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Financial Impact of Out-of-Pocket Costs Among Patients Undergoing Resection for Colorectal Carcinoma

Introduction Little is known about the societal burden of cancer surgical care in terms of out-of-pocket (OOP) costs. The current study sought to define OOP costs incurred by patients undergoing colorectal cancer resection. Methods Privately insured patients undergoing colorectal cancer resection between 2013 and 2017 were identified from the IBM MarketScan database. Total and OOP costs were calculated within 1 year prior to and 1 year post surgery. A multivariable linear regression model was used to estimate total OOP costs relative to patient demographic and clinical characteristics. Results Among 10,935 patients, 7289 (66.7%) had primary colon cancer while 3643 (33.3%) had rectal cancer. Median total costs were US$93,967 (IQR US$51027–168,251). Median OOP costs were US$4417 (IQR US$2519–6943), or 4.5% (IQR 2.2–8.1%) of total costs. OOP costs varied over the course of patient care; specifically, median OOP costs in the preoperative period were US$432 (IQR US$130–1452) versus US$2146 (IQR US$851–3525) in the perioperative period and US$969 (IQR US$327–2239) in the postoperative period. On multivariable analysis, receipt of chemotherapy (+US$1368, 95%CI +US$1211 to +US$1525) or radiotherapy (+US$842, 95% CI +US$626 to +US$1059) was associated with higher total OOP costs. Patients with a health maintenance organization (HMO) (−US$2119, 95% CI −US$2550 to −US$1689) or a point-of-service plan (−US$938, 95% CI −US$1385 to −US$491) had lower total OOP costs than patients with comprehensive insurance. In contrast, patients with a consumer-driven or a high-deductible health plan had considerably higher total OOP costs than patients with comprehensive insurance (+US$1400, 95% CI +US$972 to +US$1827 and +US$3243, 95% CI +US$2767 to +US$3717, respectively). Conclusions Privately insured colorectal cancer patients undergoing surgical resection pay a median of US$4417 in OOP costs, or 4.5% of total costs. OOP costs varied with receipt of chemotherapy or radiotherapy, region of residence, and insurance plan type. Supplementary Information The online version contains supplementary material available at 10.1245/s10434-022-11755-2.

well younger or less educated individuals are more likely to experience financial hardship following a cancer diagnosis. 12 Colorectal cancer represents the third most common cancer and the second leading cause of cancer-related death in the USA. 13,14 Its treatment commonly involves a combination of surgical resection, chemotherapy, and/or radiotherapy, resulting in substantial costs. 15 As such, the associated OOP costs can result in financial strain among colorectal cancer patients and survivors. 16,17 Most literature and public discourse on the financial hardship experienced by patients as a result of OOP costs has focused on the cost of drug treatments. [18][19][20] Several studies have noted that OOP costs associated with cancer care spike immediately following diagnosis due to the high OOP costs relative to inpatient services, including surgery for potentially resectable cancers. 21 OOP costs experienced by colorectal cancer patients who undergo surgical treatment remain poorly defined, however. As such, the objective of the current study is to determine total OOP costs among privately insured colorectal cancer patients incurred between 1 year prior to and 1 year following surgery. Additionally, we sought to identify the demographic and clinical factors associated with total OOP costs over this time period.

Patient Population
Patients with colorectal cancer who underwent surgical resection between 2013 and 2017 were identified from the commercial IBM MarketScan database, which contains medical and drug data retrieved from employers and health plans for more than 203 million individuals annually. 22 Patients diagnosed with colon or rectal cancer were identified using the corresponding codes of the International Classification of Diseases, 9th and 10th revisions (ICD-9 and ICD-10) (Supplementary Table 1). Patients who underwent surgical resection of their primary tumor were identified using a combination of ICD-9, ICD-10, and Common Procedural Terminology (CPT) codes (Supplementary Table 2). Patients with an additional cancer diagnosis were excluded. Additionally, patients without continuous enrollment and drug coverage over the study period (from 12 months before surgery to 12 months following surgery) were excluded.

Variables and Outcomes
Variables of interest included patient age, sex, employment status (active full time, active part time, Consolidated Omnibus Budget Reconciliation Act (COBRA) continuee, etc.), health insurance type, and US Census Bureau region of residence, as well as whether patients resided in a Metropolitan Statistical Area (MSA). Patient health insurance types included comprehensive health coverage, exclusive provider organization (EPO), health maintenance organization (HMO), point-of-service (POS) plans, preferred provider organization (PPO), consumer-directed health plans (CDHP), and high-deductible health plans (HDHP). The 2010 Standards for delineating MSA require that the area must have at least one urbanized region of 50,000 or more inhabitants. 23 In the current study, residence in a MSA was used as a proxy for residence in an urban setting. Preoperative comorbidities were accounted for using the Charlson Comorbidity Index (CCI). [24][25][26] Information on treatment included year of surgery as well as receipt of chemotherapy and/or radiotherapy. Patients who received chemotherapy or radiotherapy were identified using the relevant revenue and CPT codes.
Total costs were calculated as the sum of all healthcare expenditures between 12 months prior to surgery and 12 months following surgery, including costs reimbursed by the primary insurance provider, out-of-pocket (OOP) costs incurred by the patient, as well as benefits received by other insurance carriers. OOP costs were calculated as the sum of deductibles, copayments, and coinsurance, as available in the IBM MarketScan commercial database. The proportion of OOP costs relative to total costs (OOP/total) was then calculated.
Total costs were the sum of expenditures associated with claims over four distinct time periods: the preoperative (from 1 year prior to surgery to 90 days prior to surgery), the perioperative (from 90 days prior to surgery to 30 days following surgery), the adjuvant (from 30 days following surgery to 90 days following surgery), and the surveillance period (from 90 days following surgery to 1 year following surgery). The definition of these four time periods was consistent with previous studies on OOP costs among cancer patients undergoing surgery. 27

