In July, CMS released star ratings for thousands of hospitals across the country.
Although the ratings aim to give consumers an easy way to compare care options and make good decisions for themselves and their loved ones, the ratings have received negative feedback – from care providers and industry stakeholders, and even from members of Congress. With the consumerization of healthcare gaining popularity, it is understandable why CMS believes this ratings system would be helpful. Consumers have options when it comes to where they receive care, and they want an easy way to determine the best choice, just as they can gauge the best restaurant or hotel from a simple rating.
However, there is a big problem with treating your healthcare in the same way as a hotel or restaurant: boiling down quality to a star rating is not likely to give you an accurate view into a hospital or health system, and there are a number of reasons why not. In fact, there is one inherent underlying problem that exists with the star ratings and others like it: they are based on the erroneous assumption that the data used to calculate them is accurate and complete.
Hospitals are under enormous pressure to not only provide quality care, but to also achieve top rankings. The best way to showcase this is through documentation. However, as mentioned before, many of the CMS star rating calculations are based on billing data (not clinical data as people might think), and that is not always correct or complete. There are three key variables that impact the way patient data is collected and managed that can ultimately affect these ratings:
• Healthcare data is typically episodic – Most patients come to the hospital to be treated for a certain condition or complaint, but they often have other ongoing health conditions. If data about their other conditions is not available or just not documented at the time of that one intervention/visit, it is typically not entered into their chart and will not be captured in the billing data. This causes a patient's information to be measured separately from event to event, rather than following a patient throughout their whole journey. For example, if a patient goes to the ER with congestive heart failure, that information will get documented, but if the patient also has diabetes and has had renal failure in the past, that may not get noted in this episode. Those other conditions very much impact the outcome and severity of the patient.
• Differences in coding – Different people can look at the same information and come to different conclusions. Meaning, coders do not always interpret documentation in the same way. The major issue here is the fact that physicians usually document with a clinical mindset, while coders focus on billing, so there is often a disconnect on which diagnoses are captured that impact Diagnosis-Related Groups through ICD-10. This leaves things up to interpretation at times when the coder does not understand what was intended by the physician, and the physician does not understand what information is important to the coder. Unless this is clarified then accurate capture of the diagnosis may not make it to the final coded bill.
• Not capturing data correctly at the front end – Incomplete documentation that may result from how information is entered into the electronic medical record can cause confusion and leads to inaccurate records. Correctly capturing patient information at the front end of documentation allows physician notes to depict a patient's conditions, including severity, more accurately. Without this, coders do not have clarity into what variables are causing skewed information. The earlier in the process documentation is correct and complete, the better it is for care and quality measures in the long run.
Looking past these variables and their impact on the data, there is also another point about these ratings to take into consideration. Boiling quality down to the star rating system of today negates individual items that are important to different consumers when deciding where to go for care. Averaging out quality across different areas does not paint a true picture of the care a certain hospital provides. For example, certain hospitals could be average in patient experience, yet exceptional in mortality ratings, but these ratings do not distinguish which is which because they are taking information about different measurements, grouping it all together and then averaging it out. Consumers may be misled by a high rating, assuming that provider will deliver the best care, but they cannot know which end of the scale is tipping it towards that higher rating and if that end aligns with what they want.
Unfortunately the star ratings, and others like it, have oversimplified things to the point where it may be misleading. They do not provide the level of detail that consumers need to make informed decisions about their care, leaving them unable to distinguish what kind of care they will get from one hospital versus another. Better documentation is the path to helping give consumers a clear picture of their care options. If the healthcare system can understand the important role complete and accurate documentation plays in the way care is reflected, star ratings could someday become a real way to judge hospital systems.
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