[Skip to Content]
Sign In
Individual Sign In
Create an Account
Institutional Sign In
OpenAthens Shibboleth
[Skip to Content Landing]
Figure 1.
Unadjusted Mean in Use of Immediate Postmastectomy Breast Reconstruction (IPBR) and Racial/Ethnic Disparities in New York and California
Unadjusted Mean in Use of Immediate Postmastectomy Breast Reconstruction (IPBR) and Racial/Ethnic Disparities in New York and California

Top graphs show use of IPBR; bottom graphs, disparities measured compared with white patients. Data were obtained from the 2008-2011 Healthcare Cost and Utilization Project state inpatient databases.

Figure 2.
Estimated Reduction in Racial/Ethnic Disparities in Immediate Postmastectomy Breast Reconstruction (IPBR)
Estimated Reduction in Racial/Ethnic Disparities in Immediate Postmastectomy Breast Reconstruction (IPBR)

Data use the National Academy of Medicine definition of disparity as any difference between white and minority subpopulations in access to or use of health care services not owing to health needs or patient preferences. Comparisons in disparities between white and minority groups were made before (2008-2010) and after (2011) enactment of New York Public Health Law 2803-o between white and minority patients. Data were obtained from the 2008-2011 Healthcare Cost and Utilization Project state inpatient databases. Error bars represent 95% CIs.

aP = .75.

bP < .001.

