Abstract
Purpose:
Socioeconomic disparities in post-mastectomy breast reconstruction exist. Key informants have suggested that finding providers who accept Medicaid insurance and longer travel time to a plastic surgeon are important barriers. Our objective was to assess the relationship between these factors and reconstruction for socioeconomically disadvantaged women in Wisconsin.
Methods:
We identified women <75 years of age with stage 0-III breast cancer who underwent mastectomy using the Wisconsin Cancer Reporting System. Women in the most disadvantaged state-based tertile of the Area Deprivation Index were included (n=1,809). Geocoding determined turn-by-turn drive time from women’s address to the nearest accredited Commission on Cancer or National Accreditation Program for Breast Centers. Multivariable logistic regression determined the relationship between reconstruction, Medicaid and travel time, controlling for patient factors known to impact reconstruction. Average adjusted predicted probabilities of receiving reconstruction were calculated.
Results:
Most patients had early stage breast cancer (51% stage 0/I) and 15.2% had Medicaid. 37% of women underwent reconstruction. Socioeconomically disadvantaged women with Medicaid (OR=0.62, 95% CI 0.46–0.84) and longer travel times (OR=0.99, 95% CI 0.99–1.0) were less likely to receive reconstruction. Patients with the lowest predicted probability of reconstruction were those with Medicaid who lived furthest from a plastic surgeon.
Conclusion:
Amongst socioeconomically disadvantaged women, Medicaid and travel remained associated with lower rates of reconstruction. Further work will explore opportunities to improve access to reconstruction for women with Medicaid. This is particularly challenging as it may require socioeconomically disadvantaged women to travel further to receive care.
Introduction:
Post-mastectomy breast reconstruction is a well-recognized component of comprehensive, high-quality breast cancer care and is associated with improved quality of life in addition to improved physical, psychosocial, and sexual wellbeing.[1–4] The importance of the potential benefits associated with reconstruction is reflected in the implementation of legislation mandating insurance coverage for post-mastectomy breast reconstruction[5] and creation of a practice standard for the National Accreditation Program for Breast Cancers that “all appropriate patients undergoing mastectomy are offered a preoperative referral to a reconstructive/plastic surgeon.”[6]
Despite these known benefits to reconstruction, socioeconomically disadvantaged women are less likely to undergo immediate post-mastectomy breast reconstruction.[7–23] Although this disparity is well recognized, less work has been done to understand the processes by which socioeconomic disadvantage leads to lower rates of reconstruction. This understanding is a critical step towards identifying actionable practice changes that could reduce observed socioeconomic disparities in breast reconstruction.
We began this research trajectory by talking informally with key informants about challenges socioeconomically disadvantaged women may face when considering reconstruction. Two commonly described barriers were 1) finding surgeons that accept Medicaid insurance, and 2) the travel required to consult with a plastic surgeon. Numerous prior studies have reported lower rates of reconstruction for women with Medicaid insurance, comparing Medicaid versus other types of insurances for women with varied household incomes.[8, 9, 12–23] However, many of these studies have also reported a strong association with household income.[8, 9, 12, 16, 21, 22] Because Medicaid insurance is so tightly associated with income, it is difficult to disentangle the effects of low income versus Medicaid insurance in these studies. Distance from patients’ residence to a plastic surgeon has also been associated with lower rates of reconstruction.[21] For rural states, the straight-line distance to the nearest plastic surgeon may underestimate the challenge that travel poses, especially for socioeconomically disadvantaged women for whom travel may be especially burdensome.
In this study, we examined rates of reconstruction within Wisconsin. Wisconsin has more than 35 cancer specialty accredited centers geographically dispersed across the state, which provides access to reconstruction services statewide. Approximately 24.7% of Wisconsin residents are classified as having income less than 200% of the federal poverty level and 17% are underinsured (on Medicaid or uninsured).[24] This is similar to the United States as a whole. The objective to assess the relationship between patients with Medicaid insurance and travel time to a plastic surgeon and receipt of post-mastectomy breast reconstruction for socioeconomically disadvantaged women in Wisconsin.
