Bigger doesn’t always mean better when it comes to health care data

LH_low-resMost health care organizations have terabytes of patient data at their disposal. But without the right analytics programs, all that information is just words and numbers. “Big data” doesn’t always equal “good data.”

Providers now know that to get a full picture of patients’ health status they need data from many sources, including claims, clinical, administrative and socio-demographic data repositories. Data analytics show how care is delivered, the populations that care reaches and how individual practitioners are performing against quality metrics.

Value-based care puts emphasis on patient risk, and organizations that can leverage good data are better positioned to build risk-bearing systems and financial models that support positive care outcomes.

But what is “good data?” Raw information from claims or electronic medical records don’t work for analysis. Good data includes inpatient and outpatient clinical information plus detailed financial figures that show the total cost of care. This mix of clinical and claims data is then normalized and validated using a robust analytics platform. The result: information that provides trustworthy feedback for use in maximizing patient care, reducing risk and boosting financial bottom lines.

Good data means accurate data. Human data entry errors are common — records may show men having babies or Daffy Duck visiting an emergency room. Part of the validation process must include cleansing data for abnormalities. Organizations also must not get caught up in data gathering for data’s sake. Make the information actionable and determine how to best use it once you have it.

One key use of actionable data is development of accurate registries for care management. Normally built using claims data, registries that add clinical information provide organizations with a more accurate snapshot of patients with the same disease.

With good data in hand, the next step is to invest in advanced analytical systems that provide accurate, timely and precise risk perspectives. Such analyses provide a more-complete view of population health, help identify at-risk patients to reduce preventable costs and improve performance using comparative clinical benchmarks.

For a closer look at the power of good data, download the Optum white paper, “Getting from big data to good data: Creating a foundation for actionable analytics,” by clicking here.

In our next post, we’ll discuss how the power of good data can improve patient care.


About the Author:

Leslie Cozatt currently serves as Director of Marketing, Optum Provider – Thought Leadership and Content Strategy.

She directs the development of content that spotlights the role of data analytics in healthcare – specifically the transition to value-based care, risk management and population health management. She brings to her role more than 20 years of experience developing B2B and B2C integrated marketing campaigns for companies including ThreeWire, Eliance and 3M. Leslie attended the University of Minnesota and graduated from Wellington College with a BS in International Business & Communication.

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