There are a few limitations to this study. We did not have data about breast cancer stage, but we excluded all patients with metastatic cancer, and the likelihood of death from early-stage breast cancer is low. Moreover, stage should not significantly have an impact on short-term 90-day survival. Similarly, we also did not have data about receipt of chemotherapy or radiation treatment, which can affect survival, but most nonmetastatic breast cancer survivors will survive greater than 90 days after surgery, and the receipt of chemotherapy or radiation treatment should also not have an impact on such short-term survival. We were also unable to obtain data on delay in treatment or poorer treatment adherence, but 90-day postsurgical survival should also not be affected by these factors. Moreover, Pfister et al26 recently showed that it is possible to demonstrate outcome differences by hospital type with administrative data and that the addition of patient-level data (such as cancer stage or date of diagnosis) do not appreciably alter the findings. In addition, although year of surgery was included as a confounding variable, we can not explain variations in 90-day survival by year of surgery. Last, although facilities with the highest Medicaid volume had sicker patients who had a greater number of comorbidities, even after adjustment for type and number of comorbidities, we found a survival difference between women who received breast cancer surgery at the very low Medicaid quintile facilities compared with the very high Medicaid quintile facilities.
Even after adjusting for multiple patient-level factors, we found that 90-day survival was significantly lower at NYS facilities in the highest Medicaid quintile, suggesting that these hospitals may provide poorer quality care for patients with breast cancer. The enactment of the ACA has improved access to care and has decreased racial disparities in insurance coverage, particularly in states with expanded Medicaid programs.27–30 However, the challenge of improving patient outcomes through the ACA will persist if quality of care varies at under-resourced, financially strained hospitals that serve a predominantly Medicaid population.
To further compound these issues, with the implementation of the ACA, safety-net hospitals that rely predominantly on DSH payments are experiencing greater penalties under the Hospital Readmissions Reduction Program, thus exposing them to even greater financial constraints.20 Neuhausen et al. demonstrated that safety-net hospitals in California could face substantial funding gaps of up to $1.5 billion by 2019 because decreases in uncompensated care costs would not match increases in revenue from insured patients under the current ACA implementation plans with DSH payment reductions.32 Given that these hospitals take care of our most vulnerable patients with higher medical complexity, it is crucial that we better understand the factors associated with worse quality of care to develop interventions that can reduce these disparities in care.
One factor that has been shown to be associated with worse outcomes and quality of breast cancer care has been hospital surgical volume.33 For complex surgeries of relatively uncommon cancers such as pancreatectomy and esophagectomy, the underlying assumption of improved outcomes harkens back to the “practice makes perfect” adage. But breast cancer is a relatively common cancer and with a fairly straightforward surgical procedure and negligible operative mortality. Our finding of significantly higher short-term mortality rates in high Medicaid facilities raises concerns about the quality of perioperative and postoperative care. Hospitals that perform fewer surgeries have been consistently shown to have higher mortality rates and worse quality process indicators for breast cancer.34–36 A policy approach that has been undertaken by some states to help improve cancer care quality is to restrict state payments to lower-volume hospitals. For example, in 2009, NYS implemented limitations on Medicaid reimbursement to facilities that performed fewer than 30 breast surgery cases a year.37 But even with this limitation, most NYS breast cancer surgical cases covered by Medicaid are performed at safety-net hospitals, and this limitation has performed little to have an impact on sites of breast cancer care. Furthermore, an unintended consequence of such policies is that they may limit access to breast cancer treatment for more vulnerable rural patients with limited access to care. Thus, development of policies to improve overall cancer care must ensure that they do not adversely affect access and places the responsibility of improving surgical outcomes with the hospitals themselves. The challenge for hospital administrators becomes even greater: how can care be improved when patient volume is increasing and hospital reimbursement decreasing? Possible strategies include negotiating with organizations such as the Commission on Cancer or American College of Surgeons' National Surgical Quality Improvement Program38 to obtain markedly reduced fees or have Offices of Medicaid incentivize hospitals' participation in such efforts.
