In a related article, FRG introduced the first pillar of the three pillars of transparency, a framework created and closely followed by FRG that emphasizes the importance of transparency in value-based agreements. This article will cover frequent data sharing, the second pillar of transparency.

What Does Frequent Data Sharing Mean in Value-Based Agreements?

In value-based agreements, frequent data sharing means achieving a timely, complete, and actionable exchange of information between health plans and providers accompanied by regular discussions of trends and performance.

Timeliness involves both prompt and predictable delivery of information on a schedule. For example, health plans could deliver restated claims on the 15th of each month paid through the end of the prior month. The two concepts that this conveys are that a) on the 15th of every month information should be exchanged like clockwork and b) the content of the information should be relatively fresh.

To achieve a clockwork schedule, health plans and provider groups need to coordinate either directly or through an intermediary data distribution partner. They must achieve a process that repeats each month on or about the same dates, allowing all parties to have expectations about when to take appropriate action. When there is a delay, communication is critical. If the delay is due to missing components, control should be in place to stop the process, and downstream recipients should be notified after a defined period of time.

For information to be fresh, there cannot be a significant delay between the closing of a period of activity and the delivery of information associated with it, a concept known as minimal lag time. For example, when information is provided on the 15th of the month and paid through the end of the previous month it is often consumed by the aligned provider group on or about the 20th, making it almost a month old on delivery and likely a full month old by the time it’s analyzed. This is a gold standard as of 2024, but some organizations have been known to share information that is six months old. Unfortunately, if an organization is at risk for high-cost members and adverse utilization in a data set that is six months old, they have no opportunity to address trends, the relationship will sour, and the goal of value-based care is not achieved.

Completeness in data sharing means providing each of the necessary pieces to have an understanding of performance trends and outliers. When data is shared, recipients expect a complete set of information. This is distinct from full disclosure in the sense that complete data contains each of the defined pieces of an exchange. For example, member eligibility, premium detail, and paid claims are three elements of a complete set of data. If one of these is missing it is impossible to produce a simple loss ratio analysis. Therefore, if each of these pieces is defined when the information sharing is set up, at a particular cycle if one of them is not available then the cycle must wait. FRG uses file manifest concept to help submitters and data processors declare and acknowledge a complete set of data has been transmitted. If a complete data set is not transmitted, it’s not data sharing!

Actionability comes from the content of the information that is shared. Full disclosure, timeliness, and completeness enable a number of actions when the data set is cohesive. A data set is actionable when it is granular enough to be loaded to an information management system and consistently uses common keys for patient identifiers and common timeframes for paid-through dates and activity dates. Actionable data allows for developing various analyses. Many providers, for example, will like to develop their own lag triangles to understand how their population’s completion factors may be different from the plan level reserves. Also, high-cost member analysis can be refreshed with a new month of claims. Although each time data is refreshed the most recent months of activity are incomplete, members that have demonstrated high-cost patterns in the claims that are shown and paid are candidates for outreach. Further, understanding which members have not been properly risk-adjusted because they haven’t been seen or properly coded is possible with actionable data. At each update cycle, providers need to be able to understand the best possible information about risk adjustment opportunities. If patients haven’t been seen, they need to be prioritized for scheduling, and if patients have been seen their charts need to be coded. Once a patient is seen and their chart is coded, a claim needs to be submitted, whether or not a fee is due, so that CMS can accept the associated diagnosis codes. Regular exchange of risk adjustment data, which indicates the completion of these activities is a key component of an actionable data set.

FRG offers regular data transparency to clients through AccuReports®, a proprietary software that presents information from multiple sources in a crisp, consistent format, and enables health plans and providers to quickly spot trends, understand the drivers, and act on opportunities to improve financial performance.

Can Data Sharing Become Too Frequent?

If frequent data sharing needs to be timely, complete, and actionable, can it be too frequent? That depends.

The purpose of frequent data sharing is to enable parties to collaborate on trends and opportunities in the data itself and make value-based agreements work. When trends are discussed regularly, all parties develop a mutual understanding of the business they describe, and they can identify solutions to address inefficiencies together. In this context, at the same time information is moving electronically, team members can schedule regular conversations to discuss its availability, completeness, and content.

FRG typically suggests meeting with clients monthly to review performance data. Preparing for each of these meetings requires reviewing, analyzing, and highlighting opportunities in the data set. For this to be successful, the data needs to be stable from the time of the analysis to the time of the presentation, much like corporate financial statements. So, updating the data monthly is often sufficient for a strategic analysis. It is then up to the parties to act over the next month to improve performance.

However, some think if a leadership team can identify strategic opportunities more frequently, they can increase performance faster. This has two key dependencies: a) how frequently the data can be updated and b) how frequently the analysis can be refreshed.

Most health plans share data with aligned providers on a monthly basis because preparing and distributing information is a burden on their IT departments. If a provider can only get information monthly, then the analysis should only be developed monthly. Depending on the size of the data set, organizations can perform an analysis each week on different parts of the monthly data package, like reviewing inpatient admissions during week one, specialty cost trends during week two, patients without primary care visits outreach during week three, and high-cost pharmacy during week four.

On the other hand, some health plans are willing to share claims data with their provider partners on a weekly or daily basis, but the utility of this information is limited. Fresh information can be used in a clinical context to enable primary care providers to see recent prescriptions, hospitalizations, and emergency room visits, for example. However, this information can often be captured in the process of taking a patient’s medical history or through electronic medical record exchanges, making it unnecessary. Further, any data set takes time to import into information systems. Unless this time can be reduced to a trivial overnight refresh, strategic reports can be delayed or contain inconsistent data. Worse, incorporating information into reporting requires work on the part of many different team members: data processors, analysts, leaders, schedulers, and clinicians. Work requires resources. In FRG’s experience, the dedication of resources to more frequent reviews of trends that are often observable over multiple months to weekly or semi-monthly reviews is inefficient. If weekly data sets are available organizations should think carefully through their utility.

High-Value Care Starts with FRG!

For the last decade, the Financial Recovery Group has helped health plans and physician groups create transparency in risk contracting, improve the financial performance of value-based agreements, and recover millions of dollars in overpayments through the company’s online analytical reporting and expert claims audit services. For additional information about frequent data sharing or FRG’s services, call 888-466-1025 or email info@frgsystems.com.