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On the Horizon for Value-Based Oncology Care: Predictive Analytics, Novel Therapy Pricing Pressures, New Payment Models, and a Rise in Complex Data Sources

Authored by

Charles Saunders, MD; Jennifer Webster, MS


Integra Connect, West Palm Beach, FL


Dr Saunders is chief executive officer of Integra Connect, and Ms Webster is vice president of analytics at Integra Connect, a health care technology company focused on oncology and urology practices, as well as emergency medicine companies and the broader life sciences industry.


J Clin Pathways. 2019;5(5):37-39. doi:10.25270/jcp.2019.06.00084
Received March 12, 2019; accepted April 22, 2019.


Dr Charles Saunders

Chief Executive Officer

Integra Connect

501 South Flagler Drive, Suite 600

West Palm Beach, FL 33401

Phone: (800) 742-3069


Abstract: January 2019 represented another major inflection point for the Oncology Care Model (OCM), marking the halfway point of the 5-year program. Overall, while OCM participants have expressed concerns about perceived flaws in the program, from attribution logic to novel therapy adjustment, the cohort of OCM participants who work with Integra Connect all agree that value-based cancer care is inevitable and are motivated to help drive its success­—both under the OCM and in the long-term as more commercial payers adopt value-based models. With 2018’s lessons under their belts, we see four main areas of focus OCM participants are prioritizing for the year ahead and beyond, including application of predictive models; use of advanced data management tools; efforts to enhance their understanding of total costs of care, and leverage of the OCM framework in innovative advanced payment models.

In February 2018, the Center for Medicare and Medicaid Innovation (CMMI) released its first set of Oncology Care Model (OCM) performance results to the more than 180 community oncology practices participating in the program. The OCM had already been in full swing for 18 months, but this was the first time that participants received detailed feedback on their aggregate quality score and resource utilization. In addition, CMMI provided participants with a snapshot of the relative performance of practices as compared with their peers. January 2019 represented yet another major inflection, marking the halfway point of the 5-year program. It is therefore a natural time to reflect on lessons learned in 2018 and anticipate the evolving journey that still lies ahead.

Representing one of the largest cohorts of OCM providers and patients nationwide, Integra Connect has been vigilant alongside our practice clients, gaining insights into their trials and tribulations through the OCM program. While Performance Period 1 (PP1) represented a “transition period” for these practices, what came as an unwelcome surprise was the recoupment of Monthly Enhanced Oncology Services (MEOS) payments—the $160 per patient per month for each 6-month qualifying chemotherapy episode used to fund practice transformation initiatives and enhanced services such as care coordination. By the time Performance Period 2 (PP2) results were released in late August 2018, practices had already shown progress in reducing their total cost of care, primarily due to hospital-related costs savings.1 At the same time, rising levels of MEOS recoupment indicated ongoing challenges to identify eligible patients, which proved especially problematic for patients with multiple comorbidities. Overall, while OCM participants have expressed concerns about perceived flaws in the program, from attribution logic to novel therapy adjustment, our cohort of OCM participants all agree that value-based cancer care is inevitable and are motivated to help drive its success—both under the OCM and in the long-term as more commercial payers adopt value-based models. 

Outlook on Key Trends for 2019

This year will be a seminal one for the OCM and its participating practices. With 2018’s lessons under their belts, we see four main areas of focus for the year ahead and beyond.

Making Analytics More Actionable by Applying Predictive Models

As positive trends in resource utilization between PP1 and PP2 demonstrated, oncology practices are doubling down on the most impactful transformation initiatives that can lower costs, namely, reducing avoidable emergency room (ER) visits and hospitalizations; utilizing novel therapies based on value, not just cost; and effectively managing end-of-life (EOL) resources. To continue moving the needle, some OCM participants are now turning to predictive analytics to target patients more proactively and cost efficiently along three dimensions:  

Predicting Readmissions to the ER. Per the guidance of the OCM program, participants began leveraging care coordination services to intervene with high-risk patients, resulting in a reduction in avoidable ER visits and hospitalizations. While this proved effective at the aggregate level, it proved challenging to intervene with the right patients at the right time. By introducing predictive analytics, OCM practices can identify the specific behaviors and characteristics that are most likely to trigger an adverse event, leverage these insights to identify which patients within their population are most likely to return to the ER imminently, and engage them with the appropriate level of intervention.   

