Bridging the Gap Between Oncologists and Payers: Impact of an EHR-Embedded CDS Tool in Oncology Clinical Pathway (OCP) Adherence

J Clin Pathways. 2024;10(4):32-35. doi:10.25270/jcp.2024.06.03

Oncology clinical pathways (OCPs) have emerged as a payer strategy to promote evidence-based care while controlling costs by reducing unwarranted care variation and spending on low-value drugs. Pathway concordance has been associated with equal or better survival outcomes at lower costs in common cancer diagnoses such as non–small cell lung cancer (NSCLC)¹ and stage II colon cancer.² Despite these compelling quality and financial indicators, compliance has proved challenging, with claims data showing only 64% of patients with newly diagnosed metastatic cancer receive on-payer pathway treatments.³

Extensive research has been done to better understand barriers to pathway con­cordance and reveals a complex and multifaceted challenge spanning development to implementation. This prompted the American Society of Clinical Oncology (ASCO) to release a policy statement outlining recommendations and best practices for the use of OCP in clinical practice, addressing important concerns such as transparency into the authoring process, timely incorporation of new evidence, industry collaboration to reduce the high administrative burden associated with tracking compliance, identi­fying opportunities for prior authorization efficiency gains with pathway adherence, as well as promotion of educational and clinical trial inclusion.⁴ While many factors contribute to pathway adherence, one known barrier to clinician adoption of payer-sponsored value-based models that include OCPs is the lack of workflow integration into the electronic health record (EHR) where clinicians docu­ment care, order treatment, and bill for their work.⁵

Flatiron Assist (FA) is an EHR-embedded and locally cus­tomizable Clinical Decision Support (CDS) tool for medical oncologists that facilitates systemic treatment selection and documentation of National Comprehensive Cancer Network (NCCN) Guideline concordant, NCCN Preferred, and/or cus­tomized locally preferred treatment regimens (Figure 1). Prior research has shown that CDS tools such as FA can facilitate value-based cancer care delivery1 and enable measurement of guideline and pathway concordance to improve quality and re­duce variation in care. FA is embedded within the patient chart and fully integrated into the order entry workflow of Onco­EMR, an oncology-specific EHR. As clinicians enter pertinent patient information, a personalized treatment recommendation based on the patient’s unique clinical characteristics is suggest­ed, which the clinician can then select to order. All metadata re­lated to a treatment decision, such as guideline concordance and pathway adherence, is captured seamlessly in the background for downstream use cases like interaction checking, medication administration record (MAR) administration, prior authoriza­tion, and connection to other data analytics platforms.

Oncology is a complex and rapidly changing health care spe­cialty. For nearly two decades, specialty care management company New Century Health, now part of Evolent, has de­veloped and updated high-value clinical pathways that incor­porate the latest science and new innovative therapies. Drawing from clinical trials and other high-quality evidence, the highest tier level 1 (L1) medical oncology pathways prioritize treatment options that offer the highest quality, greatest efficacy, and low­est toxicity, while recommending lower-cost options among regimens that are roughly equivalent in quality. Developed and overseen by employed clinicians under quarterly guid­ance from independent scientific advisory boards, comprising renowned academic and community-based specialty physi­cians, these pathways ensure the most effective, least harmful treatment for patients at lower costs.

In September 2023, a pilot project seeking to increase adop­tion of Evolent L1 pathways was launched across three com­munity oncology practices where L1 pathways were embedded into FA and labeled as Evolent pathway treatment regimens. Medical oncologists could select from Evolent pathway-desig­nated treatment regimens in addition to NCCN Preferred when ordering treatment in FA for patients with insurance where Evolent managed oncology benefits for three cancer types, in­cluding colorectal cancer, prostate cancer, and NSCLC. This analysis includes results and findings from the American On­cology Network (AON), which is one of the three participating practices. AON is a large community oncology network com­prising 92 clinics and 240+ providers operating across 21 states.