Table 1.  
Characteristics of the Study Population
Characteristics of the Study Population
Table 2.  
Results of the GEE Regression Examining the Probability of IPBRa
Results of the GEE Regression Examining the Probability of IPBRa
Table 3.  
Adjusted Estimated Disparities in PBRa
Adjusted Estimated Disparities in PBRa
1.
Breastcancer.org. US breast cancer statistics. http://www.breastcancer.org/symptoms/understand_bc/statistics. Updated September 2016. Accessed October 16, 2016.
2.
Siegel  RL, Miller  KD, Jemal  A.  Cancer statistics, 2016.  CA Cancer J Clin. 2016;66(1):7-30.PubMedGoogle ScholarCrossref
3.
Miller  KD, Siegel  RL, Lin  CC,  et al.  Cancer treatment and survivorship statistics, 2016.  CA Cancer J Clin. 2016;66(4):271-289.PubMedGoogle ScholarCrossref
4.
Al-Ghazal  SK, Fallowfield  L, Blamey  RW.  Comparison of psychological aspects and patient satisfaction following breast conserving surgery, simple mastectomy and breast reconstruction.  Eur J Cancer. 2000;36(15):1938-1943.PubMedGoogle ScholarCrossref
5.
Cordeiro  PG.  Breast reconstruction after surgery for breast cancer.  N Engl J Med. 2008;359(15):1590-1601.PubMedGoogle ScholarCrossref
6.
Neto  MS, de Aguiar Menezes  MV, Moreira  JR, Garcia  EB, Abla  LE, Ferreira  LM.  Sexuality after breast reconstruction post mastectomy.  Aesthetic Plast Surg. 2013;37(3):643-647.PubMedGoogle ScholarCrossref
7.
Burwell  SR, Case  LD, Kaelin  C, Avis  NE.  Sexual problems in younger women after breast cancer surgery.  J Clin Oncol. 2006;24(18):2815-2821.PubMedGoogle ScholarCrossref
8.
Rowland  JH, Desmond  KA, Meyerowitz  BE, Belin  TR, Wyatt  GE, Ganz  PA.  Role of breast reconstructive surgery in physical and emotional outcomes among breast cancer survivors.  J Natl Cancer Inst. 2000;92(17):1422-1429.PubMedGoogle ScholarCrossref
9.
Heneghan  HM, Prichard  RS, Lyons  R,  et al.  Quality of life after immediate breast reconstruction and skin-sparing mastectomy: a comparison with patients undergoing breast conserving surgery.  Eur J Surg Oncol. 2011;37(11):937-943.PubMedGoogle ScholarCrossref
10.
Elder  EE, Brandberg  Y, Björklund  T,  et al.  Quality of life and patient satisfaction in breast cancer patients after immediate breast reconstruction: a prospective study.  Breast. 2005;14(3):201-208.PubMedGoogle ScholarCrossref
11.
Kanavos  P, Gemmill-Toyama  M.  Prescription drug coverage among elderly and disabled Americans: can Medicare–Part D reduce inequities in access?  Int J Health Care Finance Econ. 2010;10(3):203-218.PubMedGoogle ScholarCrossref
12.
California Association of Physician Groups. Knox-Keene Health Care Service Plan Act of 1975. California Association of Physician Groups. http://www.capg.org/index.aspx?page=124. Accessed July 16, 2016.
13.
FindLaw. New York Insurance Law § 3221: group or blanket accident and health insurance policies; standard provisions. http://codes.findlaw.com/ny/insurance-law/isc-sect-3221.html. Accessed July 16, 2016.
14.
California Legislative Information. SB-255 health care coverage: breast cancer. http://leginfo.legislature.ca.gov/faces/billTextClient.xhtml?bill_id=201120120SB255. Filed September 22, 2012. Accessed July 16, 2016.
15.
Wilkins  EG, Alderman  AK.  Breast reconstruction practices in North America: current trends and future priorities.  Semin Plast Surg. 2004;18(2):149-155.PubMedGoogle ScholarCrossref
16.
Alderman  AK, Wei  Y, Birkmeyer  JD.  Use of breast reconstruction after mastectomy following the Women’s Health and Cancer Rights Act.  JAMA. 2006;295(4):387-388.PubMedGoogle Scholar
17.
Lang  JE, Summers  DE, Cui  H,  et al.  Trends in post-mastectomy reconstruction: a SEER database analysis.  J Surg Oncol. 2013;108(3):163-168.PubMedGoogle ScholarCrossref
18.
Agarwal  S, Liu  JH, Crisera  CA, Buys  S, Agarwal  JP.  Survival in breast cancer patients undergoing immediate breast reconstruction.  Breast J. 2010;16(5):503-509.PubMedGoogle ScholarCrossref
19.
Offodile  AC  II, Tsai  TC, Wenger  JB, Guo  L.  Racial disparities in the type of postmastectomy reconstruction chosen.  J Surg Res. 2015;195(1):368-376.PubMedGoogle ScholarCrossref
20.
Paul  H  Jr, Prendergast  TI, Nicholson  B, White  S, Frederick  WA.  Breast reconstruction: current and future options.  Breast Cancer (Dove Med Press). 2011;3:93-99.PubMedGoogle Scholar
21.
Shippee  TP, Kozhimannil  KB, Rowan  K, Virnig  BA.  Health insurance coverage and racial disparities in breast reconstruction after mastectomy.  Womens Health Issues. 2014;24(3):e261-e269.PubMedGoogle ScholarCrossref
22.
Tseng  JF, Kronowitz  SJ, Sun  CC,  et al.  The effect of ethnicity on immediate reconstruction rates after mastectomy for breast cancer.  Cancer. 2004;101(7):1514-1523.PubMedGoogle ScholarCrossref
23.
Brennan  ME, Spillane  AJ.  Uptake and predictors of post-mastectomy reconstruction in women with breast malignancy: systematic review.  Eur J Surg Oncol. 2013;39(6):527-541.PubMedGoogle ScholarCrossref
24.
Kruper  L, Xu  XX, Henderson  K, Bernstein  L, Chen  SL.  Utilization of mastectomy and reconstruction in the outpatient setting.  Ann Surg Oncol. 2013;20(3):828-835.PubMedGoogle ScholarCrossref
25.
Greenberg  CC, Schneider  EC, Lipsitz  SR,  et al.  Do variations in provider discussions explain socioeconomic disparities in postmastectomy breast reconstruction?  J Am Coll Surg. 2008;206(4):605-615.PubMedGoogle ScholarCrossref
26.
Alderman  AK, Hawley  ST, Waljee  J, Morrow  M, Katz  SJ.  Correlates of referral practices of general surgeons to plastic surgeons for mastectomy reconstruction.  Cancer. 2007;109(9):1715-1720.PubMedGoogle ScholarCrossref
27.
Hartocollis  A. Before breast is removed, a discussion on options. New York Times. August 18, 2010. http://www.nytimes.com/2010/08/19/nyregion/19surgery.html. Accessed December 15, 2016.
28.
Montefiore. New law requires hospitals to inform breast cancer patients of breast reconstruction options. http://www.montefiore.org/body.cfm?id=1738&action=detail&ref=244. Published August 17, 2010. Accessed December 15, 2016.
29.
Garfein  ES.  The privilege of advocacy: legislating awareness of breast reconstruction.  Plast Reconstr Surg. 2011;128(3):803-804.PubMedGoogle ScholarCrossref
30.
FindLaw. New York Public Health Law § 2803-o. Hospital care for mastectomy, lumpectomy, and lymph node dissection patients. http://codes.findlaw.com/ny/public-health-law/pbh-sect-2803-o.html. Accessed July 16, 2016.
31.
New York State Department of Health. Dear Chief Executive Officer letter: advise facilities of recently-enacted laws that directly impact the operations of hospitals in New York State, January 11, 2011. https://www.health.ny.gov/professionals/hospital_administrator/letters/2011/2011-01-11_recently_enacted_laws_impacting_hospitals.htm. Published January 11, 2011. Accessed December 15, 2016.
32.
The New York State Senate. Public health. https://www.nysenate.gov/legislation/laws/PBH/2803. Accessed December 15, 2016.
33.
Healthcare Cost and Utilization Project. Central Distributor SID description of data elements: all states. Published April 2008. https://www.hcup-us.ahrq.gov/db/state/siddist/sid_multivar.jsp. Accessed May 2, 2016.
