Trilliant Health

The U.S. health economy is $4.5T – more than the entire GDP of any country in the world other than China – and is projected to grow to $7.7T by 2032 – more than the combined total GDP of Germany and India. What is society’s return on this massive investment? Not much, according to our latest report, the 2024 Trends Shaping the Health Economy.  The 2024 edition of our Trends Shaping the Health Economy Report explores the 8 macro trends that will define the emerging landscape of the U.S. healthcare system and concludes that the winners of healthcare’s negative-sum game will be those who deliver optimal value to their customers. 🔗 https://lnkd.in/eqEqsPX3

We’re excited to formalize and expand our machine learning-driven approach with the introduction of our Machine Learning Team. The reality: Healthcare claims data contains countless variations and exceptions that simple rules-based systems cannot handle effectively. Our ML-first approach enables us to resolve many of the most complex challenges in claims data with: 🏷️ Labeled data collection 🚀 Deployment pipelines 📊 Performance monitoring frameworks 🏅 Data quality processes Our ML-first approach powers our ability to process raw, incomplete claims data and turn it into meaningful insights about longitudinal patient journeys and physician relationship networks. The outcome: Healthcare stakeholders gain unprecedented visibility into physician decisions that directly impact their market position. #HealthcareAnalytics #MachineLearning #DataScience

For #lifesciences companies, knowing which physicians prescribe your drugs and implant your devices — and those of your competitors — is table stakes to win healthcare’s negative-sum game. Our Provider Directory offers visibility not only into physician #referral patterns but also the financial relationships between those physicians and life sciences firms. How it works:  1️⃣ Search for any U.S. physician.  2️⃣ Analyze their procedure volumes and practice patterns.  3️⃣ Understand their existing relationships with life sciences companies through #SunshineAct data.  4️⃣ Refine your targeting and strategy with these insights. 📈 Ready to gain a competitive edge? Start with our free provider directory. https://lnkd.in/epu2nvad

The Trump Administration's latest Executive Order on #pricetransparency underscores the administration’s commitment to lowering healthcare costs. To make the case, the announcement points to a single patient’s experience—an anecdote of one person saving $1,095 by shopping between two hospitals just 30 minutes apart. But this isn’t just one patient’s story. Our 2024 Trends Shaping the Health Economy Report analyzes health plan price transparency data and reveals that price variation is widespread but unexplainable across and within markets. Across markets, the negotiated rates across a basket of four common heart and vascular surgical procedures ranged from $26.5K for a hospital in St. Louis to $153.8K for a hospital in New York City (5.8X). Market medians: Dallas: $77.0K  New York: $75.8K  Atlanta: $63.2K  Los Angeles: $58.8K  Miami: $55.3K  Houston: $50.2K  Phoenix: $46.7K  Chicago: $42.9K  St. Louis: $38.1K Even within the same market, significant variation is prevalent. In the New York-Newark-Jersey City market, the negotiated rate varies by more than 4X. Importantly, higher rates are not associated with higher quality, demonstrating that in healthcare you rarely get what you pay for. If the principle of “regression to the mean” manifests in healthcare as it has in other industries, total spending could be reduced without negatively impacting quality or significantly reducing patient choice. Read the full report: https://lnkd.in/gQWuQE63

The success (or failure) of every #healthsystem depends on a physician’s decision to: 🏥 Admit patients for inpatient care - or not  🩺 Schedule procedures and surgeries - or not  🏪 Refer to another provider - or not  🦿Order diagnostic testing - or not  💊 Prescribe medications - or not Each of these clinical decisions influences #hospital volumes, network integrity and ultimately, market share. Yet most organizations have limited visibility into physician activity beyond their own four walls, leaving them unaware of how much of the shrinking market they control. Understanding which of these decisions your organization wins – and which you lose to your competitors – requires granular insights into #physician decisions and patient journeys.  Learn to develop data-driven physician strategies with the Field Guide. https://lnkd.in/exeg_dKn 

This week, I had the honor to be a part of a great discussion at #ViVE2025 with Alya Sulaiman, Zachary Lipton & Randi Seigel on the future of AI policy and regulation. One thing we all agreed on: there is a lot of nuance in #AI policy, and clear definitions matter. Before we can shape policies, we need to align as an industry on what we mean when we say AI and the use cases where we agree on the rules of interpretation. From my perspective, one of the biggest challenges is distinguishing where AI is truly well-suited versus where subjectivity still plays a role. AI excels in objective, binary outcomes, yet many processes—like prior authorization—may seem rule-based but still involve subjectivity in decision-making. We also discussed the critical distinction between administrative and clinical AI use cases. With administrative expenditures rising 40% from 2011 to 2021, now on par with direct patient care costs, there is a massive opportunity to apply AI to repeatable administrative tasks and improve efficiency. Before we can regulate AI effectively, we need a more data-driven landscape assessment to understand where the real opportunities lie and what specific problems we are solving. Without this clarity, there’s a risk of either overregulating areas where AI can drive meaningful efficiency gains or underestimating the complexities of more nuanced use cases.

⚠️ The #NHE is an estimate of estimates Most health economy stakeholders assume the National Health Expenditure (NHE) precisely measures U.S. healthcare spending. A number so widely cited—used by policymakers, analysts and executives—must be based on hard data, right? Not exactly. 🗳️ The reality The estimates of America's healthcare system, representing nearly 18% of GDP, are based on surprisingly limited data. The issue stems from the methodology. Instead of using comprehensive #healthcare data sources, the NHE relies primarily on surveys that are not specific to healthcare: Census Bureau “estimates” from the Economic Census (EC) (available for years ending in 2 and 7), the Service Annual Survey (SAS) and the Census of Retail Trade (CRT). 🤔 What's notably absent from the NHE methodology? Data from CMS's Healthcare Cost Report Information System (HCRIS). These cost reports, filed under penalty of perjury, carry more weight than voluntary surveys. 💡 The inescapable truth The NHE is an estimate of estimates, primarily based on non-healthcare data. This means the federal government is approximating the size of the largest sector in the world's biggest economy using indirect measurements. What other "estimates" are you basing your decisions on? For more insights into how flawed data impacts the health economy, subscribe to Counterpoint. https://hubs.ly/Q037mvMy0

Cardiovascular disease continues to be the leading cause of death in the U.S., responsible for 21.4% of all deaths in 2022. While there have been improvements since 1999, the #cardiovascular disease mortality rate has increased by 10.9% since 2012.  Despite the prevalence of cardiovascular disease, data reveals that there is significant variation in price across #heart and #vascular procedures, with very little (if any) correlation between rate and quality. The lack of relationship between rate and quality exposes inefficient and wasteful spending in #cardiology, likely exacerbated by how common cardiovascular disease is and the wide variations in price. 

Join our Chief Research Officer at ViVE 2025 on February 18th at 1:30 PM CST on the Rock-n-Roll Stage 🎸 for a discussion on #AI regulation in healthcare with industry leaders from Abridge, Datavant, the Assistant Secretary for Technology Policy Office and Manatt, Phelps & Phillips, LLP. #ViVE2025

What the #Indiana House of Representatives is considering with HB 1003 and HB 1004 portends catastrophic damage to the operating models of every health economy stakeholder.   What starts with the #hospitals will not end there. Price caps will limit medical loss ratios, which will limit health plan profits. Eliminating the gamesmanship of 340B pricing seems certain to impact #pharmaceutical companies. And, when the “Big 3” of the health economy – hospitals, #payers and pharma – get squeezed, everyone else will as well.   More in this special edition of #Counterpoint ⤵️