If you’re like me, you remember the first round of capitated payments in the late 1980s and early 1990s. There were some good reasons why that grand experiment in managed care eventually collapsed, but one of the biggest culprits was lack of useful and actionable data as well as detailed analytics. Providers and payers did not have the information or tools to measure and manage total cost of care or establish fact-based per member per month (PMPM) payments.
Building on those lessons and other innovative care and payment models since, health care is in the midst of another major movement to risk-based contracting. The pandemic is spurring this effort forward as fee-for-service providers saw their revenues largely disappear along with non-COVID-19 patient volume even as providers operating with risk-based contracting continued receiving monthly member payments independent of volume.
This time, providers can benefit from huge advances in data collection, information sharing and analytics to prosper with PMPM payments. Of course, not all data or analytics are equal. So it’s critical to understand exactly what your data is, what it means and how to leverage it to improve care and control costs.
The pros and cons of insurer-supplied grouper data
Providers entering PMPM contracts with payers will typically receive grouper data, which covers the total cost of care by diagnosis, such as diabetes. Insurers sometimes segment grouper data by diagnosis severity, such as four levels of patients with diabetes starting with those with no complications and using oral medication up to patients with three or more complications.
Some limitations of grouper data:
- The episode of care costs for setting PMPMs may not be all-inclusive, such as not including medication and pharmacy costs.
- The format and grouper data may differ by health plan. That makes it difficult to compare data for the same diagnosis across plans.
- Data is available on each plan’s platform, not consolidated or accessible from a single source.
- It is generally only available once a year, severely limiting providers’ ability to track and react in timely way to outlying spending or other key metrics and adjust care and costs.
- Total cost of care, and the resulting PMPMs, is averaged based on claims in a particular market, which can differ widely depending on a health plan’s membership. For a New York City provider, for instance, the region for one insurer could cover the entire state of New York but only Manhattan for another payer. Often, these are risk-adjusted via standard methodologies
Investing in third-party data and analytics
Providers can outsource some, much or all of their data analytics by partnering with third party experts. Options include subscribing to a data analytics platform that collects provider-specific data and lets providers then do their own analysis. Others will also do the data analysis based on provider requests for information. Some provide the analysis in performance reports by physician, department or other segmentation and set the frequency of those reports based on client needs.
A major advantage of this approach is payer data for each provider is aggregated and normalized on a single platform, making analysis much easier and faster. What’s more, these companies often collect data from more sources than the providers’ payer claims, allowing benchmarking against other providers or industry averages.
Just as with grouper data, the data analytics capabilities and data sources of these firms do vary widely. Features to consider:
- Is it designed for non-data analytics experts to use it?
- What data sources are included?
- What other features are available? One software, for example, not only enables providers to determine their actual care costs, but they can manipulate the data to create scenarios that allow them to understand the net financial effect of specific care and cost changes.
Regardless of the data analytics sources, providers need to use the information to understand and manage their costs and care. They are obligated to show they are meeting program and payer quality requirements, such as prescribing annual mammograms for all adult women. Providers also need to ensure ongoing financial viability by keeping spending with the PMPM payments overall.
Please contact us at firstname.lastname@example.org to learn more about leveraging PMPM analytics.