In conclusion, patients with breast cancer who received surgery in hospitals with the highest Medicaid volumes had a greater than 2-fold risk of death in the 90 days after surgery compared with those who received surgery in hospitals with the lowest Medicaid volume. These high Medicaid hospitals that already disproportionately serve poorer and minority patients with breast cancer may be at a greater risk of worsening quality of care with reductions in DSH payments and Hospital Readmission Reduction Program penalties under the ACA mandate because patient volume may increase but reimbursements drop. Further research should be made to assess how the implementation of these programs affect outcomes for the most vulnerable cancer patients who are receiving care at these lower-margin, financially strained hospitals.
Lawmakers and hospital leadership must ensure that quality of care and access are not negatively affected by these policies, which may contribute to worsening healthcare disparities.
References
1. Hershman D, McBride R, Jacobson JS, et al. Racial disparities in treatment and survival among women with early-stage breast cancer. J Clin Oncol. 2005;23:6639–6646.
2. Ooi SL, Martinez ME, Li CI. Disparities in breast cancer characteristics and outcomes by race/ethnicity. Breast Cancer Res Treat. 2011;127:729–738.
3. Byers TE, Wolf HJ, Bauer KR, et al. The impact of socioeconomic status on survival after cancer in the United States: Findings from the National Program of Cancer Registries Patterns of Care Study. Cancer. 2008;113:582–591.
4. Sprague BL, Trentham-Dietz A, Gangnon RE, et al. Socioeconomic status and survival after an invasive breast cancer diagnosis. Cancer. 2011;117:1542–1551.
5. Livaudais JC, Hershman DL, Habel L, et al. Racial/ethnic differences in initiation of adjuvant hormonal therapy among women with hormone receptor-positive breast cancer. Breast Cancer Res Treat. 2012;131:607–617.
6. Bickell NA, Wang JJ, Oluwole S, et al. Missed opportunities: Racial disparities in adjuvant breast cancer treatment. J Clin Oncol. 2006;24:1357–1362.
7. Crowley MM, McCoy ME, Bak SM, et al. Challenges in the delivery of quality breast cancer care: Initiation of adjuvant hormone therapy at an urban safety net hospital. J Oncol Pract. 2014;10:e107–e112.
8. Warner ET, Tamimi RM, Hughes ME, et al. Racial and ethnic differences in
breast cancer survival: Mediating effect of tumor characteristics and sociodemographic and treatment factors. J Clin Oncol. 2015;33:2254–2261.
9. Wu AH, Gomez SL, Vigen C, et al. The California breast cancer survivorship consortium (CBCSC): Prognostic factors associated with racial/ethnic differences in
breast cancer survival. Cancer Causes Control. 2013;24:1821–1836.
10. Adams SA, Butler WM, Fulton J, et al. Racial disparities in breast cancer mortality in a multiethnic cohort in the southeast. Cancer. 2012;118:2693–2699.
11. Ayanian JZ, Kohler BA, Abe T, Epstein AM. The relation between health insurance coverage and clinical outcomes among women with breast cancer. N Engl J Med. 1993;329:326–331.
12. 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;103:701–710.
13. Sail K, Franzini L, Lairson D, Du X. Differences in treatment and survival among African-American and Caucasian women with early stage operable breast cancer. Ethn Health. 2012;17:309–323.
14. Bickell NA, Weidmann J, Fei K, Lin JJ, Leventhal H. Underuse of breast cancer adjuvant treatment: Patient knowledge, beliefs, and medical mistrust. J Clin Oncol. 2009;27:5160–5167.
15. Dehal A, Abbas A, Johna S. Comorbidity and outcomes after surgery among women with breast cancer: Analysis of nationwide in-patient sample database. Breast Cancer Res Treat. 2013;139:469–476.