Methods:
Setting
Data Source
The Wisconsin Cancer Reporting System (WCRS) was used for this study.[25] The WCRS contributes data to the North American Association of Central Cancer Registries (NAACCR), and follows the Facility Oncology Registry Data Standards for data collection (FORDS). The WCRS also provided identifiable patient data (e.g. patient address) with special request, which allows for the assessment of neighborhood-level socioeconomic factors and driving distance. This study was approved by the University of Wisconsin Institutional Review Board.
Study Inclusion/exclusion criteria
We identified women age 18–75 diagnosed with stage 0-III breast cancer who underwent a mastectomy between 2009 and 2014. For the current analysis, we excluded women older than 75 years of age given the observed low rate of reconstruction for these women (<3%). We included women with common breast cancer histology (invasive ductal and lobular cancer, ductal carcinoma in situ). To limit our cohort to socioeconomically disadvantaged women, we used the area deprivation index (ADI, 2013). The ADI is publicly available and includes a zip code +4 composite measure of socioeconomic deprivation that is approximated from Census block groups.[26–28] The index is constructed based on components of socioeconomic disadvantage, including median family income, percentage of population with at least a high school diploma, median gross rent, monthly mortgage, percent of single parent households with children <18, and percent of households without a motor vehicle, telephone or plumbing. State-based tertiles of ADI were calculated. We included patients within the highest (most disadvantaged) tertile (n=1,804).
Study Variables
The primary outcome variable was receipt of immediate breast reconstruction. The two explanatory variables were Medicaid (yes/no) and distance to the closest accredited Commission on Cancer (CoC) or National Accreditation Program for Breast Centers (NAPBC) facility.[29, 30] Insurance is classified as outlined by the FORDS manual. In our dataset, a very low number of women were uninsured (~1%) or had unknown insurance (<1%). These women were categorized as not having Medicaid in this manuscript. These 47 accredited facilities located throughout the state were used as a surrogate for location of a plastic surgeon, as the majority of plastic surgeons (>95%) within the state work at these centers. Drive-time distance to the nearest accredited center was determined through geocoding using turn-by-turn distance. For this process each accredited center and patient address were converted to latitude-longitude data using the Melissa Data database of addresses. Drive time for each patient-accredited center combination was calculated. Addresses that could not be converted to latitude-longitude point data had addresses estimated based on the zip + 4 level (midpoint of zip+4). Turn-by-turn distance from each patient address to the closest accredited center was then estimated.
Control variables included age at diagnosis, race, AJCC stage, bilateral mastectomy (yes/no), post-mastectomy radiation (yes/no), chemotherapy (yes/no), estrogen/progesterone receptor (positive/negative), Her2neu receptor (positive/negative), and year of diagnosis. Race was categorized as white/black/other, as only 3% of the cohort was classified as neither white nor black.
Data analysis
Descriptive statistics were generated for the cohort. Multivariable logistic regression was used to determine the relationship between reconstruction and Medicaid and travel time, controlling for variables known to influence the receipt of breast reconstruction. Results are presented as odds ratios (OR) with associated 95% confidence intervals (CI). Average adjusted predicted probabilities of receiving immediate breast reconstruction based on the multivariable logistic regression models were estimated. We estimated probability with and without Medicaid insurance, and with a 10 and 45 minute drive-time (to approximate the 50th and 75th percentile in the data). We assumed a patient was aged 45–55 with stage I cancer, underwent a unilateral mastectomy and did not receive radiation. These values were selected as they are associated with higher rates of reconstruction and facilitate a comparison of the impact of Medicaid and travel time on the receipt of immediate breast reconstruction. Stata software (version 15) was used for all statistical analyses with p <0.05 considered statistically significant.
