Five reasons why health payers care about episode analytics

By Jeff Alford, SAS Insights Editor

If you work for a health care payer or provider, you’re acutely aware of the often complex process of “an episode of care.” Accurately capturing relevant moments along a care journey – from detection or diagnosis to treatment and care management – requires an analyst to carefully track patterns and codes in claims data and stitch them together into an episode. Just like a puzzle, the pattern becomes clearer over time.

Repeat this thousands, or hundreds of thousands of times, for hundreds of patients and treatment regimens, and you’ll realize why health care organizations need to understand and learn from these care models. These models provide excellent care for patients and value for payers and providers alike.

Analytics is critical, taking the unrelenting flow of patient and operational data to build value-based care models informed by episode analytics.

Measuring the cost and quality of clinically relevant episodes of care lets payers confidently accomplish five important goals: 

Plan, negotiate and administer condition-specific, value-based contracts such like bundled payments.

Episode analytics assembles all claims related to a specific condition, like a knee replacement, to calculate costs and measure quality outcomes. Understanding those costs, particularly variation by provider and differences in outcome, is necessary for a successful bundled payment program.

A recent study by the RAND Corporation found a bundled payment program for three major surgical procedures reduced total surgery costs by an average of $4,229, or 10.7%.

Episode analytics also lets payers identify populations with target conditions, as well as providers who attain the quality outcomes desired. With these insights, payers can confidently develop, administer and evaluate bundled payment programs.

Create payment policies and value-based benefit designs to promote high-value treatment options.

When an emerging health concern is addressed effectively, at low cost to the individual or payer, everyone wins. Episode analytics lets payers study comparative cost-effectiveness and use that evidence to move providers and members to lower-cost but equally effective services through financial incentives.

Analytics can also monitor the progression of chronic diseases like diabetes and recommend intervention if an individual’s care has deviated from the recommended pathway. Based on episode analytics, payers can design programs for members that incentivize high-value treatment options and preferred treatment providers. Some of the most common incentives are reduced or eliminated copays and deductibles.

Support care management programs through improved candidate identification and care plan analysis.

Every health care encounter has three primary contributors – patients, providers and payers. Understanding each contributor lets you identify areas of success, failure and friction points.

According to McKinsey & Company, "Episodes of care lays the basis for detecting statistical correlations between different types of episodes, enabling a holistic view of patients that informs better treatment decisions and prevention of potentially avoidable complications (PACs)."

Improved health outcomes require the right interventions at the right time, using the most appropriate resources. Episode analytics helps providers determine the best treatment strategies to optimize care delivery and resource efficiency. This is done by analyzing the most clinically relevant data during care episodes to understand patient needs, service utilization and outcomes.

Care delivery rarely occurs at a single entity by a single provider. Episode analytics provides the care delivery team a systemwide view of care across many health care settings and an expanded view of patients' behaviors affecting their health. Understanding the care delivery interventions that produce the best outcomes fosters better program design and clinical operations.

Improve population health targeting and programming with more specific clinical insights.

Population health has an essential synergistic relationship with value-based care. Value-based care initiatives rely heavily on data and analytics to establish high-risk cohorts or other cohorts of interest and understand where in the care continuum to focus program/policy intervention efforts.

Episode analytics plays a key role in assisting organizations with vital population health efforts. It helps organizations create a more holistic picture of populations affected by high-risk conditions and the care they receive. For example, several impactful insights include:

·       Analysis of true total cost of care and associated attribution for all services contained within a clinical episode of care.

·       Implementing interventions for potentially avoidable complications.

·       Designing care models based on variation in providers/site of service.

·       Using severity risk-adjusted scoring for identifying risk groups.

Any population health initiative using episode analysis can improve value-based care initiatives like Medicare Access and CHIP Reauthorization Act of 2015 (MACRA) and care treatment programs/policies and help better manage costs and improve outcomes. 

Improve actuarial prediction of cost with episode-based cost and utilization metrics. 

Actuaries in health care payer organizations commonly use episode-based analytics to perform a wide variety of actuarial tasks. Foremost, episode-based actuarial projection models are among the small set of traditional modeling approaches actuaries use in underwriting and pricing models for large commercial employer and group lines of business. This is particularly true for commercial pharmacy and stop-loss benefits pricing, where federal law poses fewer restrictions in underwriting based on individual health statuses of covered members.

Actuarial use cases for episode-based analytics don't stop there. On the reserving side of the house, grouping claims into episodes of care creates valuable insight and supports greater accuracy in IBNR reserving models. In medical and pharmacy economics teams, actuaries and health economists more often use episode-based models for provider assessment and profiling activities in determining network composition and adequacy, as well as clinical effectiveness and outcomes. All of these are significant inputs into value-based contract negotiations between health payer organizations and provider networks.

For all health care actuaries, and specifically actuaries working in government (such as public exchange plans, Medicare Advantage and Medicaid), using episode-based models as tools for internal risk assessment and strategic planning can deliver insight into many factors health payers must consider to enter additional markets and grow in existing ones.

Health care organizations can share the rewards of a higher standard of care with a patient-centric focus – all made possible with analytics. By better understanding the complexity of patient care in a specific context, payers can better recognize what services are provided to individual patients – both case-by-case and in aggregate.


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