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Figure.
Cumulative Probability of Starting Radiation Therapy After Breast-Conserving Surgery, With Number of Patients at Risk and 95% Hall-Wellner Bands for the Exchange and Nonexchange Groups
Cumulative Probability of Starting Radiation Therapy After Breast-Conserving Surgery, With Number of Patients at Risk and 95% Hall-Wellner Bands for the Exchange and Nonexchange Groups
Table.  
Comparison of Radiation Therapy Use and Patient Characteristics Between BCS Patients Enrolled in the Exchange Group and Age State-Matched Controls in the Nonexchange Group
Comparison of Radiation Therapy Use and Patient Characteristics Between BCS Patients Enrolled in the Exchange Group and Age State-Matched Controls in the Nonexchange Group
1.
Churilla  TM, Egleston  B, Bleicher  R, Dong  Y, Meyer  J, Anderson  P.  Disparities in the local management of breast cancer in the US according to health insurance status.  Breast J. 2017;23(2):169-176.PubMedGoogle ScholarCrossref
2.
Freedman  RA, Virgo  KS, He  Y,  et al.  The association of race/ethnicity, insurance status, and socioeconomic factors with breast cancer care.  Cancer. 2011;117(1):180-189.PubMedGoogle ScholarCrossref
3.
Desch  CE, McNiff  KK, Schneider  EC,  et al.  American Society of Clinical Oncology/National Comprehensive Cancer Network Quality Measures.  J Clin Oncol. 2008;26(21):3631-3637.PubMedGoogle ScholarCrossref
4.
Freedman  RA, Virgo  KS, Labadie  J, He  Y, Partridge  AH, Keating  NL.  Receipt of locoregional therapy among young women with breast cancer.  Breast Cancer Res Treat. 2012;135(3):893-906.PubMedGoogle ScholarCrossref
5.
Martinez  SR, Beal  SH, Chen  SL,  et al.  Disparities in the use of radiation therapy in patients with local-regionally advanced breast cancer.  Int J Radiat Oncol Biol Phys. 2010;78(3):787-792.PubMedGoogle ScholarCrossref
Research Letter
October 2017

Association Between Quality of Care for Breast Cancer and Health Insurance Exchange Coverage: An Analysis of Use of Radiation Therapy After Breast-Conserving Surgery

Author Affiliations
  • 1Department of Health Services Research, University of Texas MD Anderson Cancer Center, Houston, Texas
  • 2Department of Breast Medical Oncology, University of Texas MD Anderson Cancer Center, Houston, Texas
  • 3Department of Radiation Oncology, University of Texas MD Anderson Cancer Center, Houston, Texas
JAMA Oncol. 2017;3(10):1425-1426. doi:10.1001/jamaoncol.2017.1287

Research comparing quality of cancer care by insurance categories concluded that cancer patients without insurance or with Medicaid experienced inferior quality of care compared with those with private insurance.1,2 A new insurance category created from the Affordable Care Act (ACA) is insurance purchased from the Health Insurance Marketplace (also known as the exchange). The present study provides empirical investigations of the quality of cancer care under the ACA by examining patterns of radiation therapy (RT) following breast-conserving surgery (BCS), an important quality of care indicator for breast cancer.3

Methods

We used 2014 Health Care Cost Institute (HCCI) (http://www.healthcostinstitute.org/) deidentified data, a commercial claims database covering 50 million insured individuals per year. The study was exempt for approval by the institutional review board at The University of Texas MD Anderson Cancer Center for the use of deidentified data. In November 2016, the HCCI released a new variable for 2014 data that allowed identification of individuals insured through an exchange, creating an unprecedented opportunity to understand quality of care received by this group. We identified our study cohort as breast cancer patients who received BCS after obtaining insurance through an exchange or other private insurance and had no mastectomy within 6 months of BCS, and constructed 1-to-2 case-control cohort (matched by age group and state of residence). To determine whether a patient received RT within 6 months of BCS, a minimum of 6 months of continuous enrollment since BCS was required to ensure complete information. We compared rate of RT and distribution of time to RT initiation (TTI) between the exchange and nonexchange groups using χ2 and log-rank test, respectively. We employed logistic regression and Cox proportional hazards regression model that accounted for paired data structure to determine factors (covariates see Table) associated with RT use and TTI, respectively. We performed sensitivity analyses on a 1-to-3 matched cohort.

