Confusing utilization and quality

By | January 17, 2017

Value’s variables often affect each other

Value has three variables: quality, service and cost. Many times we confuse one of these variables for the other. As these different variables each affect value differently, it’s important to understand what activities falls under each variable and how they interact. For example, we want to increase quality and service while decreasing cost, but there can be situations where decreasing cost can lead to decreased quality or service and vice versa.

I read a great article in HealthLeaders by John Commins, Hospital Readmissions are Not the Enemy, discussing this exact point as it relates to hospital readmissions. At the heart of the study discussed was the finding that readmissions did not have an impact on overall mortality rates. What was more important concerning the conversation was the discussion around how readmissions should not be viewed as a quality metric. Instead, it is a utilization metric. Length of stay could be viewed the same way, and there are those that say increasing length of stay could lower readmissions and overall costs in a manner that is quite cost effective. The last day of admission is by far the least costly from a utilization standpoint, and if many of the social issues can be addressed during that time, better care can be delivered post admission.

My point is not about lessening focus on readmissions or length of stay, but making sure that when we focus on these issues, we realize which part of the value equation we are addressing. There are multiple correct answers, but they are dependent on each other, so there is not one correct answer.  We must continuously strive to manage these polarities if we truly want to increase the value we deliver.

Spending more time defining which variable we are impacting will help us understand and manage the dualities that we live with every day. By looking at it from this standpoint, we will be able to better design balanced scorecards that measure these within the dynamic of their relationship to each other.  We will be able to better see if we are turning one dial too much in a certain direction that causes another dial to spin in the opposite direction, and be able define causal effects more accurately and adjust our models accordingly. We need to continue to strive to improve what we are doing through innovating, learning, and being open to the voice of those we serve.