Healthcare Training Measurement: Learning & Data Ecosystems

In this three-part blog series, we’ll look at the tried-and-true steps to utilizing learning analytics to measure the effectiveness of your healthcare training programs. Specifically, we'll look at the importance of getting data from your learning ecosystem to power measurement, where you can get started in measuring learning impact in your organization right now, and how other organizations are leading the way.

Are you utilizing the vast amount of data you already have to empower your team, relieve executive and administrative pressure, and make colleagues’ lives better? Insights from big data—or more to the point, valuable data—is within reach; you just need to identify the data, cleanse it, aggregate it, make sense of it, and distribute it. Sound daunting? You're not alone.

You Already Have a Learning Ecosystem

It isn’t possible to talk learning analytics without a clear understanding of available data. Healthcare systems are no stranger to ecosystems in general, nor to measurement and analytics. The spider web graphic in Figure 1 shows the types of measurements within a typical healthcare system and where/how they’re already taking place. Of course, L&D isn’t responsible for all of these areas—but everything is interconnected and L&D touches training and development on each of these areas.

©Datavant

The first step in your learning analytics journey is to gather the data. More to the point, recognize that you have a learning ecosystem, which integrates with all functions in the broader organization. Then you can begin to gather the data generated from the components within that ecosystem.

Beyond learning data, organizational performance goals and KPIs are usually established and documented in systems that exist in an organization. These performance systems typically are housed within or interface with your human resources management system (HRIS) or your enterprise resource planning (ERP) system—both of which help make up an organization’s ecosystem. A typical learning ecosystem is often composed of:

  • a learning management system (LMS),
  • a learning experience platform (LXP),
  • HRIS/ERP systems
  • assessment tools,
  • SharePoint sites,
  • video portals, and
  • anywhere else someone goes to learn or complete training.

Whether you’re exploring patient satisfaction surveys and contemplating how you can influence your team and improve the numbers or looking at how incident reports affect the bottom line, you and your team have influence on these measurements.

By understanding your ecosystem, you’ll have better visibility not only into your programs, but you will also provide better visibility of the value L&D brings to other parts of the organization.

Let Your Data Mix and Mingle

Once you establish the components of the ecosystem, you will find that the data generated by these systems is siloed. One Watershed client likened these siloed data sources to patient data in an EMR—where pieces of healthcare-related data get scattered across disconnected clinical, research, administrative, and financial software systems.

The result is a hodgepodge of information that originates outside of the established system—such as lab tests, medications and other procedures—and they’re not always incorporated into the primary record. This prevents everyone on the healthcare team, and the patient, from having the benefit of the big picture.

Data silos make it difficult to identify and address important trends, whether it’s specific to L&D or personalized healthcare. The result can be passive, frustrated, uninformed patients who don’t have the tools they need to be proactive, so they wait until they get sick before taking any action. This example may also be likened to the state of your employees.

Once you’ve identified where and how data is stored, the second step to getting started with learning analytics is “getting to know your data.” You’ll now need access to all this data, and you’ll likely want to combine this data so reports are comprehensive and make sense. That can mean submitting support tickets to access reports, combing over CSVs to create spreadsheets—or using a learning record store (LRS) to take the brunt of that work.

Up Next: Quick Wins for Your Learning Analytics Journey

So, this looks nice in theory but you might be a bit overwhelmed. Rest assured, it is happening in the real world. In my next blog post, we’ll explore ways you can score some quick wins in your learning analytics journey.

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