Data can help agencies get ahead of increasing health care costs amid funding uncertainty
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States are turning to data to inform health care spending decisions. One expert says tech like artificial intelligence will play a large role in enhancing those decisions.
Easing high health care costs for Americans has long been a goal of governments at every level. Last month President Donald Trump, signed an executive order aimed at increasing hospital and insurers’ price transparency in a bid to lower costs for consumers.
The order builds upon work Trump initiated during his first presidential term, said John Hargraves, director of data strategy at the Health Care Cost Institute, a non-profit research institute. In 2020, Trump signed the No Surprises Act, which restricts health care providers from billing consumers with unexpected charges if the person received care from an out-of-network provider at an in-network facility.
But the federal Center for Consumer Information and Insurance Oversight, the agency tasked with implementing the law, lost about 15% of its staff earlier this month under Trump’s plan to reduce the federal workforce, which could impact its rollout.
At the same time, GOP leaders are proposing to slash federal funding for Medicaid, a move that would likely drive up states’ health spending. And the federal Congressional Budget Office recently raised concerns that, without decreased funding for Medicaid and Medicare, the GOP will fail to meet its goal of reducing the federal government’s spending by $1.5 trillion over the next decade.
States have taken increased action to address rising health care costs to protect consumers from exorbitant prices for health care and services, Hargraves said.
“I don’t think the idea that the cost of health care is an issue for most folks is new,” he said, but dramatic increases in prices over the last 20 years have “made it harder for people to understand why.”
Connecticut is just one state where officials are trying to uncover that reason. The state’s Office of Health Strategy is leveraging new dashboards to track health care spending, as well as cost trends and drivers across public and private providers in the state. The data tools, launched last week, were developed by the policy research firm Mathematica based on data from Connecticut’s App-Payers Claim Database.
The three dashboards track prices of health care, hospital and prescription drug utilization to help inform policymakers’ decisions to develop and implement cost reduction efforts to improve the affordability and accessibility of health care across the state.
“Increased transparency into what is causing healthcare costs to climb can inform and enhance decisions about how best to address them,” said Josh Baker, vice president of the state and local government division at Mathematica, in a statement. “With these dashboards, health decision makers in Connecticut will have easy access to the data and insights they need to effectively track healthcare costs and take steps to contain excess spending.”
With more granular data on statewide health spending, policymakers can better identify cost trends, such as concentrated costs at a particular hospital or health care provider, said JP Wieske, vice president of state affairs at Horizon Government Affairs, a health care policy consulting firm.
If health care data revealed that there is a single care provider with a high concentration of opiate prescriptions, for instance, that could indicate to policymakers that there is a lack of adequate providers, he explained. Lawmakers could then implement strategies to increase competition and affordable provider options for consumers.
As more states increase their data collection and analysis efforts, artificial intelligence and other innovative tech will play a critical role in increasing the efficiency of how data is managed and leveraged by policymakers, Wieske said. States are already experimenting with how AI and tech could help governments’ bottom lines while also improving service delivery.
AI can help deliver actionable insights that can help officials narrow down specific cost drivers or trends in their state populations’ health outcomes so they can better tailor their health spending and budget plans, he explained. With more “personalized care” available to residents, states could cut unnecessary spending while also reducing the potential price of more severe health claims in the long term, he added.
States have long understood the value of big data to inform decision-making, Wieske said, but now the next hurdle for policymakers is to incorporate how they will safely and responsibly integrate that information with more advanced technology to meet their goals of reducing health care spending.