Readmission Rates: A Step Toward Better Healthcare Business Intelligence

Originally published 4 August 2009

Performance measurement is growing up in healthcare. And this will drive the need for more sophisticated business intelligence for providers, payers, regulators, quality improvement groups and patients.

Recently, the Centers for Medicare and Medicaid Services (CMS) released a study on thirty-day readmission rates among the nation’s hospitals. The basis for this announcement is three years of readmission data, which can be found at Readmission rates, according to the CMS, show how frequently patients return to a hospital 30 days after being discharged, which is a possible indicator of how well the hospital did the first time the patient was in the hospital.

Strategically, the thinking behind readmission rates is that by reducing them, patients will get higher quality care that will make them healthier and reduce costs at the same time. Common sense tells us this. And we can see where this is leading –  i.e., to linking payment for services to the readmission rates. This makes sense too.

Tactically, the release of this data has started a flurry of slicing and dicing the data by hospitals to find out where they rank compared to the competition. This ranking is both overall, as well as for selected medical conditions such as pneumonia, heart attack, etc.

Both levels of analysis of readmission rates will increase the need for business intelligence across all participants in the healthcare industry.

Performance Measurements Come Full Circle

Let’s take a step back for a moment to see the trend in performance measurement in healthcare. Most quality measurements on the clinical side of healthcare deal with the inputs to care. For instance, HEDIS measures such as weight assessment and counseling for nutrition and physical activity for children and adolescents, well-child exams, childhood immunizations, breast cancer screening, cholesterol management for patients with cardiovascular condition, etc. measure the actions taken by healthcare providers to improve health. Joint Commission measures also evaluate the inputs leading to healthy outcomes. Readmission rates are an example of measurements of the results of those actions in terms of whether the inputs worked the first time. Analysis of these results will lead to further analysis of the inputs that led to a readmission, or better yet, to the inputs that prevented a readmission.

This means that clinical performance measurement will come full circle. In doing so, clinical performance measurement will mirror financial performance measurement. No business would have its financial analysts measure investments or operational activity without evaluating them in terms of the results on the bottom line. Nor would that business simply report the financial results without a thorough analysis of the causes for those results. We take this for granted in financial management. We will now be seeing more of this cause and effect analysis in clinical performance management as well.

Impact on Business Intelligence Initiatives

This will have two key effects on business intelligence programs for healthcare providers. The first will be more analysis of the readmission results in order to support reporting such as:

Or for those hospitals that are not doing as well, to prepare a defense:
The second effect will be an increase in the analysis of the causes of readmission rates in order to reduce them. This analysis will involve hospital processes, medical interventions, patient demographics, and further analysis of post-discharge patient actions, etc. No stone will be left unturned.

Next Steps

Use the data you already have to understand both the causes and the results of your hospital services in terms of readmission rates. Analysis and reporting of this measure are only going to increase in both quantity required and complexity of the metrics. And this measure and measures like it will increasingly be linked to reimbursement and revenue.

Thanks for reading!

SOURCE: Readmission Rates: A Step Toward Better Healthcare Business Intelligence

  • Scott WanlessScott Wanless

    Scott is the Healthcare Analytics Director for Cipe Consulting Group. He has more than 30 years of experience in business intelligence strategic planning, analytics application development and business analysis across numerous industries including hospitals, physician groups, healthcare payers, laboratory research, insurance, lending, manufacturing, retail and state government. Scott can be reached at

    Editor's note: More healthcare articles, resources, news and events are available in the BeyeNETWORK's Healthcare Channel featuring Scott Wanless and Laura Madsen.

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