Retailers have vast access to data. They use it daily and in real-time to connect meaningfully with customers and provide a customized experience. Amazon, for instance, is able to predict when customers are going to make an order.
Imagine if instead of automating a prompt like, “because you purchased this book, you may like this one,” we could know in real-time “because you have this specific patient history… you’re at greater risk of x, y and z.”
Unfortunately, healthcare has a way to go before we offer patients a similar experience. The good news is the data we need is there.
The challenge is to capture it accurately and make it accessible for real-time analysis.
Here are the ways we see that the industry can overcome the challenges or make data more useful:
- Collect a sufficient data set. It’s not unusual for health systems to find themselves drowning in a sea of data they don’t know what to do with. What we find is more prevalent is a data set that is not large enough to produce conclusive evidence.
- Ensure data sets are being completed. When fields are left blank, correlations can be affected, invalidating results.
- Hold data in a uniform and consistent way. You need discrete fields in order to turn data into insights.
Of course, planning and getting data sets right from the beginning are critical. (Stay tuned for our upcoming white paper on the very topic!) Data becomes ineffective when you change course in the midst of the process, risking the consistency of your data collection. Your research staff and/or data registry partner should guide you through that process. Spend this time on criteria up front.
If you’ve had similar challenges and would like to discuss, we are happy to answer your questions. Contact Us now.