Before the pilot started, researchers reviewed AON’s base­line data, which was monitored by Evolent. They included the average L1 pathway adherence rates for colorectal, NSCLC, and prostate cancer from January 2023 to August 2023, ex­cluding reauthorizations. Over the 8-month period, the aver­age L1 pathway rate for colorectal cancer ranged from 53% to 75%, with an overall on-pathway average of 64%. For NSCLC, the rates varied from 53% to 82%, averaging at 70%. Prostate cancer had rates between 58% and 100%, averaging at 78%. The average L1 pathway rate across all three cancer types was 70%. These figures provide insights into the relative performance of L1 pathway rates across different cancer types over the specified months.

The primary objective of this retrospective analysis was to compare pre- and post-L1 pathway adherence rates at AON. A secondary objective was to assess whether prompting clinicians with alternative on-pathway treatment regimens when off-pathway regimens were selected would change the treatment decision. If an off-pathway regimen is selected in FA, users are provided with alternative on-pathway treatment options based on a patient’s clinical scenario. Providers then select the alter­native treatment or provide a reason why they are ordering the nonpreferred option.

This study is a retrospective, observational, real-world study of treatment selection patterns across AON alliance oncologists accessing L1 pathways embedded within FA. For a given clini­cal scenario for patients with insurance where Evolent manages the oncology benefit, FA surfaces therapeutic options as:

• Evolent pathway;
• NCCN Preferred;
• Both Evolent pathway and NCCN Preferred;
• NCCN concordant, not preferred; or
• NCCN nonconcordant.

While FA can support additional local custom practice pref­erences, there were no AON-specific preferences configured during this trial period.

A clinical scenario was defined as a unique set of clinical data elements that describe a patient’s cancer diagnosis. FA uses clin­ical scenarios to categorize NCCN indications. As part of the regimen ordering process in FA, clinicians must select the clini­cal scenario that best describes their patient so that concordance data is known. Eligible insurance plans were identified through an EHR text search for insurers in which Evolent manages the oncology benefit. These lists were sent to practices to confirm but may not encapsulate all potential eligible insurers.

This study used the nationwide Flatiron Health EHR-de­rived database—a longitudinal database, comprising de-iden­tified, patient-level, structured and unstructured data, curated via technology-enabled abstraction to analyze treatment regi­men orders placed in FA during the 5-month observation pe­riod (September 8, 2023, through February 26, 2024) by 135 clinicians across the AON network. The study includes all treat­ment selection episodes in which FA was used to assist in selec­tion of systemic therapy for colorectal cancer, prostate cancer, and NSCLC, and each episode of treatment selection using FA is characterized as a unique event. We assessed patterns of pre­ferred and nonpreferred treatment regimen ordering to deter­mine the percentage of on-pathway orders when Evolent path­way regimens were available. We also assessed the number of times a clinician was redirected to an Evolent pathway regimen when they chose a nonpreferred option, as well as the number of times they opted to order the Evolent pathway regimen instead.

In addition, overall adherence to Evolent pathway regimens following the pilot launch was compared to adherence in the baseline period based on all prior authorizations for pathway-eligible orders (eg, not restricted to orders placed via the CDS). The difference in percentage adherence was estimated, and 95% CIs and P-values were reported.

We analyzed a total of 3430 orders placed at AON. Of the 79 orders placed at AON (36 in NSCLC, 30 in colorectal can­cer, 13 in prostate cancer) where Evolent pathway regimens were available, an Evolent pathway regimen was selected 76 times, an overall order rate of 96.2% (95%, CI; 89.4%-98.7%) (Table 1). Of note, Evolent pathway regimens were also NCCN Preferred in 36 of the 76 orders and total NCCN con­cordance rates across these three diseases for the 5-month pilot period was 93%.

In addition to the AON analysis, we identified 13 episodes where a nonpreferred regimen was selected, and the clinician was prompted with alternative preferred treatments for the same clinical scenario. This resulted in the clinician switching to the Evolent pathway treatment regimen one time, a suc­cessful redirect rate of 7.7%. The most common reasons docu­mented for the 12 episodes where an off-pathway regimen was selected include patient status and physician choice.

