Associations Between Patient Experience With Care, Race and Ethnicity, and Receipt of CRC Treatment Among SEER-CAHPS Patients With Multiple Comorbidities

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Stephanie Navarro Department of Population and Public Health Sciences, Keck School of Medicine of USC, Los Angeles, California

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Jennifer Tsui Department of Population and Public Health Sciences, Keck School of Medicine of USC, Los Angeles, California
USC Norris Comprehensive Cancer Center, Los Angeles, California

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Afsaneh Barzi City of Hope Comprehensive Cancer Center, Duarte, California

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Mariana C. Stern Department of Population and Public Health Sciences, Keck School of Medicine of USC, Los Angeles, California
USC Norris Comprehensive Cancer Center, Los Angeles, California

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Trevor Pickering Department of Population and Public Health Sciences, Keck School of Medicine of USC, Los Angeles, California

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Albert J. Farias Department of Population and Public Health Sciences, Keck School of Medicine of USC, Los Angeles, California
USC Norris Comprehensive Cancer Center, Los Angeles, California

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Background: Patients with colorectal cancer (CRC) and multiple comorbidities are less likely to receive guideline-concordant treatment (GCT), a disparity exacerbated by racial and ethnic disparities in GCT. Yet, positive patient experiences with care are associated with more appropriate care use. We investigated associations between patient experiences with care, race and ethnicity, and receipt of GCT for CRC among older adults with multiple comorbidities. Methods: We used SEER-Consumer Assessment of Healthcare Providers and Systems (CAHPS) data to identify participants diagnosed with CRC from 2001 to 2017 at age ≥67 years with additional chronic conditions. Stage-specific GCT was identified following recommendations in the NCCN Guidelines for Colon and Rectal Cancer. Patient experiences with care were identified from CAHPS surveys. Multivariable log-binomial regression estimated associations between race and ethnicity and receipt of GCT by experiences with care. Results: A total of 2,612 patients were included. Those reporting excellent experience with getting care quickly were 5% more likely to receive GCT than those reporting less-than-excellent experience (relative risk [RR], 1.05; 95% CI, 1.04–1.05). When reporting less-than-excellent experience with getting care quickly, non-Hispanic Black (NHB) patients were less likely than non-Hispanic White (NHW) patients to receive GCT (RR, 0.80; 99.38% CI, 0.78–0.82), yet NHB patients were more likely to receive GCT than NHW patients when reporting excellent experience (RR, 1.05; 99.38% CI, 1.02–1.09). When reporting less-than-excellent experience with getting needed care, Hispanic patients were less likely than NHW patients to receive GCT (RR, 0.91; 99.38% CI, 0.88–0.94), yet Hispanic patients were more likely to receive GCT than NHW patients when reporting excellent experience (RR, 1.06; 99.38% CI, 1.03–1.08). Conclusions: Although excellent patient experience among those with multiple comorbidities may not be strongly associated with receipt of GCT for CRC overall, improvements in experiences of accessing care among NHB and Hispanic patients with CRC and additional comorbidities may aid in mitigating racial and ethnic disparities in receipt of GCT.

Background

Patients with colorectal cancer (CRC) and comorbid chronic conditions are less likely to receive curative surgical resection, adjuvant chemotherapy, and surveillance colonoscopy.16 Despite potential complications associated with additional chronic conditions, several studies have demonstrated that the use of guideline-concordant treatment (GCT) among this patient group may present little to no additional risks to patient safety under certain circumstances and that clinical outcomes may improve when patients receive GCT.79 In fact, the NCCN Clinical Practice Guidelines in Oncology (NCCN Guidelines) for Older Adult Oncology10 recommend that older adults with multiple comorbidities be considered as candidates for GCT on a case-by-case basis, with consideration of comorbidity management and discussion between providers and patients.

Further complicating disparities in receipt of GCT for CRC among patients with multiple comorbidities are racial and ethnic disparities in receipt of GCT. Compared with non-Hispanic White (NHW) patients, non-Hispanic Black (NHB) and Hispanic patients are more likely to experience delays in receipt of GCT, and NHB patients are less likely to receive surgical resection, chemotherapy, radiotherapy, and surveillance colonoscopy after a CRC diagnosis.1113

To identify specific aspects of health care provision that can be strengthened to address disparities in care, patient experiences with care can be measured as a component of patient-reported care quality. Patient experiences with care are derived from subjective patient reports of interactions with health care providers and the health care system, and are associated with objective measures of care quality and outcomes of care.1416 Patient experiences with aspects of care such as physician communication may be especially important among those with CRC and comorbid chronic conditions; NCCN Guidelines for Older Adult Oncology recommend communication between patients, primary care providers, and specialty providers in order to provide care that is as effective and safe as possible for each individual patient.10

Yet, experiences with care are not equal for all patients, with consistent disparities reported for patients of different races and ethnicities and for patients with an increasing number of comorbidities.1719 Therefore, understanding how differences in experiences with care are associated with differential outcomes may be useful in identifying where care may be improved in order to mitigate disparities. Accordingly, among patients with CRC and comorbid chronic conditions, this study aims to understand whether patient experiences with care are associated with receipt of stage-specific GCT for CRC and how these associations might change by patient race and ethnicity. We hypothesized that better experiences with care would be associated with increased likelihoods of receiving GCT as well as mitigation of racial and ethnic disparities in receipt of GCT.

Methods

This study used SEER-Consumer Assessment of Healthcare Providers and Systems (CAHPS) data. SEER-CAHPS is a nationally representative and population-based data set that includes linked data from the SEER cancer database (including registry reported information on individual patient cancer diagnoses, first course of treatment, and patient characteristics), Medicare beneficiary enrollment and claims files (including information on all individual patient care received through Medicare fee-for-service claims as well as patient characteristics), and Medicare CAHPS patient experience surveys (including information from individual patient responses to surveys of experiences with care as well as patient-reported demographics). A complete description of this data has been described elsewhere.20 Use of these data and completion of this study with regard to the protection of human subjects was approved by the University of Southern California Institutional Review Board (HS-22-00034).

