Data are Cold and Dumb: Make Them Smart Please

Ever met someone who seemed both ‘smart and dumb’ at the same time? Like someone who is ‘book smart’ but ‘real world na?ve?’ Like they’re the one who can solve a complex physics math problem but can’t seem to be on time to a meeting?

That’s what’s going on in the world of data.  I work with ‘tech-entrepreneurs’ who are thrilled by their abilities to create new sources of data, which can then be bundled into bigger data sets, or conversely, carved-out to make micro data sets, yet these same (very) smart professionals seem unclear how to use all this ‘new gold.’ And data are gold…but even gold needs a marketplace to be valuable.

Discovering new sources of data, creating new data sets are ‘all the rage’ now in many industries, including healthcare. In healthcare everyone talks a lot about ‘population health’ and being able to predict which age group might get diabetes or heart disease, which patients are on medications for multiple conditions, which population cohort is at risk for Alzheimer’s Disease, yet very little is mentioned about how to convert these data into real-world patient improvements.

Recently I heard an expert from Capital One Financial talking about how the amount of data doubles every 18 months. Back in the day when doctors and nurses got their ‘new knowledge’ from journals and conferences, even that rate of new information was too much to get absorbed into actual clinical practice.

In fact, it takes, on average, 17 years for a new discovery or proven medical evidence to make it to the clinical bedside. Another way to say this is that it takes 17 years to move from ‘bench’ to ‘bedside.’

An example of what this means is, even though the evidence showed patients who have a heart attack have a higher survival rate when they are given one baby aspirin, it took 17 years for doctors and nurses to do this routinely.  And even now, on average, providers follow these ‘best practices’ only about 50% of the time.

And in today’s universe of data doubling every 18 months, it’s no surprise that there is a growing gap between ‘what is known’ and the actual meaningful utilization of those data to improve healthcare.

So, the presence of data does not create insights, impact or improvement. In fact, a big mistake I’m seeing in the market place right now is misconstruing data for knowledge. Data does not create knowledge—nor does it create insights. And do not conflate availability of data with transformation or change.

What creates improvement is a steady ‘change management cocktail’ of three ingredients: insight that change is needed because the current state is inadequate or failing, motivation to disrupt the status quo, and the stomach to ‘walk the work’ for a long time.

At an individual level for example, the ‘change equation’ looks like this: Imagine someone you know who smokes but does not see a real big issue with this despite every single evidence showing that smoking creates lung problems and shortens life. In the presence of overwhelming data, no change will happen here because the individual doesn’t perceive the ‘current state’ to be a problem, therefore no change activities can occur. The missing ‘cocktail ingredient’ here is the first one: a lack of insight that there is a problem needing to be fixed.

At an organizational level, the ‘change equation’ looks like this: The hospital you work at has higher than average infection rates and the executive team realizes this is a problem but lack the motivation to change the physician practices to realize the improvement. They don’t want to ‘walk the work’ because it might irritate the doctors and nurses if you change some protocol. Here the missing ‘cocktail ingredient’ is both the second and third ingredient of not having the motivation to create the disruption and lacking the stomach for change.

While data are the very oxygen every organization needs to live, data are cold, flat, two-dimensional and they need warm ‘enablers’ to come alive—to become purposeful and three-dimensional.

Data need to be in service of a vision. And to thrive, visions need improvement goals which have a strong governance structure, clinical workflows and targeted success metrics. And all this must be powered by change management.

In this ‘manifest destiny’ to reach new frontiers of bigger data, we can’t forget that data are in service to something else…Data always serve a higher master. In healthcare that’s patient engagement, healthcare quality and safety and provider effectiveness.

About the author: Julie Kliger is recognized by LinkedIn as a "Top Voice" in Health Care in 2015 & 2106, & 2107. She is a Healthcare ‘Strategic Realist’ who is passionate about improving health care and improving lives. She specializes in future-oriented healthcare redesign, optimizing existing operations, implementing new care models and strategic