34.
Healthcare Cost and Utilization Project. HCUP User Support (HCUP-US).Updated April 2017. https://www.hcup-us.ahrq.gov/home.jsp. Accessed May 2, 2016.
35.
Healthcare Cost and Utilization Project. Elixhauser Comorbidity Software, Version 3.7. Updated March 2017. https://www.hcup-us.ahrq.gov/toolssoftware/comorbidity/comorbidity.jsp. Accessed August 2, 2016.
36.
Wooldridge  J. What’s new in econometrics? difference-in-differences estimation. NBER Summer Institute, miméo. http://www.nber.org/WNE/lect_10_diffindiffs.pdf. Published 2007. Accessed August 2, 2016.
37.
Imbens  GW, Wooldridge  JM.  Recent developments in the econometrics of program evaluation.  J Econ Lit. 2009;47(1):5-86.Google ScholarCrossref
38.
Institute of Medicine (US) Committee on Understanding and Eliminating Racial and Ethnic Disparities in Health Care; Smedley BD, Stith AY, Nelson AR, eds.  Unequal Treatment: Confronting Racial and Ethnic Disparities in Health Care. Washington, DC: National Academies Press; 2003.
39.
Cook  B, McGuire  TG, Lock  K, Zaslavsky  AM.  Comparing methods of racial and ethnic disparities measurement across different settings of mental health care.  Health Serv Res. 2010;45(3):825-847.PubMedGoogle ScholarCrossref
40.
Mahmoudi  E, Jensen  GA.  Has Medicare Part D reduced racial/ethnic disparities in prescription drug use and spending?  Health Serv Res. 2014;49(2):502-525.PubMedGoogle ScholarCrossref
41.
Wanzel  KR, Brown  MH, Anastakis  DJ, Regehr  G.  Reconstructive breast surgery: referring physician knowledge and learning needs.  Plast Reconstr Surg. 2002;110(6):1441-1450.PubMedGoogle ScholarCrossref
42.
Morrow  M, Mujahid  M, Lantz  PM,  et al.  Correlates of breast reconstruction: results from a population-based study.  Cancer. 2005;104(11):2340-2346.PubMedGoogle ScholarCrossref
43.
Potter  S, Mills  N, Cawthorn  S, Wilson  S, Blazeby  J.  Exploring information provision in reconstructive breast surgery: a qualitative study.  Breast. 2015;24(6):732-738.PubMedGoogle ScholarCrossref
44.
Alderman  AK, Hawley  ST, Janz  NK,  et al.  Racial and ethnic disparities in the use of postmastectomy breast reconstruction: results from a population-based study.  J Clin Oncol. 2009;27(32):5325-5330.PubMedGoogle ScholarCrossref
45.
Stacey  DH, Spring  MA, Breslin  TM, Rao  VK, Gutowski  KA.  Exploring the effect of the referring general surgeon’s attitudes on breast reconstruction utilization.  WMJ. 2008;107(6):292-297.PubMedGoogle Scholar
46.
Gamble  VN.  Under the shadow of Tuskegee: African Americans and health care.  Am J Public Health. 1997;87(11):1773-1778.PubMedGoogle ScholarCrossref
47.
Copeland  VC.  African Americans: disparities in health care access and utilization.  Health Soc Work. 2005;30(3):265-270.PubMedGoogle ScholarCrossref
48.
Boulware  LE, Cooper  LA, Ratner  LE, LaVeist  TA, Powe  NR.  Race and trust in the health care system.  Public Health Rep. 2003;118(4):358-365.PubMedGoogle ScholarCrossref
49.
Caito  N, Hood  S, Thompson  VL.  Discussing cancer: communication with African Americans.  Soc Work Health Care. 2014;53(6):519-531.PubMedGoogle ScholarCrossref
50.
Wachterman  MW, McCarthy  EP, Marcantonio  ER, Ersek  M.  Mistrust, misperceptions, and miscommunication: a qualitative study of preferences about kidney transplantation among African Americans.  Transplant Proc. 2015;47(2):240-246.PubMedGoogle ScholarCrossref
51.
Ghods  BK, Roter  DL, Ford  DE, Larson  S, Arbelaez  JJ, Cooper  LA.  Patient-physician communication in the primary care visits of African Americans and whites with depression.  J Gen Intern Med. 2008;23(5):600-606.PubMedGoogle ScholarCrossref
52.
Siminoff  LA, Graham  GC, Gordon  NH.  Cancer communication patterns and the influence of patient characteristics: disparities in information-giving and affective behaviors.  Patient Educ Couns. 2006;62(3):355-360.PubMedGoogle ScholarCrossref
53.
Eggly  S, Barton  E, Winckles  A, Penner  LA, Albrecht  TL.  A disparity of words: racial differences in oncologist-patient communication about clinical trials.  Health Expect. 2015;18(5):1316-1326.PubMedGoogle ScholarCrossref
54.
Johnson  RL, Roter  D, Powe  NR, Cooper  LA.  Patient race/ethnicity and quality of patient-physician communication during medical visits.  Am J Public Health. 2004;94(12):2084-2090.PubMedGoogle ScholarCrossref
55.
Ginzberg  E.  Access to health care for Hispanics.  JAMA. 1991;265(2):238-241.PubMedGoogle ScholarCrossref
56.
Mahmoudi  E, Jensen  GA, Tarraf  W.  Effects of Medicare Part D on racial/ethnic disparities in hospital utilization among seniors.  J Aging Health. 2015;27(5):797-826.PubMedGoogle ScholarCrossref
57.
Sommers  BD, Chua  KP, Kenney  GM, Long  SK, McMorrow  S.  California’s early coverage expansion under the Affordable Care Act: a county-level analysis.  Health Serv Res. 2016;51(3):825-845.PubMedGoogle ScholarCrossref
58.
Chen  J, Vargas-Bustamante  A, Mortensen  K, Ortega  AN.  Racial and ethnic disparities in health care access and utilization under the Affordable Care Act.  Med Care. 2016;54(2):140-146.PubMedGoogle ScholarCrossref
59.
Castillo-Page  L. Diversity in the Physician Workforce Facts and Figures 2010. Association of American Medical Colleges. https://www.aamc.org/initiatives/diversity/179816/facts_and_figures.html. Published March 14, 2011. Accessed September 18, 2016.
60.
Moreno  G, Walker  KO, Grumbach  K.  Self-reported fluency in non-English languages among physicians practicing in California.  Fam Med. 2010;42(6):414-420.PubMedGoogle Scholar
61.
Jaramillo  J, Snyder  E, Dunlap  JL, Wright  R, Mendoza  F, Bruzoni  M.  The Hispanic Clinic for Pediatric Surgery: a model to improve parent-provider communication for Hispanic pediatric surgery patients.  J Pediatr Surg. 2016;51(4):670-674.PubMedGoogle ScholarCrossref
62.
Dunlap  JL, Jaramillo  JD, Koppolu  R, Wright  R, Mendoza  F, Bruzoni  M.  The effects of language concordant care on patient satisfaction and clinical understanding for Hispanic pediatric surgery patients.  J Pediatr Surg. 2015;50(9):1586-1589.PubMedGoogle ScholarCrossref
63.
Alderman  AK, Wilkins  EG, Kim  HM, Lowery  JC.  Complications in postmastectomy breast reconstruction: two-year results of the Michigan Breast Reconstruction Outcome Study.  Plast Reconstr Surg. 2002;109(7):2265-2274.PubMedGoogle ScholarCrossref
64.
Cooper  LA, Roter  DL, Johnson  RL, Ford  DE, Steinwachs  DM, Powe  NR.  Patient-centered communication, ratings of care, and concordance of patient and physician race.  Ann Intern Med. 2003;139(11):907-915.PubMedGoogle ScholarCrossref
65.
Ashton  CM, Haidet  P, Paterniti  DA,  et al.  Racial and ethnic disparities in the use of health services: bias, preferences, or poor communication?  J Gen Intern Med. 2003;18(2):146-152.PubMedGoogle ScholarCrossref
66.
Roughton  MC, DiEgidio  P, Zhou  L, Stitzenberg  K, Meyer  AM.  Distance to a plastic surgeon and type of insurance plan are independently predictive of postmastectomy breast reconstruction.  Plast Reconstr Surg. 2016;138(2):203e-211e.PubMedGoogle ScholarCrossref
Original Investigation
August 2017

