Thu, 07/26/2018

Rather than think about how we tackle data issues for population health, value based care, AI, and predictive analytics, healthcare organizations need to think about what their data strategy is and what platform should be used across the entire enterprise.

Organizations need to take into account data sources, volume, and usage that will be growing year after year. Due to the increased volume, data analysts, who want to use data for impactful change, are really data jockeys, spending more than 80% of their time preparing data for projects.

For data to be most helpful, it must be integrated quickly and at scale from a diverse set of sources, such as: legacy applications, machine data, spreadsheets, web services, user generated data, and more. This data then must be mastered, cleansed, harmonized, and prepared for analytical use. This process seems straightforward, but it not happening enough.

Some of the reasons why healthcare organizations aren’t tackling data as an enterprise issue are:

  1. They all want to continue to use their existing EHR systems, in which they have invested millions of dollars. They hope the EHR will figure out the data and analytics issues on their own.
  2. The landscape is filled with HIE and population health vendors that are struggling with the data challenge.
  3. Healthcare organizations have by and large under-invested in both the talent and the platform to make enterprise data and analytics a core capability and competitive advantage.

Our partner, St. Luke’s University Health Network, has had great success implementing Omni-HealthData to take a truly enterprise approach to data management by combining over 50 data sources. The story of how St. Luke’s underwent a journey to make enterprise data and analytics a fundamental competency of the organization leads to major questions from healthcare organizations who are struggling with contemplating such an approach:

  1. How do you justify the investment by defining ROI? Once you embark on an enterprise approach to data and serve it out widely into the organization, every program and decision can start to be traced back to data and analytics from the project. So separating the value from the underlying data infrastructure and the care and quality teams doing good work becomes difficult.
    1. Is there any Hard ROI to be found? Yes. When you look at an enterprise healthcare data management platform like Omni-HealthData its capabilities include a number of technologies that are probably under consideration somewhere in the organization already or are already costs within an organization.
    2. How about Soft ROI? Ideally with an enterprise approach to data and analytics the flow and adoption of leveraging data will become pervasive in the organization. St. Luke’s looked at 7 key areas where they could define a 5-year ROI through better use of data. The 3 key buckets are improving care, reducing costs, and improving market share. IT management works hand-in-hand with the business so that even the on-boarding of data is prioritized by business impact.
  2. How do you start looking at an enterprise approach to data with all the competing use cases and needs in an organization? In most healthcare organizations there is an employee that is leading data and analytics efforts, but often they are focused on a smaller day-to-day outlook. It’s a challenge to both take an enterprise approach to data and analytics while struggling to support current requests. At St. Luke's support for their project started with their CEO who led the way by proclaiming data must become an enterprise asset. Business sponsors who believe that a commitment to an enterprise approach to data management is essential to change must be found.

The final takeaway is that it’s not easy to break free of the EHR inertia and commit to an independent enterprise approach to data management and analytics, but the rewards can great. So, go out there and break down those silos.

For more information about St. Luke’s and their success with Omni-HealthData, read our story.