From insights to action: A new approach to revenue integrity analytics

By Colleen O. Hall, CPC, CPMA, CIRCC; and Shinal Patel, MHSA
| 4/20/2021
From insights to action: A new approach to revenue integrity analytics

It has been estimated that as much as 30% of the world’s stored data is generated by the healthcare industry.1 The amount of big data is expected to grow even faster in healthcare than in any other industry, due largely to technological advancements in analytics tools, medical imaging, and increased availability of real-time data such as that used in clinical decision-making.2

The challenge for today’s revenue integrity departments isn’t the availability of data; it’s putting that data to use in meaningful ways.

Today’s organizations need an analytics approach that both illustrates trends and can drive solutions. Consider when doctors meet patients. They might use the patients’ symptoms to glean insights on their condition, but treatment is directed at the underlying problem. A similar approach can be applied to data – does your analytics program track symptoms or diagnose root causes?

By drilling down into the data to not only identify problems but diagnose the root causes of those problems, you can turn valuable insights into actionable solutions. This approach considers how all the underlying factors of an issue drive various key performance indicators (KPIs) and how all those factors, in turn, affect each other. Such an approach would use a valuable KPI dashboard that doesn’t simply follow and monitor trends but also connects disparate data points to help organizational leadership diagnose problems and prioritize efforts to begin making improvements.

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How does this approach work?

This intention-based approach parallels clinical decision-making in many ways. Big challenges in healthcare cannot be fixed by “Band-Aid solutions” or “milewide, inch-deep” initiatives. Organization leaders must take an integrated approach to diagnose the underlying causes of issues in revenue analytics. With this approach, leaders:

  • Triage data to prioritize and align symptoms to tell a more holistic story about what is happening within the organization. When previously decentralized analytics become more integrated, they provide a better overall picture about what is happening within the organization.

    For example: Multiple variables are involved with tackling longer length of stay at a hospital for patients under observation. Length of stay might be affected by admit time, physician group, payer class, Medicare Severity Diagnosis Related Group, and more. By collaborating with all key players in the process (for example, case managers and physician advisers), leaders can connect relevant data to illustrate valuable insight.
  • Diagnose the root cause contributing to organizational performance. A close look into the data can help reveal gaps and broken processes hindering operational success. Identifying the underlying issues allows for targeted action to further improve and sustain performance.

    For example: Perhaps an organization identifies that observation length of stay is highest with a particular physician group. While useful, this insight does not necessarily explain the high length of stay. It also doesn’t provide an actionable next step. Using data to examine what specific factors contribute to an issue will reveal underlying causes. In this case, looking closely at length of stay by physician group might reveal that length of stay is highest on a certain admit day and time of the week. This in turn might reveal that physician rounding times contribute to higher length-of-stay metrics. By diagnosing the root cause, the organization now can take steps to solve the problem.
  • Treat the underlying cause with a targeted action plan. Once root causes are identified, key players are able to take action independently. With the right data, a solutions-based approach can lead to a user-driven action plan. The value is not in the number of metrics provided but rather in providing KPIs that identify underlying causes and prompt users to spend more time creating targeted action plans and less time trying to interpret the data or address surface-level symptoms.

    With actionable insights, temporary quick fixes can become standardized processes, and milewide solutions can go deeper to create sustainable performance improvement.

    For example: Once actionable insight from the data is identified – in this case, the insight that length of stay is highest during a specific admit time – case managers can work with physician group leads to prioritize coverage and identify optimal rounding times to tackle higher patient volume. By simply reframing existing data to be actionable, leaders can engage in feasible action plans to drive sustainable results.

Taking the first steps

A revenue integrity department can take these first steps toward using a more solutions-based analytics approach:

  1. Determine what data the organization has. Team members should take stock of the data they have at their disposal and assess how they review that data currently.
  2. Discover connections between different sources of metrics. Organizations can do this by asking the right questions – and a lot of questions – about the metrics to target areas for improvement.
  3. Design a better dashboard. Once organizations make logical connections between disparate sets of data, they can create better dashboards that allow for increased interconnectivity among various metrics. An ideal dashboard is not only easy for users to interact with but can reveal root causes of identified problems.
  4. Execute actionable steps. After they have identified which factors are causing problems, revenue integrity team members can determine and then execute the actionable steps that can be taken to help address those problems.

Putting data to work

Healthcare organizations don’t need more data – they need a plan to help them make sense of the vast amount of data they already have. Revenue integrity departments need analytics that can move beyond snapshots of high-level trends and shine a light on the root causes of problems that are holding them back from performance excellence.

A solutions-based analytics approach such as that outlined here can help organizations take existing, disparate information and connect it to reveal actionable insights and solutions to today’s most vexing problems – and whatever challenges lie ahead. To help put data to work and find their organization’s next best moves, leaders should consider seeking the expertise of third-party specialists in this area.

1 Marco D. Huesch and Timothy J. Mosher, “Using It or Losing It? The Case for Data Scientists Inside Health Care,” NEJM Catalyst, May 4, 2017,

2 Jessica Kent, “Big Data to See Explosive Growth, Challenging Healthcare Organizations,” Health IT Analytics, Dec. 3, 2018,

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Colleen O. Hall
Colleen O. Hall
Managing Principal, Healthcare
Shinal Patel