Skip to main content

Lessons learned from the Oncology Care Model

After a six-year run, the Oncology Care Model is due to sunset in June. Designed to provide better quality, highly coordinated oncology care, OCM offered oncologists the opportunity to improve person-centered care. It also gave participating practices access to new data across the care continuum to support practice transformation.

Practices that participated in OCM were required to commit to providing enhanced services to their Medicare patients. These enhanced services, which were well received by cancer patients, became part of the practices’ transformation plans.

Practices focused on:

  • better symptom management to reduce emergency department utilization;
  • depression and pain screenings to support psychosocial needs;
  • navigation for high-risk patients;
  • advanced care planning; and
  • end-of-life care.

The challenges of implementing the Oncology Care Model

Despite the care delivery improvements made under OCM, participating practices faced several challenges that were beyond their control.

Better risk adjustment will be essential in any future model with oncology episodes of care. Claims do not capture enough relevant clinical information to meaningfully understand expenditure patterns in oncology episodes. When integrated with administrative claims data, information about cancer staging, current clinical status and treatment regimen can improve the predictability of oncology episode expenditures. This would help with setting target prices.

CMS tried to improve the performance-based payment methodology throughout the model, such as identifying high-risk versus low-risk drug adjustments for some cancer types, and metastatic at initial diagnosis adjustments for three cancer types. However, CMS needs to make more methodology improvements in any future model that includes as many different cancer types as OCM.

Better accounting for drug expenditures within an oncology episode is another area where significant changes are needed, as the rising cost of drugs was not well controlled in OCM. Unfortunately, this created scenarios of “always lose” cancer types in the program, especially as new drugs and treatment regimens became the standard of care. This was disheartening for participants who closely monitored and evaluated their high-cost episodes, only to determine that the expenditures were unavoidable as the steps taken and drugs prescribed were clinically appropriate.

As the next wave of Advanced Payment Models are developed, momentum exists for future oncology-focused programs

Despite the challenges presented by OCM, most oncologists were involved for the right reasons, demonstrating an altruistic attitude for the better good of the patient and the ability to transform the care delivery model. Even when financial results did not meet expectations, many providers recognized that practice transformation was the right thing to do for their patients and was made possible by the resources gained by participating in OCM.

Given the strong willingness to improve care delivery for cancer patients, OCM participants are ready to consider future value-based care opportunities. CMS should consider this as it develops new Advanced Alternative Payment Models. CMS should seize upon the momentum created by participants in OCM to build a more robust initiative moving forward.

Providers considering participating in similar APMs should understand the importance of using data to evaluate and monitor performance. A strong healthcare data analytics infrastructure will ensure the best performance, locking in better patient and financial outcomes and ensuring program success.

Comments

Popular posts from this blog

Community Health Needs Assessment examples: Q&A on CHNA data reporting

Include integral data in your Community Health Needs Assessment examples  Community Health Needs Assessment (CHNA) examples tend to focus on case studies. However, using integral data for your CHNA can provide overall guidance, making it easier to start and complete your final report. In this Q&A, DataGen’s Melissa Bauer, principal healthcare informatics analyst, explains why using data in the CHNA is key and what types of data you should collect.   Q1: What is CHNA data?   A CHNA requires two types of data: primary and secondary. Using these two data streams, organizations can better characterize the community's health. This helps the organization conducting the CHNA best understand their community needs. It also informs them on the best ways to respond to them, providing guidance on where to start and how to evaluate impact and outcomes. Here’s a further explanation of the data found in a CHNA:  Primary data includes community surveys, focus groups, in-depth interviews, and c

Five key components of a strong patient safety culture

In today’s healthcare environment, ensuring patient safety is more than just a priority — it’s a fundamental component of quality care. Establishing a strong patient safety culture within hospitals and health organizations can dramatically reduce errors, increase patient satisfaction and improve overall healthcare outcomes. But what exactly is a patient safety culture, and how can institutions cultivate it effectively?  This blog post explores the five key components that make up a robust patient safety culture, along with insights from the Agency for Healthcare Research and Quality (AHRQ) and The Joint Commission.  What is patient safety culture?  AHRQ defines patient safety culture as how an organization's culture supports and promotes patient safety. This can extend to multiple levels, from individual units to departments to system levels. The AHRQ patient safety culture survey encompasses the shared values, beliefs and norms of healthcare practitioners and staff that influence