Healthcare Data Is Your Organization's Crystal Ball

Haley Mullins, Quality Improvement and Outcomes Engagement Manager

You have access to healthcare data everywhere you look. It's coming at you from all sides—your EMR, various payers, the EMRs used by other systems your patients come from, and each of your vendors. The sheer volume of data at your fingertips can be a blessing and a curse. But when you harness its power and use only the data you need, your organization can predict the future—and change it for the better.

Don't be overwhelmed by mountains of healthcare data. By understanding your end goal ahead of time, you can avoid the dreaded "analysis paralysis" and use just a small fraction of that information.

  1. Establish your QI goal

    When designing a quality improvement (QI) project (or setting any goal, for that matter), the key is to begin with the end in mind. What do you want to achieve? Who do you want to help? When do you want to achieve your goal? Be as specific as possible. It's easy to fall into the trap of setting a goal that's too broad—after all, if you cast a wide enough net, you're sure to catch something. But will it be what you were trying to catch?

    Focusing on one specific outcome, such as increasing HCAHPS scores, allows you to direct all your resources at it, which increases your chances of success. And knowing exactly what you want to achieve will help you decide which metrics to measure. Trying to measure and influence multiple aspects of care with one QI project can be tempting, especially to the people in your organization tasked with finding the money for your project. But if you spread your resources too thin, you risk failure on all fronts.
  2. Decide how you'll measure your progress

    The next step is to break that larger goal into smaller measurable milestones you can use to judge your progress along the way. After all, you don't want to wait until the very end of the project to find out whether you're moving in the right direction. You also need to decide how you'll know when you've reached that goal.

    Data-analysis types call these "lag measures" and "lead measures."
    • A lag measure shows whether you've achieved the goal. It records what has already happened.
    • A lead measure tells you if you're likely to achieve a goal. It predicts the future.
    Let's use increased HCAHPS scores as an example. In this case, higher patient satisfaction scores would be the lag measure. Instead of waiting to receive the scores, however, you could track measurements associated with higher patient satisfaction. Since several HCAHPS questions center on how well patients feel doctors and nurses communicated with them, you might choose to track metrics related to communication.

    One way to measure communication is to track how often your patients receive educational content. This becomes your lead measure. Patient education helps clinicians communicate and build trusting relationships with patients, so it follows that using this material more often should increase patient satisfaction scores.
  3. See where you've been and where you're going

    Tracking lead measures lets you evaluate your intervention and adjust your efforts as needed. For our HCAHPS scores example, you would establish a baseline by finding out how often you gave out patient educational content over the past 6–12 months. You could then compare that with your HCAHPS data from the same time period and quickly see whether there was a correlation between your scores and your utilization of education.

    Once you begin your QI project, you can track your lead measures right away, which lets you pivot or step up efforts when necessary. For example, if you notice that specific departments show a dip in utilization, you can correct the issue immediately.
  4. Share the results of your QI project

    The ability to show your results to other colleagues and departments is one of the most important parts of any QI project, but it can also be the most difficult. Plugging your data into charts, graphs, and presentation software can help you prove and communicate your findings to the rest of your organization.

Parkview Health's Vicki Maisonneuve and Healthwise's Marta Sylvia hosted a live webinar detailing a Parkview Noble initiative that used data to connect patient education to outcomes. Watch the webinar to learn more about how you can launch a successful QI project with your own healthcare data.