Statistical Analysis
Descriptive statistics are presented as median (interquartile range, IQR) for continuous variables and frequency (relative frequency, %) for categorical variables. Bivariate associations between cancer location (colon or rectum) and patient demographic or clinical characteristics were assessed using Kruskal-Wallis one-way analysis of variance for continuous variables and chi-squared tests for categorical variables. A multivariable linear regression model was developed to predict the overall OOP costs over the study period based on relevant patient demographic and clinical characteristics. All analyses were performed using SAS version 9.4. Statistical significance was assessed at a = 0.05.
Only a small minority of patients had OOP costs associated with receipt of chemotherapy or radiotherapy ( Table 2) (Table 3).

Multivariable Analysis
On multivariable analysis, several patient demographic and clinical characteristics were associated with total OOP costs between 1 year preoperatively and 1 year postoperatively ( Additionally, there was substantial regional variability in total OOP costs. Patients from the Northeast Costs calculated only for patients who had at least one claim associated with OOP costs in the period of interest (n) OOP out-of-pocket *Costs associated with inpatient or outpatient services also include costs associated with chemotherapy and/or radiotherapy

DISCUSSION
Curative treatment of colorectal cancer requires a multidisciplinary approach that involves a combination of surgery, chemotherapy, and/or radiotherapy, leading to high treatment costs. 28,29 In recent years, insurers have attempted to counteract the rising costs of cancer care by shifting a greater proportion of these costs to the patient through deductibles, copayments, and coinsurance. 30 As a result, even insured colorectal cancer survivors often face significant financial hardship due to the direct and indirect costs of their treatment. 19,31,32 As financial hardship is associated with worse outcomes for cancer patients, it is of utmost importance that patient-provider discussions on cancer treatment also include a discussion of the OOP costs associated with each treatment option. 33 Existing evidence suggests that cancer patients would be comfortable with and open to such discussions. 34 Despite this, patient-provider cost communication only rarely occurs in clinical practice. 35 In the case of colorectal cancer patients, one obstacle to having meaningful and impactful patient-provider discussions on treatment costs is the lack of reliable estimates of OOP costs associated with curative treatment. Therefore, the current study is important because we assessed OOP costs between 1 year preoperatively and 1 year postoperatively in a large cohort of commercially insured colorectal cancer patients undergoing surgical resection. We found that patients pay a median of US$4417 in OOP costs over this period, or 4.5% of total costs. While OOP costs represented a lower proportion of total costs in the postoperative period, they were still significantly higher than the costs in the preoperative period. In addition, OOP costs varied widely relative to receipt of chemotherapy or radiotherapy, region of residence, employment status, and insurance plan type. The main finding of the current study was that privately insured patients who underwent surgical resection for colorectal carcinoma spent a median of US$4417 in OOP costs between 1 year preoperatively and 1 year postoperatively. Somewhat unsurprisingly, OOP costs spiked in the perioperative period and gradually decreased in the postoperative period. However, postoperative OOP costs never returned to their preoperative levels ( Table 2; Fig. 1). These findings are in line with a previous study by Dieguez et al., who noted a similar pattern of OOP spending among commercially insured colorectal cancer patients diagnosed in 2011. 21 Specifically, Dieguez et al. reported that, following an initial peak associated with treatment, OOP costs did not return to baseline for as long as 3 years after the initial cancer diagnosis. Of note, the bulk of OOP costs over the study period was associated with inpatient services, while costs associated with outpatient services only represented a minor share of all OOP costs (Fig. 1). In a 2017 analysis of 1409 Medicare beneficiaries diagnosed with cancer, Narang et al. similarly reported that inpatient services accounted for a vast majority of total OOP costs. 36 The current analysis was the first to note that radiotherapy and chemotherapy were also associated with meaningful OOP costs in the preoperative and postoperative period, respectively (Fig. 1). On multivariable analysis, receipt of chemotherapy and radiotherapy were both associated with a drastic increase in total OOP costs over the study period (Table 4). Since patients of lower socioeconomic status tend to place a disproportionate importance on costs when making treatment decisions, the OOP costs associated with radiotherapy and chemotherapy may be contributing to existing disparities in receipt of these treatment modalities for colorectal cancer treatment. [37][38][39] Of note, several patient demographic and clinical characteristics were associated with OOP costs on multivariable analysis (Table 4). Specifically, older age was associated with a decrease in OOP costs, albeit a minor one. Previous studies had noted that younger cancer patients were particularly vulnerable to financial hardship following a cancer diagnosis. 7,40 Results of the current study suggested that the financial impact of surgical treatment associated with colorectal cancer treatment among younger patients was mainly mediated by differences in employment and health insurance status, rather than by younger age itself. In particular, COBRA continuees faced higher OOP costs than full-time employees, who in turn incurred higher OOP costs than early retirees and Medicare eligible retirees. Additionally, there was a notable yet nonsignificant trend for higher OOP costs among part-time employees compared with full-time employees (Table 4). Colorectal cancer and its treatment are known to severely limit patient ability to work, resulting in lost wages and income, as well as disruptions in health insurance coverage. 