Readmission Rates: A Step Toward Better Healthcare Business Intelligence

Originally published August 4, 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 hospitalcompare.hhs.gov. 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!

  • 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 scott.wanless@cipeconsulting.com.

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

Recent articles by Scott Wanless



 

Comments

Want to post a comment? Login or become a member today!

Posted August 7, 2009 by Scott Wanless scott.wanless@gmail.com

George and Chris.  Thank you both for your comments on the article on readmission rates.  I believe that both of you are right on in that this measure needs to be combined with other measures to make it truly valuable.

If you look upstream from this measure, you find that you need to look into causes such as co-morbidities, infection rates, business processes, clinical processes, patient actions (or inactions), etc.

If you look downstream from this measure, you find that the ramifications of doing well or doing poorly on readmission will have many potential business, financial, legal, medical, operational and public relations impacts.

We are just getting started seeing measures of results such as this.

Thanks again for your great comments!

Scott

 

Is this comment inappropriate? Click here to flag this comment.

Posted August 5, 2009 by George Allen

Excellent article.  I have been seeing just this issue pop up in meetings over the past few weeks at my hospital.  And using the data we already gather is going to help us solve the issue. 

What co-morbid conditions are leading to the readmission?  Are there processes we are using that are not addressing lingering ailments on discharge?  Are there business decisions being made by us, or our payers, that are contributing factors? 

Much like a car company dealing with recalls or high post-sale maintenance costs, healthcare needs to mine the data it already collects, and the business rules it lives by, to ferret out the causes of the problem and to improve its rules and processes to improve patient care.

  

Is this comment inappropriate? Click here to flag this comment.

Posted August 5, 2009 by Chris Cammers

As a quality of care measure the readmission rate is a good start but it should probably be combined with other measures like incidental infection rate. Combining incidental infections with readmission would give us some insight into the "quality" of the initial admissions that don't result in a readmission. If we are to answer the question of quality care then it is important to acknowledge that an admission extended by an incidental infection is no better than one resulting in multiple inpatient stays.

 

Thanks for the article Scott, I really appreciated the link to the database.

 

Chris

Is this comment inappropriate? Click here to flag this comment.