A major new study showing that hospital prices vary enormously between different American cities will impact the strategy of all hospital executives and call into question one of the theories behind the Affordable Care Act.
Aetna, Humana and UnitedHealth contributed data on the spending and utilization of 92 billion health insurance claims from 88 million Americans who have employer-sponsored health insurance.
"Virtually everything we know about health spending and most of the basis for federal health policy comes from the analysis of Medicare data," says Yale University's Zack Cooper, who is a co-author of the new study. "The rub is that Medicare only covers 16 percent of the population. The majority of individuals—60 percent of the U.S. population--receive healthcare coverage from private insurers. This new dataset really allows us to understand what influences health spending for the majority of Americans. This information is critical to creating better public policy."
Using Medicare data, healthcare policy experts who crafted the ACA used cities like Grand Junction, Colorado, Rochester, Minnesota, and La Crosse, Wisconsin, as models to be emulated by the rest of the country. Since these cities were among the lowest in healthcare spending of the nation's 306 hospital markets when ranked by Medicare spending per beneficiary, the theory has been that other cities could decrease their healthcare spending by learning how those cities deliver care.
Likewise, McAllen, Texas, which ranked high in healthcare spending based on Medicare spending per beneficiary became the poster child city for wasteful health-care delivery. President Barack Obama shared an article by Atul Gawande focusing on McAllen with House and Senate members while crafting the ACA, according to the New Yorker.
The biggest bombshell delivered by the study is that there is a low correlation (14 percent) between spending on Medicare beneficiaries and spending on the privately insured. Grand Junction, Rochester and La Crosse do spend less than most to take care of Medicare patients, but the new study shows that they are relatively expensive at taking care of privately insured patients. For example, Grand Junction had the third-lowest Medicare spending per beneficiary among the 306 hospital markets, but the ninth highest inpatient prices and the 43rd highest spending per privately insured patient. And McAllen, Texas, when viewed through the lens of cost per privately insured beneficiary, comes in below the national average.
Some of the findings in the study include:
- Lower limb MRIs cost 12 times more in the Bronx than in Baltimore
- Lower limb MRIs can vary by a factor of nine within the same city (Miami)
- Knee replacement facility prices are six times more expensive at the highest ranked Atlanta hospital compared to the least expensive
- Colonoscopy facility prices are six times more expensive at the highest ranked Philadelphia hospital compared to the least expensive
The take-home messages for hospital leaders, according to the study authors, are:
- Cities with hospital consolidation are associated with higher hospital prices
- Price is the primary driver of spending variation for privately insured patients
- Monopoly hospitals have a 15.3 percent price premium
- Strategies to address healthcare spending variation across the U.S. may differ for publicly and privately insured populations
- Reducing spending for the privately insured will come via targeting high prices and service intensity by anti-trust enforcement, as well as price regulation
- There is a significant opportunity to save by steering patients toward low cost/high quality providers via value-based insurance design
- There's a significant need to make prices more transparent to consumers
All hospital leaders will need to carefully read this new white paper, which calls into question some of the fundamental beliefs that have driven organizational strategy up to this time. Using only Medicare data and not private insurance data can result in decisions that will be harmful to the organization's survival in a time of rapid change and uncertainty.
Kent Bottles, M.D., is a lecturer at the Thomas Jefferson University School of Population Health and chief medical officer of PYA Analytics.