Association of a Policy Mandating Physician-Patient Communication With Racial/Ethnic Disparities in Postmastectomy Breast Reconstruction

Author Affiliations
  • 1Section of Plastic Surgery, University of Michigan Medical School, Ann Arbor
  • 2Office of Health Equity and Inclusion, Michigan Health Science Undergraduate Research Academy, University of Michigan, Ann Arbor
  • 3currently an undergraduate student at Youngstown State University, Youngstown, Ohio
JAMA Surg. 2017;152(8):775-783. doi:10.1001/jamasurg.2017.0921
Key Points

Question  Is the 2011 New York legislation mandating physicians to communicate about breast reconstruction with their patients undergoing mastectomy associated with reduced racial/ethnic disparities in immediate postmastectomy breast reconstruction?

Findings  In this evaluation of state inpatient data that included 42 346 women undergoing mastectomy, physician communication about breast reconstruction was associated with decreases in disparities in immediate postmastectomy breast reconstruction between Hispanic and white patients (9 percentage points) and other minorities and white patients (13 percentage points) but not between African American and white patients (1 percentage point).

Meaning  Physician-patient communication may reduce disparities in immediate postmastectomy breast reconstruction between white patients and certain minorities.

Abstract

Importance  With the stabilization of breast cancer incidence and substantial improvement in survival, more attention has focused on postmastectomy breast reconstruction (PBR). Despite its demonstrated benefits, wide disparities in the use of PBR remain. Physician-patient communication has an important role in disparities in health care, especially for elective surgical procedures. Recognizing this, the State of New York enacted Public Health Law (NY PBH Law) 2803-o in 2011 mandating that physicians communicate about reconstructive surgery with patients undergoing mastectomy.

Objective  To evaluate whether mandated physician-patient communication is associated with reduced racial/ethnic disparities in immediate PBR (IPBR).

Design, Setting, and Participants  This retrospective study used state inpatient data from January 1, 2008, through December 31, 2011, in New York and California to evaluate a final sample of 42 346 women aged 20 to 70 years, including 19 364 from New York (treatment group) and 22 982 from California (comparison group). The primary hypothesis tested the effect of the New York law on racial/ethnic disparities, using California as a comparator. The National Academy of Medicine’s (formerly Institute of Medicine) definition of a disparity was applied, and a difference-in-differences method (before-and-after comparison design) was used to evaluate the association of NY PBH Law 2803-o mandating physician-patient communication with disparities in IPBR. Data were analyzed from July 1, 2016, to February 24, 2017.

Exposures  New York PBH Law 2803-o was implemented on January 1, 2011. The preexposure period included January 1, 2008, through December 31, 2010 (3 years); the postexposure period, January 1 through December 31, 2011 (1 year).

Main Outcomes and Measures  The primary outcome was use of IPBR among white, African American, Hispanic, and other minority groups before and after the implementation of NY PBH Law 2803-o.

Results  Among the 42 346 women (mean [SD] age, 53 [10] years), 65.3% (27 654) were white, 12.7% (5365) were Hispanic, 9.4% (3976) were African American, and 12.6% (5351) were other minorities. The new legislation was not associated with the overall IPBR rate or disparity in IPBR between whites and African Americans (reduction of 1 percentage point; 95% CI, −0.02 to 0.04), but it was associated with a reduction in disparities in IPBR between Hispanic and white patients by 9 (95% CI, 0.06-0.11) percentage points and between other minorities and white patients by 13 (95% CI, 0.11-0.16) percentage points.

