Why Data Governance Requires a Henry Kissinger
The number of mergers, acquisitions, and collaborative partnerships in healthcare continues to skyrocket. That’s not going to change for the next few years unless the FTC decides to be more restrictive. In all of these activities, older generation executives (I can say that because I’m older) have underestimated the importance and difficulties—technically and culturally—of integrating data and data governance in these new organizations, and the difficulties are exponentially more complicated in partnerships and collaboratives that have no formal overarching governance body. In 2014, 100 percent of Pioneer ACOs reported that they had underestimated the challenges of data integration and how the lack of data integration has had a major and negative impact on the performance of the ACOs.
Seamless Data Governance
After 33 years of professional observations and being buried up to my neck in this topic, especially the last two years as the topic finally matures in healthcare, I’m convinced that the role model organizations in data governance practice it seamlessly. That is, it’s difficult to point a finger directly at a thing called “Data Governance” in these organizations, because it’s completely engrained, everywhere. As I’ll state below, it reminds me of the U.S. transition in the early 1980s when organizations finally realized that product quality was not something that you could put in an oversight-driven Quality Department, operating as a separate function. Quality must be culturally embedded in every teammates’ DNA. Data governance is the same, especially data quality.
How to Execute Seamless Data Governance
This week, one of my teammates sent me an email, paraphrased and anonymized below:
“We are headed to John Doe Health Center Network next week to talk to them about how we can help them with analytics/quality improvement. This organization provides managed care services to 8 community health centers in their county and our main champion is fighting for a shared analytics platform. Since they do not own any of the health centers, they are struggling with how to establish data governance with this type of environment (rather than a single entity).
Do you have any recommendations or talking points that we should make clear with this group as to how they may find success with this model?”
Here is my response:
“It’s the soft side of trust and leadership that makes these things possible. The [anonymous] project that I’ve been working on in [another country] has firmly crystallized in my mind that the success of these data-sharing initiatives come from 90% diplomacy, 10% technology; and genuinely finding a way for the contributors of data to the platform to receive more value from their contribution of the data than if that data were not shared.
The facilitator/leader of the data-sharing initiative has to wriggle their way through all the participants’ motives—that leader has to craft a strategy and broker the personal relationships that provide compelling and attractive data value back to each of the participants. The participation in the data-sharing initiative must scratch every organization’s need for increasing the mastery of their mission; increasing the organization’s autonomy to execute their mission without having to coordinate and ask for more permission from members of the initiative; and the data has to feed the organization’s desire to be a part of a purpose that is larger than themselves.
In this sort of setting, you can start by chartering a steering and governance committee that is comprised from volunteer representatives in each organization. Simple things get complicated quickly, but can be solved. For example, who has voting rights on the committee (biggest data contributor has the most voting rights or is this going to be a Senate model?), and who is going to chair the committee that is trusted and respected by all members? Who is going to contribute money to development and operations of the shared data platform, and how are you going to calculate those relative contributions? What are the subcommittees and working groups, and who is going to lead those? Long term, in these settings, you need to plot a trajectory towards creating a separate legal entity and small company that can manage the asset, manage the funding, leverage the asset to the value of the organizations, and handle liability, data commercialization, etc. issues that will eventually emerge.
‘Fighting’ for a shared analytics platform won’t be successful. The leader has to sell the vision of data sharing, the data synergy that comes with it, and answer ‘what’s in it for us?’ so that organizations are fighting to get in, not fighting to stay out. The mantra I use in these situations is: stop convincing and start connecting.”
Bringing Together the Loosely Affiliated for the Benefit of All
Data governance in healthcare today feels like the quality movement of the U.S. in the early 1980s. Data governance cannot act or feel like a separate, technology-driven entity. Successful data governance is culturally embedded and in those cases where sharing data is important to loosely affiliated organizations, the leader of the effort to bring that data together and leverage it for the benefit of the participants must be a data-savvy version of Henry Kissinger.