Administrators Will Focus Less on Describing and Admiring the Problem and More On Prediction and Prescription of the Solution

By Sanjeev Agrawal, president, LeanTaaS.

Everywhere, everyone is building dashboards: Tableau reports, Excel spreadsheets and others. To paraphrase many hospital leaders I meet: “We’ve spent tens of millions of dollars on an EHR implementation. On top of that, we have invested a lot on reporting capabilities; we have lots of dashboards throughout the hospital to keep track of everything. And teams of people dedicated to BI, reporting, data visualization, ETL, and custom report generation. How can we leverage this investment to improve operational performance?”

The issue is we often “admire the problem” and end up with results that aren’t too actionable, resembling what you can do by looking at yesterday’s weather. As an example, for operating room performance, most health systems can track room and block utilization and drill down to individual surgeons to see their metrics: utilization, first-case on-time starts, turnover time, etc. However, making the metric visible isn’t the same thing as improving on it. If a surgeon’s block utilization is, say, 53%, what can we do about it? Can we take away 47% of his or her allocated time? No. Let’s say, hypothetically, that we eliminated all first-case delays. Can we really reclaim those pockets of time and put cases in them? Not likely. So, what exactly is the purpose of measuring block utilization?

Going forward, hospitals will need to go beyond dashboards and describing or diagnosing the problem and actually predict what’s likely and prescribe the action they can take in a data-driven and defensible way. For example, in the above scenario, imagine looking at truly repurposable portions of time being left on the table by block owners; taking into account past case volume and mix, seasonality, and other key factors to predict which ones won’t need all the time allocated; and being able to produce the type of “prescription” that is surgeon-centric and data-driven as well as fully defensible.

Data will drive action based on prediction and prescription — much like Waze, Uber surge pricing, and so many other real-world examples that we all use in our day-to-day lives.

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