Results:
Patient and tumor characteristics for our cohort of socioeconomically disadvantaged women, overall and by receipt of immediate breast reconstruction, are summarized in Table 1. A total of 1,804 women met our inclusion/exclusion criteria. The majority of women were white (82.5%) with early stage breast cancer (51.3% stage 0/I). Overall, 37% underwent immediate reconstruction.
Table 1.
Patient and Clinical Characteristics Overall and By Receipt of Reconstruction
| Overall (1,804) | Reconstruction (659) | No Reconstruction (1,145) | |
|---|---|---|---|
|
| |||
| Age, % (N) | |||
|
| |||
| ≤45 | 21.5% (388) | 32.5% (214) | 15.2% (174) |
|
| |||
| 46–55 | 29.6% (533) | 38.1% (251) | 24.6% (282) |
|
| |||
| 56–65 | 27.8% (501) | 22.0% (145) | 31.0% (356) |
|
| |||
| 66–75 | 21.2% (382) | 7.4% (49) | 29.1% (333) |
|
| |||
| Stage, % (N) | |||
|
| |||
| 0 | 16.9% (305) | 23.0% (152) | 13.4% (153) |
|
| |||
| I | 34.4% (621) | 34.9% (230) | 34.1% (391) |
|
| |||
| II | 39.3% (709) | 36.0% (237) | 41.2% (472) |
|
| |||
| III | 9.4% (169) | 6.1% (40) | 11.3% (129) |
|
| |||
| ER/PR Receptor Status, % (N) | |||
| Negative | 18.1% (327) | 18.5% (122) | 17.9% (205) |
| Positive | 80.5% (1,452) | 80.0% (527) | 80.8% (925) |
| Missing | 1.4% (25) | 1.5% (10) | 1.3% (15) |
|
| |||
| Her2neu Status, % (N)* | |||
| Negative | 64.3% (964) | 64.3% (326) | 64.3% (638) |
| Positive | 14.6% (219) | 18.7% (95) | 12.5% (124) |
| Unknown | 20.1% (316) | 17.0% (76) | 23.2% (230) |
|
| |||
| Race, % (N) | |||
| White | 82.5% (1,488) | 80.6% (531) | 83.6% (957) |
| Black | 14.1% (255) | 16.1% (106) | 13.0% (149) |
| Other | 3.0% (54) | 2.9% (19) | 3.1% (35) |
| Unknown | 0.4% (7) | 0.5% (3) | 0.3% (4) |
|
| |||
| Medicaid (vs other), % (N) | 15.2% (274) | 15.0% (99) | 15.3% (175) |
|
| |||
| Travel time | |||
| 25th percentile | 6 min | 6 min | 7 min |
| 50th percentile | 12 min | 10 min | 14 min |
| 75th percentile | 44 min | 34 min | 47 min |
|
| |||
| Radiation, % (N) | |||
| No | 79.8% (1,432) | 82.1% (541) | 77.8% (891) |
| Yes | 20.1% (362) | 17.9% (118) | 21.3% (244) |
| Missing | 1% (10) | 0% | 0.9% (10) |
|
| |||
| Chemotherapy, % (N) | |||
| No | 49.3% (890) | 51.0% (336) | 48.4% (554) |
| Yes | 50.7% (914) | 49.0% (323) | 51.6% (591) |
|
| |||
| Year of Diagnosis, % (N) | |||
| 2009 | 16.0% (288) | 11.8% (78) | 18.3% (210) |
| 2010 | 16.8% (303) | 16.3% (107) | 17.1% (196) |
| 2011 | 15.6% (281) | 17.2% (113) | 14.7% (168) |
| 2012 | 18.1% (326) | 18.2% (120) | 18.0% (206) |
| 2013 | 17.4% (314) | 20.9% (138) | 15.4% (176) |
| 2014 | 16.2% (292) | 15.6% (103) | 16.5% (189) |
for patients with invasive cancer only
Based on the multivariable logistic regression model, socioeconomically disadvantaged women who had Medicaid insurance (OR=0.55, 95% CI 0.4–0.7) or lived further from an accredited center (OR=0.99, 95% CI 0.99–1.0) were less likely to undergo immediate breast reconstruction (Table 2). Older age and higher stage cancer were associated with decreased odds of undergoing immediate breast reconstruction, while undergoing a bilateral mastectomy as associated with increased odds of undergoing immediate breast reconstruction.
