The recent Supreme Court ruling on health care reform, validating the health mandate, changes everything in your plans—or does it? Despite political battle lines being drawn and continuous sound bites from pundits praising or decrying health care reform, have government regulations really changed anything in the delivery of health care? If the Affordable Care Act were overturned, would it change the delivery of health care? The logical answer—not really.
The fact of the matter is that government regulations more often act to jump start the industry into moving in the direction it already knows is the right course. And once the industry gains traction, it outruns the government by internally implementing the changes that are needed to take health care to the next level. A look back in history can inform what is happening in health care today.
In the 1980s, runaway costs led Medicare to institute prospective payment controls in the form of diagnosis-related groups (DRGs), which paid for care by the case rather than individual lab tests and procedures. The institution of DRGs led to gnashing of teeth and claims of unfairness.
But hospitals realized that change was in the wings, and they began to rotate their businesses. They became cost-efficient by determining the most efficient way to perform a lab test or x-ray. They examined utilization on a patient basis and began to control costs. Then at some point, they became as efficient as they could by using these types of cost controls.
Jump forward to the ’90s when health care costs rose at double the rate of inflation. It was not enough to make sure that an x-ray itself was performed cost-effectively. The question became, “Is that x-ray necessary?” Managed care began paying a flat fee per patient for a fixed period of time, not for every x-ray performed. Once again, there was gnashing of teeth and claims of unfairness. As in the ’80s, however, hospitals realized that change was necessary, and they began implementing total quality management (TQM), total quality improvement (TQI) initiatives, and clinical program improvements.
Then in 1999, the Institute of Medicine (IOM) published To Err is Human: Building a Safer Health System. According to the IOM, 100,000 lives were being lost every single year in American hospitals because of adverse events—drug-drug interactions, infections caused at the hospital, etc. The government stepped in with mandated quality measures, incentives, and more to jump start the health industry toward change. After gnashing of teeth and claims of unfairness, hospitals responded by improving processes independently of regulation. Care management and involvement of all stakeholders led to greater integration of care across providers. But the focus on episodic approaches to managing care, while evolutionary, wasn’t enough to improve overall health and decrease costs.
Now in 2012, both the industry and health care reform are moving it forward again, driving clinical integration as the way to focus on population health and preventive care. Under the Affordable Care Act, the federal government initiated pilot programs for accountable care organizations (ACOs) to determine if such models, in which groups take responsibility for the care of patients over the lifespan, are effective in reducing costs and improving quality of care. Media hoopla once again abounds while the health care industry quietly goes about making internal changes to meet these same ends.
Clinical integration is allowing the industry to gain a full view of patient health—the cost of the complete approach. Organizations like Geisinger Health System in Pennsylvania, Sentara Healthcare in Virginia, Sharp Health Plan in California, and Novant Health in North Carolina are following patients by collecting and analyzing data from a variety of views—inpatient, episodic, payer, and outreach, and using predictive analytics to parse the data.
Combining retrospective and current data with predictive analytics, providers and payers can now predict what interventions and management techniques should be offered to resolve current health issues and predict the care patients might need in the future. Payers and providers can slice the data to identify a population of asthmatic patients, for example, who are adherent to therapies and motivated to exercise and change their lifestyles. Such a population would then benefit from programs that focus on an active approach to their health.
Predictive analytics enable ACOs and other health care reform models to assume responsibility and risk for patient populations in a way that will reduce costs of care in the long term. Health care providers and payers now have the ability to look at what happened to patients in the past, what is happening to them in process, and what may happen in their future. The reality, as I believe is becoming clearer, is that our focus on clinical integration, quality improvement, and population management is core to the future of health, regardless of payment/incentive models, government initiatives or organizational structure.