Slide after slide, chart after chart, stat after stat, Morales explored how to use data to get employers to understand the misalignment between health care and and health insurance. He began with a readily addressable area: prescription drug spending. He pointed out the common statistic that a small percentage (1%-3%) of employees often account for the majority (50%-60%) of an employer's drug spend.

He then critiqued the traditional reliance on pharmacy benefit managers (PBMs), whose profit model centers on drug markups.

"Write down this term: Lowest net cost," Morales advised. "If you have a $100,000 drug that pays a $15,000 rebate, then the net cost is $85,000. Nine out of ten people, if you ask them why they’re working with their PBM today, they’ll tell you it’s because of the rebates. Don’t chase rebates."

Instead, Morales advocated for strategies like international pharmacy plans and manufacturer assistance programs, which can significantly lower costs -- even though they don’t come with rebates. He also underscored the importance of focusing on high-cost medications, identifying this as the area with the greatest potential for savings. He shared an example of an employer-client who implemented these strategies, targeting just 15 drugs driving the highest spending for a small group of employees, resulting in over $9 million in savings from a total drug spend of $24 million.

Moving beyond pharmaceuticals, Morales addressed the often-cited disconnect between health care price and quality. "Most often, health care has an inverse relationship between quality and cost," he said, contrasting it with things like cars and houses where higher price often correlates with higher quality.

In fact, for some procedures, there really isn’t a lot of variation--at least not enough to justify the wide range of prices. “There are three manufacturers of MRI machines in the world,” Morales said, sharing an example using data provided by one of his partners, Green Imaging. “The average cost of a CT scan in this market was $250 to $600. This client was paying over $1,000. They had 600 claims of over $1,000 each.”

Surgical procedures are another area where having data can significantly empower an employer. Morales shared data provided by an employer showing their surgical claims via a major carrier--all rolled up without any breakdown of codes. “Forty thousand for a hernia,” Morales pointed out. “A hernia should cost between $4,000-$6,000, maybe $8,000-1$2,000 if it’s complicated.”

Finally, Morales examined the cost structures associated with J-codes, commonly used for infusion therapies, including cancer treatments. "It typically has two components from a cost standpoint: the facility and the cost of the drug," he explained, sharing an example of a $700,000 claim for an employee earning only $59,000, who also faced a $9,100 out-of-pocket expense, in addition to the employer's $600,000 outlay.

First, they focused on the drug itself, using the strategies outlined earlier to find the best price. And then, the facility. “Why are we sending people who need an infusion to the hospital, the dirtiest place on earth?

There are three different types of places you could send somebody: the hospital, an infusion center, or their couch.”

The final cost for the drug to be administered to the patient in the comfort of their own home? $39,000. And the final cost for the actual employee, given that an employer who utilizes these strategies to reduce their health care costs can pass those savings onto the employee? $0.

"This is all data. It’s not inherently sexy," Morales said. "But when you talk about the things that people do every day — when we talk about drugs, MRIs, the things that are fairly easily manageable if you just help people direct the care they’re having — you can have a monumental impact on the plan, the person, and the doctor."