41,42 Results of the current study suggest that patients who are in less stable positions and are more prone to such disruptions face higher OOP costs when undergoing surgical treatment of colorectal cancer. Nevertheless, the single most important factor determining the amount of OOP costs incurred by colorectal cancer patients undergoing resection was their health insurance plan type. Notably, postoperative OOP costs accounted for a smaller proportion of overall costs than preoperative OOP costs ( Table 2). As such, healthcare insurance was mostly effective at mitigating the financial impact of the surgical treatment of colorectal cancer. However, the amount of OOP costs paid by patients varied widely based on the specific insurance plan type. Specifically, patients with a CDHP or HDHP paid as much as US$1400 and US$3242 more, respectively, than patients with a comprehensive plan, who in turn paid US$2119 more than patients with an HMO plan (Table 4). Of note, HDHPs have recently grown in popularity, and as many as 51% of all US workers were enrolled in one in 2019. 43 As such, OOP costs associated with the surgical treatment of colorectal cancer can be expected to have an increasingly large impact on a growing number of patients.
Findings from the current study may inform initiatives aimed at mitigating the financial impact of surgical treatment of colorectal cancer patients. Specifically, the fact that OOP costs remain elevated well beyond the initial spike associated with surgical treatment suggested that patient-provider cost discussions should not stop at the treatment selection phase, but should also include the longterm financial repercussions of treatment (Fig. 1). Additionally, the type of health insurance plan in which colorectal cancer patients were enrolled was the single most important factor in determining the amount of OOP costs incurred, as had been similarly reported relative to other cancer patient populations (Table 4). 44,45 As such, colorectal cancer patients should be counseled about the options available to switch to a more favorable health insurance plan during the next available open enrollment period. Should patients decide to remain enrolled in a HDHP, the high deductibles associated with such plans may be at least partially offset by participation in a health savings account (HSA). Of note, however, significant raceand income-based disparities exist in HSA participation, to the point that not all patients may be able to benefit from the financial protection a HSA offers. 46 Several factors other than treatment options have an impact on OOP costs associated with cancer care, including the setting in which the treatment is provided and the involvement of out-ofnetwork providers at in-network hospitals. 2,47,48 Transparency in patient-provider cost discussions about such factors would greatly limit their impact on the OOP costs associated with surgical treatment of colorectal cancer.
Several limitations should be considered when interpreting the results of the current study. The IBM MarketScan commercial database is based on a large, nonrandom convenience sample that may lead to a sample bias (i.e., the South portion of the USA overrepresented), leading to lack of generalizability. 49 As with all studies relying on administrative databases, only variables associated with specific ICD or CPT codes could be examined. As such, no information on tumor stage or guideline-concordant care was available. This shortcoming is particularly relevant because associations between factors such as region of residence and OOP costs may be at least in part explained by differences in tumor stage at presentation. Additionally, the current study only included commercially insured individuals, who represent approximately twothirds of the US population. 50 As such, results of the current study cannot be extrapolated to patients who are insured through a public plan or are uninsured. Moreover, information on monthly premiums paid by patients was not available. Since premiums represent a portion of OOP costs for commercially insured individuals and differ based on plan type, we were limited in our ability to assess the financial OOP burden associated with each plan type. Of note, the current study only considered direct OOP costs associated with cancer treatment. However, indirect costs associated with transportation or lost income may be equally as impactful on patient finances. 51 Lastly, patients included in the current study underwent surgery between 2013 and 2017. The ongoing coronavirus disease 2019  pandemic is likely to have had a large impact on the costs of cancer care by means of delayed or skipped cancer screening, postponed or missed cancer treatment, and insurance coverage disruptions. 52,53 The current study could not capture these recent changes.
In conclusion, privately insured patients who underwent surgical resection of colorectal cancer paid a median of US$4417 in OOP costs within 1 year prior and 1 year after surgery, which corresponded to 4.5% of total costs. Notably, OOP costs varied widely with receipt of chemotherapy or radiotherapy, region of residence, employment status, and health insurance plan type. By providing estimates of excess OOP costs associated with several patient-and treatment-level factors, results of the current study may inform patient-provider discussions on treatment preferences. Specifically, these data may assist patients in assessing the cost-benefit ratio of various treatment options, plan around the expenses associated with cancer care, and be promptly referred to financial navigation services if difficulties with payments are expected. The data highlight the need for policies to ensure that OOP costs do not dissuade cancer patients from seeking optimal care.