By enabling healthcare organizations to better assess risk at the patient level and develop a more nuanced understanding of care delivery, episode-based analytics are essential to the healthcare industry’s shift from volume to value.
Episode-based payments, or bundled payments, have become an increasingly important part of value-based care agreements between payers and providers in recent years. An episode of care is a group of clinically related services delivered to a patient over time, such as the term of a pregnancy culminating in delivery, or a knee replacement and rehab.
Many episode-based payment models have shown potential to lower costs while maintaining or improving quality. For example, Horizon Blue Cross Blue Shield of New Jersey reported that its episodes-based program for commercial and Medicare Advantage Plan members reduced hospital readmission rates after hip replacement by 37 percent and the rate of C-sections among pregnant women by 32 percent.
More recently, thanks to advances in computing power and greater sophistication of analytics packages, the healthcare industry finds itself with a new opportunity. By leveraging the insights gained from episode-based analytics, we can uncover new ways to improve care and lower costs under all types of payment models; new, alternative, and even fee-for-service (FFS).
Anyone with even a passing familiarity with U.S. healthcare policy is all-too-aware of the cost trend problem, which is largely driven by misplaced FFS incentives that reward providers for the volume of medical services provided, with less incentives placed on outcomes. Attempts to reverse this cost trend have yielded a number of alternative payment models, including capitation, shared savings, and others. This shifts a portion of payer financial risk to providers with the goal of creating greater alignment among payers and providers.
In the transition to value-based agreements, we see advances in analytics capabilities that make today’s solutions more scalable, efficient, and sophisticated than previous iterations. These solutions unlock the data that undergirds the foundation of value-based agreements by helping HCOs perform a more refined risk assessment at the patient level, rather than a broad, population-level analysis.
With more accurate risk assessments, such as stratifying patients into levels of low-, medium-, and high-risk for a certain chronic condition, HCOs can better anticipate cost and utilization needs of certain patients. This enables them to perform interventions now that could eliminate the need for more costly procedures or interventions in the future. Additionally, by understanding health risks at an individual level, HCOs can begin to develop a strategy of addressing issues related to social determinants of health (SDOH).
Further, a significant advantage of episode-based payment analytics is their ability to isolate opportunities for improvement through accurate and fair performance measurement and comparison. For example, in conducting an analysis of knee-replacement episodes, a large, integrated health system may find that certain locations spend more on upfront care coordination. Those cases, however, are
associated with fewer long-term complications and lower total costs, providing the health system with an opportunity to implement new best practices system-wide.
Although episode-based payments have been proven to yield cost and quality benefits, some HCOs still hesitate to embrace the model. Some mistakenly believe that episode-based payments apply only to procedure-based episodes, that they will conflict with other alternative payment models, or that they require too heavy of a lift to design and administer. While there may have been some truth to these ideas in the past, today they are no longer accurate.
For healthcare organizations that still harbor doubt about the benefits of episode-based analytics, consider the following.
Evaluating network design: Episode-based analytics offer an advanced metric-driven way for health plans to design “narrow” provider networks based on provider-performance comparisons that factor in quality as well as costs, unlike many provider comparison tools that base assessments only on the unit cost of single-billed services. Further, heath plans can use episode-based analytics to examine the total costs incurred for a specific condition or procedure, not just what is paid directly to a single provider. In addition, it allows for evaluation of supporting providers (not just facilities and surgeons and how they affect outcomes).
Utilization management: Data gleaned from episode analytics can assist health plans in designing, implementing, and evaluating medical policies and utilization management programs, increasing their efficiency and effectiveness. For example, health plans can view condition-specific utilization rates to find gaps in medical policies by identifying conditions or service lines that could benefit from changes.
Care coordination: Episode-based analytics can help HCOs better understand patient needs, provider utilization patterns and outcomes, enabling them to focus care-coordination resources on patients who would benefit the most from interventions. This data also can furnish care coordinators with a system¬wide view of care delivery and give providers a longitudinal view of patient behavior that each party may not have previously fully appreciated.
If you can’t measure it, you can’t improve it. Episode-based analytics provide the specific, granular, patient-level data needed to quantify virtually any cost and quality improvement HCOs seek. By delivering value-based insights that can only come through a deep dive into the data, episode-based analytics represent the industry’s escape valve from the pressure of fee-for-service cost trends.