Since 2017, the Centers for Medicare & Medicaid Services (CMS) has heavily invested in the shift to alternative payment models driven by quality and value. The established Health Care Payment & Learning Action Network (HCPLAN) has ambitious goals of steering 50% of Medicaid payments, 50% of commercial payments, 100% of Medicare Advantage (MA) payments, and 100% of traditional Medicare payments to two-sided risk payment models by 2030.
As managed Medicaid, commercial, and MA plans evolve to evaluate and administer value-based contracts, network contractors and market CFOs will find that the traditional ways of contract evaluations and network optimization may no longer suffice. Retrospective analysis of allowed and paid claims no longer accurately reflects provider performance. Many of these contracts require not only comparison of revenue versus claims to identify an experienced medical loss ratio (MLR), but must also consider all other incentive program costs amended into contracts. These include the cost of quality bonus payments, stop-loss, and capitations paid outside of live claims feeds. This comprehensive evaluation is necessary to truly evaluate the performance of a contract, make informed negotiations at renewals, and optimize in-network provider selection.
Optimizing network analytics in value-based care
Effective data architecture needed for value-based care
This should be the first consideration for any organization looking to enhance its data warehousing and systems. In addition to claims and enrollment, there is a need for comprehensive contract data. These warehouses must keep track of all value-based care contract elements, such as target MLR, risk type (upside, downside, full), shared savings percentage, capitation payments outside of claims, and any other payments that are applicable to the group. The contract warehouse must also easily join with claims and enrollment systems so that all related data can be identified for analysis.
Equip the enterprise for value-based care
Develop scalable and comprehensive reporting for major stakeholders: contract negotiators profit and loss (P&L) owners and executives. For contract negotiators, reports should allow them to scenario test varying contract stipulations through what-if analysis across varying target MLRs, shifting across the value-based spectrum from fee-for-service (FFS) to upside/downside or even full risk. Forecasting based on future trends, adjusting quality bonus payments or capitation rates, and accounting for the impacts of changes to star ratings for MA plans, or risk capture and any other negotiation levers, should also be included. Additionally, an emphasis around providing benchmarking and acceptable ranges should be predefined within the reporting to guide negotiations towards target improvement.
Reports for P&L owners and executives are meant to aggregate the analytics provided to contract negotiators. The same levers can be incorporated, such as the ability to shift target MLR up 1% or accounting for expected improvements in risk capture, but the reports should provide a view of the book of business as a whole and market or product level performance. The purpose of these reports is to allow the enterprise to evaluate the impacts of increasing target MLR across all contracts in each region/product/category or understanding what financials would look like if all upside-only contracts were shifted to full risk in future years. These reports may also rank the order of the worst performing contracts and hotspot for improved future profitability.
Unlock the power of internal data value
An oftentimes overlooked value add to these analytics are comparisons and targets that can be extrapolated from in-house data — for example, the use of tier 2 or tier 3 network provider performance as a benchmark for tier 1. Tier 1 providers performing worse than tier 2 providers may be renegotiated or removed from the network. Additionally, development of peer groups within products can provide a yardstick for continuous improvement — for example, comparing a given full risk health maintenance organization (HMO) with more than 5,000 members with the aggregate performance of all full risk HMOs with more than 5,000 members present in your data. This establishes a hurdle rate for negotiations where the expectation is that contracts are not signed unless they exceed the existing peer group performance. These benchmarks can also be used to establish reasonable profitability targets for varying types of products or across regions.
Boosting network and contract optimization
With the right data architecture, scalable reporting packages, benchmarks, and target profit margins, network optimization can quickly become one of the greatest cost containment and pricing strategies for payers and the most important revenue enhancement avenue for providers. In fact, for payers, these cost containment strategies are enhanced at scale due to tax implications on revenue, which is not at play when producing savings. Also, P&L owners will be equipped to scenario test broad stroke initiatives such as shifts in target MLR or risk type across entire cohorts of the network, add/remove providers that improve unit cost, model migration or substitution impacts of shifting from one system to another, and evaluate the impacts of legislative changes to provider payments.
In addition to this enhanced ability to sculpt future profitability, similar analytic approaches could be layered into reporting packages to inform decision makers on qualitative considerations, such as a provider’s contribution to network adequacy requirements and market level nuances like consumer demand for specific flagship systems.
With this framework in mind, both payers and providers can direct their organizations towards greater profitability.