Using data analytics to identify revenue at risk

Predictive and comparative analytics have the potential to drive improved value by pinpointing areas where proactive steps can better support optimal revenue cycle performance—as well as the organization’s mission.

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The trend toward using predictive and comparative analytics to improve value in health care is on the rise, driven by advancements in technology, healthcare reform, regulatory mandates and the emergence of value-based payment models.

 Key factors for successfully using data analytics to improve revenue cycle performance include the following:

  • Senior leaders who engage physicians and work with business unit owners to gain groundlevel insights
  • Communication and learning
  • Embedded analytics
  • Transparency related to what the data show, how the data will be used, and what items have been brought to light via data analysis
  • Real-time monitoring of data
  • Incorporation of staff feedback in continually improving analytical modeling capabilities
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