Best Practices for Data-Driven Benchmarking

Benchmarking adds an important dimension to measuring and propelling performance and market competitiveness. It enables providers and payers to understand how they stack up against industry leaders and local players on key performance indicators as well as national standards of excellence.

The first step in a successful benchmarking process is to establish a baseline of an organization’s quality, equity, efficiency, costs, patient experience and outcomes. It’s important for provider-led risk-bearing entities to look beyond their four walls, too,  in order to be able to leverage benchmarking for key network development, optimization and contracting decisions. Done well, benchmarking serves as a foundation for increasing revenue and market share while improving care, quality and patient experience.


Getting benchmarking right

As important as benchmarking is, there are plenty of ways it can go wrong. Most involve problems with the data or how it is interpreted, including:

  • Inability to collect, consolidate and normalize useful data
  • Lack of or gaps in germane and timely organizational data
  • Lack of access to relevant national data
  • Inability to correctly compare, interpret and analyze data

In these cases, organizations can end up making major decisions based on faulty, old or incomplete information. To avoid going down the wrong paths, payers and providers need to apply these best practices and guidelines for data-driven benchmarking.


1. Invest in robust data and analytics.

Organizations have a range of options for ensuring they have the right data and benchmarking expertise to drive impactful decisions. At one end, they can outsource analysis, benchmarking, reporting and recommendations to a data analytics-as-a-service provider. It will ingest the organization’s claims and other data while also drawing on de-identified data from other clients and, in a few cases, national sources. The provider will build a full picture of how different segments within an organization or network are performing on any number of important measures as well as how the organization compares to industry leaders and standards.

At the other end, organizations can recruit a team of data analysts and equip them with a data analytics platform, third-party data sets to supplement internal claims and other data and additional tools to produce accurate, actionable and timely insights.


2. Compare apples to apples.

This maxim certainly applies to patient and attributed member populations, whether it’s by geography, age, lines of business or panel size. There’s little to no value in evaluating a Medicaid population in rural California versus a commercial population in New York City.

Additionally, it’s critical to assess similar providers instead of measuring a provider with a heavy concentration of pediatric patients against one with a higher mix of Medicare patients, for example. Like means like: For instance, it’s misleading to compare interventional cardiologists with non-invasive cardiologists even from the same practice or geography. The bottom line is the closer the match between populations, lines of business and providers, the more useful the comparison.


3. Prioritize key opportunities.

There’s no need to boil the ocean. Organizations can leverage benchmarking to target a known problem or strategic initiative, such as reducing out-of-network leakage or overuse of the emergency department.

If an organization is spending more than its per-member, per-month (PMPM) payments, benchmarking data can help identify where this disproportionate cost is occurring. Are average costs higher? Perhaps there is an out-of-network leakage concern where members are receiving services at a higher cost. Are utilization rates higher? The answer may lie in determining the root cause of why members are overutilizing the emergency department for preventable visits when a primary care physician or urgent care could have averted the unnecessary ED visit.


4. Be open to mixed or mediocre findings.

It’s hard for individual providers or organizations to learn they are not top performers. The initial instinct is to dispute or downplay these findings. But data-driven benchmarks and factual comparisons tend to extinguish arguments and counter claims. They then lead to a more productive discussion and planning to turn less-than-stellar areas into improvement opportunities.


5. Take into account the broader context and changing conditions.

Setting a goal of saving 5% a year may have made sense before COVID-19 hit. But the pandemic made it impossible for payers and providers to achieve that year-over-year improvement. Similarly, 2021 is not a good year to set as a baseline.

Rather, organizations should adjust their benchmarking and goals as situations change. A more realistic target might be performing in the top quartile of all comparable providers or payers.


6. Don’t make it the be-all and end-all.

Not everything can be explained by benchmarking alone. A provider may appear to perform poorly compared to peers. But a conversation could uncover that a few patients are throwing off all of the metrics.

For providers and health plans, benchmarking done right can serve as a critical tool and process for driving improvement, gauging progress and achieving strategic goals. The cornerstone is real data–the organization’s paired with national information and benchmarks. Equally important is the expertise to accurately analyze and compare timely performance metrics, then develop recommendations focused on priority problems, gaps and opportunities.

As health care organizations work to build capability and competency in new and better ways of doing health care, especially population health and total cost of care management, benchmarking supplies essential information and insight to develop and follow a roadmap to success.


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