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3 analytic drivers to monitor Enhancing Oncology Model performance

3 analytic drivers to monitor EOM performance

Many CMS value-based care models seek to improve care coordination and reduce Medicare fee-for-service spending through episode-based payment and practice transformation. The agency’s new Enhancing Oncology Model applies these objectives to cancer care.

There are many good reasons for any oncology practice to join EOM and improve the delivery of cancer care to its patients. But value-based care also raises the stakes. Participation alone doesn't guarantee success. Using analytics helps providers “trust but verify” ─ to not simply believe they are improving care quality and reducing costs, but know where they stand through tangible metrics. This blog post explores three best practices that help ingrain analytics in EOM practice, redesign and performance.

How to anchor analytics for EOM performance

1. Estimate episode target prices for financial analyses

Financial realities dictate whether practices join EOM, under what risk arrangement and if it's for the long term. Participating oncology practices should estimate their episode target prices and compare them to their actual Medicare episode expenditures on an ongoing basis throughout each performance period. Target prices in EOM are specific to an individual episode so the amount of financial risk a practice undertakes in a given performance period will be heavily influenced by the realized patient case mix. 

Managing costs for oncology episodes of care will be an ongoing challenge for participating practices. Episode expenditures under the model tend to be dominated by the cost of chemotherapy drugs. There are few opportunities to prevent expensive outliers. It takes advanced EOM analytics and a skilled internal team to uncover potential opportunities to control the cost to Medicare and improve care for oncology patients.

2. Practice proactive oncology care management

Unplanned events can undermine care coordination and cost management strategies. Events that impact patients can include preventable emergency department visits, observation stays and hospital admissions. Linking the following oncology care components to analytics can strengthen practice episode and cost management:

  • Chemotherapy management: Experts consider this to be a vital part of cancer care. Practices must monitor patient response to chemo type, dose and frequency in conjunction with the patient’s individual care plan and evidence-based guidelines, and avoid exposing patients to high-risk care settings (i.e., emergency departments) when managing adverse symptoms.
  • Supportive oncology drugs: These drugs help patients manage adverse side effects of cancer and its treatment. From antiemetics to hematological supports, these drugs can improve the overall quality of life for patients. In certain cases, there are biosimilar alternatives that can do so just as effectively but for less.
  • Palliative care: Palliative care can improve quality of life and can be introduced at any point after diagnosis — even while a patient is actively undergoing therapy. Early introduction of palliative care and the formation of an advance care plan can help mitigate returns to the hospital in the weeks before death and signal when to activate hospice care in partnership with the patient and their loved ones.

These examples demonstrate why practice redesign is inextricable from EOM and other value-based care models. CMS’ EOM requirements support redesign and help maintain specific standards, such as 24/7 clinician access, high-quality practice data and analytics, continuous outpatient navigation and detailed, shared patient care plans.

3. Align data to practice, process and people

Data management has always been challenging for healthcare: Collect, monitor, evaluate, report and repeat. In addition, EOM practices face unique data obstacles as they strive to:

  • drive insights from CMS episodes and claims data files received throughout the performance period;
  • abstract clinical data elements for 90% of attributed episodes semi-annually;
  • compile aggregate quality measure data for all patients annually; and
  • collect and report beneficiary-level sociodemographic data elements to CMS once per performance period.

To make data and analytics an integral part of oncology practice redesign, EOM participants must ask three questions:

  1. Does the practice EHR capture the required data?
  2. Are success markers in place to track, report and improve quality?
  3. Does the practice have an internal team with the skill sets required to execute these needs?

Want to boost your EOM performance?

If you need key data insights backed by an analytics-first approach, contact DataGen for a free consultation. With DataGen’s support, you can focus on boosting your EOM performance through quality analytics.

Looking for more details on EOM? Read DataGen’s blogs on how to operationalize the model and how EOM differs from CMS' Oncology Care Model. To see DataGen's key findings and in-depth analysis of EOM’s national baseline and prediction module methodology, watch our recorded webinar.

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