SEER-CAHPS participants were included in this study if they were diagnosed with stage I–III CRC from 2001 to 2017, were at least aged 67 years at diagnosis, had continuous Medicare Parts A and B coverage and no Medicare Part C coverage from 24 months before to 24 months after CRC diagnosis, completed a CAHPS patient experience survey within 3 years before to 3 years after diagnosis, and met diagnostic inclusion criteria for 1 of 3 chronic conditions prior to CRC diagnosis. To ensure complete and accurate identification of the health services received, patients with Medicare Part C coverage were excluded because care received through Medicare Part C was not available in Medicare claims data included in the SEER-CAHPS data set. A complete flowchart of cohort selection is included in supplemental eFigure 1 (available with this article at JNCCN.org).

Comorbid Chronic Conditions

Comorbid chronic condition–defining diagnoses included diabetes, hyperlipidemia, and hypertension, which constitute the 3 most prevalent Centers for Medicare & Medicaid Services (CMS)–defined chronic conditions that are sensitive to ambulatory care and present a relatively low risk of short-term mortality.21 Chronic condition diagnoses were identified through the use of CMS algorithms in Medicare claims files.22 Supplemental eTable 1 provides a complete description of this process.

Patient Race and Ethnicity

Individual patient race and ethnicity information was derived from self-report on Medicare CAHPS surveys. Patients were first identified as Hispanic or non-Hispanic and, if non-Hispanic, were identified as NHW, NHB, or non-Hispanic Asian (NHA). If CAHPS data on race and ethnicity were not available, then these data were derived from SEER registry data or from Medicare beneficiary enrollment files if not available within CAHPS or SEER data.

CAHPS Patient Experiences With Care

The Medicare CAHPS survey is a validated tool for understanding patient views of their health care providers and systems.2325 This study investigated CAHPS composite measures of experiences with getting care quickly, getting needed care, and physician communication. Composite measure scores range from 0 to 100 and are computed by combining answers to survey questions that ask about care received within domains of care provision. As composite scores tend to cluster at the upper end of the rating scales, to use composite scores as main independent variables in our study, we categorized scores ≥90 as “excellent” and scores <90 as “less than excellent,” as previous work has done.2628

Receipt of GCT

GCT for CRC was defined following NCCN stage-specific guidelines for the treatment of colon and rectal cancer.29,30 We aimed to determine the receipt of standard patterns of treatment within general stage groupings (stage I, II, or III) for colon and rectal cancer, including care received from the time of surgical resection (as the most important component of curative treatment of CRC) to receipt of adjuvant therapy or cancer surveillance (dependent on general stage group). For those diagnosed with stage I or II CRC, GCT was defined as the receipt of surgical resection within 6 months of CRC diagnosis, followed by surveillance colonoscopy within 6 to 18 months of surgery. Because NCCN Guidelines recommend a colonoscopy 12 months after surgery, this window aimed to capture all colonoscopies completed within a reasonable amount of time surrounding this target date. For patients diagnosed with stage III CRC, GCT was defined as the receipt of surgical resection within 6 months of CRC diagnosis, followed by adjuvant chemotherapy within 6 months of surgery.29,30 Receipt of surgical resection within 6 months of CRC diagnosis was first determined in either Medicare claims files or SEER registry information. Subsequently, adjuvant and surveillance procedures were identified in Medicare claims files using approaches outlined in previous work.3134 A summary of this approach is described in supplemental eTable 2.

Covariates

Covariates included as potential confounding factors between patient experiences with care and receipt of GCT and/or patient race and ethnicity and receipt of GCT included patient age at diagnosis, sex (male, female), education level (less than high school, high school, greater than high school), area-level poverty concentration (0 to <10%, 10% to <20%, ≥20%), SEER region (West, Midwest, Northeast, South), months from CRC diagnosis to CAHPS survey completion, year of CRC diagnosis, CRC stage at diagnosis (I, II, III), modified Charlson comorbidity index score in the 12 months prior to CRC diagnosis (0, 1, ≥2), and diagnoses of diabetes, hyperlipidemia, and hypertension.

Statistical Analyses

Descriptive statistics reported patient characteristics by patient race and ethnicity, experiences with care, and receipt of GCT using chi-square (or the Monte Carlo estimate of Fisher exact test when cell counts were <5), ANOVA, and Kruskal-Wallis tests. Simple survey-weighted multivariable log-binomial regression estimated associations between patient experiences with care and receipt of GCT. Findings were considered statistically significant when P<.05. Simple survey weights were provided in SEER-CAHPS data and yield estimates that reflect Medicare beneficiary populations of each US state.35 Simple survey-weighted multivariable log-binomial regression also estimated associations between race and ethnicity and receipt of GCT by experiences with care through the inclusion of product interaction terms between race and ethnicity and experiences with care. Findings of models measuring interaction effects were considered statistically significant when P<.00625, using a Bonferroni corrected α level to account for a total of 8 multiple comparisons. Analyses were performed using SAS 9.4 (SAS Institute Inc.).

Results

This study included 2,612 SEER-CAHPS patients with CRC, including 2,224 (85.2%) NHW, 148 (5.7%) NHB, 125 (4.8%) Hispanic, and 115 (4.4%) NHA. Compared with all other racial and ethnic groups, NHW participants were slightly older at CRC diagnosis (mean age, 78.1 vs <76.5 years; P<.0001). Among all racial and ethnic groups, NHB patients had the highest proportion with a modified Charlson comorbidity index score ≥2 (29.1%), and NHA patients had the lowest proportion (11.3%; P=.0058). NHB patients had the highest proportions of those with diabetes (52.7%; P=.0003) and hypertension (>90%; P=.0098), whereas NHA patients had the highest proportion of those with hyperlipidemia (80.0%; P=.2032) (Table 1). The characteristics of our study cohort by experiences with care are reported in supplemental eTable 3.

