models informed by performance insights only available through big data analytics, delivered through autonomous reports and dashboards. Clarify Health solves this need through the Atlas platform that leverages big healthcare data analytics and is designed specifically to address these mythologies. Many industries have utilized information, AI, and machine learning to deliver insights that improve quality, lower costs, and drive efficiency. The power of such technologies has yet to be utilized effectively to deliver similar results in healthcare and most importantly, to improve the patient care journey. Clarify’s approach is built on the same foundations used by leading banks, consumers, and logistics companies, coupled with the unique nature and context of healthcare. The Atlas platform has been purposely built to help position clinicians at the center of a customer-driven healthcare system by delivering precise case-mix adjustments delivered in a manner that drives true healthcare transparency. This philosophy and approach enable the best quality care to be delivered to those who matter most, patients. Clarify, at its core, delivers insights and provider benchmarks around cost and quality that are fair and useful. This is achieved by drilling down to the individual physician and patient cohorts, an approach called precision cohorting. This approach provides clinicians and providers with a level of granularity that reveals actionable performance insights, relatable healthcare data points, and, over time, a comprehensive view of a patient’s care journey that is bespoke and specific to them, rather than an ambiguous average that does not apply to their panel population. This benchmark or expected value is called “Blue Diamonds” in the analyses. They deliver timely, trusted, personalized performance insights that cut through the noise and immediately suggest areas for improvement. Powering these diamonds requires large datasets and complex data science techniques. For every single one of our expected values or Blue Diamonds, we enable the clinician to see all the different factors that go into the creation of that value. The level of transparency you see in our provider performance analytics creates trust with clinicians as they are no longer being compared to a “black box”. Fundamentally, Clarify’s derived performance insights are more trusted by and useful to clinicians because they predict expected values at the patient level. This enables the creation of cohorts of patients that are matched precisely to the clinician’s own. To learn more about how you can bring fair and actionable provider performance benchmarking into your organization, download our white paper on the future of provider benchmarking.Leveraging AI and machine learning foundations from other sectors
Creating greater trust with useful performance insights
- Author Details