I want to dispel a common myth: the myth that there is not enough data or enough of the right data to accomplish meaningful clinical improvement. The fact is we have enough data to reach the ultimate pursuit: reducing clinical variation and improving quality at the same time.
The key is having the right amount of the right data. This means having data that is transparent, comes with the ability to drill down substantially and includes comparable benchmarks.
A single source of truth
Health care organizations that choose a single source of truth for their data tend to be the ones reaping the biggest benefits. Organizations that purchase and use parts of a number of different databases and analytics products meanwhile, often find themselves struggling to orchestrate these tools in a meaningful way.
While having a single source of truth is a first step, it’s not the biggest step. The real challenge lies in transforming that data into insights that drive change. This also means the more we argue about data, the less we get to the most important step – change.
Data in and of itself doesn’t motivate change, and this is where technology and people come together. The data goes through analytics tools to provide information, but that information alone doesn’t do anything. It needs to get into the hands of the right people who can add context and understanding, ultimately leading to the insights that when presented to the right people can actually start to motivate change.
The role of data science
There’s been a lot of talk about data scientists recently and how they can help in the performance improvement equation. In fact, they are essential. The movie Hidden Figures recounts the tale of a team of female mathematicians, notably Dorothy Vaughan and Katherine Johnson, who served vital roles at NASA during the early years of the U.S. space program.
One of the women, Dorothy Vaughan, was the only person able to take a new computer at NASA and put it to work in a way that created meaningful information. To everyone else, the computer was spitting out information that didn’t make sense with regard to astronaut John Glenn’s reentry point into the Earth’s orbit. Glenn also knew Katherine Johnson and he requested that she take on the data to ensure his calculations were correct.
In many ways, they were pioneering data scientists who understood that technology is only as useful as the meaning it creates. While today’s American health care system has invested billions in the technology side of data science, we are still lacking in our collective ability to cultivate and develop people who can take that information, turn it into insights and present those insights.
Care improvement requires collaboration
The reality is that improvement is a team sport. If you’re comparing yourself to only yourself and only working within your own organization, you’re not going to get to where you want to be. Comparing and working with other similar organizations is essential to accelerating improvement.
Imagine if you were just given a metric that showed your risk-adjusted cardiology was a red dot compared to 150 other organizations. To me, that is useless. You need to be able to drill down to truly understand why you have that red dot, whether it’s a documentation and coding effort, whether it’s due to complications, whether it’s due to who you’re bringing into the hospital, where you’re sending people, or length of stay by physician.
The bottom line is that organizations must be able to drill into that metric substantially for greater understanding, ideally by engaging in the right data and doing it collaboratively. Having the right data is just a first step. Data plus a change equals information, and the more we argue about data or think we don’t have the right data or enough of it, the farther we get from the most important step – driving change.
To download the white paper, “The Hospital’s Clear Path to Improving Care Delivery,” or to register for the third and final webinar in our Improve Care Delivery webinar series, click here.