Table 1.

Patient Characteristics

Table 1.

Patients who received stage-specific GCT were younger (mean age, 76.0 vs 78.9 years; P<.0001) and had a higher proportion with greater than high school education (44.1% vs 36.8%; P<.0001) compared with those who did not receive GCT. Lower proportions of those who received GCT had a modified Charlson comorbidity index score of ≥2 (16.4% vs 24.5%; P<.0001) and a diagnosis of hypertension (83.2% vs 87.5%; P=.0022) (Table 2).

Table 2.

Distribution of Patient Characteristics by Receipt of Stage-Specific Guideline-Concordant Treatment of CRC

Table 2.

In multivariable models among our entire cohort, those reporting excellent experience with getting care quickly were 5% more likely to receive GCT compared with those who reported less-than-excellent experience with this measure (RR, 1.05, 95% CI, 1.04–1.05). However, we did not find that excellent experiences with getting needed care or physician communication were associated with greater likelihoods of receiving stage-specific GCT compared with less-than-excellent experiences (Table 3).

Table 3.

Likelihood of Receiving Stage-Specific GCT of CRC by CAHPS Patient Experiences With Carea

Table 3.

Among reporting less-than-excellent experience with getting care quickly, NHB patients were 20% less likely than NHW patients to receive stage-specific GCT (RR, 0.80; 99.38% CI, 0.78–0.82). However, among those reporting excellent experience with getting care quickly, NHB patients were 5% more likely than NHW patients to receive GCT (RR, 1.05; 99.38% CI, 1.02–1.09). Among those reporting less-than-excellent experience with getting needed care, Hispanic patients were 9% less likely than NHW patients to receive GCT (RR, 0.91; 99.38% CI, 0.88–0.94). However, among those reporting excellent experience with getting needed care, Hispanic patients were 6% more likely than NHW patients to receive GCT (RR, 1.06; 99.38% CI, 1.03–1.08) (Table 4).

Table 4.

Likelihood of Receiving Stage-Specific GCT of CRC by CAHPS Patient Experiences With Care and Patient Race and Ethnicitya

Table 4.

Discussion

Among SEER-CAHPS patients with CRC and comorbid chronic conditions, excellent (compared with less-than-excellent) patient experiences with getting care quickly were associated with a marginally increased likelihood of receiving GCT. Additionally, compared with NHW patients, disparities in receiving GCT among NHB patients reporting less-than-excellent experience with getting care quickly and among Hispanic patients reporting less-than-excellent experience with getting needed care were reversed when NHB and Hispanic patients reported excellent experiences with these measures.

Experience With Getting Care Quickly Among NHB Patients

Previous analyses of SEER-CAHPS data have revealed that although NHB patients with CRC rate experiences with getting care quickly lower than NHW patients, excellent experiences of getting care quickly among NHB patients are associated with better CRC outcomes, such as lower stage at diagnosis.36,37 However, our study is the first to demonstrate that disparities in NHB patient experiences with getting care quickly may also be related to disparities in receiving stage-specific GCT for CRC. In fact, research has found that patient race and ethnicity may be one of the most influential factors mediating cancer treatment delays, which may be reflected in lower scores for patient experiences with ability to get care quickly and contribute to disparities in receipt of GCT.12,3841 Furthermore, previous work has found that the factors mediating relationships between minority race and ethnicity and cancer treatment delays may include socioeconomic status, comorbidity load, and type of care facility delivering treatment.12,39,41,42 Although these individual patient factors are largely nonmodifiable in the relatively short time from cancer diagnosis to the first course of treatment, successful interventions have promoted racial and ethnic equity in timely cancer care through the use of oncology patient navigation programs as well as the use of an antiracist framework implementing timely reminders to providers and patient navigators.4345 Thus, comparable interventions may be effective in promoting racial and ethnic equity in experiences of getting care quickly as well as in receipt of stage-specific GCT for CRC among NHB older adults with comorbid chronic conditions.

Experience With Getting Needed Care Among Hispanic Patients

We also found that improvements in patient experiences of getting needed care among Hispanic patients may mitigate racial and ethnic disparity in receiving GCT compared with NHW patients. Disparities in access to care for CRC among Hispanic patients compared with NHW patients are well-described in the literature.12,46,47 In addition, compared with NHW patients, Hispanic patients disproportionately receive care at less-resourced hospitals with worse overall clinical and quality-of-care outcomes.4850 One scoping review found that interventions increasing trust, cultural competency, enrollment in clinical trials, and representation within the health care workforce may be effective in increasing Hispanic patient access to care.51 Thus, similar interventions may be impactful in both improving Hispanic patient experiences of getting needed care as well as receipt of stage-specific GCT for CRC among older adult Hispanic patients with comorbid chronic conditions.