Conclusions and Relevance  Physician-patient communication may help to address inequity in the use of elective surgical procedures, such as IPBR. However, lack of patient trust and/or effective physician-patient communication may reduce the potential effect of mandatory communication for some subpopulations, including African American individuals.

Introduction

One in 8 women in the United States is diagnosed with breast cancer,1,2 and about one-third of these women undergo mastectomy to combat the disease.3 In the past few decades owing to advancement in detection techniques and treatment, an increasing number of women have survived breast cancer. Thus, a focus on the importance of reconstructive surgery for women who have undergone mastectomy has emerged. Breast reconstructive surgery provides psychological benefits, such as improved self-esteem and decreased anxiety,4,5 reduced sexual dysfunction,6,7 and improvements in overall quality of life.8-10

In 1998, the Women’s Health and Cancer Rights Act (WHCRA) passed, mandating that insurance companies provide coverage for postmastectomy breast reconstruction (PBR).11-14 Although initial studies questioned the WHCRA’s effectiveness,15,16 the legislation was found to increase the rate of PBR.17 Despite mandated insurance coverage and increasing awareness about its benefits, numerous studies have documented widening racial/ethnic disparities in PBR. White patients have a higher rate of PBR than do patients of other racial/ethnic groups.18-21 Some of the factors that fuel these disparities are inherent differences in insurance type, women’s educational attainment, and income level.20-24 One of the greatest predictors and most easily modifiable factors affecting disparity in PBR has been the initial patient-physician discussion.25 Research shows that only 24% of breast surgeons referred their patients to plastic surgeons to discuss reconstruction.26 To reduce disparity and improve access to PBR,27 the New York City Council suggested that informing women about PBR should be required by state law. The leadership at Montefiore Medical Center, Bronx, New York,28 and the state’s legislators drafted the bill, which passed in August 2010.29

On January 1, 2011, the State of New York enacted Public Health (NY PBH) Law 2803-o, which mandates that surgeons advise their patients undergoing mastectomy on available breast reconstruction options, advantages and disadvantages of each option, referrals and names of surgeons who perform breast reconstructive surgery, and insurance coverage of reconstruction.30 In January 2011, the New York State Department of Health sent a memorandum to all hospitals enumerating the law’s requirements31 and providing links to websites to help the hospitals compile information for patients. Similar to any PBH law, the legislation is subject to regulation and oversight. The health commissioner can audit hospitals to check whether they are properly administering the law. A facility in violation will have 30 days to rectify the situation and will be subject to fines.32

Based on our knowledge, no study has evaluated the effectiveness of NY PBH Law 2803-o in improving disparities in PBR, resulting in little information on the association of physician-patient communication with reducing racial/ethnic disparities. The purpose of this study is to fill this void by evaluating the effectiveness of the legislation. Using 2008-2011 state inpatient data from New York and California and applying a difference-in-differences (DD) approach, we aimed to evaluate the association of NY PBH Law 2803-o with racial/ethnic disparities in immediate PBR (IPBR). We used and quantified the definition of a racial/ethnic disparity from the National Academy of Medicine (NAM; formerly Institute of Medicine) and hypothesized that mandated physician-patient communication would reduce disparities in IPBR.

Methods
Data Source

We performed a retrospective study using 2008-2011 data from the state inpatient databases for California and New York.33 The state inpatient database is one of many databases from the Healthcare Cost and Utilization Project, managed by the Agency for Healthcare Research and Quality.34 No 2012 data from California were available; therefore, we limited our postexposure period analysis to 2011 for both states. The University of Michigan institutional review board determined that approval was not required because the data cannot be tracked to a human subject.

Patient Selection

Postmastectomy breast reconstruction is not applicable to male patients. We selected all female patients who had breast cancer and underwent mastectomy from January 1, 2008, through December 31, 2011, in New York and California (eFigure in the Supplement). These patients were selected using diagnosis and procedure codes from the International Classification of Disease, Ninth Revision, Clinical Modification (eTable 1 in the Supplement). Our original samples included 24 268 patients from New York and 31 617 patients from California who underwent mastectomy; after excluding patients with missing values (1873 patients [3.4%]), sample sizes included 24 071 and 29 941 patients, respectively. Differences in characteristics of patients, with and without missing values, are presented in eTable 2 in the Supplement. Our final sample size, after excluding patients who were younger than 20 or older than 70 years of age, was 42 346 (eFigure in the Supplement).

Dependent and Explanatory Variables

Our outcome of interest was whether patients used IPBR. For explanatory variables, we included age at the time of surgery, number of comorbidities, certain chronic conditions, state of residence, year (2008-2010 vs 2011), race/ethnicity, median household income, payer, interaction terms between state and year 2011, and 3-way interactions among race/ethnicity, state, and year 2011.

Age was measured as a continuous variable ranging from 20 to 70 years. Race/ethnicity was provided by the data source and categorized into white, African American, Hispanic, and other minority (including Asian or Pacific Islander and Native American). Payers included Medicare, Medicaid, private payer, no insurance, and others. Zip code–level median household income included 4 quartiles, with the fourth quartile representing the highest income level. An unspecified income category was created for median household income; thus, we did not have to exclude those with missing values (13.2% of the sample size) from our regression model. Number of comorbidities was calculated using the Creation of Comorbidity Variables Software (provided by the Healthcare Cost and Utilization Project35), with a maximum value of 29.35 A list of specific comorbidities is shown in eTable 3 in the Supplement.

Statistical Analysis

Data were analyzed from July 1, 2016, to February 24, 2017. We applied a DD approach,36 using a generalized estimating equation model (to adjust for potential correlation within hospitals) to examine whether enactment of the NY PBH Law 2803-o in 2011 influenced rates of IPBR (using California for comparison). For the DD approach to be valid, one should not observe different trends in the outcome variable between the comparison and control groups before a change in policy.37 We examined the unadjusted racial/ethnic differences in IPBR rates before the law’s implementation in 2011 (Figure 1) and observed no significant differences in disparities between New York and California. Second, we used the NAM definition of a racial/ethnic disparity to estimate changes in disparities in IPBR and whether the implementation of the law decreased disparities between white and minority populations. NAM defined disparity to be any difference between white and minority subpopulations in access to or use of health care services not owing to health needs or patient preferences.38 Cook et al39 introduced a method to empirically implement the NAM definition, and we followed their approach in this study. Use of the NAM definition of a disparity in a DD method has been explained in detail elsewhere.40 We also added a detailed description of the NAM method in the eMethods in the Supplement. First, we fitted a DD logistic model. Second, we estimated the health index scores for white patients and each minority group in New York and California based on the coefficients (for age, certain conditions, and number of comorbidities as need indicators) of our regression model in the first step and the actual observations. Third, we used the rank-and-replace algorithm39,40 to replace the health index score of white patients for those of minority groups in the original regression model to estimate the NAM-adjusted predicted values for each minority group. Last, we calculated the differences between white and racial/ethnic subgroups included in the study to obtain disparity values.

