What does it take to be a data-driven practice?

As value-based payment models become increasingly prevalent across the country, more healthcare systems and practices are participating in risk-laden contracts. Being successful in risk contracts requires practices to make many changes, including changes to workflows, staffing composition, approaches to patient engagement and physician compensation models.

One of the most fundamental changes required for success is for practices to truly become “data-driven organizations.”  This is a term that is commonly applied to non-healthcare companies and organizations, and in that context, much is written about what it takes to become a data-driven organization. In a recent Upside article, the author outlines characteristics of data-driven companies. These characteristics include: 

1. Creative executives who run their businesses with passion and curiosity. 
2. A company culture that incentivizes and fosters the use of data and data-driven decisions.
3. The support of free unencumbered access to data across the company. 
4. Data literacy, which entails providing robust data skills to all members of the organization.
5. The ability to automate the integration of data insights into all company workflows.

I believe we are making great strides in creating truly data-driven healthcare organizations. Leadership teams in healthcare have always led with passion and a strong sense of mission, and many are now rapidly realizing that rich multisourced data is essential for their success. Creating practice- and organization-wide culture shifts is a slow process, particularly in the healthcare industry where there is still a strong tendency to do things a certain way because “this is how we always have done it”—in spite of having data that points to the need for a new or different course. Many systems still have much of their revenue coming from fee-for-service payment models where data is less critical and success is guaranteed as long as volumes of care are maintained. 

Creating unencumbered access to data across healthcare organizations poses many challenges. The first barrier was historically the absence of structured data that could be accessed. This was remedied with the broad implementation of electronic health records, but this after all is a relatively recent change. Now that structured data is broadly available, the complexity and heterogeneity of the data, along with the need to fiercely protect the privacy of the data, at times encumbers and slows access and flow of data within healthcare organizations. It is not unusual to encounter healthcare systems where data is segregated in certain domains in the organization with limited access to the data across the rest of the organization. 

Data literacy is a work in progress universally, this is true for healthcare systems as well. There are certainly members of many healthcare teams with highly evolved data and analytics skills, but in many organizations, there is work to be done to further train broadly all care and administrative teams. As for the ability to automate and integrate data insights into team workflows, this is actually an area where the healthcare industry has made great strides. With the deployment of advanced, integrated population health analytic platforms like the NextGen Population Health platform, clinical teams can now access at the point of care many powerful population health insights, such as gaps in care or patient risks that drive data-driven decisions and workflows. Clearly, this is an area where we have made great progress. 

Considering that as an industry we have had access to structured data only in the last 20 or so years, we are making great strides to becoming a data-driven industry, and the shift to value-based care is accelerating this progress. If all goes well over the next few years, we should have a lot more data to support this assessment