Table 2:
Multivariable logistic regression analysis for immediate breast reconstruction by patient factors
| Odds Ratio (OR) | 95% Confidence Interval (CI) | P-value | |
|---|---|---|---|
|
| |||
| Medicaid | 0.62 | 0.46–0.84 | 0.002 |
|
| |||
| Travel time to accredited center | 0.99 | 0.99–1.00 | 0.017 |
|
| |||
| Age <40 | Reference | -- | <0.0005 |
| 40–50 | 0.74 | 0.56–0.99 | |
| 50–60 | 0.31 | 0.23–0.43 | |
| 60–70 | 0.11 | 0.07–0.16 | |
|
| |||
| Stage 0 | Reference | -- | 0.001 |
| I | 0.67 | 0.43–1.1 | |
| II | 0.50 | 0.31–0.82 | |
| III | 0.30 | 0.16–0.57 | |
|
| |||
| Bilateral mastectomy | 2.22 | 1.8–2.8 | <0.0005 |
|
| |||
| Radiation | 0.89 | 0.65–1.2 | 0.46 |
|
| |||
| Chemotherapy | 0.84 | 0.62–1.12 | 0.23 |
Also controlled for Estrogen/Progesterone receptor, Her2neu status, and Year of diagnosis
To facilitate interpretation of findings, adjusted predicted probabilities of reconstruction were estimated (Table 3). Patients with non-Medicaid insurance who lived closer to a plastic surgeon had the highest predicted probability of reconstruction, at 50% (95% CI 44–57%). The lowest predicted probability of reconstruction was for patients with Medicaid insurance who lived further from a plastic surgeon (32%, 95% CI 24–40%).
Table 3:
Predicted Probabilities of Receiving Immediate Reconstruction Based on Medicaid Insurance and Drive Time Distance
| Predicted Probability of Reconstruction (95% Confidence Interval) | |||
|---|---|---|---|
| Medicaid Insurance | Non-Medicaid Insurance | ||
| Drive Time Distance | 10 minutes | 38% (29–46%) | 49% (42–56%) |
| 45 minutes | 34% (25–42%) | 45% (38–52%) | |
Predicted probability of undergoing reconstruction, assuming a patient was 45–55 years of age, had stage I cancer, had a unilateral mastectomy without radiation
Discussion:
In our study examining factors associated with reconstruction for socioeconomically disadvantaged women in Wisconsin, we confirmed that both Medicaid insurance and longer drive-time distance to a plastic surgeon are associated with lower rates of reconstruction. Socioeconomic disparities for breast reconstruction have long been reported.[7–23] Our data expands upon the current literature and provides insight into factors that may be contributing to the lower rates of reconstruction for socioeconomically disadvantaged women. This understanding is a critical step towards identifying actionable practice changes that could reduce observed socioeconomic disparities in breast reconstruction.
Medicaid insurance has been associated with lower rates of reconstruction in other studies.[8, 9, 12–23] However, these studies generally were comparing Medicaid against other insurance within a broader population of women with varied incomes. In this setting, it is difficult to separate the impact of Medicaid insurance itself from patients’ social context. It is interesting that in our cohort of socioeconomically disadvantaged women, Medicaid continued to be associated with lower rates of reconstruction. Although our study cannot determine the cause of the observed association, we hypothesize a number of possibilities. It is possible that the lower reimbursement for reconstruction associated with Medicaid may cause some plastic surgeons to not accept patients with Medicaid in their practice, making it more challenging for patients to access reconstructive services.[31, 32] Alternatively, some breast/general surgeons may be more reluctant to refer patients with Medicaid insurance to see a plastic surgeon. Finally, having Medicaid (and the social context surrounding this insurance) may influence patient’s motivation to undergo reconstruction due to other competing priorities. More work is needed to understand the mechanism by which Medicaid insurance leads to lower reconstruction rates, as addressing each of these alternatives would require quite different approaches.