To measure the standard errors for the NAM estimations, we used a bootstrapping technique by replicating our entire sample 100 times with replacement and reestimated the counterfactual NAM disparities with each bootstrapped sample. Throughout the analysis, a 2-sided t test at a 5% level was used to detect statistical significance. The data analysis was generated using SAS (version 9.3; SAS Institute, Inc) and R (version 3.3.1; https://www.r-project.org) software.

Results

In the overall sample of 42 346 women, the mean (SD) age was 53 (10) years, with patients in New York being, on average, a year younger than patients in California (mean [SD] age, 54 [10] vs 53 [10] years; P < .001) (Table 1). Most patients were white (65.3%) in both states; however, we found differences in the overall distribution of races. In New York, African American individuals constituted 12.9% and Hispanic individuals constituted 9.2% of the population compared with 6.4% and 15.6%, respectively, in California. Although most patients undergoing mastectomy were in the highest income quartile (30.5%) in both states, more patients in California were in higher income categories (the third and fourth quartiles) than patients in NY (59.6% vs 46.3%; P < .001).

Figure 1 shows the unadjusted differences in IPBR in New York and California (eTable 4 in the Supplement). In general, New York had higher rates of IPBR compared with California (65.4% vs 51.5%; P < .001). The gap in IPBR between white and African American individuals was slightly larger in New York than in California (22% vs 18%; P = .001), with no substantial change in 2011. From 2008 to 2011, the gap between white and Hispanic individuals was 15% in New York (P < .001) vs 21% in California (P = .02), which in 2011 changed to 6% in New York (P = .02) vs 19% in California (P < .001). Before 2011, however, trends in racial/ethnic differences in IPBR in both states were almost parallel, with no significant differences in IPBR disparities between the 2 states. In 2011, the gaps between white and Hispanic individuals in New York decreased by 9 percentage points (95% CI, 0.02-0.15); between white individuals and other minorities in New York, by 8 percentage points (95% CI, 0.07-0.19; P < .001). The gap between white and African American individuals in New York decreased slightly, but the change was not statistically significant. No significant change in the differences between white individuals and minorities was observed in California.

Residing in New York compared with California was associated with higher odds of IPBR (odds ratio [OR], 1.72; 95% CI, 1.34-2.20; P < .001) (Table 2). The year 2011 was associated with higher odds of IPBR (OR, 1.37; 95% CI, 1.23-1.51; P < .001), showing a positive temporal effect in both states. However, the interaction of year 2011 and New York was not significant, showing that the law was not effective in increasing the overall IPBR rate in New York. Being African American (OR, 0.63; 95% CI, 0.55-0.73; P < .001), Hispanic (OR, 0.59; 95% CI, 0.50-0.69; P < .001), or another minority (OR, 0.48; 95% CI, 0.41-0.56; P < .001) was associated with lower odds of IPBR compared with being white, indicating a lower probability of undergoing IPBR among minorities regardless of where they lived. With use of the highest household income quartile as the reference, the odds of IPBR were lower in the first (OR, 0.40; 95% CI, 0.34-0.48; P < .001), second (OR, 0.44; 95% CI, 0.38-0.50; P < .001), and third (OR, 0.59; 95% CI, 0.54-0.66; P < .001) quartiles. In addition, payer was a significant predictive variable. Compared with private insurance, having Medicaid (OR, 0.29; 95% CI, 0.24-0.34; P < .001), Medicare (OR, 0.50; 95% CI, 0.46-0.54; P < .001), or no insurance (OR, 0.38; 95% CI, 0.27-0.55; P < .001) was associated with lower odds of IPBR. Finally, the combination of being Hispanic, living in New York, and the year 2011 was associated with higher odds of IPBR (OR,  2.08; 95% CI, 1.26-3.42; P = .004), suggesting that the law was effective in reducing the gap between white and Hispanic individuals in New York.

Table 3 shows the adjusted predictive disparities using the NAM definition. Although statistically significant, the decrease in disparities between African American and white individuals in New York and California was small. Disparities between Hispanic and white individuals decreased from 22% to 12% (P < .001) in New York compared with 26% to 25% in California (P < .001). The disparities between other minorities and white individuals decreased in New York from 31% to 23% (P < .001) but increased in California from 19% to 24% (P < .001).

Figure 2 shows the estimated effect of the NY PBH 2803-o law in IPBR disparities. The change in disparity between African American and white individuals was small and insignificant (1 percentage point; 95% CI, −0.02 to 0.04). However, the decreases in disparities between white and Hispanic individuals (9 percentage points; 95% CI, 0.06-0.11 percentage points; P < .001) and between white individuals and other minorities (13 percentage points; 95% CI, 0.11-0.16 percentage points; P < .001) were substantial.

Discussion

Our study highlighted 3 main findings pertaining to the effectiveness of the 2011 NY PBH Law 2803-o concerning disparities in IPBR. First, within the first year of implementation, the policy was not effective in increasing the overall rate of IPBR. Second, it did not reduce disparity in IPBR between white and African American individuals. Third, it substantially decreased disparities between white and Hispanic individuals and between white individuals and other minorities.

Although the rate of increase in IPBR varied among different population groups, IPBR increased over time in both states. After analysis of the effect of temporal increases in IPBR, the 2011 NY Law PBH 2803-o was not significant in increasing the overall rate of IPBR. One factor that may have contributed to this observation is the lack of enough data available for this policy evaluation owing to a short timeframe because we were only able to use data collected after 1 year of the enactment of the law.

Another factor contributing to the lack of a significant increase in the use of IPBR may be lack of physician knowledge about its benefits, with many referring physicians rating their knowledge about reconstruction as low.41 Although the 2011 NY Law PBH 2803-o mandates that hospitals provide information on the benefits and insurance coverage available for the procedure, physicians may avoid direct communication about PBR. Many patients reported communicating about PBR with their clinicians; however, only a small percentage of women reported having enough knowledge.42,43 With African American women being more likely than white women to report not knowing about PBR, racial disparity in knowledge could affect the use of PBR.42,44 Finally, the sex of the physician who communicates with the patient, whether the physician works in a cancer center, and the attitudes and biases that the physician may hold can also affect the likelihood of the physician referring a patient for reconstructive surgery.26,45 Increasing physician education about PBR and its potential benefits could lead to an increase in the overall effectiveness of the law.

Furthermore, despite speaking the same language, lack of trust and effective communication is more pronounced among African American individuals than among other minorities. Although the Tuskegee Syphilis Study ended nearly half a century ago, the bias of African American individuals about the medical system continues.46-48 For example, physician distrust among African American individuals negatively affects their conception about kidney transplant or their adherence to colorectal cancer screening.49,50 Compared with white individuals, African American individuals have fewer patient visits that include rapport building with their physicians.51

On the contrary, previous studies show that young, educated white patients have effective communication with their physicians, asking the most questions and providing useful information voluntarily.52 Physicians also ask more questions of their white patients compared with patients from minority groups.52 For example, African Americans’ visits with oncologists are reported to be shorter and to contain less discussion about the illness and potential risks related to their illness.52 Eggly et al53 and Johnson et al54 demonstrated that physicians were 23% more verbally dominating and 33% less patient centered when communicating with African American compared with white patients.

