Better Quality Measures = Better Population Health Outcomes

Better quality measures, analytics are needed for the effective development of ACO models. Providers are rapidly transitioning to accountable care models, but without better quality measures, these plans may have limited success.

Many payers and providers have high hopes for the ongoing, industry-wide transition to pay-for-performance models, but poorly defined quality metrics and a lack of analytics technology adoption could derail these accountable care models before they have a chance to deliver on their promise.

“We have a situation that is actually very disappointing,” said Allan Goroll, physician at Massachusetts General Hospital and professor of medicine at Harvard Medical School. “We have poor metrics for performance, little work being done on improving those measures and very little attention being paid by payers to more meaningful metrics. Instead we’re just doing the quick and dirty.”

Goroll, who is in favor of the theory behind pay-for-performance, said failure at this stage could have major consequences. During this time of transition, if ACO models do not contribute to improved value in healthcare, the entire concept may be abandoned.

An Industry in Transition

The momentum behind performance-based payment models is significant and growing. Most private payers operate some form of pay-for-performance reimbursement system. Performance-based payments are becoming baked into Medicare, and Congress has authorized a system that ties reimbursement to quality care.

But much of this movement toward pay-for-performance may be built on shaky ground. Undergirding the whole system is a collection of quality metrics organizations must meet in order to receive reimbursement. Goroll said many of these metrics fail to address the health needs of patients.

For example, most performance-based plans have quality metrics that require physicians to get the blood pressure or hemoglobin A1c of diabetic patients to a certain range. However, Goroll said achieving a specific number on these measures is not what makes a person healthier. Instead it is the degree to which a patient improves on these measures.

If a physician is able to help a diabetic patient significantly lower their blood pressure or hemoglobin A1c within six months, that doctor is probably providing high-value care. However, if the patient’s measures remain just outside the target level, the doctor will not be recognized or rewarded for it. This is the problem, according to Goroll.

He contends that quality metrics have been developed in this vein because they are easier for payers to define and easier for physicians to track. He thinks it is the responsibility of payers to help physicians adopt computer systems, possibly electronic health records, that make it possible to capture more clinically meaningful evidence of improved care. Without this progress, support for ACO models could collapse as physicians start to view quality incentive programs as irrelevant.

“What you have is bonus by target rather than by degree of improvement — and that makes no sense,” Goroll said. “It’s actually giving performance measurement a bad name because clinicians see this as silly. There’s a general sense that these are silly metrics and they have no credibility and that they are really of no value.”

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Original article written by Ed Burns, TechTarget.
 

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