Optimizing EOL Resources. The last 90 days of life are often the costliest, as frequency of ER visits and hospitalizations increase. To address this, OCM participants have begun to reconsider aggressive therapy in advanced stages of illness when the possibility of clinical benefit is highly remote and instead refer appropriate patients to hospice or palliative care programs, which studies have shown both reduce resource utilization and improve quality of life.2,3 To optimize the use of EOL resources, OCM practices may soon turn to predictive models that advise which patients are most likely to be candidates based on the specifics of their disease state and treatment plan.  

Novel Therapy Use for the Right Patient at the Right Time. With a decline in costs due to reduced ER visits and hospitalizations, novel therapies now represent an even larger portion of total costs of care. To address this, OCM practices are also looking to predictive models to identify patients who may benefit from transitioning to a new line of therapy based on patient-specific disease progression and genomic testing, thereby ensuring the most appropriate treatment is used for the right patient at the right time—in line with the vision of precision medicine.

Rapid Proliferation of Novel Therapies Compels Pharma and Physicians to Address Pricing and Utilization

With cancer drugs representing more than one-third of all specialty drugs in the development pipeline4 and oncology care becoming transformed by cell therapy treatments like immuno-oncology agents, the use of novel therapies in cancer care is expected to become even more prevalent—and more expensive. Success under value-based models will therefore compel oncology practices to adjust their approach to treatment decisions to accommodate appropriate utilization of novel therapies while considering sustainable total costs of care.

In response to this burgeoning need, practices have started to take steps toward understanding the overall value of specific therapies. They are needing to consider not only efficacy and toxicity, but also the impact on total cost per episode of care, including the likelihood of high-cost resource utilization, such as ER visits and inpatient hospitalizations. In the case of oral agents, practices have also begun implementing new protocols to ensure prescriptions get filled, using methods such as telephonic outreach via a dedicated care management team and accessing electronic data feeds from specialty pharmacies.  

While performance improvements across our cohort of OCM practices have been attributed, in part, to practice transformation activities and related cost-efficiencies, obtaining novel therapy adjustments also played a significant role. For large practices that use novel therapies often, it will be paramount to use novel therapies in alignment with evidence-based pathways, ensuring OCM adjustments provide the necessary financial protections. Moreover, leveraging genomic testing to identify the most appropriate patients for novel therapies will also help to optimize clinical outcomes while mitigating high drug costs.   

Pharma is also facing unprecedented pricing pressure, highlighted by the Health and Human Service’s proposed reforms that reduce reimbursement levels for drugs administered on-site and eliminate pass-through discounts to pharmacy benefit managers.5,6 In response, pharma is already looking to engage with payers and oncologists in creative pricing agreements, such as value-based drug contracts, which are designed to align incentives by linking pricing to a drug’s efficacy.7 

Leveraging the OCM Framework for Next Wave of Oncology Advanced Payment Models 

Despite its flaws, OCM remains the primary reference point for value-based payment models in oncology. It is therefore not surprising that, as cost trends continue to improve under the OCM program period-over-period, further iteration and innovation in alternative payment models gained tailwinds at the end of 2018.   

One prominent example is the Community Oncology Alliance’s OCM 2.0 initiative, which aims to “develop a payment model template that can be used to frame a new payment system for cancer patients that can be used by Medicare, commercial plans, and by self-insured employers, irrespective of their type or size, whose ultimate mission is to provide cost-effective quality care.”8 While its foundational elements reference many of those in the current OCM program, they also incorporate changes to address some of the shortcomings cited by participants. For example, to improve patient attribution, OCM 2.0 proposes to use G-codes to make it clearer—and easier—to predict which patients are attributed to which practices.

Another example of a program that takes an alternative approach to the OCM is the Making Accountable Sustainable Oncology Networks (MASON) program, spearheaded by
Barbara McAneny, MD.  The MASON program is modeled after the American Society of Clinical Oncology’s (ASCO) Patient-Centered Oncology Payment (PCOP) model9 and builds upon the foundation of Dr McAneny’s COME HOME initiative, which originally launched in 2012 and expanded in 2017 in collaboration with ASCO.10 MASON leverages real-time analyses of practice patterns to compare toxicity, outcomes, and costs across different treatment regimens, then recommends to participating practices the best pathways to optimize care while driving meaningful cost savings.11 By utilizing a blend of clinical and claims data, MASON’s objective is to set cost targets based on factors that physicians can control. 