Results

The study cohort included 279 breast cancer patients (93 in the exchange group). Approximately 60% of patients were ≥ age 55 and the primary insurance holder (72.4%). The unadjusted rate of RT was similar between the exchange and nonexchange groups (64.5% vs 66.1%, P = .79) (Table). Logistic regression showed that the likelihood of receiving RT did not differ by whether the insurance was obtained through the exchange (odds ratio = 0.89, 95% CI, 0.49-1.63). No statistically significant difference in distribution of TTI was found between the exchange and nonexchange groups both in the univariate (median TTI 63 vs 74 days, P = .98) and multivariable analysis (hazard ratio [HR]: 1.17, 95% CI, 0.78-1.75) (Figure). The only significant predictor of TTI was chemotherapy (HR 0.30; 95% CI, 0.15-0.54). Sensitivity analysis showed similar patterns.

Discussion

Our analysis showed breast cancer patients in the exchange group had quality of care similar to those in the nonexchange group, as indicated by similar rate of RT and TTI between the two groups. BCS patients should be comparable between these two groups as comparisons of surgery type by exchange status showed similar rate of BCS. Our finding implies that the ACA has exerted its intended effect to improve the quality of care for breast cancer patients who would otherwise be uninsured or underinsured without purchasing insurance acquired through the exchange. The lower rate of RT reported here likely reflected a shorter time window employed to identify RT and a relatively younger study cohort as research has shown a lower RT rate among younger women.4 An important data limitation is the lack of information on race/ethnicity, which is known to be associated with RT use.5 Future policies to replace the ACA should ensure that any transitioning plans will not jeopardize the access, continuity, and quality of care and will further expand accessibility to patients who remain uninsured or underinsured.

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Article Information

Accepted for Publication: March 28, 2017.

Corresponding Author: Ya-Chen Tina Shih, PhD, Professor of Health Economics, Chief, Section of Cancer Economics and Policy, Department of Health Services Research (Unit 1444), The University of Texas MD Anderson Cancer Center, 1515 Holcombe Blvd, Houston, TX 77030 (yashih@mdanderson.org).

Published Online: June 1, 2017. doi:10.1001/jamaoncol.2017.1287

Author Contributions: Dr Shih had full access to all of the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.

Concept and design: Shih, Guadagnolo.

Acquisition, analysis, or interpretation of data: Shih, Xu, Chavez-MacGregor, Smith, Giordano.

Drafting of the manuscript: Shih, Guadagnolo.

Critical revision of the manuscript for important intellectual content: Shih, Xu, Chavez-MacGregor, Smith, Giordano.

Statistical analysis: Shih, Xu, Chavez-MacGregor, Guadagnolo.

Obtained funding: Shih.

Administrative, technical, or material support: Shih, Giordano.

Supervision: Shih.

Conflict of Interest Disclosures: None reported.

Funding/Support: This work was supported by the Duncan Family Institute, and the National Cancer Institute (R01 CA207216).

Role of the Funder/Sponsor: The funders had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication.

References
1.
Churilla  TM, Egleston  B, Bleicher  R, Dong  Y, Meyer  J, Anderson  P.  Disparities in the local management of breast cancer in the US according to health insurance status.  Breast J. 2017;23(2):169-176.PubMedGoogle ScholarCrossref
2.
Freedman  RA, Virgo  KS, He  Y,  et al.  The association of race/ethnicity, insurance status, and socioeconomic factors with breast cancer care.  Cancer. 2011;117(1):180-189.PubMedGoogle ScholarCrossref
3.
Desch  CE, McNiff  KK, Schneider  EC,  et al.  American Society of Clinical Oncology/National Comprehensive Cancer Network Quality Measures.  J Clin Oncol. 2008;26(21):3631-3637.PubMedGoogle ScholarCrossref
4.
Freedman  RA, Virgo  KS, Labadie  J, He  Y, Partridge  AH, Keating  NL.  Receipt of locoregional therapy among young women with breast cancer.  Breast Cancer Res Treat. 2012;135(3):893-906.PubMedGoogle ScholarCrossref
5.
Martinez  SR, Beal  SH, Chen  SL,  et al.  Disparities in the use of radiation therapy in patients with local-regionally advanced breast cancer.  Int J Radiat Oncol Biol Phys. 2010;78(3):787-792.PubMedGoogle ScholarCrossref
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