Financial Toxicity Order Set: Implementing a Simple Intervention to Better Connect Patients With Resources

Abstract

PURPOSE

Financial toxicity of cancer treatment is well described in the literature, including characterizations of its risk factors, manifestations, and consequences. There is, however, limited research on interventions, particularly those at the hospital level, to address the issue.

METHODS

From March 1, 2019, to February 28, 2022, a multidisciplinary team conducted a three-cycle Plan-Do-Study-Act (PDSA) process to develop, test, and implement an electronic medical record (EMR) order set to directly refer patients to a hospital-based financial assistance program. The cycles included an assessment of the efficacy of our current practice in connecting patients experiencing financial hardship with assistance, the development and piloting of the EMR referral order, and the broad implementation of the order set across our institution.

RESULTS

In PDSA cycle 1, we found that approximately 25% of patients at our institution experienced some form of financial hardship, but most patients were not connected to available resources because of our referral mechanism. In PDSA cycle 2, the pilot referral order set was deemed feasible and received positive feedback. Over the 12-month study period (March 1, 2021-February 28, 2022) of PDSA cycle 3, 718 orders were placed for 670 unique patients across interdisciplinary providers from 55 treatment areas. These referrals resulted in at least $850,000 in US dollars (USD) in financial aid in 38 patients (mean = $22,368 USD).

CONCLUSION

The findings from our three-cycle PDSA quality improvement project demonstrate the feasibility and efficacy of interdisciplinary efforts to develop a hospital-level financial toxicity intervention. A simple referral mechanism can empower providers to connect patients in need with available resources.

Financial toxicity order empowers providers to connect patients to financial counseling and resources.

INTRODUCTION

The financial toxicity of cancer treatment is broadly defined as the economic burden associated with cancer care, including the out-of-pocket expenses patients face and reduction in wages because of disrupted employment.^1,2 As cancer care delivery costs and drug prices continue to rise, health insurance companies increasingly shift more payment burden onto the patient through cost-sharing mechanisms. As a result, up to 73% of patients with cancer have reported some form of subjective financial hardship, and close to one-half (approximately 48%) of cancer survivors note monetary difficulties.³ The experience of financial toxicity in patients with cancer is now well described, owing to an increasingly robust body of literature characterizing its risk factors, manifestations, and consequences. Despite the recent steady increase in publications on the financial impact of cancer on patients,⁴ there is limited research on interventions to mitigate financial toxicity, although the need for such work has been described in previous commentaries and research.^5-7

CONTEXT

• Key Objective

• To assess the feasibility of developing and implementing a novel electronic medical record (EMR) order set to refer patients who may be at risk for financial toxicity to a hospital-based financial counseling and assistance program.

• Knowledge Generated

• The efforts of an interdisciplinary team to engage multiple stakeholders yielded a feasible operational intervention, with 718 orders placed for patients from 55 treatment areas in the first year of the order. The order set helped to streamline the workflow to connect patients in need with available resources.

• Relevance

• Clinically, the findings from this analysis suggest the feasibility of using the EMR as a mechanism to connect patients who may be at risk for financial issues during their treatment to available resources.

Although financial toxicity is acutely experienced at the patient level, interventions must consider the interconnected systems within which patients receive care.⁸ At the hospital level, for example, there are opportunities to engage patients and caregivers in interventions for screening, navigation, and resource referral.⁹ At our urban National Cancer Institute–designated cancer center, we created a multidisciplinary team to address financial toxicity among patients and to create solutions to improve the affordability of cancer care. Key initial steps in this process were to estimate and characterize the extent of financial toxicity at our institution and to evaluate the processes through which patients experiencing financial toxicity were connected with available resources. These efforts ultimately resulted in the development of a financial toxicity order set to improve and streamline the referral process for patients to be connected to our institution's financial counseling and resource program.

METHODS

The multidisciplinary team, which included physicians, nurses, social workers, health service researchers, data analysts, strategists, information technology (IT) specialists, and financial counselors, conducted a three-cycle Plan-Do-Study-Act (PDSA) process to develop, test, and implement an electronic medical record (EMR) order set to refer patients directly to Patient Financial Services (PFS), a program that provides insurance and financial counseling and facilitates applications for financial assistance to copayment assistance programs sponsored by pharmaceutical companies or supported through philanthropy; direct financial assistance for nonmedical essential needs provided through our Department of Social Work; and other mechanisms for financial aid for which a patient may be eligible. Our Institutional Review Board determined this work encompassed quality improvement, and because of this determination, subject-specific consent was not required or sought.

