What is the “Mortality Index” and Why Should I Care?

Have you ever wondered if your facility is especially good or bad at taking care of certain patients?

You’re not alone. I’ve talked to professionals across the nation, and this is a common concern – particularly when burnout sets in. When you study errors all day, you may even start to wonder if your facility is worse than every other facility.

I recently complimented a colleague at a local facility for having fantastic scores on infection control and sepsis treatment. Those scores are published on the CMS website, but my friend was surprised that they were performing well. They scored the best CLABSI and CAUTI management rates in our area, but even attentive employees had no idea they were doing a good job.

Sometimes, it’s just hard to get perspective on these things. That’s why we try to sample data to get an idea of where we stand on performance. But how do you account for all those individual characteristics and unique variables? How can someone really “sample” death rates, for example, when no heart disease patient is alike?

This predicament of sampling data is one of the reasons why the Mortality Index was created. With a Mortality Index, patients could be compared to similar populations by diagnosis and risk (an equal standard). There are many “really sick patients” in hospitals but being sick should not necessarily lead to death. 

When we study mortality, we especially want to know if a death was likely to happen anyway, or if the quality of care affected the outcome in some way. 

The Mortality Index is one way to determine if quality of care needs to be investigated when a mortality occurs; it considers whether a death was expected and includes a risk adjustment for underlying health issues and the likelihood of a terminal outcome. 

Specifically, the Mortality Index is a ratio of deaths actually Observed against the number of deaths Expected for the patient’s age (O/E) and risk of that population. A perfect match between actual deaths and expected deaths would be an index score of 1, and a ratio of greater than 1 is considered an excessive mortality score.

For example, a Mortality Index ratio for someone whose cause of death was a stroke might be 1.17 if the patient had no other problems—meaning observed deaths were greater than expected and the patient was not expected to die. However, the Mortality Index ratio might be 0.98 if most stroke patients also had blood pressure problems, diabetes, kidney disease, and a recent terminal lung cancer diagnosis to indicate the death was expected. 

By measuring this way, hospitals are not penalized when they treat “really sick patients” with deadly illnesses because the population and context is weighed against the occurrences of death. When the Mortality Index ratio is greater than one, hospitals should review mortality cases individually and look for reasons the mortalities occurred, looking for any adjustments and opportunities to improve patient care.

So next time you have a chance, check out your CMS mortality index scores. You might be surprised by what you find.