Data-Driven Benchmarking Proves How Local Healthcare Really Is | A Conversation with the Chief Analytics Officer at Bon Secours Mercy Health
The following is an excerpt from a conversation on the limitations of national benchmarking with Trilliant Health's SVP of Market Strategy and Chief Research Officer, Sanjula Jain, Ph.D., and Deepesh Chandra, Chief Analytics Officer of Bon Secours Mercy Health.
Uncovering Aspirational Benchmarks | Deepesh Chandra - Chief Analytics Officer at Bon Secours Mercy Health
Understanding Pandemic-Deferred Care | Deepesh Chandra - Chief Analytics Officer at Bon Secours Mercy Health
The Limitations of Traditional Benchmarking | Deepesh Chandra - Chief Analytics Officer at Bon Secours Mercy Health
Sanjula Jain Ph.D.: The SimilarityIndex™ introduces a new set of benchmarks, which were generated from a machine-learning algorithm, which we call the SimilarityEngine™ that lets health systems think about benchmarking in more of a mathematical way. What makes this approach to benchmarking different than some of the traditional top hospital lists or other benchmarks that we're used to leveraging?
Deepesh Chandra: When you think about benchmarks that are created nationally, it takes a huge amount of variability that exists in different markets, and sets a mean, across the entire nation. That’s great, to some extent, when you’re looking at macro numbers, but when you’re operating in a local market, you often wonder if these national standards do any justice to your local realities or not. Sometimes, it is more important for you to find a mirror image of your geography and your circumstances in different parts of the country, and then begin to understand how those dynamics are working. Trilliant Health’s work in building the SimilarityIndex™ is great for someone to understand - if I’m working in the Cincinnati, Ohio market, what are similar markets that exist across the country? What’s happening in those markets? How close are mine in terms of performance and growth and attracting the consumer base? Are there a set of learnings we can draw versus constantly trying to draw things from a national level?
Sanjula Jain Ph.D.: We love to use the term best practices in care. What role does benchmarking whether it's inter-organizational or intra-organizational play at Bon Secours Mercy Health?
Deepesh Chandra: When you are trying to chase those benchmarks, often it is lost as to how those benchmarks were created, by whom, and under what assumptions. In the healthcare era that we live in, these benchmarks are significantly tied to reimbursements, quality scores, and things of that nature. Often, you see health systems chasing these benchmarks that were constructed with several sets of assumptions that may or may not be relevant for their market. Either I may be constantly overperforming on those benchmarks, or I may be completely underperforming even after doing everything possible. That variability is always challenging, and it is a convergence towards the mean that happens. We lose consideration of local aspects and local measures.
Sanjula Jain Ph.D.: We looked at Richmond, which is one of Bon Secours markets. What were the top five most similar markets to Richmond from a consumer attributes perspective? On that list, you have markets like Chicago and Minneapolis, and Rochester, New York. Then when we look at the most similar markets to Richmond on a combination of factors like consumer and growth, demographics, and economics and competition, the list looks really different. Then you get Virginia Beach, Baltimore, Philadelphia, and St. Louis. Knowing that right that you have different market peers on different dimensions, how does that change what Bon Secours might actually do or think differently about on an actual decision?
Deepesh Chandra: This brings an exciting concept around - which are my twin markets across the country? Also learning from our peers who are operating in those markets, what are they doing? What are they still struggling with? It gives you a crystal ball, showing what might work in my market and what might not. In a great sense, you see a bit of A/B testing of your strategy in those markets. As you look through your twins across the country, and especially when it trickles down into your strategy around population health, how would you model your contracts with the pair? How will you think about care delivery? How will you think about growth and expansion in ASCs, urgent care, and others? This gives you a great simulation of what might happen, given that you have a twin on the other side of the country that has gone through the process of what's happening there. It's a great learning experience before you make capital decisions.
Learn more about the SimilarityIndex™ and explore our publicly available tool to learn how your market ranks.