Bundled Payments Claims Lag

Providers of healthcare are very familiar with the billing process as this is key to ensuring consistent revenue for hospitals and physicians. What is less understood is the lag between when a service occurs and when the claims data is available for measuring the clinical success and financial impact of value-based programs. There are many sources of delay that create this lag. Billing delays, claims processing delays, and data transfer are the primary sources of claims lag. Claims Lag_Photo

Billing: Some organizations submit bills to payers at a slower pace than others. Physician offices vary in their coding ability and timing. Some physician offices submit batches of claims for a week or two weeks rather than at the time of service. Hospitals have to wait for discharge rather than submitting at the time of admission (though interim billing does occur). Home health agencies and physical therapy providers typically submit weeks of visits in one claim. Alternatively, pharmacy prescriptions and claims are primarily run through electronic processes and the data is available very quickly.

Payment: Claims processing is a continuous process, but not every claim makes it through the process all the way to payment on the first submission. Frequently, claims are denied or sent back for revision because of incorrect or incomplete coding. This can sometimes result in delays that last months or even a year!

Warehousing: Once a claim has been submitted and paid, it has to be processed into the data warehouse and then transferred to the organization or organizations that are responsible for measurement. Sometime claims are processed daily and sent to the warehouse, but more often claims are processed on a weekly or even monthly basis. This results in significant delays in getting the data to the measurement organization (even if that group is within the same entity e.g. CMS). Lastly, the claims must be uploaded to the measurement organization system and cleaned and processed to make the data available in a usable format to providers.

While this process has implications for revenue in fee-for-service systems it has greater impact on the ability of providers to successfully intervene on patients in a timely manner and to make programmatic adjustments in a bundled payment environment.

Incurred But Not Reported Factors

Actuaries have come up with a very useful framework for using months with incomplete claims to understand incurred costs. Claims lag is a somewhat predictable process. For example, most pharmacy claims are processed daily and therefore claims lag for pharmacy is very small. Inpatient claims, on the other hand, are the longest to process due to both submission lag and the higher degree of scrutiny (and therefore rejection and revision). Professional providers vary in the length of lag, but lag tends to be predictable by service type (physician office, home health agency, laboratories, etc.). Actuaries use a variety of methods to calculate incurred but not reported factors (IBNR) that inflate claims without runout to create an estimate of what they will cost once all of the claims make it to the processing organization. Physician office bills are relatively quick with about 75% claims processed in the first two months after the service is provided (almost no claims are processed in the same month the service occurs). Hospital bills have about 60% (or less) of total claims processed in the first two months after the service month.

IBNR factors are very useful for estimating performance in a value-based program, but they are still only useful after a few months of data have come in to the measurement organization. Getting real-time predictions requires a new source of information.