Convergence and the Three Rules for Data Governance

Across the industry novel provider-payer collaborations have arisen – something we refer to as convergence. The macro-factor driving this push to convergence is simple; the migration to newer value-based care (VBC) reimbursement models and the rise of consumerism in healthcare.

Convergence comes in many forms ranging from Accountable Care Organizations (ACOs) to provider-owned health plans (payvider) to payer-owned provider networks and the most interesting of all – deep strategic partnerships, including joint ventures (JV), that have arisen between a provider and payer. And we are only just getting started.

Anthem refers to their initial foray in convergence – Vivity Health, the seven-system provider network partnership with California Blue Cross as Convergence 1.0. One of their more recent partnerships with Aurora Health in Wisconsin is referred to as Convergence 2.0.

Aetna has also been an early proponent of convergence with its first JV, Innovation Health, which was established a few years back with Virginia’s Inova Health. Since then, Aetna has announced four additional JVs, (Allina, Banner, Sutter and Texas Health Resources). In each of these instances, Aetna is seeking to partner with a healthcare organization to provide a more seamless and complete healthcare service that will be highly attractive to self-insured employers and individuals buying insurance via an exchange. Aetna EVP, Gary Loveman, who is leading this effort, will be one of our keynote speakers at our Convergence conference next month.

Regardless of whether or not it is Convergence 1.0, 2.0, a deeply binding JV or some other form of convergence, core to the success of any of these strategies rests on the need to have a clear data sharing strategy. The deeper the level of convergence – moving from transactional processes to strategic – the greater the need for data transparency. If the convergence strategy is deep, the sharing of data must likewise be comprehensive to ensure that all parties are working from a “single version of the truth.”

Data sharing will be critical to support the applications and workflows that extend across the converged entity. The shared data asset will also be paramount for establishing mutually agreed to key performance indicators (KPIs) such as quality and costs of delivery care, care variability and administrative actions/burden, etc. These KPIs will help to optimize processes and drive alignment across the converged entity’s health service chain.

But this is where the true challenge to convergence arises.

Much of the data that may be necessary for success, is highly sensitive to one party or the other. If there is a lack of trust between partners a converged strategy will most likely fail. This gets to the core of any convergence strategy – mutual respect and trust is the starting point, followed by a strong desire or need to partner. That need to partner, to collaborate deeply must be shared by all parties.

But well-meaning intent and a strong desire to share data in support of a convergence strategy is only the beginning of the process. The hardest step will be to define the rules of data usage requiring a strong, mutually agreed to data governance policy.

In our conversations with countless healthcare organizations, we find time and time again that data governance is one of the most oft overlooked aspects of their data curation and analytics strategy. Therefore, it is not too surprising for us to see the struggles that many an organization is facing today with governance that extends beyond their four walls to include a partner, who may at one time have been a competitor.

There are three simple rules to data governance in a converged strategy.

1. Ensure parity between the two partnering organizations. If one has the upper hand, data sharing will likely be problematic compromising convergence goals and objectives.
2. Define upfront what datasets will be required and for what purposes. In addition to what types of data and who is responsible for it, address issues such as latency, usage, quality and purposes for which data will be used.
3. Place a skilled diplomat in charge of your data governance strategy. Governance tackles “soft issues” such as policies, people, privacy, security and trust, all key skills of one with strong diplomatic skills.

Be you a provider or payer, follow these rules to data governance will go a long way to establishing the trusted foundational framework for your own convergence efforts.