The Importance of Using Data to Improve Care Quality and Lower Costs

Delivering high-quality care doesn't just improve patient health - it's financially beneficial, too, for payers and physicians. In coming years, physician practices that can show definite improvement in patient outcomes could earn some pretty lucrative payer incentives.

But how can physician practice truly improve outcomes, and provide care at lower costs?

During his Tuesday session at the Medical Group Management Association Annual Conference, "Understanding Data: How to Improve Quality, Access and Affordability of Care," Robert A. Greene, MD, national vice president, clinical analytics, for UnitedHealthcare, addressed this issue.

"If we improve outcomes and we improve the patient experience of care and we're working on decreasing cost, then generating value comes from improving outcomes and lowering costs," said Greene, adding that UnitedHealthcare currently rewards physicians for meeting these goals.

But simply reporting the rate of patients with a certain condition who have gotten better isn't necessarily showing a measurable difference. Therefore, healthcare organizations need to use data-extraction tools and technology to demonstrate quality improvement. Such data will only become more important in future pay-for-performance contracting and Medicare Physician Quality Reporting System (PQRS) initiatives.

Measuring data - including patient-reported symptoms, complications, and improvements over time - may seem like a daunting task to practices, but there are plenty of ways practices can establish benchmarks by which to measure quality improvement.

Greene suggested looking into established benchmarks (such as the average total cost of disease-management programs) from one of the many agencies that generates benchmark measures such as the National Quality Forum.

After using benchmarks to identify areas you might want to improve, your practice needs to set goals for quality improvement that are based on those benchmarks. Finally, implement a process to analyze the raw data.  

Where physicians typically fall short on quality improvement projects is not having understandable, or specific action items (such as interventions for patients not hitting certain benchmarks), Greene said.

Fortunately, there are a number of technology tools in the marketplace that can help practices with analyzing data.

Jon Goates, CEO of Davis Family Physicians in Layton, Utah, told Physicians Practice in an interview at MGMA13 that he uses Clinigence's PQRS reporting capabilities in the EHR's data analytics tool - one of a growing number of data-analytics products physicians are snapping up - to easily compare outcomes data for his diabetic patients. When certain patients stand out as not achieving certain benchmarks, his practice has the data immediately available so it can make interventions.

"We know pay for performance is coming, so we're learning to use these practice-integration tools before it is applied in the real world," said Goates. Using the tool will also help Goates' practice meet Stage 2 meaningful use and PQRS goals, he added.

For example, for his diabetic patients, "if we measure A1C scores and we have a certain population over the score of seven, we can get to those people with greater ease with the technology in place," said Goates. "We can communicate with them and say, 'We had an 'aha' moment when you scored an 8.3,'" and follow up with interventions such as healthy cooking tips, menu planning, or recommendations for cooking classes. According to Goates, these recommendations have made a difference in patients' A1C levels.

If his practice didn't have the tools to see the patients whose outcomes were at risk for getting worse, Goates added that his staff may not have know to follow up with such interventions.

Previously when the practice undertook quality improvement efforts by using rudimentary technology to extract data from spreadsheets, the process took four to six hours a day. Now, it takes about 20 minutes, Goates said.