PDSA 1 (March 2019)

To understand the magnitude of the issue at our institution, initial project efforts focused on (1) measuring levels of financial toxicity among patients on active treatment for cancer, (2) assessing the proportion of patients who experienced financial hardship and received PFS assistance, and (3) determining the process by which patients in need were referred to PFS. Since there was no systematic financial toxicity screening process, we used the following proxy evaluation metrics: social work consultation for financial concerns; payment issues (ie, two or more bills eligible to be sent to collections, use of a timed-payment plan, patient-reported bankruptcy, or bills in settlement); and use of hospital-based financial assistance (drug copayment assistance, philanthropic funds for nonmedical essential needs, financial assistance for medical bills).¹⁰ Hospital data sources (eg, billing, EMR) were queried for patients receiving active treatment (ie, had an inpatient stay, underwent surgery, or received radiation therapy, intravenous chemotherapy, or oral chemotherapy) from January 2016 to December 2018, and patients were deemed as having experienced financial hardship if at least one of the aforementioned issues applied. We evaluated and clarified the processes for referral to PFS through discussion with clinical and PFS team members.

PDSA 2 (January 2021)

An EMR order set to allow providers and staff to directly refer patients was developed in consultation with clinical team members, PFS, and IT staff. The order set included referral indication, priority, patient treatment status, and free text space to communicate other information to PFS staff. As the project team leader (E.M.A.) and sponsor (N.A.R.) were members of the gynecologic oncology service, we conducted a 2-month pilot test on that service, and providers were queried via email for feedback on acceptability and feasibility. Specifically, providers were asked four yes or no questions to determine if the order set was easy to use, if they experienced any issues placing an order, and if the order set was helpful for them and their patients. Providers were also offered the opportunity to share additional thoughts on the order through an open-ended question.

PDSA 3 (March 2021)

After a successful pilot test, we activated the order set across the institution, in conjunction with a series of staff education programs. All health care team members could place an order, and referrals were tracked on an institutional dashboard. We evaluated order indications and frequency of orders across patient and provider demographics and conducted an analysis of response to each order, including amount of aid distributed for copayment and essential needs assistance. Rollout included staff education at departmental grand rounds and disease service meetings, with presentations tailored by service and attendee role (eg, physician and nurse).

We analyzed data during each PDSA cycle using descriptive statistics (eg, frequencies and means) before proceeding to the next cycle. In PDSA 3, we compared demographic and clinical subgroup orders placed to institutional averages that were drawn from a random sample of 5,000 actively treated patients from August 2021 through February 2022.

RESULTS

PDSA 1

Of 89,283 identified patients treated during the period of analysis, 25% (n = 22,578) met the proxy definition of financial toxicity. Table 1 details both the count and percent of patients experiencing each issue, along with the median and IQR of months since diagnosis that the patient experienced the issue. The most frequently occurring proxy outcomes included two or more bills eligible to be sent to collections (13%; n = 11,665), receipt of social work financial assistance (6%; n = 5,652), and receipt of general financial assistance (6%; n = 5,204)—categories were not mutually exclusive. Taken collectively, 63% of patients experiencing financial toxicity using proxy measures had payment issues; 49% applied for some form of assistance; and 3% contacted social work for financial concerns (combined categories were not mutually exclusive). The median time to experiencing a proxy outcome ranged from 3 to 25 months.

TABLE 1.

Proxy Experience of Financial Toxicity

Findings from a process review to understand the clinical workflow to refer patients to PFS showed that if patients were found to be experiencing financial issues, they were first referred to social work, who then determined whether a referral to PFS were needed and then sent an email to a member of the PFS team. Yet, in the EMR referral order to social work, there was no direct indication for financial difficulties. Social workers on the team, meanwhile, noted the burden this triaging placed on their already-heavy caseloads of psychosocial support provision and indicated a preference for streamlined referral process that did not involve first contact with social work before PFS. As such, the team began work on the creation of an order to directly refer patients to PFS.

PDSA 2

As noted above and seen in Figure 1, the team collaborated with our IT staff to design the order to include the referral indication (high/outstanding balance, patient report of high out-of-pocket expenses, out-of-network insurance coverage, difficulty meeting essential needs [eg, transportation, food], need for copayment assistance); referral priority (urgent [response within in 24 hours] or routine [response within 72 hours]); treatment status (new diagnosis, starting treatment, planned surgery, immediate postsurgery, ongoing treatment, active surveillance, long-term survivors); patient location; and primary diagnosis.

FIG 1.

Order set.