GCT for CRC Among Older Adults With Comorbid Chronic Conditions

Despite findings regarding associations between experiences with care and racial and ethnic disparities in receipt of GCT, we did not find that excellent experiences with getting needed care or with physician communication were associated with a greater likelihood of receiving GCT among older adults with CRC and comorbid chronic conditions overall. In addition, we found that, compared with those reporting less-than-excellent experience, excellent experiences with getting care quickly were associated with only a marginally greater likelihood of receiving GCT. Snyder et al52 found similar results of no differences in patient experiences among those who received GCT for colon cancer and those who did not among SEER-CAHPS participants. However, our cohort of participants with multiple comorbidities makes our findings unique. In particular, patients with a higher number of chronic conditions are more likely to adopt a usual source of health care and are less likely to lose their usual source of care.53,54 Patients with multiple comorbidities are also more likely to be enrolled in chronic care management, suggesting that participants in our cohort may have been more likely to receive intensive care from a trusted care team, reflected in positive reports of experiences with care.55 In addition, as individual patient comorbidity load and complexity of comorbidities increase, individuals with CRC are less likely to receive GCT due to an increased risk of complications.56 Thus, our findings of excellent experiences with care not being associated with any substantial increases in the likelihoods of receiving GCT may be partially explained by residual confounding due to an increased use of comprehensive and continuous care management among those with higher comorbidity loads.

Strengths and Limitations

The use of nationally representative and population-based SEER-CAHPS data allowed for a large and reasonably representative sample of Medicare beneficiaries with CRC and comorbid chronic conditions. These data also allowed chronic condition diagnoses and receipt of GCT to be identified from Medicare claims files, which are highly reliable in identifying specific diagnoses and treatments.57,58 SEER-CAHPS data also allowed us to control for a thorough list of individual sociodemographic and clinical factors that may act as confounding variables.

However, this study was cross-sectional in nature, and we cannot show any directional effect. In addition, we were unable to control for additional factors such as the type of hospital where CRC treatment was received, patient proximity to health care, and individual income, which may act as residual confounding variables. Furthermore, NHW Medicare beneficiaries have higher response rates to Medicare CAHPS surveys than racial and ethnic minority beneficiaries, which may introduce participation bias into our study.59 Nonetheless, the use of survey weighting allowed survey responses to be representative of the population enrolled in Medicare fee-for-service in each US state.

Lastly, to achieve a sufficient sample size and focus on experiences with care around the time of CRC diagnosis and first course of treatment, we included CAHPS survey responses from a relatively wide window surrounding CRC diagnosis. However, sensitivity analyses revealed that the findings did not substantially differ when limiting to smaller windows of survey completion, and multivariable analyses controlled for time from CRC diagnosis to CAHPS survey.

Conclusions

Among Medicare fee-for-service beneficiaries with CRC and comorbid chronic conditions, patients reporting excellent experiences with getting care quickly were only marginally more likely to receive stage-specific GCT for CRC than those reporting less-than-excellent experience. Nonetheless, compared with NHW participants, there are disparities in receiving GCT among NHB and Hispanic participants reporting less-than-excellent experiences with getting care quickly and getting needed care. Efforts to improve experiences with getting care quickly and getting needed care may help to alleviate disparities in receipt of GCT among NHB and Hispanic beneficiaries with CRC and comorbid chronic conditions.

References

  • 1.

    Lemmens VE, Janssen-Heijnen ML, Verheij CD, et al. Co-morbidity leads to altered treatment and worse survival of elderly patients with colorectal cancer. Br J Surg 2005;92:615623.

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 2.

    Boakye D, Nagrini R, Ahrens W, et al. The association of comorbidities with administration of adjuvant chemotherapy in stage III colon cancer patients: a systematic review and meta-analysis. Ther Adv Med Oncol 2021;13:1758835920986520.

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 3.

    Etzioni DA, El-Khoueiry AB, Beart RW Jr. Rates and predictors of chemotherapy use for stage III colon cancer: a systematic review. Cancer 2008;113:32793289.

  • 4.

    Gross CP, McAvay GJ, Guo Z, et al. The impact of chronic illnesses on the use and effectiveness of adjuvant chemotherapy for colon cancer. Cancer 2007;109:24102419.

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 5.

    Sisler JJ, Seo B, Katz A, et al. Concordance with ASCO guidelines for surveillance after colorectal cancer treatment: a population-based analysis. J Oncol Pract 2012;8:e6979.

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 6.

    Ford ME, Sterba KR, Armeson K, et al. Factors influencing adherence to recommended colorectal cancer surveillance: experiences and behaviors of colorectal cancer survivors. J Cancer Educ 2019;34:938949.

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 7.

    Peltrini R, Imperatore N, Carannante F, et al. Age and comorbidities do not affect short-term outcomes after laparoscopic rectal cancer resection in elderly patients. A multi-institutional cohort study in 287 patients. Updates Surg 2021;73:527537.

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 8.

    Cronin DP, Harlan LC, Potosky AL, et al. Patterns of care for adjuvant therapy in a random population-based sample of patients diagnosed with colorectal cancer. Am J Gastroenterol 2006;101:23082318.

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 9.

    Lemmens VE, Janssen-Heijnen ML, Houterman S, et al. Which comorbid conditions predict complications after surgery for colorectal cancer? World J Surg 2007;31:192199.

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 10.

    Dotan E, Walter LC, Beechinor R, et al. NCCN Clinical Practice Guidelines in Oncology: Older Adult Oncology. Version 1.2023. Accessed February 20, 2023. To view the most recent version, visit https://www.nccn.org

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 11.

    Simpson DR, Martínez ME, Gupta S, et al. Racial disparity in consultation, treatment, and the impact on survival in metastatic colorectal cancer. J Natl Cancer Inst 2013;105:18141820.

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 12.

    Obrochta CA, Murphy JD, Tsou MH, et al. Disentangling racial, ethnic, and socioeconomic disparities in treatment for colorectal cancer. Cancer Epidemiol Biomarkers Prev 2021;30:15461553.

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 13.

    Sanchez JI, Shankaran V, Unger JM, et al. Inequitable access to surveillance colonoscopy among Medicare beneficiaries with surgically resected colorectal cancer. Cancer 2021;127:412421.

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 14.

    Anhang Price R, Elliott MN, Zaslavsky AM, et al. Examining the role of patient experience surveys in measuring health care quality. Med Care Res Rev 2014;71:522554.

