Grouping Groupers: How They Differ and Why That Can Impact Your Value-Based Care Strategy
Anyone who has developed successful alternative payment models knows that the use of data analytics to identify opportunities to improve care quality and reduce costs is essential. But while the data and methodology for value-based care is available, the volume of data can be overwhelming, and requires sophisticated analytics to ensure performance data is accessible, clear, and actionable. In any value-based care strategy its likely you will encounter a piece of software called a medical grouper, which is used to help identify services related to a clinical episode. By grouping services, they can be analyzed for cost and quality. Today, many payers use groupers to scale the impact of their value-based programs across multiple episodes and specialties. Groupers are one of the linchpins of an effective alternative payment strategy. But, while they are widely used, they are also commonly misunderstood. There are fundamental differences between groupers and their strategies. Failing to understand these differences and unique applications puts healthcare organizations at risk of missing the insights needed to develop and manage effective alternative payment models that help move the needle on care quality. To help users get the most value from the use of groupers, here is an overview of the various grouper types and how they are applied to successful value-based care strategies.
Episode-based groupers use algorithms and clinical content, such as ICD and CPT codes, to identify and group all services related to a clinical episode—such as a knee replacement, open-heart surgery, or caesarian section.
They provide consistent, replicable analyses of how well providers are coordinating care for patients across an episode. They help reconcile bundled payments and identify preferred specialists for Accountable Care Organizations (ACOs). But different groupers assign services to episodes differently and are designed to support a variety of purposes. It’s important to understand the different grouper types and their appropriate application.
There are four primary types of episodes: procedures, conditions, events, and encounters. And there are three varieties of groupers: procedure-, encounter-, and condition-based. Most episode groupers reflect the patient’s experience of comprehensive care—from initiation to full recovery and exit of the episode. (See Table 1 for a summary of common episode-based grouper applications.)
Examples of procedure-based groupers include the BPCI initiative, from CMS, and PROMETHEUS Analytics® knee replacement episodes, which include all services provided within a 90-day period.
Encounter-based groupers focus on high-cost services, such as a caesarian section, but are limited to services provided during the inpatient stay and exclude services provided after the patient is discharged.
Condition-based groupers look at all services related to a chronic condition, such as diabetes or heart failure, for a set time period (usually one year). For example, PROMETHEUS Analytics incorporates condition-based episodes that include basic care for the condition, in addition to procedural and event-based episodes, like coronary angioplasty and heart attack episodes for the chronic condition, coronary artery disease.
Groupers today are used in a variety of ways –– from performance analytics, to price transparency, to fueling value-based care transformation. Additionally, some are continuously updated and enhanced with physician input to improve their accuracy.
Episode groupers are primarily used to analyze physician performance, reconcile bundled payments, and identify preferred specialists for ACOs.
Attribution methods differ by grouper type, and some groupers support multiple attribution types per episode, such as professional and facility attributions. Groupers like ETGs from Optum and MEGs from IBM have been used for decades for physician profiling. These groupers are helpful for understanding general utilization of services by episode, but do not have the specificity for reconciling contracts. In other words, they cannot be used to establish and scale a bundled payment alternative payment program with provider networks.
Conversely, PROMETHEUS and BPCI were developed to support the cost specificity required for contract reconciliation to enable bundled payment programs. They lack the coverage of ETGs and MEGs in terms of services assigned to any episode, but they are useful for understanding which specialists are performing well with regard to cost and quality for the purpose of creating referral lists.
This emerging application for groupers can help patients understand the full cost of an episode of care and potentially allow them to comparison shop. However, this is a nascent area, primarily due to the limitations of determining the true cost of care for a given patient. A patient’s benefit status, variable coverage, and out-of-pocket responsibilities make it difficult to determine the cost for an episode that might span multiple providers and facilities that provide care over several days, weeks, or months. Most price transparency efforts are focused on estimating up-front costs for specific procedures and then determining the member’s financial responsibility— they do not address the full episode of care.
Value-based care transformation requires incentivizing clinician behavior to induce action. Simply doing an analysis doesn’t solve a problem, but doing the analysis and creating an incentive based on that analysis leads providers to change how they do things, and improve care quality and control costs. With these types of grouper models, including PROMETHEUS Analytics, third party vendors can add value with software solutions that help payers facilitate payer-provider communication, collaboration, and transparency in contract negotiations.
The most effective groupers have been enhanced with input and feedback from physicians who use the output of the analyses to meet their value-based goals.
Some groupers, such as PROMETHEUS, are published and open, and therefore highly transparent— containing a combination of evidence-based content and clinical experience that allows for reliable analyses. This level of reliability and accuracy leads to increased adoption because physicians understand it can be trusted. They read, review, and challenge the content, which is updated as required—further improving the quality of the grouper.
Payers are building member benefits around full episodes of care to improve outcomes and reduce costs, while providing transparency. The PROMETHEUS and BPCI are oriented toward facilitating this contemporary approach to care. By providing insight and transparency around provider performance, they allow members to self-select providers with proven results.
Using the detailed insights of episode analytics, such as those provided by PROMETHEUS and BPCI models, the healthcare industry can position itself to adopt approaches to care and payment that wrap together episodes of care from the PCP to the specialist. Making it work requires using appropriate intelligence gained through clinically validated analytics that help to produce a more complete view of the care continuum as well as reveal important opportunities to improve care and affordability. With groupers, even greater insights are possible.