Wisconsin is fortunate to have a large number of cancer specialty accredited centers that are geographically dispersed across the state. Reconstruction services are in close proximity for most women, as evidenced by the 12-minute median drive time (25th percentile 6 minutes, 75th percentile 44 minutes) from patients’ residence to the closest center. Despite this, drive time was associated with receipt of reconstruction in this cohort of socioeconomically disadvantaged women. Transportation can present a challenge for socioeconomically disadvantaged women’s cancer care overall, both in rural and urban settings.[21] As reconstruction is an elective component of cancer treatment, it is reasonable to imagine that travel barriers may influence a woman’s ability or even willingness to travel for reconstruction. However, given the importance of reconstruction on quality of life and well-being, identifying opportunities to support women who need to travel further distances for care is an important step. This may be especially challenging for women with Medicaid insurance and access issues, as this may require women to travel further for care.
In this study, we chose to use the ADI as a way of quantifying socioeconomic disadvantage.[26–28] As a composite measure, the ADI reflects social determinants of health at the neighborhood level and is a more complex construct than considering income or education alone. By providing insight about where a patient lives, we believe the ADI is a robust way of identifying a cohort of women who may be at risk of experiencing socioeconomic disparities in reconstruction.
A few limitations to our current study should be addressed. First, we were unable to determine the specific facility where each patient received the different components of their multidisciplinary breast cancer care (including surgery). In this study, we chose to measure drive-time distance using the nearest CoC or NAPBC center to a patient’s address, as these are the most likely locations where a patient would be able to undergo reconstructive surgery. However, we are aware that some plastic surgeon may perform outreach or practice at locations outside of their primary institution and we may not be capturing all options for reconstruction. Additionally, our data only captured immediate breast reconstruction and does not account for those undergoing delayed reconstruction. Our data set does not include any information on patients’ comorbidity, which could impact receipt of reconstruction. Finally, our study is limited to Wisconsin. Our long-term goal for this research is to develop and implement interventions to address barriers associated with reconstruction for socioeconomically disadvantaged women. We deliberately limited this study to Wisconsin in order to directly translate our findings into a statewide study to address disparities. However, as Wisconsin’s observed socioeconomic disparities in reconstruction mirror national trends, it is likely that findings from this study can be extrapolated beyond the boundaries of the state.
Conclusion:
In our cohort of low SES/socioeconomically disadvantaged women living in Wisconsin, having Medicaid and living further from an accredited center are strongly associated with lack of receipt of immediate breast reconstruction. Further work is needed to obtain more understanding into the mechanisms of these barriers to reconstruction, including how surgeons may influence receipt of reconstruction through their presentation of the option and how factors such as travel time influence women’s preferences. This understanding is a critical step towards identifying and developing opportunities to improve access to reconstruction for socioeconomically disadvantaged women who desire this preference-sensitive component of cancer care.
Funding:
This study was supported by a Society of Surgical Oncology Clinical Investigator Award, awarded to Dr. Neuman. Dr. Stankowski was supported by the National Cancer Institute of the NIH via grant T32CA090217.
This study was approved by the University of Wisconsin Institutional Review Board.
Statements and Declarations
Dr. Stankowski is supported by the National Cancer Institute of the NIH via grant T32CA090217. This work was supported by a Society of Surgical Oncology Clinical Investigator Award awarded to Dr. Heather Neuman.
Footnotes
The authors have no relevant financial or non-financial interests to disclose.
The data used in the analysis was available through a Data Use Agreement with the Wisconsin Cancer Registry System and cannot be publically shared outside that agreement.
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