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 15.

    Navarro S, Ochoa CY, Chan E, et al. Will improvements in patient experience with care impact clinical and quality of care outcomes?: a systematic review. Med Care 2021;59:843856.

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 16.

    Agency for Healthcare Research and Quality. What is patient experience? Accessed March 6, 2023. Available at: https://www.ahrq.gov/cahps/about-cahps/patient-experience/index.html

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 17.

    Martino SC, Mathews M, Agniel D, et al. National racial/ethnic and geographic disparities in experiences with health care among adult Medicaid beneficiaries. Health Serv Res 2019;54(Suppl 1):287296.

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 18.

    Halpern MT, Urato MP, Lines LM, et al. Healthcare experience among older cancer survivors: analysis of the SEER-CAHPS dataset. J Geriatr Oncol 2018;9:194203.

  • 19.

    Orr N, Elliott MN, Burkhart Q, et al. Racial/Ethnic differences in Medicare experiences and immunization: the role of disease burden. Med Care 2013;51:823831.

  • 20.

    Chawla N, Urato M, Ambs A, et al. Unveiling SEER-CAHPS: a new data resource for quality of care research. J Gen Intern Med 2015;30:641650.

  • 21.

    Centers for Medicare & Medicaid Services. Chronic conditions overview. Accessed November 23, 2021. Available at: https://www.cms.gov/Research-Statistics-Data-and-Systems/Statistics-Trends-and-Reports/Chronic-Conditions

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 22.

    Chronic Conditions Data Warehouse. 27 CCW chronic conditions (1999–2021). Accessed October 28, 2022. Available at: https://www2.ccwdata.org/web/guest/condition-categories-chronic

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 23.

    Hays RD, Shaul JA, Williams VS, et al. Psychometric properties of the CAHPS 1.0 survey measures. Med Care 1999;37(3 Suppl):MS2231.

  • 24.

    Cleary PD, Lubalin J, Hays RD, et al. Debating survey approaches. Health Aff (Millwood) 1998;17:265268.

  • 25.

    Hargraves JL, Hays RD, Cleary PD. Psychometric properties of the Consumer Assessment of Health Plans Study (CAHPS) 2.0 adult core survey. Health Serv Res 2003;38:15091528.

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 26.

    Arevalo M, Pickering TA, Vernon SW, et al. Do breast cancer survivors with a recent history of clinical depression report worse experiences with care? A retrospective cohort study using SEER-CAHPS data. Cancer Med 2023;12:19491960.

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 27.

    Mohan CS, Rotter JS, Tan HJ, et al. The association between patient experience and healthcare outcomes using SEER-CAHPS patient experience and outcomes among cancer survivors. J Geriatr Oncol 2021;12:623631.

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 28.

    Lines LM, Cohen J, Halpern MT, et al. Care experiences among dually enrolled older adults with cancer: SEER-CAHPS, 2005–2013. Cancer Causes Control 2019;30:11371144.

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 29.

    Benson AB III, Venook AP, Al-Hawary MM, et al. NCCN Clinical Practice Guidelines in Oncology: Colon Cancer. Version 2.2023. Accessed April 28, 2023. To view the most recent version, visit https://www.nccn.org

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 30.

    Benson AB III, Venook AP, Al-Hawary MM, et al. NCCN Clinical Practice Guidelines in Oncology: Rectal Cancer. Version 4.2023. Accessed July 27, 2023. To view the most recent version, visit https://www.nccn.org

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 31.

    Hines RB, Jiban MJH, Specogna AV, et al. Surveillance colonoscopy in older stage I colon cancer patients and the association with colon cancer-specific mortality. Am J Gastroenterol 2020;115:924933.

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 32.

    Ramkumar N, Colla CH, Wang Q, et al. Association of rurality, race and ethnicity, and socioeconomic status with the surgical management of colon cancer and postoperative outcomes among Medicare beneficiaries. JAMA Netw Open 2022;5:e2229247.

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 33.

    Fisher DA, Princic N, Miller-Wilson LA, et al. Utilization of a colorectal cancer screening test among individuals with average risk. JAMA Netw Open 2021;4:e2122269.

  • 34.

    Méndez-Bailón M, Jiménez-García R, Muñoz-Rivas N, et al. Trends and clinical impact of gastrointestinal endoscopic procedures on acute heart failure in Spain (2002–2017). J Clin Med 2021;10:546.

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 35.

    National Cancer Institute Division of Cancer Control & Population Sciences. Survey weights. Accessed January 26, 2023. Available at: https://healthcaredelivery.cancer.gov/seer-cahps/researchers/weights.html

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 36.

    Wardrop RC, Cass AL, Quinn SA, et al. Racial and ethnic differences in patient ratings of colorectal and non-small-cell lung cancer care: a SEER-CAHPS study. Cancer Causes Control 2022;33:11251133.

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 37.

    Farias AJ, Toledo G, Ochoa CY, et al. Racial/Ethnic disparities in patient experiences with health care in association with earlier stage at colorectal cancer diagnosis: findings from the SEER-CAHPS data. Med Care 2021;59:295303.

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 38.

    Frankenfeld CL, Menon N, Leslie TF. Racial disparities in colorectal cancer time-to-treatment and survival time in relation to diagnosing hospital cancer-related diagnostic and treatment capabilities. Cancer Epidemiol 2020;65:101684.

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 39.

    Emerson MA, Golightly YM, Aiello AE, et al. Breast cancer treatment delays by socioeconomic and health care access latent classes in Black and white women. Cancer 2020;126:49574966.

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 40.

    Halpern MT, Holden DJ. Disparities in timeliness of care for U.S. Medicare patients diagnosed with cancer. Curr Oncol 2012;19:e404413.

