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Hidden Disparities: How Language Influences Patients' Access to Cancer Care.

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Journal of the National Comprehensive Cancer Network : JNCCN 2023 Vol.21(9) p. 951-959.e1
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Chen DW, Banerjee M, He X, Miranda L, Watanabe M, Veenstra CM, Haymart MR

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[BACKGROUND] Patients with limited English proficiency, a vulnerable patient population, remain understudied in the literature addressing cancer disparities.

🔬 핵심 임상 통계 (초록에서 자동 추출 — 원문 검증 권장)
  • 표본수 (n) 686
  • p-value P<.001
  • 95% CI 0.01-0.04

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BibTeX ↓ RIS ↓
APA Chen DW, Banerjee M, et al. (2023). Hidden Disparities: How Language Influences Patients' Access to Cancer Care.. Journal of the National Comprehensive Cancer Network : JNCCN, 21(9), 951-959.e1. https://doi.org/10.6004/jnccn.2023.7037
MLA Chen DW, et al.. "Hidden Disparities: How Language Influences Patients' Access to Cancer Care.." Journal of the National Comprehensive Cancer Network : JNCCN, vol. 21, no. 9, 2023, pp. 951-959.e1.
PMID 37673110

Abstract

[BACKGROUND] Patients with limited English proficiency, a vulnerable patient population, remain understudied in the literature addressing cancer disparities. Although it is well documented that language discordance between patients and physicians negatively impacts the quality of patient care, little is known about how patients' preferred spoken language impacts their access to cancer care.

[PATIENTS AND METHODS] Between November 2021 and June 2022, we conducted an audit study of 144 hospitals located across 12 demographically diverse states. Using a standardized script, trained investigators assigned to the roles of English-speaking, Spanish-speaking, and Mandarin-speaking patients called the hospital general information telephone line seeking to access care for 3 cancer types that disproportionately impact Hispanic and Asian populations (colon, lung, and thyroid cancer). Primary outcome was whether the simulated patient caller was provided with the next steps to access cancer care, defined as clinic number or clinic transfer. We used chi-square tests and logistic regression analysis to test for associations between the primary outcome and language type, region type, hospital teaching status, and cancer care requested. We used multivariable logistic regression analysis to determine factors associated with simulated patient callers being provided the next steps.

[RESULTS] Of the 1,296 calls, 52.9% (n=686) resulted in simulated patient callers being provided next steps to access cancer care. Simulated non-English-speaking (vs English-speaking) patient callers were less likely to be provided with the next steps (Mandarin, 27.5%; Spanish, 37.7%; English, 93.5%; P<.001). Multivariable logistic regression found significant associations of the primary outcome with language spoken (Mandarin: odds ratio [OR], 0.02 [95% CI, 0.01-0.04] and Spanish: OR, 0.04 [95% CI, 0.02-0.06] vs English) and hospital teaching status (nonteaching: OR, 0.43 [95% CI, 0.32-0.56] vs teaching).

[CONCLUSIONS] Linguistic disparities exist in access to cancer care for non-English-speaking patients, emphasizing the need for focused interventions to mitigate systems-level communication barriers.

MeSH Terms

Humans; Language; Thyroid Neoplasms; Ambulatory Care Facilities; Colon; Hospitals

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