During the pilot (January and February 2021), 12 providers placed referrals for 12 unique patients—five for insurance questions/issues, three for concerns of high out-of-pocket costs, two for essential needs support, and two for general financial issues. Acceptability and feasibility feedback was universally positive: All 12 providers who placed an order found the order set to be easy to use, had no difficulty placing the order, and felt it was helpful to both themselves and to their patients. These responses indicated to the team that the order set could be rolled out to other services.

PDSA 3

Over the 12-month study period (March 2021-February 2022), 718 orders were placed for 670 unique patients by 301 unique providers across 55 treatment areas (Fig 2). The order was used by a diverse group of health care team members; use included nurses (47%), advanced practice providers (20%), attending physicians (14%), and administrators (11%). Primary indications included high/outstanding balance or out-of-pocket costs (39%), copayment assistance (30%), difficulty meeting essential needs (26%), or out-of-network insurance (9%); 21% of referrals included multiple reasons. Most orders (70%) were placed for patients actively receiving treatment, although patients can receive an order throughout their cancer care continuum, including at diagnosis or into the survivorship period.

FIG 2.

Weekly order count by month. November week 1 increase occurred because of a service-specific pilot program.

Once an order was placed, a PFS representative contacted the patient to schedule a consultation. Orders may not have resulted in an appointment if the patient either did not respond to PFS outreach to schedule an appointment or declined PFS assistance if contact was established. Among orders placed to facilitate copayment assistance from a drug manufacturer or foundation (n = 218), 33% (n = 73) resulted in an appointment with PFS. However, of patients with appointments, 56% (n = 41) applied for aid; 93% (n = 38) were approved by the sponsor. In total, $850,000 in US dollars (USD) of copayment assistance was provided: The mean assistance was $22,368 USD, but because data were shared in aggregate, we cannot provide additional measures of central tendency. Among orders placed for essential needs support available through the Department of Social Work (n = 189), 39% (n = 73) led to a PFS consult, with 50 applications (68%) for aid, of which 86% (n = 43) were approved. Totals for social work aid are not reported because they include both monetary and nonmonetary mechanisms of support.

To assess patient demographic and clinical factors associated with order placement, we compared the percent of orders placed for a subgroup to the institutional average for that subgroup, although because the data were reported to us in aggregate, we could not conduct tests to assess statistical significance among differences. Several demographic subgroups were overrepresented among orders placed. Compared with the distribution of institutional averages by age, more patients age 30-39 years (8% of all orders v 5% of all patients) and 60-69 years (32% of all orders v 28% of all patients) received an EMR financial toxicity order. Compared with institutional race and ethnicity averages, Black patients (15% of all orders v 8% of all patients) and Hispanic patients (12% of all orders v 7% of all patients) were overrepresented among orders. Disease sites overrepresented among orders included breast (24% of orders v 21% of patients) and lung (10% of orders v 7% of patients) and Hodgkin lymphoma (8% of orders v 5% of patients). More female patients received orders than their representation among patients (61% of orders v 58% of patients). Variation in orders placed by primary language was ≤1% for the four most frequently spoken languages among patients (English, Spanish, Russian, and Mandarin).

DISCUSSION

The findings from our three-cycle PDSA quality improvement project demonstrate the efficacy of interdisciplinary efforts to develop a hospital-level financial toxicity intervention. In cycle 1, we identified the proportion of patients at our institution who experience financial difficulties (25%), findings consistent with prior estimates.¹¹ Of patients with payment difficulties (16%), the majority (78%) did not access available aid; our process analysis highlighted the workflow challenges causing this gap in linking patients in need to available resources. Cycles 2 and 3 attempted to fill this gap through the creation of an EMR order that eliminated social work triage and permitted direct provider and staff referrals. The positive feedback from cycle 2 (order pilot test) allowed us to proceed to the final phase—the institutional rollout of the financial toxicity order set. Rollout was widely accepted and used, resulting in approximately $850,000 USD in copayment assistance alone, not accounting for the additional aid provided by the Department of Social Work for essential needs, as well as other financial assistance. Of note, the number of preimplementation social work and PFS referrals was not available; therefore, we were unable to calculate changes in workload experienced preimplementation and postimplementation of the order.

Despite our inability to quantify preimplementation and postimplementation changes, this does not diminish that the order resulted in an improved clinical workflow and streamlined process to connect patients with PFS.