  • 41.

    Kumar V, Alhaj-Moustafa M, Bojanini L, et al. Timeliness of initial therapy in multiple myeloma: trends and factors affecting patient care. JCO Oncol Pract 2020;16:e341349.

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 42.

    Grunvald MW, Underhill JM, Skertich NJ, et al. Mediating factors between race and time to treatment in colorectal cancer. Dis Colon Rectum 2023;66:331336.

  • 43.

    Charlot M, Stein JN, Damone E, et al. Effect of an antiracism intervention on racial disparities in time to lung cancer surgery. J Clin Oncol 2022;40:17551762.

  • 44.

    Freund KM, Battaglia TA, Calhoun E, et al. Impact of patient navigation on timely cancer care: the Patient Navigation Research Program. J Natl Cancer Inst 2014;106:dju115.

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 45.

    Roland KB, Milliken EL, Rohan EA, et al. Use of community health workers and patient navigators to improve cancer outcomes among patients served by federally qualified health centers: a systematic literature review. Health Equity 2017;1:6176.

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 46.

    Hendren S, Chin N, Fisher S, et al. Patients’ barriers to receipt of cancer care, and factors associated with needing more assistance from a patient navigator. J Natl Med Assoc 2011;103:701710.

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 47.

    Haas JS, Brawarsky P, Iyer A, et al. Association of area sociodemographic characteristics and capacity for treatment with disparities in colorectal cancer care and mortality. Cancer 2011;117:42674276.

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 48.

    Zhang W, Ayanian JZ, Zaslavsky AM. Patient characteristics and hospital quality for colorectal cancer surgery. Int J Qual Health Care 2007;19 19 1120.

  • 49.

    Huang LC, Tran TB, Ma Y, et al. Factors that influence minority use of high-volume hospitals for colorectal cancer care. Dis Colon Rectum 2015;58:526532.

  • 50.

    Epstein AJ, Gray BH, Schlesinger M. Racial and ethnic differences in the use of high-volume hospitals and surgeons. Arch Surg 2010;145:179186.

  • 51.

    Kronenfeld JP, Graves KD, Penedo FJ, et al. Overcoming disparities in cancer: a need for meaningful reform for Hispanic and Latino cancer survivors. Oncologist 2021;26:443452.

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 52.

    Snyder RA, Wardrop R, McLain AC, et al. Association of patient experience with guideline-concordant colon cancer treatment in the elderly. JCO Oncol Pract 2021;17:e753763.

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 53.

    Nothelle SK, Boyd C, Sheehan O, et al. Factors associated with loss of usual source of care among older adults. Ann Fam Med 2018;16:538545.

  • 54.

    Stransky ML. Two-year stability and change in access to and reasons for lacking a usual source of care among working-age US adults. Public Health Rep 2017;132:660668.

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 55.

    Campbell C, Craig J, Eggert J, et al. Implementing and measuring the impact of patient navigation at a comprehensive community cancer center. Oncol Nurs Forum 2010;37:6168.

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 56.

    Hahn EE, Gould MK, Munoz-Plaza CE, et al. Understanding comorbidity profiles and their effect on treatment and survival in patients with colorectal cancer. J Natl Compr Canc Netw 2018;16:2334.

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 57.

    Lavery JA, Lipitz-Snyderman A, Li DG, et al. Identifying cancer-directed surgeries in Medicare claims: a validation study using SEER-Medicare data. JCO Clin Cancer Inform 2019;3:124.

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 58.

    Brault MW, Landon BE, Zaslavsky AM. Validating reports of chronic conditions in the Medicare CAHPS survey. Med Care 2019;57:830835.

  • 59.

    Klein DJ, Elliott MN, Haviland AM, et al. Understanding nonresponse to the 2007 Medicare CAHPS survey. Gerontologist 2011;51:843855.

Submitted April 24, 2023; final revision received August 8, 2023; accepted for publication August 17, 2023. Published online December 27, 2023.

Author contributions: Study concept and design: All authors. Data acquisition: Navarro, Farias. Data analysis: Navarro. Data interpretation: All authors. Writing—original draft: Navarro. Writing—review & editing: All authors.

Disclosures: The authors have disclosed that they have not received any financial consideration from any person or organization to support the preparation, analysis, results, or discussion of this article.

Funding: Research reported in this publication was supported by the National Cancer Institute of the National Institutes of Health under award number F30CA268735 (S. Navarro).

Disclaimer: The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.

Correspondence: Stephanie Navarro, PhD, Department of Population and Public Health Sciences, Keck School of Medicine of USC, 1845 North Soto Street, Los Angeles, CA 90032. Email: stephaan@usc.edu

Supplementary Materials

  • Collapse
  • Expand
  • 1.

    Lemmens VE, Janssen-Heijnen ML, Verheij CD, et al. Co-morbidity leads to altered treatment and worse survival of elderly patients with colorectal cancer. Br J Surg 2005;92:615623.

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 2.

    Boakye D, Nagrini R, Ahrens W, et al. The association of comorbidities with administration of adjuvant chemotherapy in stage III colon cancer patients: a systematic review and meta-analysis. Ther Adv Med Oncol 2021;13:1758835920986520.

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 3.

    Etzioni DA, El-Khoueiry AB, Beart RW Jr. Rates and predictors of chemotherapy use for stage III colon cancer: a systematic review. Cancer 2008;113:32793289.

  • 4.

    Gross CP, McAvay GJ, Guo Z, et al. The impact of chronic illnesses on the use and effectiveness of adjuvant chemotherapy for colon cancer. Cancer 2007;109:24102419.

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 5.

    Sisler JJ, Seo B, Katz A, et al. Concordance with ASCO guidelines for surveillance after colorectal cancer treatment: a population-based analysis. J Oncol Pract 2012;8:e6979.

