Comparative analytics and the new era of benchmarking

The phrase “you cannot manage what you do not measure” sums up the importance of adding comparative analytics capabilities
By Steve Miff
10:50 AM

With the healthcare industry moving toward a value-based care model, analytics have become one of the primary areas of focus for health systems. With this shift, the internal benchmarking typically used to evaluate performance is no longer sufficient to meet government mandates, ensure timely reimbursements and avoid financial penalties. “Comparative analytics” will be required to meet these new challenges.

Comparative analytics brings together healthcare’s “big data” (from payers, providers, supply chain and patients) in real-time giving health system administrators and service line leaders the ability to: (1) understand how their volumes, use rates, and payments shift and compare to their peers and (2) successfully deliver on the value = quality/cost equation through utilization and outcome measurements and peer benchmarking. In more simple terms, comparative analytics helps turn big data into big action.

Not surprisingly, there a myriad of solutions offered by consulting firms and technology companies promising to deliver the information and insights hospitals need to meet new requirements. Knowing how to effectively move your organization forward starts with an understanding of where you are today in the journey toward comparative analytics capabilities.

Below are five common stages along the road to achieving comparative analytics capabilities to help you gauge your progress and investment strategy in information technology:  

Stage 1: Fragmented analytical solutions
Internally focused benchmarking capabilities knitted together from various subscription-based data vendors and internally developed applications. Leaders are cautious to act on analytical recommendations due to lack of a standardized approach, lack of trust in internal data and inability to verify information with other trusted sources.

Stage 2: Standardization and data governance practices are emerging
Data warehouses are beginning to be co-located and data refreshes are becoming timelier and aligning to national standards and methods. Key performance indicators (KPIs) are shared and visible at all levels of the organization.

Stage 3: Interconnected systems with weekly data updates
Permanent multidisciplinary teams are in place and monitoring data for opportunities to improve quality across the organization.  Population-based analytics are used to identify variations and suggest improvements to individual patient care.

Stage 4: Analytics informing population health management and cost economics
Data is refreshed within one day of source system changes. Data governance creates trusted metrics and KPIs that are linked to compensation plans for clinical leaders and executives.

Stage 5: Analytics enable proactive risk management
Data is updated in “real time” to provide interventional decision support. Focus expands from case management to clinical and payer collaborative models, proactive risk management and more prescriptive analytics

The ability to get to the higher stages of analytic capability is generally only feasible through a solution that enables information sharing among all parties in the care continuum. When evaluating the range of options available in the marketplace to help you move through the stages, make sure to ask yourself these questions:

  • How quickly can I get the answers I need and are they accessible whenever/wherever I need them?
  • What level of data detail do I require, and what implication does the desired level of data have on my data governance and compliance capabilities?
  • What are the data sources and how often is the data updated?
  • Will I need to build and maintain infrastructure to drive the application?
  • What level of support will I have related to providing insights that can help improve our performance?
  • Does the solution include predictive modeling to determine potential impact on key workstreams?

The phrase “you cannot manage what you do not measure” sums up the importance of adding comparative analytics capabilities into your health system. Today’s healthcare transformation is both a sprint and a marathon, in that it’s not only how much you improve, but how your rate of improvement compares relative to others.

In a competitive and increasingly transparent market, leaders simply cannot deliver a value-based care model if they are unable to track progress and assess their rate of improvement. By properly leveraging comparative analytics, healthcare leaders will finally gain the ability to respond to the dynamic state of their organizations in real-time.

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