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As the virtual confetti is swept up after the curtain falls on 2020, hospitals will have entered a brave new world of price transparency. As of January 1, 2021, regulations require hospitals to post to their websites all of their negotiated payment rates in one sprawling machine-readable file1, although many hospitals may not meet the initial deadline. The aim of the regulation is to increase price transparency with the goal that such transparency will lead to increased competition, improved consumer choice, and ultimately lower prices. Challenges will exist, though, to extract useful competitive information from the files. This paper explores those challenges.
Hospitals must also post consumer-friendly information on negotiated rates for 300 shoppable services. Shoppable services are defined as those that can be scheduled in advance. This posting must contain similar data elements as the comprehensive file, but in a user-friendly format. The regulation lists 70 specific shoppable services that must be included; hospitals are then able to select 230 additional services to reach the required 300.
Let’s walk through these step by step and explore the inherent challenges.
Fortunately, this step should be easy as long as the target hospitals have complied with the regulation and posted files. The file must be on each hospital’s website and not behind any required log-in or paywall.
Our focus here is on analyzing the comprehensive machine-readable file that contains all of the hospital’s negotiated rates. The 300 shoppable items posting should be helpful for a quick price check on certain procedures, consistent with its intended purpose as a reference for consumers. However, the shoppable file will not enable one to understand the overall price level of a hospital/payer contract. Typically in contractual negotiations, both parties focus on the overall impact of the proposed changes rather than trying to right-size the price for every service. Given that, extrapolating overall cost level from a few shoppable services could produce skewed results and is not advised.
In theory, the hospital’s negotiated rate posting can be thought of as the same information that is in a contractual payment addendum between the hospital and payer. This will be a listing of thousands of prices for each payer, one price for each service or bundle. Because contractual structures often vary across payers, one cannot simply compare service-specific costs across payers-- that is, the definition of what constitutes a service will differ in the file for different payers. For example, implants may be part of the case rate in one contract, and carved out with a separate amount in another.
In order to get an understanding of the contract’s overall price point, the reimbursement terms must be aggregated to a level that can be compared with other contracts. Prices for the thousands of services must be rolled up using an assumed utilization distribution. But what utilization distribution should be used? Utilization profiles are vastly different for commercial, Medicare, and Medicaid populations. They also vary significantly based on the type of hospital-- community versus tertiary, for example.
Ideally, the hospital’s own utilization distribution with the health plan would be used. That utilization distribution is the gold standard and what is typically used in contract negotiations. However, competitors wanting to model another hospital’s or health plan’s rates will typically not have access to this utilization distribution.
The next best distribution is one for a similar population or hospital. A health plan could assume Hospital X’s utilization profile with another health plan is similar to Hospital X’s utilization profile for its own members, and perform analysis on that data. A hospital could assume that a competitor hospital’s utilization mix is similar to its own or perhaps similar with one or two differences that can be adjusted for (for example, the volume of maternity deliveries).
For Medicare Advantage (MA) business, publicly available hospital-specific utilization can be used from the fee-for-service Medicare program, with some consideration for potential service mix differences in an MA population.
The main point is that the utilization distribution should reflect the service distribution expected at the facility as closely as possible. If none of the above approaches are available, a utilization distribution provided by an outside source could be used. These can be crafted based on specific characteristics of the hospital and population in question. For example, commercial utilization distributions can be created for community hospitals, tertiary hospitals, academic medical centers, children’s hospitals, and rural hospitals. Geographic utilization patterns can be taken into account. Managed Medicaid utilization distributions can be created for specific eligibility categories such as Temporary Assistance for Needy Families (TANF)/Pregnant Women, Expansion, and Disabled.
In some states, publicly available all-payer discharge databases can be used to create hospital-specific inpatient utilization distributions.
|Table: Utilization profile options|
The utilization distribution assumed will have a large impact on the overall price level evaluation. Multiple distributions could be modeled to assess how sensitive the price level answer is to the utilization and give the end user more confidence in the accuracy of the competitive information.
With the contractual rates and utilization distribution in hand, the next step is the repricing. At first blush, this might appear easy. Unfortunately, there are many potential pitfalls. First, many organizations are adept at repricing their own contract structures, but struggle to reprice a different structure. For example, an organization that contracts for inpatient primarily on a per diem basis may struggle to reprice a contract that is based on a percent of Medicare. An organization that contracts for outpatient primarily on a percent of charge basis may struggle to reprice an Ambulatory Payment Classification (APC) based contract.
Further, the rates posted by hospitals are likely to be difficult to interpret. The final regulation did not specify a standard required file layout. Without a standard layout and because hospital contracts can be complex and varied, key information may also be excluded from the posted files, such as:
An analyst without significant contract modeling experience could easily misinterpret the files and draw incorrect conclusions.
The outlier (especially), inlier, and multiple procedure discounting assumptions can have a large impact on the overall price level of a contract. Of course, if these items are excluded from the hospital’s posted file, they will not be known, but modeling should test a range of assumptions for these to assess the potential impact.
For value-based risk sharing, capitations, and care management payments, it is likely no meaningful information will be available.
Another modeling difficulty will be any contractual provisions that are influenced by the billed charge level. Outlier provisions are a common example, but many contracts also include a percentage discount on certain services or bundles. In some cases, the hospital file might specify the billed charge in the comprehensive file (if the service links directly to the chargemaster). In many cases, though, it likely will not (for example, there is no chargemaster billed charge for an inpatient Diagnosis Related Group [DRG]) and certainly cannot in the case of outlier claims. To model this impact, the analyst will need to develop an estimate of the billed charge level for the facility. Milliman maintains an assessment of the billed charge level for every hospital in the country that can help in this regard. If a contract has material exposure to billed charges, consideration of hospital-specific billed charge level is critical to the analysis due to wide variation in billed charge levels among hospitals.
With the modeling done, results can now be viewed. The two primary approaches are:
In general, using a percent of Medicare benchmark is more flexible, can be applied across a range of hospitals, and provides a widely understood benchmark of the magnitude of the price level (rather than just the price relative to another hospital).
While the negotiated rate files required under the hospital transparency rule contain critical competitive information, extracting usable and accurate information from them will not be easy. Milliman has consultants dedicated to provider contracting. We have the industry expertise, contract knowledge, utilization data, modeling experience, and repricing tools to efficiently extract competitive information from the newly required comprehensive hospital price transparency files. Equally important, we can assess shortcomings in the files and quantify the likely impact of what is not reported.
1 Federal Register, Vol. 84, No. 229 (November 27, 2020). Medicare and Medicaid Programs: CY 2020 Hospital Outpatient PPS Policy Changes and Payment Rates and Ambulatory Surgical Center Payment System Policy Changes and Payment Rates. Price Transparency Requirements for Hospitals To Make Standard Charges Public. Final Rule. Retrieved on December 23, 2020, from https://www.govinfo.gov/content/pkg/FR-2019-11-27/pdf/2019-24931.pdf