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 6.

    Ford ME, Sterba KR, Armeson K, et al. Factors influencing adherence to recommended colorectal cancer surveillance: experiences and behaviors of colorectal cancer survivors. J Cancer Educ 2019;34:938949.

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 7.

    Peltrini R, Imperatore N, Carannante F, et al. Age and comorbidities do not affect short-term outcomes after laparoscopic rectal cancer resection in elderly patients. A multi-institutional cohort study in 287 patients. Updates Surg 2021;73:527537.

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 8.

    Cronin DP, Harlan LC, Potosky AL, et al. Patterns of care for adjuvant therapy in a random population-based sample of patients diagnosed with colorectal cancer. Am J Gastroenterol 2006;101:23082318.

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 9.

    Lemmens VE, Janssen-Heijnen ML, Houterman S, et al. Which comorbid conditions predict complications after surgery for colorectal cancer? World J Surg 2007;31:192199.

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 10.

    Dotan E, Walter LC, Beechinor R, et al. NCCN Clinical Practice Guidelines in Oncology: Older Adult Oncology. Version 1.2023. Accessed February 20, 2023. To view the most recent version, visit https://www.nccn.org

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 11.

    Simpson DR, Martínez ME, Gupta S, et al. Racial disparity in consultation, treatment, and the impact on survival in metastatic colorectal cancer. J Natl Cancer Inst 2013;105:18141820.

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 12.

    Obrochta CA, Murphy JD, Tsou MH, et al. Disentangling racial, ethnic, and socioeconomic disparities in treatment for colorectal cancer. Cancer Epidemiol Biomarkers Prev 2021;30:15461553.

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 13.

    Sanchez JI, Shankaran V, Unger JM, et al. Inequitable access to surveillance colonoscopy among Medicare beneficiaries with surgically resected colorectal cancer. Cancer 2021;127:412421.

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 14.

    Anhang Price R, Elliott MN, Zaslavsky AM, et al. Examining the role of patient experience surveys in measuring health care quality. Med Care Res Rev 2014;71:522554.

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 15.

    Navarro S, Ochoa CY, Chan E, et al. Will improvements in patient experience with care impact clinical and quality of care outcomes?: a systematic review. Med Care 2021;59:843856.

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 16.

    Agency for Healthcare Research and Quality. What is patient experience? Accessed March 6, 2023. Available at: https://www.ahrq.gov/cahps/about-cahps/patient-experience/index.html

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 17.

    Martino SC, Mathews M, Agniel D, et al. National racial/ethnic and geographic disparities in experiences with health care among adult Medicaid beneficiaries. Health Serv Res 2019;54(Suppl 1):287296.

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 18.

    Halpern MT, Urato MP, Lines LM, et al. Healthcare experience among older cancer survivors: analysis of the SEER-CAHPS dataset. J Geriatr Oncol 2018;9:194203.

  • 19.

    Orr N, Elliott MN, Burkhart Q, et al. Racial/Ethnic differences in Medicare experiences and immunization: the role of disease burden. Med Care 2013;51:823831.

  • 20.

    Chawla N, Urato M, Ambs A, et al. Unveiling SEER-CAHPS: a new data resource for quality of care research. J Gen Intern Med 2015;30:641650.

  • 21.

    Centers for Medicare & Medicaid Services. Chronic conditions overview. Accessed November 23, 2021. Available at: https://www.cms.gov/Research-Statistics-Data-and-Systems/Statistics-Trends-and-Reports/Chronic-Conditions

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 22.

    Chronic Conditions Data Warehouse. 27 CCW chronic conditions (1999–2021). Accessed October 28, 2022. Available at: https://www2.ccwdata.org/web/guest/condition-categories-chronic

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 23.

    Hays RD, Shaul JA, Williams VS, et al. Psychometric properties of the CAHPS 1.0 survey measures. Med Care 1999;37(3 Suppl):MS2231.

  • 24.

    Cleary PD, Lubalin J, Hays RD, et al. Debating survey approaches. Health Aff (Millwood) 1998;17:265268.

  • 25.

    Hargraves JL, Hays RD, Cleary PD. Psychometric properties of the Consumer Assessment of Health Plans Study (CAHPS) 2.0 adult core survey. Health Serv Res 2003;38:15091528.

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 26.

    Arevalo M, Pickering TA, Vernon SW, et al. Do breast cancer survivors with a recent history of clinical depression report worse experiences with care? A retrospective cohort study using SEER-CAHPS data. Cancer Med 2023;12:19491960.

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 27.

    Mohan CS, Rotter JS, Tan HJ, et al. The association between patient experience and healthcare outcomes using SEER-CAHPS patient experience and outcomes among cancer survivors. J Geriatr Oncol 2021;12:623631.

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 28.

    Lines LM, Cohen J, Halpern MT, et al. Care experiences among dually enrolled older adults with cancer: SEER-CAHPS, 2005–2013. Cancer Causes Control 2019;30:11371144.

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 29.

    Benson AB III, Venook AP, Al-Hawary MM, et al. NCCN Clinical Practice Guidelines in Oncology: Colon Cancer. Version 2.2023. Accessed April 28, 2023. To view the most recent version, visit https://www.nccn.org

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 30.

    Benson AB III, Venook AP, Al-Hawary MM, et al. NCCN Clinical Practice Guidelines in Oncology: Rectal Cancer. Version 4.2023. Accessed July 27, 2023. To view the most recent version, visit https://www.nccn.org

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 31.

    Hines RB, Jiban MJH, Specogna AV, et al. Surveillance colonoscopy in older stage I colon cancer patients and the association with colon cancer-specific mortality. Am J Gastroenterol 2020;115:924933.

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 32.