Although African Americans and other minorities disproportionately continue to have less access to quality health care in the United States, mainly because of socioeconomic factors, Hispanic individuals and other minorities do not share the same background and history as African American individuals. Research shows larger positive effects in response to improvement in access to care among Hispanic individuals compared with African American individuals.55 For example, Medicare Part D was more effective in reducing disparities between whites and Hispanic individuals in prescription drug use, spending, and hospitalization than it was in reducing these disparities between white and African American individuals.40,56 Another study indicates that the uninsured rate decreased by 12% among Hispanic individuals from before the Affordable Care Act to the first quarter of 2015, while the rate decreased by 6% among white individuals.57 In 2014 after passage of the Affordable Care Act, Hispanic individuals were 5% more likely to have a physician visit than in 2011 compared with white individuals, with a 3% increased probability and African American individuals with a 2% increased probability.58

Previous studies have noted language as a barrier for Hispanic individuals in access to care. Because many US plastic surgeons are white59 and speak English, with only 37% of US medical graduates reporting fluency in a language other than English,60 one would expect language to be a barrier in access to care for non–English-speaking patients. In 1998, the Office for Civil Rights of the Department of Health and Human Services issued a memorandum banning any barrier to health care because of patients’ limited English proficiency. Research indicates that non–English-speaking patients tend to ask more questions in a language-concordant setting.61 For example, a study conducted on language-concordant care in pediatric surgery found it to significantly increase understanding and patient satisfaction among Hispanic families when compared with groups who were serviced by an interpreter.62

Limitations

Our study had a few limitations. First, the Healthcare Cost and Utilization Project only provides information on IPBR. Because we did not have access to the longitudinal histories of the patients, individuals who received delayed breast reconstruction were defined as not undergoing IPBR. However, when clinically appropriate, approximately 82% of plastic surgeons perform IPBR.63 Second, we were unable to control for patient preferences regarding breast reconstruction. According to NAM, similar to health needs, differences in patients’ preferences should be adjusted for when estimating racial/ethnic disparities. For example, the proportion of differences between white individuals and minorities in IPBR, if related to their personal preferences, should not be considered as a disparity; unlike differences in socioeconomic status, the differences in patients’ preferences can be justified. Third, 1 year of data to measure the legislation’s effect on racial/ethnic disparities in IPBR is minimal; this time line may hamper our conclusion. As more data become available, further evaluation is warranted. Fourth, although we applied the DD approach to mitigate potential effects of extraneous events, the 2008 recession could have affected IPBR rates differently among various racial/ethnic groups in each state. Although the economic downturn might have affected overall rates of IPBR, we found no evidence of substantial differential effects between the 2 states. Finally, we lacked information regarding severity and stage of cancer, which could potentially affect a patient’s decision regarding IPBR. A substantial change, however, in racial/ethnic variations in cancer stage at the time of diagnosis or mastectomy before and after the law’s enactment is highly unlikely. Although we lacked this information, we do not expect it to have substantially changed our findings.

Conclusions

Our findings agreed with those of previous research that showed wide disparities in IPBR.18-21 In addition, research reveals a wide gap between white individuals and minorities in communication with their physicians.54,64,65 As of 2008, only 232 Hispanic and 151 African American plastic surgeons practiced in the United States compared with 3439 white plastic surgeons.59 This large difference in the race and ethnicity of plastic surgeons may have contributed to the disparities that we observed.

Our study found that passage of NY Law PBH 2803-o on physician-patient communication was associated with reducing disparities between white and Hispanic individuals and white individuals and other minorities, with no association between use of IPBR and disparities between white and African American individuals. Less knowledge about PBR,44 more financial barriers,42 and less timely access to plastic surgeons among women with lower income and fewer resources66 may reduce the potential effects of the law.

Back to top
Article Information

Corresponding Author: Elham Mahmoudi, PhD, MS, Section of Plastic Surgery, University of Michigan Medical School, 2800 Plymouth Rd, North Campus Research Complex, Bldg 16, Room G024W, Ann Arbor, MI 48202 (mahmoudi@med.umich.edu).

Accepted for Publication: March 4, 2017.

Published Online: May 31, 2017. doi:10.1001/jamasurg.2017.0921

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

Study concept and design: Mahmoudi, Metz, Momoh, Chung.

Acquisition, analysis, or interpretation of data: Mahmoudi, Lu.

Drafting of the manuscript: Mahmoudi, Metz.

Critical revision of the manuscript for important intellectual content: All authors.

Statistical analysis: Lu.

Obtained funding: Chung.

Administrative, technical, or material support: Mahmoudi, Momoh, Chung.

Study supervision: Mahmoudi.

Conflict of Interest Disclosures: None reported.

Funding/Support: This study was supported by Midcareer Investigator Award in Patient-Oriented Research 2 K24-AR053120-06 from the National Institutes of Health (Dr Chung).

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

Disclaimer: The conclusions and opinions presented herein are solely the responsibility of the authors and do not necessarily represent the official views the National Institutes of Health.

