Care coordination – data standoffs and how to resolve them

How ‘data as a service’ can play a significant role in easing data exchange between payers and provider organizations, bypassing current roadblocks. 

The payer’s data team steps into the room and sits at one side of the table. The health system’s data team already sits at the other end. There are tens of millions of dollars at stake for a value-based care contract, and both parties need it to be successful. After a quick exchange of pleasantries, data exchange discussions begin.  

The data standoff...these negotiations commonly occur between payers and providers across the country.

The payer team wants to receive clinical data in its homegrown format and asks if the provider folks have reviewed the specifications. A representative from the provider says she has, but gently pushes back. “We would prefer to share the data with you in our own standard format. We have a high-quality process for exchanging clinical data and do not want to disrupt it by introducing different formats for different partners.”  

Someone from the payer side protests: “We have a large number of contracts and can’t afford to receive data from your health system in one format and from other providers in another. It will take people and time to use your data.” 

A provider-side representative responds: “We also work with a large number of payers on a large number of contracts. Because you are an important partner, we want to give you the highest quality and consistent product possible.”  

...and on it goes. 

This is what we refer to as a “data standoff,” with both sides angling to get the data they need in the format they want. These types of negotiations commonly occur between payers and providers across the country. 

Sometimes, they lock horns and cannot make process. Other times, they agree on an approach but cannot deliver in time to make the data useful.  

Failure on the data side results in inefficiency on the operations side and can cost both sides millions. More importantly, patients who could be getting services are not.  

Using data as a service to avoid standoffs 

A solution to data standoffs is a well-executed data as a service, or DaaS, strategy, which enables healthcare organizations to exchange a standard set of data domains. A DaaS strategy includes the following elements: 

  • Data standards development 
  • Contract language standardization 
  • Common data model formation 
  • Data sharing infrastructure 

Data standards development 

Data standoffs will continue to play out as long as providers and payers are using their own proprietary formats.  

Interoperability at scale is only possible if all parties can all agree on a backbone of flexible data standards. These standards must cover the data domains of member eligibility in risk arrangements, detailed healthcare spend, clinical gaps in care and other kinds of administrative and clinical data.  

Payers, providers, electronic medical records system companies and interoperability organizations are creating national data standards through the Da Vinci Project and other initiatives.  

If these efforts are successful, there is a good chance that the Office of the National Coordinator for Health IT will mandate that payers and providers across the nation implement the data standards. Even if their use is not mandated, the powerful organizations that developed the standards will use them and urge others to follow. 

Contract language standardization 

Instead of having data conversations during the contract implementation process, healthcare companies are increasingly adding data exchange language to their contracts with other companies.  

Healthcare organizations actively manage what they call “data addendums,” which provide detailed descriptions of the data domains to be exchanged, the methods of exchange and the expected delivery timelines.  

Representatives from contracting teams attach the relevant portions of this document to contracts between companies. Either party is in breach of contract if it cannot deliver the data in the agreed upon format, and some contracts describe financial penalties.  

It should be no surprise that payers and providers are much more responsive and willing to comply when data exchange language is included in the contract. 

Common data model formation 

A successful DaaS strategy requires that data for the relevant domains be accessible in the same place.  

Healthcare systems and payers are each bringing together clinical, financial and administrative data from the disparate parts of their organizations and storing the consolidated data in a single location. Some large healthcare systems, for example, are storing clinical and payer data related to tens or hundreds of risk arrangements in a single common data model on local servers or in the cloud.  

Healthcare companies and vendors also are implementing sophisticated processes for ingesting, normalizing and checking healthcare data.  

Having the data available centrally enables healthcare companies to: 

  • Share performance analytics and financial details for the entire portfolio on an apples-to-apples basis. 
  • Efficiently load member details into internal systems (such as EMRs) for operational purposes. 
  • Share data with vendors and other partners through a single, high-quality pipeline. 

Data sharing infrastructure 

Historically, when one healthcare company needed to share healthcare data with another, someone had to spend months writing data queries and testing them to get the data needed for the project. With new data standards and a common data model filled with information for the entire portfolio, healthcare companies can quickly share data with other companies.  

Instead of writing a query with results specific to a project, the authorized organization is granted access to the minimum data necessary for a project. For example, a Medicare Advantage payer might get access to the member list domain, the supplemental clinical data domain and the alternative submission method coding data domain managed by a health system.  

One goal of DaaS is to limit the number of project-specific queries. With DaaS, an administrator simply adds a new data user to the system, flips a few electronic switches and the data is then accessible. Access to the healthcare data is granted in a matter of minutes instead of in weeks or months. Data users can then access member and patient data through secure application program interfaces over the internet.  

Data security is critical to the success of the DaaS model. Payers and vendors will only be able to get access to information for specific members during a certain time period for a specific risk arrangement. And they will only get to see the data domains related to the data domains described in the contract.  

The payer also will have the ability to extract test data and test the connection with DaaS. 

The future with DaaS 

Imagine a world in which healthcare data could be instantaneously ingested and interpreted.  

In this world without data friction, payers and providers would be more likely to partner together on value-based care contracts. Payers and providers would not call the same patient to provide duplicate services. They would be able to tell if there were issues with an ongoing contract and intervene during the contract period. Patients would receive more timely, individualized and relevant services.  

It would be a better world with DaaS. 

Michael Westover is vice president for population health informatics for Providence. 

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