Lastly, in response to the market demand for an alternative payment model that addresses other types of oncology specialists, a new option for radiation oncology was submitted to the Physician-focused Payment Model Technical Advisory Committee by the American Society for Radiation Oncology (ASTRO). Much like the OCM, which was only made available to medical oncologists, the Radiation Oncology Alternative Payment Model (RO-APM) offers $160 per month per patient during an episode of care for delivery of enhanced services and requires that a host of practice transformation objectives be met, including a 13-point care plan, demonstrated use of evidence-based guidelines, and reporting of quality performance metrics—all while achieving a target price per episode.12 

Evolving Data Management Capabilities to Account for New, Complex Data Sources

It should come as no surprise that as the demand for new, predictive analytics grows, so does the demand for more timely and “rich” data. To ensure they are making the most of the sources available, including unstructured data from genomics reports, OCM practices continue to invest in more comprehensive approaches to data collection and management. This may include the application of Natural Language Processing or Optical Character Recognition to quickly and cost-effectively curate data from unstructured fields or partnering with an outside vendor who specializes in data curation and analytics. 

The use of real-world evidence to support clinical trials, observational studies, and validation of clinical pathways is growing in prominence, which further underscores the need for broad, real-time data access. To support these efforts, and in response to the costs and technical challenges associated with accessing data, the Office of the National Coordinator for Health Information Technology recently announced new rules to drive interoperability, including vendor guidelines, “naming and shaming” for data withholding, and application programming interface guidelines for extraction of data on whole patient populations.13


By the end of 2019, practices will know whether they generated savings within at least one performance period through Performance Period 4 and will progress to the two-sided risk model or will be exiting the program altogether. Irrespective of the outcome, the OCM program’s success to date has made it the cornerstone against which all future programs will be measured. A pipeline of new fee-for-value efforts behind it will ensure that value-based care continues to take root more broadly across the community oncology landscape.  


1. Saunders C. The Oncology Care Model performance period 2 results: practices are making some progress, but major challenges remain. J Clin Pathways. 2018;4(10):53-57. doi:10.25270/jcp.2018.12.00050

2. Triplett DP, LeBrett WG, Bryant AK, et al. Effect of palliative care on aggressiveness of end-of-life care among patients with advanced cancer. J Oncol Pract. 2017;13(9): e760-e769. doi:10.1200/JOP.2017.020883

3. Temel JS, Greer JA, Muzikansky A, et al. Early palliative care for patients with metastatic non-small-cell lung cancer. N Engl J Med. 2010;363(8):e733-e742. doi:10.1056/NEJMoa1000678

4. Blank C. Top blockbuster drugs for 2019. Managed Healthcare Executive. November 19, 2018.
Accessed May 23, 2019. 

5. Office of Inspector General, Department of Health and Human Services. Fraud and Abuse; Removal of Safe Harbor Protection for Rebates Involving Prescription Pharmaceuticals and Creation of New Safe Harbor Protection for Certain Point-of-Sale Reductions in Price on Prescription Pharmaceuticals and Certain Pharmacy Benefit Manager Service Fees. 84 FR 2340. Published February 6, 2019. Accessed May 24, 2019.

6. HHS advances payment model to lower drug costs for patients [press release]. Washington, DC: US Department of Health & Human Services; October 25, 2018. Accessed May 24, 2019.

7. Iskowitz M. Payer-pharma collaboration through value-based contracts is set to accelerate. Medical, Marketing and Media. January 7, 2019. Accessed May 24, 2019.

8. Dangi-Garimella S. COA’s OCM 2.0: moving toward a universal payment model. Am J
Manag Care. October 30, 2018.
. Accessed May 23, 2019.

9. American Society of Clinical Oncology. HHS advisory group recommends implementing oncology payment model based on ASCO’s PCOP. Published December 19, 2018. Accessed May 23, 2019.

10. ASCO launches COME HOME initiative to give oncology practices concrete path toward alternative payment system [news release]. Alexandria, VA: American Society of Clinical Oncology; November 1, 2016.
. Accessed May 23, 2019.

11. Robeznieks A. Therapeutic pathways embedded in EHR to improve cancer care. American Medical Association website. Published February 1, 2019. Accessed May 23, 2019.

12. American Society of Radiation Oncology. Radiation Oncology Alternative Payment Model (RO-APM) Description. Published April 27, 2017. Accessed May 23, 2019.

13. The Office of the National Coordinator for Health Information Technology (ONC). Notice of Proposed Rulemaking to Improve the Interoperability of Health Information. website. Updated April 24, 2019. Accessed May 23, 2019.

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