    Ramkumar N, Colla CH, Wang Q, et al. Association of rurality, race and ethnicity, and socioeconomic status with the surgical management of colon cancer and postoperative outcomes among Medicare beneficiaries. JAMA Netw Open 2022;5:e2229247.

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 33.

    Fisher DA, Princic N, Miller-Wilson LA, et al. Utilization of a colorectal cancer screening test among individuals with average risk. JAMA Netw Open 2021;4:e2122269.

  • 34.

    Méndez-Bailón M, Jiménez-García R, Muñoz-Rivas N, et al. Trends and clinical impact of gastrointestinal endoscopic procedures on acute heart failure in Spain (2002–2017). J Clin Med 2021;10:546.

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 35.

    National Cancer Institute Division of Cancer Control & Population Sciences. Survey weights. Accessed January 26, 2023. Available at: https://healthcaredelivery.cancer.gov/seer-cahps/researchers/weights.html

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 36.

    Wardrop RC, Cass AL, Quinn SA, et al. Racial and ethnic differences in patient ratings of colorectal and non-small-cell lung cancer care: a SEER-CAHPS study. Cancer Causes Control 2022;33:11251133.

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 37.

    Farias AJ, Toledo G, Ochoa CY, et al. Racial/Ethnic disparities in patient experiences with health care in association with earlier stage at colorectal cancer diagnosis: findings from the SEER-CAHPS data. Med Care 2021;59:295303.

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 38.

    Frankenfeld CL, Menon N, Leslie TF. Racial disparities in colorectal cancer time-to-treatment and survival time in relation to diagnosing hospital cancer-related diagnostic and treatment capabilities. Cancer Epidemiol 2020;65:101684.

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 39.

    Emerson MA, Golightly YM, Aiello AE, et al. Breast cancer treatment delays by socioeconomic and health care access latent classes in Black and white women. Cancer 2020;126:49574966.

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 40.

    Halpern MT, Holden DJ. Disparities in timeliness of care for U.S. Medicare patients diagnosed with cancer. Curr Oncol 2012;19:e404413.

  • 41.

    Kumar V, Alhaj-Moustafa M, Bojanini L, et al. Timeliness of initial therapy in multiple myeloma: trends and factors affecting patient care. JCO Oncol Pract 2020;16:e341349.

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 42.

    Grunvald MW, Underhill JM, Skertich NJ, et al. Mediating factors between race and time to treatment in colorectal cancer. Dis Colon Rectum 2023;66:331336.

  • 43.

    Charlot M, Stein JN, Damone E, et al. Effect of an antiracism intervention on racial disparities in time to lung cancer surgery. J Clin Oncol 2022;40:17551762.

  • 44.

    Freund KM, Battaglia TA, Calhoun E, et al. Impact of patient navigation on timely cancer care: the Patient Navigation Research Program. J Natl Cancer Inst 2014;106:dju115.

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 45.

    Roland KB, Milliken EL, Rohan EA, et al. Use of community health workers and patient navigators to improve cancer outcomes among patients served by federally qualified health centers: a systematic literature review. Health Equity 2017;1:6176.

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 46.

    Hendren S, Chin N, Fisher S, et al. Patients’ barriers to receipt of cancer care, and factors associated with needing more assistance from a patient navigator. J Natl Med Assoc 2011;103:701710.

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 47.

    Haas JS, Brawarsky P, Iyer A, et al. Association of area sociodemographic characteristics and capacity for treatment with disparities in colorectal cancer care and mortality. Cancer 2011;117:42674276.

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 48.

    Zhang W, Ayanian JZ, Zaslavsky AM. Patient characteristics and hospital quality for colorectal cancer surgery. Int J Qual Health Care 2007;19 19 1120.

  • 49.

    Huang LC, Tran TB, Ma Y, et al. Factors that influence minority use of high-volume hospitals for colorectal cancer care. Dis Colon Rectum 2015;58:526532.

  • 50.

    Epstein AJ, Gray BH, Schlesinger M. Racial and ethnic differences in the use of high-volume hospitals and surgeons. Arch Surg 2010;145:179186.

  • 51.

    Kronenfeld JP, Graves KD, Penedo FJ, et al. Overcoming disparities in cancer: a need for meaningful reform for Hispanic and Latino cancer survivors. Oncologist 2021;26:443452.

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 52.

    Snyder RA, Wardrop R, McLain AC, et al. Association of patient experience with guideline-concordant colon cancer treatment in the elderly. JCO Oncol Pract 2021;17:e753763.

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 53.

    Nothelle SK, Boyd C, Sheehan O, et al. Factors associated with loss of usual source of care among older adults. Ann Fam Med 2018;16:538545.

  • 54.

    Stransky ML. Two-year stability and change in access to and reasons for lacking a usual source of care among working-age US adults. Public Health Rep 2017;132:660668.

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 55.

    Campbell C, Craig J, Eggert J, et al. Implementing and measuring the impact of patient navigation at a comprehensive community cancer center. Oncol Nurs Forum 2010;37:6168.

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 56.

    Hahn EE, Gould MK, Munoz-Plaza CE, et al. Understanding comorbidity profiles and their effect on treatment and survival in patients with colorectal cancer. J Natl Compr Canc Netw 2018;16:2334.

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 57.

    Lavery JA, Lipitz-Snyderman A, Li DG, et al. Identifying cancer-directed surgeries in Medicare claims: a validation study using SEER-Medicare data. JCO Clin Cancer Inform 2019;3:124.

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 58.

    Brault MW, Landon BE, Zaslavsky AM. Validating reports of chronic conditions in the Medicare CAHPS survey. Med Care 2019;57:830835.

  • 59.

    Klein DJ, Elliott MN, Haviland AM, et al. Understanding nonresponse to the 2007 Medicare CAHPS survey. Gerontologist 2011;51:843855.

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