So much potential remains untapped in healthcare data analytics. Transformation is possible in terms of care quality, efficiency, population health and more.
As we continue working toward these big improvements with big data, however, I believe it’s crucial for us to continue making headway on a smaller scale. How can we keep making progress on the ground, where it matters most?
I recently helped lead a focus group of Healthcare CIOs from a variety of backgrounds.
Reflecting on this group and my experience over the past few years, here are five key actions healthcare organizations can take to build and sustain results from data analytics.
1. Ask the right questions for intelligent analytic content
We have data by the truckload. In some cases CIOs don’t want more. The challenge is more about what to make of it all. We’ve got to focus on solving problems that matter. This reminds me of a previous post of mine about big dialogue. We need to make space and time for talking through the issues. Learning how to ask the right questions that can be translated into actionable insights from data is like exercising a muscle, and it often involves big dialogue. What are the dynamic drivers of performance and the business? How are we doing? What is the goal? What exactly do you want to find out and what will you do with that insight? What is the value? Where do we begin? Who are the users and what are their needs? Where will the data come from? Is the data structured or unstructured? The more you do it, the better you get. How are you enabling your organization do this better?
2. Get the right people in the right place
Let’s be honest. As far as the technologies have advanced, leveraging data in analytics still takes people with the right skills, interests and motivation. Building superstar analytics apps that will make a difference requires the right talent and know-how. It’s about more than technical chops. Healthcare IT needs people who are passionate about understanding the many challenges providers are facing (starting with the right questions). Then it takes practical expertise to translate that understanding into real solutions. Whether you build, buy or partner, how will you build this competency?
3. Bring actionable insights to those who need them daily
Management reports and directives from the ivory tower aren’t the answer. We need to extract and deliver insights from data when and where people need help making key decisions. The opportunities are endless, but as organizations look to empower people to act, we must to make sure the solutions are there to help them. It’s important to think of IT end-users as consumers with problems to solve. If you don’t ease their pain, you won’t get them excited about your analytics app, so what are the chances it will be adopted and used?
4. Seize the most visible opportunities for early results
Don’t let perfection be the enemy of getting something great done. While we work on solving big, complex problems with big data, let’s also start to get quick wins by unleashing data where we have latent opportunity and visible frustration. There’s a reason why productivity experts recommend tackling an easy task first. Sometimes, the best way to get started, well … is to get started. Build momentum from the ground up. Get people engaged in meaningful results.
5. Zero in on technical data challenges bite by bite
Just because we have data doesn’t mean we can use the data. There are many challenges around interoperability, silos, data governance and data quality and management just to start. Tackling these issues is critical. But don’t let it delay creating more targeted analytics that can drive results using smaller data sets. These ongoing efforts are natural extensions of many performance improvement programs. Working on these smaller initiatives as part of comprehensive analytics strategy and portfolio can help you proceed in a way that benefits your organization both in the short and long term.