References
1.
Breastcancer.org. US breast cancer statistics. http://www.breastcancer.org/symptoms/understand_bc/statistics. Updated September 2016. Accessed October 16, 2016.
2.
Siegel  RL, Miller  KD, Jemal  A.  Cancer statistics, 2016.  CA Cancer J Clin. 2016;66(1):7-30.PubMedGoogle ScholarCrossref
3.
Miller  KD, Siegel  RL, Lin  CC,  et al.  Cancer treatment and survivorship statistics, 2016.  CA Cancer J Clin. 2016;66(4):271-289.PubMedGoogle ScholarCrossref
4.
Al-Ghazal  SK, Fallowfield  L, Blamey  RW.  Comparison of psychological aspects and patient satisfaction following breast conserving surgery, simple mastectomy and breast reconstruction.  Eur J Cancer. 2000;36(15):1938-1943.PubMedGoogle ScholarCrossref
5.
Cordeiro  PG.  Breast reconstruction after surgery for breast cancer.  N Engl J Med. 2008;359(15):1590-1601.PubMedGoogle ScholarCrossref
6.
Neto  MS, de Aguiar Menezes  MV, Moreira  JR, Garcia  EB, Abla  LE, Ferreira  LM.  Sexuality after breast reconstruction post mastectomy.  Aesthetic Plast Surg. 2013;37(3):643-647.PubMedGoogle ScholarCrossref
7.
Burwell  SR, Case  LD, Kaelin  C, Avis  NE.  Sexual problems in younger women after breast cancer surgery.  J Clin Oncol. 2006;24(18):2815-2821.PubMedGoogle ScholarCrossref
8.
Rowland  JH, Desmond  KA, Meyerowitz  BE, Belin  TR, Wyatt  GE, Ganz  PA.  Role of breast reconstructive surgery in physical and emotional outcomes among breast cancer survivors.  J Natl Cancer Inst. 2000;92(17):1422-1429.PubMedGoogle ScholarCrossref
9.
Heneghan  HM, Prichard  RS, Lyons  R,  et al.  Quality of life after immediate breast reconstruction and skin-sparing mastectomy: a comparison with patients undergoing breast conserving surgery.  Eur J Surg Oncol. 2011;37(11):937-943.PubMedGoogle ScholarCrossref
10.
Elder  EE, Brandberg  Y, Björklund  T,  et al.  Quality of life and patient satisfaction in breast cancer patients after immediate breast reconstruction: a prospective study.  Breast. 2005;14(3):201-208.PubMedGoogle ScholarCrossref
11.
Kanavos  P, Gemmill-Toyama  M.  Prescription drug coverage among elderly and disabled Americans: can Medicare–Part D reduce inequities in access?  Int J Health Care Finance Econ. 2010;10(3):203-218.PubMedGoogle ScholarCrossref
12.
California Association of Physician Groups. Knox-Keene Health Care Service Plan Act of 1975. California Association of Physician Groups. http://www.capg.org/index.aspx?page=124. Accessed July 16, 2016.
13.
FindLaw. New York Insurance Law § 3221: group or blanket accident and health insurance policies; standard provisions. http://codes.findlaw.com/ny/insurance-law/isc-sect-3221.html. Accessed July 16, 2016.
14.
California Legislative Information. SB-255 health care coverage: breast cancer. http://leginfo.legislature.ca.gov/faces/billTextClient.xhtml?bill_id=201120120SB255. Filed September 22, 2012. Accessed July 16, 2016.
15.
Wilkins  EG, Alderman  AK.  Breast reconstruction practices in North America: current trends and future priorities.  Semin Plast Surg. 2004;18(2):149-155.PubMedGoogle ScholarCrossref
16.
Alderman  AK, Wei  Y, Birkmeyer  JD.  Use of breast reconstruction after mastectomy following the Women’s Health and Cancer Rights Act.  JAMA. 2006;295(4):387-388.PubMedGoogle Scholar
17.
Lang  JE, Summers  DE, Cui  H,  et al.  Trends in post-mastectomy reconstruction: a SEER database analysis.  J Surg Oncol. 2013;108(3):163-168.PubMedGoogle ScholarCrossref
18.
Agarwal  S, Liu  JH, Crisera  CA, Buys  S, Agarwal  JP.  Survival in breast cancer patients undergoing immediate breast reconstruction.  Breast J. 2010;16(5):503-509.PubMedGoogle ScholarCrossref
19.
Offodile  AC  II, Tsai  TC, Wenger  JB, Guo  L.  Racial disparities in the type of postmastectomy reconstruction chosen.  J Surg Res. 2015;195(1):368-376.PubMedGoogle ScholarCrossref
20.
Paul  H  Jr, Prendergast  TI, Nicholson  B, White  S, Frederick  WA.  Breast reconstruction: current and future options.  Breast Cancer (Dove Med Press). 2011;3:93-99.PubMedGoogle Scholar
21.
Shippee  TP, Kozhimannil  KB, Rowan  K, Virnig  BA.  Health insurance coverage and racial disparities in breast reconstruction after mastectomy.  Womens Health Issues. 2014;24(3):e261-e269.PubMedGoogle ScholarCrossref
22.
Tseng  JF, Kronowitz  SJ, Sun  CC,  et al.  The effect of ethnicity on immediate reconstruction rates after mastectomy for breast cancer.  Cancer. 2004;101(7):1514-1523.PubMedGoogle ScholarCrossref
23.
Brennan  ME, Spillane  AJ.  Uptake and predictors of post-mastectomy reconstruction in women with breast malignancy: systematic review.  Eur J Surg Oncol. 2013;39(6):527-541.PubMedGoogle ScholarCrossref
24.
Kruper  L, Xu  XX, Henderson  K, Bernstein  L, Chen  SL.  Utilization of mastectomy and reconstruction in the outpatient setting.  Ann Surg Oncol. 2013;20(3):828-835.PubMedGoogle ScholarCrossref
25.
Greenberg  CC, Schneider  EC, Lipsitz  SR,  et al.  Do variations in provider discussions explain socioeconomic disparities in postmastectomy breast reconstruction?  J Am Coll Surg. 2008;206(4):605-615.PubMedGoogle ScholarCrossref
26.
Alderman  AK, Hawley  ST, Waljee  J, Morrow  M, Katz  SJ.  Correlates of referral practices of general surgeons to plastic surgeons for mastectomy reconstruction.  Cancer. 2007;109(9):1715-1720.PubMedGoogle ScholarCrossref
27.
Hartocollis  A. Before breast is removed, a discussion on options. New York Times. August 18, 2010. http://www.nytimes.com/2010/08/19/nyregion/19surgery.html. Accessed December 15, 2016.
28.
Montefiore. New law requires hospitals to inform breast cancer patients of breast reconstruction options. http://www.montefiore.org/body.cfm?id=1738&action=detail&ref=244. Published August 17, 2010. Accessed December 15, 2016.
29.
Garfein  ES.  The privilege of advocacy: legislating awareness of breast reconstruction.  Plast Reconstr Surg. 2011;128(3):803-804.PubMedGoogle ScholarCrossref
30.
FindLaw. New York Public Health Law § 2803-o. Hospital care for mastectomy, lumpectomy, and lymph node dissection patients. http://codes.findlaw.com/ny/public-health-law/pbh-sect-2803-o.html. Accessed July 16, 2016.
31.
New York State Department of Health. Dear Chief Executive Officer letter: advise facilities of recently-enacted laws that directly impact the operations of hospitals in New York State, January 11, 2011. https://www.health.ny.gov/professionals/hospital_administrator/letters/2011/2011-01-11_recently_enacted_laws_impacting_hospitals.htm. Published January 11, 2011. Accessed December 15, 2016.
32.
The New York State Senate. Public health. https://www.nysenate.gov/legislation/laws/PBH/2803. Accessed December 15, 2016.
33.
Healthcare Cost and Utilization Project. Central Distributor SID description of data elements: all states. Published April 2008. https://www.hcup-us.ahrq.gov/db/state/siddist/sid_multivar.jsp. Accessed May 2, 2016.
34.
Healthcare Cost and Utilization Project. HCUP User Support (HCUP-US).Updated April 2017. https://www.hcup-us.ahrq.gov/home.jsp. Accessed May 2, 2016.
35.
Healthcare Cost and Utilization Project. Elixhauser Comorbidity Software, Version 3.7. Updated March 2017. https://www.hcup-us.ahrq.gov/toolssoftware/comorbidity/comorbidity.jsp. Accessed August 2, 2016.
36.
Wooldridge  J. What’s new in econometrics? difference-in-differences estimation. NBER Summer Institute, miméo. http://www.nber.org/WNE/lect_10_diffindiffs.pdf. Published 2007. Accessed August 2, 2016.
37.
Imbens  GW, Wooldridge  JM.  Recent developments in the econometrics of program evaluation.  J Econ Lit. 2009;47(1):5-86.Google ScholarCrossref
38.
Institute of Medicine (US) Committee on Understanding and Eliminating Racial and Ethnic Disparities in Health Care; Smedley BD, Stith AY, Nelson AR, eds.  Unequal Treatment: Confronting Racial and Ethnic Disparities in Health Care. Washington, DC: National Academies Press; 2003.
39.
Cook  B, McGuire  TG, Lock  K, Zaslavsky  AM.  Comparing methods of racial and ethnic disparities measurement across different settings of mental health care.  Health Serv Res. 2010;45(3):825-847.PubMedGoogle ScholarCrossref
40.
Mahmoudi  E, Jensen  GA.  Has Medicare Part D reduced racial/ethnic disparities in prescription drug use and spending?  Health Serv Res. 2014;49(2):502-525.PubMedGoogle ScholarCrossref
41.
Wanzel  KR, Brown  MH, Anastakis  DJ, Regehr  G.  Reconstructive breast surgery: referring physician knowledge and learning needs.  Plast Reconstr Surg. 2002;110(6):1441-1450.PubMedGoogle ScholarCrossref
42.
Morrow  M, Mujahid  M, Lantz  PM,  et al.  Correlates of breast reconstruction: results from a population-based study.  Cancer. 2005;104(11):2340-2346.PubMedGoogle ScholarCrossref
43.
Potter  S, Mills  N, Cawthorn  S, Wilson  S, Blazeby  J.  Exploring information provision in reconstructive breast surgery: a qualitative study.  Breast. 2015;24(6):732-738.PubMedGoogle ScholarCrossref
44.
Alderman  AK, Hawley  ST, Janz  NK,  et al.  Racial and ethnic disparities in the use of postmastectomy breast reconstruction: results from a population-based study.  J Clin Oncol. 2009;27(32):5325-5330.PubMedGoogle ScholarCrossref
45.
Stacey  DH, Spring  MA, Breslin  TM, Rao  VK, Gutowski  KA.  Exploring the effect of the referring general surgeon’s attitudes on breast reconstruction utilization.  WMJ. 2008;107(6):292-297.PubMedGoogle Scholar
46.
Gamble  VN.  Under the shadow of Tuskegee: African Americans and health care.  Am J Public Health. 1997;87(11):1773-1778.PubMedGoogle ScholarCrossref
47.
Copeland  VC.  African Americans: disparities in health care access and utilization.  Health Soc Work. 2005;30(3):265-270.PubMedGoogle ScholarCrossref
48.
Boulware  LE, Cooper  LA, Ratner  LE, LaVeist  TA, Powe  NR.  Race and trust in the health care system.  Public Health Rep. 2003;118(4):358-365.PubMedGoogle ScholarCrossref
49.
Caito  N, Hood  S, Thompson  VL.  Discussing cancer: communication with African Americans.  Soc Work Health Care. 2014;53(6):519-531.PubMedGoogle ScholarCrossref
50.
Wachterman  MW, McCarthy  EP, Marcantonio  ER, Ersek  M.  Mistrust, misperceptions, and miscommunication: a qualitative study of preferences about kidney transplantation among African Americans.  Transplant Proc. 2015;47(2):240-246.PubMedGoogle ScholarCrossref
51.
Ghods  BK, Roter  DL, Ford  DE, Larson  S, Arbelaez  JJ, Cooper  LA.  Patient-physician communication in the primary care visits of African Americans and whites with depression.  J Gen Intern Med. 2008;23(5):600-606.PubMedGoogle ScholarCrossref
52.
Siminoff  LA, Graham  GC, Gordon  NH.  Cancer communication patterns and the influence of patient characteristics: disparities in information-giving and affective behaviors.  Patient Educ Couns. 2006;62(3):355-360.PubMedGoogle ScholarCrossref
53.
Eggly  S, Barton  E, Winckles  A, Penner  LA, Albrecht  TL.  A disparity of words: racial differences in oncologist-patient communication about clinical trials.  Health Expect. 2015;18(5):1316-1326.PubMedGoogle ScholarCrossref
54.
Johnson  RL, Roter  D, Powe  NR, Cooper  LA.  Patient race/ethnicity and quality of patient-physician communication during medical visits.  Am J Public Health. 2004;94(12):2084-2090.PubMedGoogle ScholarCrossref
55.
Ginzberg  E.  Access to health care for Hispanics.  JAMA. 1991;265(2):238-241.PubMedGoogle ScholarCrossref
56.
Mahmoudi  E, Jensen  GA, Tarraf  W.  Effects of Medicare Part D on racial/ethnic disparities in hospital utilization among seniors.  J Aging Health. 2015;27(5):797-826.PubMedGoogle ScholarCrossref
57.
Sommers  BD, Chua  KP, Kenney  GM, Long  SK, McMorrow  S.  California’s early coverage expansion under the Affordable Care Act: a county-level analysis.  Health Serv Res. 2016;51(3):825-845.PubMedGoogle ScholarCrossref
58.
Chen  J, Vargas-Bustamante  A, Mortensen  K, Ortega  AN.  Racial and ethnic disparities in health care access and utilization under the Affordable Care Act.  Med Care. 2016;54(2):140-146.PubMedGoogle ScholarCrossref
59.
Castillo-Page  L. Diversity in the Physician Workforce Facts and Figures 2010. Association of American Medical Colleges. https://www.aamc.org/initiatives/diversity/179816/facts_and_figures.html. Published March 14, 2011. Accessed September 18, 2016.
60.
Moreno  G, Walker  KO, Grumbach  K.  Self-reported fluency in non-English languages among physicians practicing in California.  Fam Med. 2010;42(6):414-420.PubMedGoogle Scholar
61.
Jaramillo  J, Snyder  E, Dunlap  JL, Wright  R, Mendoza  F, Bruzoni  M.  The Hispanic Clinic for Pediatric Surgery: a model to improve parent-provider communication for Hispanic pediatric surgery patients.  J Pediatr Surg. 2016;51(4):670-674.PubMedGoogle ScholarCrossref
62.
Dunlap  JL, Jaramillo  JD, Koppolu  R, Wright  R, Mendoza  F, Bruzoni  M.  The effects of language concordant care on patient satisfaction and clinical understanding for Hispanic pediatric surgery patients.  J Pediatr Surg. 2015;50(9):1586-1589.PubMedGoogle ScholarCrossref
63.
Alderman  AK, Wilkins  EG, Kim  HM, Lowery  JC.  Complications in postmastectomy breast reconstruction: two-year results of the Michigan Breast Reconstruction Outcome Study.  Plast Reconstr Surg. 2002;109(7):2265-2274.PubMedGoogle ScholarCrossref
64.
Cooper  LA, Roter  DL, Johnson  RL, Ford  DE, Steinwachs  DM, Powe  NR.  Patient-centered communication, ratings of care, and concordance of patient and physician race.  Ann Intern Med. 2003;139(11):907-915.PubMedGoogle ScholarCrossref
65.
Ashton  CM, Haidet  P, Paterniti  DA,  et al.  Racial and ethnic disparities in the use of health services: bias, preferences, or poor communication?  J Gen Intern Med. 2003;18(2):146-152.PubMedGoogle ScholarCrossref
66.
Roughton  MC, DiEgidio  P, Zhou  L, Stitzenberg  K, Meyer  AM.  Distance to a plastic surgeon and type of insurance plan are independently predictive of postmastectomy breast reconstruction.  Plast Reconstr Surg. 2016;138(2):203e-211e.PubMedGoogle ScholarCrossref
×