17. Bickell NA, LePar F, Wang JJ, Leventhal H. Lost opportunities: Physicians' reasons and disparities in breast cancer treatment. J Clin Oncol. 2007;25:2516–2521.
18. Linehan K. CMS's proposed rule implementing the ACA-mandated Medicaid DSH reductions. NHPF Issue Brief 2013;25:1–11.
19. Centers for Medicare & Medicaid Services (CMS), HHS. Medicaid program; state disproportionate share hospital allotment reductions. Final ruleFed Regist. 2013;78:57293–57313.
20. Boozary AS, Manchin J III, Wicker RF. The medicare hospital readmissions reduction program: Time for reform. JAMA. 2015;314:347–348.
21. Sheikh K, Bullock C. Urban-rural differences in the quality of care for medicare patients with acute myocardial infarction. Arch Intern Med. 2001;161:737–743.
22. Jha AK, Epstein AM. The predictive accuracy of the New York State coronary artery bypass surgery report-card system. Health Aff (Millwood). 2006;25:844–855.
23. Jha AK, Orav EJ, Epstein AM. Low-quality, high-cost hospitals, mainly in South, care for sharply higher shares of elderly black, hispanic, and medicaid patients. Health Aff (Millwood). 2011;30:1904–1911.
25. Charlson ME, Pompei P, Ales KL, MacKenzie CR. A new method of classifying prognostic comorbidity in longitudinal studies: Development and validation. J Chronic Dis. 1987;40:373–383.
26. Pfister DG, Rubin DM, Elkin EB, et al. Risk adjusting survival outcomes in hospitals that treat patients with cancer without information on cancer stage. JAMA Oncol. 2015;1:1303–1310.
27. Wherry LR, Miller S. Early coverage, access, utilization, and health effects associated with the Affordable Care Act Medicaid expansions: A quasi-experimental study. Ann Intern Med. 2016;164:795–803.
28. Buchmueller TC, Levinson ZM, Levy HG, Wolfe BL. Effect of the Affordable Care Act on racial and ethnic disparities in health insurance coverage. Am J Public Health. 2016;106:1416–21.
29. Collins SR, Gunja M, Doty MM, Beutel S. Americans' experiences with ACA marketplace and Medicaid Coverage: Access to care and Satisfaction: Findings from the commonwealth fund affordable care act tracking survey February–April 2016. Issue Brief (Commonw Fund). 2016;14:1–18.
30. Sommers BD, Blendon RJ, Orav EJ, Epstein AM. Changes in utilization and health among low-income adults after Medicaid expansion or expanded private insurance. JAMA Intern Med. 2016;176:1501–1509.
31. Ly DP, Jha AK, Epstein AM. The association between hospital margins, quality of care, and closure or other change in operating status. J Gen Intern Med. 2011;26:1291–1296.
32. Neuhausen K, Davis AC, Needleman J, Brook RH, Zingmond D, Roby DH. Disproportionate-share hospital payment reductions may threaten the financial stability of safety-net hospitals. Health Aff (Millwood). 2014;33:988–996.
33. Begg CB, Cramer LD, Hoskins WJ, Brennan MF. Impact of hospital volume on operative mortality for major
cancer surgery. JAMA. 1998;280:1747–1751.
34. Roohan PJ, Bickell NA, Baptiste MS, Therriault GD, Ferrara EP, Siu AL. Hospital volume differences and five-year survival from breast cancer. Am J Public Health. 1998;88:454–457.
35. Vrijens F, Stordeur S, Beirens K, Devriese S, Van Eycken E, Vlayen J. Effect of hospital volume on processes of care and 5-year survival after breast cancer: A population-based study on 25000 women. Breast. 2012;21:261–266.
36. Chen CS, Liu TC, Lin HC, Lien YC. Does high surgeon and hospital surgical volume raise the five-year survival rate for breast cancer? A population-based study. Breast Cancer Res Treat. 2008;110:349–356.