There is limited research and published quality improvement work on hospital-level financial toxicity interventions. As we, and others, have previously highlighted, financial navigation is a promising option for hospital-delivered interventions.^12-14 Other potential hospital-level interventions include financial toxicity screening, tumor board-style interdisciplinary review of specific cases, and support for patient essential needs and nonmedical costs associated with treatment (eg, parking).^9,15-18 All hospital-level interventions must be accessible to historically excluded and limited resource populations to be impactful, and intervention work must be designed to consider scalability in other practice settings. For example, although we provided a mechanism to link patients to a financial assistance program unique to our large academic medical center, it could be replicated in community-based settings provided there is at least one staff member (eg, social worker, patient/financial navigator) to facilitate applications to pharmaceutical copayment assistance programs or to connect patients to community-based organizations that provide direct assistance to patients and survivors (eg, Family Reach, The Samfund/Expect Miracles). The Association of Community Cancer Centers has established Financial Advocacy Guidelines to support community practices in taking a proactive approach to meeting the financial needs of their patients.¹⁹ Ongoing staff education is also key to sustainability and scalability; although we conducted tailored in-services and grands rounds education at the start of cycle 3, the count of orders placed in the first year is not reflective of the likely number of patients in need, indicating that we must strengthen our educational efforts.

Our findings must be interpreted in the context of several limitations. This work was conducted at a single urban comprehensive cancer center, and therefore, the experiences of developing and implementing the order set may not be generalizable to those of other institutions, particularly those that lack robust IT support. However, because of the growing awareness of financial toxicity and the importance of integration of the social determinants of health, many commercially available EMR systems now include, or can be customized to include, a similar referral mechanism as the one we developed. Relating to methodology, we did not conduct formal qualitative interviews or analyses of the experiences of clinicians to enhance our understanding of the referral process before the order set implementation and in our pilot testing phase. Rather, we relied on informal discussions as part of team and service-based meetings. The interdisciplinary nature of our quality improvement team, however, ensured that all major clinical groups involved in the referral process (ie, physicians, nurses, advanced practice providers, social workers, and financial counselors) were included in team discussions. Our analysis is limited in that we did not associate orders placed with specific treatments or treatment modality nor did we measure when in the trajectory orders were placed: Planned future analysis at the patient level will incorporate these variables to allow us to better understand both the unique and cumulative impacts of treatment modality, or combinations of treatment modalities, on financial toxicity outcomes. We were also unable to directly compare the amount of patient financial aid received before and after implementation because of variations in data collection methods between the two phases, and we were limited in our ability to conduct statistical analysis because of data only being available in aggregate.

Nonetheless, by streamlining the process by which patients experiencing financial toxicity are referred to relevant counseling and tangible financial resources, our interdisciplinary team took a first step toward addressing financial toxicity at our institution. As multilevel interventions are necessary to address financial toxicity, hospital-based EMR interventions represent progress in empowering the care team to connect patients to available resources. Future efforts will focus on developing a systematic proactive financial toxicity screening tool, with analysis to determine optimal screening intervals, clinical integration processes, and inclusive and accessible methods of screening delivery.

AUTHOR CONTRIBUTIONS

Conception and design: Bridgette Thom, Stefania Sokolowski, Joshua Allen-Dicker, Amy Caramore, Fumiko Chino, Stephanie Doyle, Christine Fitzpatrick, Francesca Gany, Allison Liebhaber, Nisha Rao, Johanna Tappen, Emeline M. Aviki

Administrative support: Nadeem R. Abu-Rustum, Allison Liebhaber, Tiffanny Newman

Collection and assembly of data: Bridgette Thom, Stefania Sokolowski, Fumiko Chino, Allison Liebhaber, Tiffanny Newman, Emeline M. Aviki

Data analysis and interpretation: Bridgette Thom, Stefania Sokolowski, Nadeem R. Abu-Rustum, Joshua Allen-Dicker, Fumiko Chino, Francesca Gany, Allison Liebhaber, Tiffanny Newman, Emeline M. Aviki

Manuscript writing: All authors

Final approval of manuscript: All authors

Accountable for all aspects of the work: All authors

AUTHORS' DISCLOSURES OF POTENTIAL CONFLICTS OF INTEREST

Financial Toxicity Order Set: Implementing a Simple Intervention to Better Connect Patients With Resources

The following represents disclosure information provided by authors of this manuscript. All relationships are considered compensated unless otherwise noted. Relationships are self-held unless noted. I = Immediate Family Member, Inst = My Institution. Relationships may not relate to the subject matter of this manuscript. For more information about ASCO's conflict of interest policy, please refer to www.asco.org/rwc or ascopubs.org/op/authors/author-center.

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