With the healthcare industry shifting from the fee-for-service model toward pay-for-performance value-based care, it is critical to begin understanding patients, the care they receive from your organization, and the social determinants they face at a deeper level than ever.
With more and more data available to healthcare providers, it’s difficult to know where to begin sourcing data for your population health management program—especially in the early days of program creation. However, choosing the right data to start with is critical to getting the fastest results from your program and demonstrating its value to stakeholders. Here are the data sources we suggest getting started with.
It’s no secret that technology and data have rapidly become a provider’s most powerful tools for reducing costs and improving care.
If you help make decisions about which vendors your business hires, then you should be familiar with Gartner’s Magic Quadrant. Magic Quadrants offer one-to-one vendor comparisons outlining strengths and cautions for each, as well as insights into overall market status.
Continuing our Tableau learning series (click here to start from the beginning), you've created a view of your data broken down by some basic categories and sub-categories. You are starting to get somewhere, but that is a lot of data to sort through. You need to easily find interesting data points and focus on specific results. Well, Tableau has some great options for that!
Continuing the theoretical request from the last blog, imagine your manager asked you to look into the overall sales and profitability for the company and to identify key areas for improvement. You have a bunch of data loaded into Tableau and you’ve set out to identify key areas for improvement, but you aren’t sure where to start.
Imagine your manager asked you to look into the overall sales and profitability for the company and to identify key areas for improvement. You have a bunch of data, but you aren’t sure where to start. Here’s how to get your data loaded into Tableau so you can begin searching for valuable insights.
IBM defines data integration as “discovery, cleansing, monitoring, transforming and delivery of data from a variety of sources.” Data integration sounds pretty simple--you take all your data and put it together, right? There’s actually a lot more to those two words.