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Transitioning Health Data into Performance Improvement

Transitioning Health Data into Performance Improvement

A question I often hear is “How can healthcare data help me reach my performance improvement goals?”

There are two seemingly different challenges that come together in this conversation. First, healthcare providers have systems and devices that collect tons of data — including information from call systems, patient portals, EHRs, practice management systems, financial systems, and survey tools. However, for the most part, most of this data is hidden, inaccessible, or meaningless.

Second, healthcare administrators often have lofty performance improvement goals, such as increasing productivity, revenues, and profitability, while decreasing costs — all while maintaining patient satisfaction. How can these two focuses converge in a way that makes sense? The answer lies in understanding the relationships between data, information, knowledge, and insights.

Analyzing the Mileage Problem

Recently, I needed to buy a new car and one of my goals was to find one that achieved better gas mileage. When I purchased my last car, I was promised decent gas mileage but was very disappointed when my actual results were far worse than advertised. I learned at that point not to listen to the estimated mileage proclamations by the car manufacturers.

After evaluating dozens of options, I purchased a car model with the dashboard feature that provided instant access to the miles per gallon based on real driving results, although I still had no idea how it would actually improve my mileage.

As I started driving the new car, it provided me exactly what I was looking for — constant updates on my current mileage. I know that my car collects hundreds of data elements under the hood, but for the first time, I could think about how my driving habits may change my results. This is an example of how raw data collected by the car’s computer was presented to me as information, allowing me to ask more questions.

Over time, I learned a few things that I could do to improve my gas mileage — things like no longer gunning the engine when the light turns green, especially going up a hill, as well as lightly “feathering” the accelerator on flat or slightly hilly surfaces. I soon realized I was gaining knowledge from the information put in front of me — a subset of the data the car captured.

At this point, I had new knowledge of how my driving habits affected my gas mileage, but nothing was going to change until I actually changed the way I drove. This last step was uncovering the insights that were helping me achieve my goals of improving my gas mileage. As I implemented these changes, I could also keep an eye on my results over time to validate that my driving modifications were indeed consistently producing the desired results.

Translating this into healthcare

Today’s healthcare practices are experiencing this same challenge of data being lost in translation on the way to insights. Practice owners, administrators, and clinical leaders have dozens of software platforms and systems to manage their activities and track work processes, but unfortunately, they spend all their time putting data into those systems and get very little tangible benefits out of them. It is quite likely my last car had monitors capturing all the data I needed to learn how to get better gas mileage, but it was what I’d consider a “closed system” and did not present the information to me in a way that I could easily understand. The data was just not actionable.

In order to access the right actionable insights, healthcare leaders must find new ways to liberate that hidden data and value from their various IT systems.  Once the relationships between data, information, knowledge, and insights are clear, practices can begin to unlock the hidden value from existing systems and meet those lofty performance improvement goals.

 

About the author

Wallace Simpson works with WhiteSpace Health customers through the implementation stages and into the identification and execution of improvement efforts, often through process optimizations. He has deep business operations process transformation experience, and his passion is to help organizations standardize and improve how things get done to maximize efficiency without sacrificing quality. Over the last twenty years while at Microsoft and other Fortune 500 companies he implemented and taught hundreds of IT professionals service delivery and project management best practices.

 
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