Data-driven healthcare is only as good as the data used to drive it.
The introduction of data to the delivery of healthcare is a good thing, allowing for better tracking of trends among patient populations and leading to quality improvements in various clinical areas, such as hand washing prior to surgery. Moreover, data as part of care delivery has been around a long time, though in recent years there’s a trend toward putting it in the driver seat. This trend has been partly due to the need to control cost and improve quality outcomes, but is it working?
Last year, I was asked to write an academic paper on the use of genomic data within electronic health records (EHRs). I was amazed to find out that this data is often obscured or hidden in some way, making it less than effective for the practice of some areas of medicine. This process led to a couple of questions in my mind:
- If only data directly related to cost and outcome quality is being tracked, and therefore managed (we know what is measured is what gets managed), is this the best use of data?
- What good is the data if the practitioner cannot locate it?
I love data, and I think most of us go into informatics because we love data. I love using data to make healthcare better, I’ve said before that my dream job is to drive healthcare innovation by using data to create actionable recommendations. Yet, I wonder if we are shortchanging healthcare providers and consumers by not fully utilizing the data being produced?
This is an interesting time to be working in healthcare informatics. There is no shortage of problems to solve, which begs the question, can we find a better way to use the data? I believe we can.
Let’s examine the questions above:
The second question is easy to answer, if the practitioner cannot locate the data when it is needed, the data is useless to him or her. Measures need to be taken to ensure the data is able to be located when it is needed. This is true for genomic data in addition to other types of data related to patient care.
The first question is more complicated: What types of data are the best types to track? This really depends on the context, everyone has different ideas and needs related to data management. For instance, laboratory data can be used to track a lot of different things in an organization, including surprisingly, financial information.
Data needs to be analyzed in a manner that allows it to be understandable and useable to the consumer of the data. Often it sits in a repository getting stale, but there’s so much more that data can do for healthcare if we unleash its full potential.
Let me ask you readers, what kind of innovation can data bring to your healthcare organization?
Rebecca Fein is the informatics researcher at The Laboratory Informatics Institute, a non-profit organization dedicated to improving the laboratory informatics industry through education, publication, and advocacy.