When assessing all prior authorization requests for the three cancer types at the participating site during the 8-month baseline period, 69.5% of 364 pathway-eligible orders were for an L1 pathway regimen, while, following the pilot launch, 78.2% of 156 pathway-eligible orders were for an L1 pathway regimen, reflecting an increase of 8.7% (95%, CI; 0.7%-16.7%; P = 0.04).

This study demonstrates that designating Evolent L1 pathway treatment regimens within the EHR-embedded CDS tool in­creases pathway adherence, a critical component of high-quali­ty, value-based cancer care delivery. Displaying payer pathway recommendations at the point of care and fully integrating them into ordering workflows provides clinicians with impor­tant scientific and financial insights at the time of treatment decision, empowering them with information they need to select preferred options for the majority of patients (Figure 2). Due to the proprietary nature of pharmaceutical procurement contracts, actual cost savings is not disclosed here but numerous publications have previously estimated cost savings⁶ through various mechanisms such as average savings of $22 543⁷ or re­duction in per member per month drug cost of 11%.⁸

More research is needed to understand the oncology deci­sion-making process at the point of care, including the impact of prompting clinicians of on-pathway options after selecting an off-pathway treatment. The limited number of successful redirects, when compared to the high pathway adherence rate resulting from a prompt that occurs before selection has been made, may suggest that earlier visibility into pathway recom­mendations that steer clinicians toward preferred pathways is more effective than prompting for a change after a decision has already been made.

In addition, this payer pilot occurred simultaneously with AON’s implementation and rollout of FA resulting in a small sample size limited to the three pilot diseases contingent on clinician adoption of the CDS tool. In the time frame since data analysis for this publication, we have seen an upward trend in FA adoption from < 50% at go-live to > 85% of all eligible orders. Ongoing post-live data collection across the AON network and further study of adherence rates expanding to common diagno­ses such as breast cancer is needed to fully understand the impact of workflow integration on pathway compliance.

This study underscores the potential of integrating clinical guidance into workflows to improve adherence to evidence-based pathways. In the face of escalating complexity in can­cer care, which is characterized by dynamic payment models, rapid therapeutic advancements, and workforce shortages, medical oncologists and their patients need cost-effective and intuitive technological solutions that increase efficiency. These tools, seamlessly embedded into clinical workflows, empower clinicians with timely updates and financial in­sights, facilitating optimal treatment decisions and enabling organizations to benchmark against industry standards for high-quality, value-based care.

Study Limitations

A limitation of this study (and all CDS tools) is the lack of complete data on orders placed outside of the CDS tool; therefore, direct comparisons between baseline rates and rates for orders placed in the CDS tool may not be appropriate. However, a direct comparison of pre-pilot adherence rates and post-pilot adherence rates based on all prior authorizations at participating sites (not just those made using the CDS) indi­cates that overall, adherence to preferred regimens increased following the pilot launch.

Authors: 

Anna Bolha, MPAS, PA-C1; Rebecca Maniago, PharmD, BCOP1; Nina Sardesh1; Taylor Dias-Foundas1; James Roose, MA1; Colin Harvey1; Marcello Ricottone1; Eric Weber2; Susan Sabo-Wagner, MSN, RN, OCN, NEA-BC3; Brian P. Mulherin, MD3; Andrew Hertler, MD2; James Hamrick, MD, MPH1

Affiliations: 

¹Flatiron Health; ²Evolent; ³American Oncology Network (AON), LLC.

Address correspondence to: 

Taylor Dias-Foundas

Flatiron Health

New York, NY

Email: taylor.diasfoundas@flatiron.com

Disclosures: 

During the study period, A.B., R.M., N.S., T.D-F., J.R., C.H., M.R., J.H. reported employment with Flatiron Health, Inc. and stock ownership in Roche.