Cutting the Costs of Care

Despite the historic signing of the health care reform bill by President Barack Obama on March 23, months—probably years—will pass before the impact of change is fully understood.

At the outset, the legislation encourages health policy experts to push the cost-cutting envelope. For one, it will create pilot programs within Medicare that will test innovative cost-reduction strategies. The goal: to move successful programs into widespread use by Medicare, and hopefully the private sector.

That’s good news for health policy experts at the Bloomberg School. For years, researchers have been working on innovative ways to solve the problem of cost-control, looking for ways to better understand disease patterns and treat illness more efficiently. There’s need for change. Health care costs have exploded with expenditures in the U.S. surpassing $2.3 trillion in 2008, more than three times the $714 billion spent in 1990.

Toward that end, Jonathan Weiner and his team have developed the widely used Adjusted Clinical Group (ACG) System, a software application now used across the U.S. and abroad. It enables public agencies and insurance companies to better understand health-condition distributions and to apply predictive modeling and risk adjustment to better manage care for entire populations. As a result, governments or companies can conduct analyses to pay providers more fairly for services, as well as allocate scarce resources more fairly.

ACG has been used for adjusting reimbursement rates for Medicaid programs in a large number of states, including Maryland. “We are working to make certain compensation matches the care provided,” says Weiner, a health services researcher. “We don’t want to overpay those who are treating healthier populations, and we don’t want to underpay those who are treating patients with multiple co-morbidities.”

U.S. health care reform is expected to encourage further use of risk adjustment for payment applications as well as use “comparative effectiveness” to find the best treatment protocols. While randomized clinical trials have long been the gold standard for setting standards of effectiveness, these studies typically focus on very narrowly defined populations.  Results of these trials are hard to generalize to “real” patient populations.

With the expected widespread adoption of electronic health records (EHRs), researchers will make use of more in-depth data on patients’ co-morbid conditions and treatments. For example, they may be able to determine more quickly the best treatment for a particular ailment or adopt more cost-effective treatment protocols for an entire population.

What's more, Weiner’s team and Johns Hopkins University and Health System colleagues are in the early phases of developing "population health IT systems," where Johns Hopkins-based health care expertise, such as treatment protocols, can be made available to health care providers through emerging digital technologies such as advanced software applications, EHRs and telecommunication devices.

These health IT systems provide the opportunity to expand the concept of “virtual medicine,” often associated with treating an individual remotely, to the idea of virtual health care management, which would export the most cost-effective and equitable methods to treat populations.

But, notes Jonathan Weiner, “We need to find an easy way for medical information system vendors to access Hopkins knowledge and apply it at the point of care. That is our challenge."