As a longtime HIMSS member and active participant in the Southern California HIMSS Chapter, my article, “A Journey to Self-Service Analytics,” was published in the SoCal HIMSS Q3 2017 Newsletter. The blog, also posted here, reflects on the transformation healthcare has been undergoing with data management and the journey to effective data governance and self-service analytics. You can read my piece on this page below, and you can check out the newsletter for other great articles on analytics and upcoming SoCal HIMSS events.
A Journey to Self-Service Analytics
We have gone from no data to EHR data to big data all while healthcare is undergoing a transformation from paper-based fee-for-service to value-based care in a digital ecosystem with advanced analytics. Additionally, the rise of ACOs, population health, mergers/acquisitions, and other risk-based initiatives are putting focus on data decision making that ranges from revenue cycle management to precision medicine. Because of these reforms, we now have the digitalization of the patient record and a new wealth of data. This data is growing and encompasses not just health data but other behavioral data from both internal and external sources.
Getting off paper and moving to digital records was a quantum leap forward. Conquering data management is the next frontier. This will require establishing a data culture within the organization with new data governance and processes. It is becoming more apparent that we can’t achieve value-base cared without value-based data that has the integrity to be used for critical decision making. You can have the most advanced analytic algorithms that produce the most advanced mistakes if you’re using bad data. Properly managed data and simple analytics can be far more effective in making sound, evidence-based decisions than using bad data with next generation analytics.
Paving the way for advanced analytics
On the road we’ve traveled, governance and process represent imposing restrictions. To achieve advanced analytics, we must pave a new road where governance and process empower and enable access to data, not restrict it. Getting the right data in the right hands at the right time requires empowering federated governance. A federated data management approach ensures the right people manage the data they are responsible for with the purpose of sharing it, not protecting it.
To improve the governance, organizations may have to break down siloed organizational structures and fragmented workflows that create data disparities between departments and systems. Moving past those roadblocks may require addressing organizational culture and data hoarding that contribute to long-standing issues around poor data quality, poor documentation and a lack of data consistency across sources. It also requires enabling the analysis by business users who have the right subject matter expertise to fully leverage the data for quality analytics. This approach ensures the person closest to the problem (i.e., researcher, physician, or informaticist) has easy access to the data and the tools that allow them to benefit from self-service analytics.
A new data management approach
When businesses need to change, they now look for data as empirical evidence that supports the best strategy. Looking to the future, I envision more and more healthcare organizations will become better at using properly managed data as well as big data lakes, and they will move from basic reporting to more integrated and shareable data that allows for advanced predictive abilities with cognitive machine-learning capabilities.
To date, end users are feeling overloaded by unmanaged data. They need it presented to them for quick actionable insights in the moment. This is where cognitive analytics can provide smart data targeted to the healthcare need. For instance, physicians may have access to the data, but they can’t use the data because they don’t have time to mine it. Our care teams need access to the right data without having to hunt it down.
A holistic approach to the processes and governance needs to be used. Under the federated structure, data is a shared responsibility. While different departments and roles can manage their parts, there is still an overall unity of standards that keeps the data management glued together. This unity and freedom gives teams the tools they need to act together while making innovative targeted decisions based on individual areas of expertise.