38. Hall BL, Hamilton BH, Richards K, Bilimoria KY, Cohen ME, Ko CY. Does surgical quality improve in the American College of Surgeons National Surgical Quality Improvement Program: An evaluation of all participating hospitals. Ann Surg. 2009;250:363–376.
Journal for Healthcare Quality is pleased to offer the opportunity to earn continuing education (CE) credit to those who read this article and take the online posttest at www.nahq.org/journal/ce. This continuing education offering, JHQ 276 (41.1 Jan/Feb 2019), will provide 1 hour to those who complete it appropriately.
Core CPHQ Examination Content Area
IV. [Domain - Quality Review and Accountability.]
Breast Cancer: Does type of hospital where you get surgery affect survival?
Learning Objectives:
After reading this article and taking this test, the learner should be able to:
- Recognize that women with breast cancer who undergo surgery at hospitals with highest Medicaid volume have higher 90-day mortality rates.
- Identify factors that may impact hospitals’ quality of care.
- Question the impact of the Affordable Care Act on improving patient outcomes at under-resourced hospitals.
- 1. Women who receive breast cancer surgery at hospitals with higher Medicaid volume are more likely to have the following characteristics:
- a. Older, minority race, fewer comorbidities
- b. Older, minority race, more comorbidities
- c. Younger, minority race, fewer comorbidities
- d. Younger, minority race, more comorbidities
- 2. The 90-day mortality hazard ratio for women who received breast cancer surgery at hospitals with the highest Medicaid volume compared to those who underwent surgery at hospitals with the lowest Medicaid volume was:
- a. 2.1
- b. 2.5
- c. 2.7
- d. 3.2
- 3. Disparities in breast cancer care for women with Medicaid may be due to the following:
- a. Lower health literacy
- b. More comorbidities
- c. More medical mistrust
- d. All of the above
- 4. Patients' 90-day mortality rates after breast cancer surgery may be affected by the following:
- a. Adherence to treatment recommendations
- b. Delay in receipt of surgery
- c. Peri- or post-operative care
- d. Receipt of chemotherapy or radiation therapy
- 5. Part of the mandate under the Affordable Care Act (ACA) includes:
- a. Decreased Disproportionate Share Hospital (DSH) reimbursements
- b. Increased Disproportionate Share Hospital (DSH) reimbursements
- c. No change in Disproportionate Share Hospital (DSH) reimbursements
- d. None of the above
- 6. Worse quality of surgical care at hospitals may be due to the following:
- a. Higher surgical volume
- b. Increased financial strain
- c. Increased staffing
- d. None of the above
- 7. In New York State, the percentage of breast cancer patients with Medicaid who receive care at hospitals that rely on Disproportionate Share Hospital (DSH) reimbursements is:
- a. 2%
- b. 30%
- c. 57%
- d. 83%
- 8. With enactment of the Affordable Care Act (ACA), safety-net hospitals in California that rely on Disproportionate Share Hospital (DSH) reimbursements may
- a. Face substantial funding gaps
- b. Increase patient volume
- c. Lose insured patients to other hospitals
- d. Receive more funding
- 9. Hospitals that rely on Disproportionate Share Hospital (DSH) reimbursements may
- a. Experience financial hardship with the enactment of the Affordable Care Act (ACA)
- b. Have higher readmission rates
- c. Both A and B
- d. None of the above
- 10. An unintended consequence of policies to limit reimbursements to hospitals with low surgical volume may be:
- a. Decreased post-operative complications
- b. Decreased treatment access for vulnerable patients with limited access to care
- c. Increased volume of insured patients at safety-net hospitals
- d. None of the above
Authors' Biographies
Jenny J. Lin, MD, MPH, is an associate professor in the Division of General Internal Medicine, Icahn School of Medicine at Mount Sinai in New York, NY. She is a primary care physician and cancer researcher investigating comorbidity management in cancer survivors. For this project, she was responsible for the conduct and interpretation of study findings, manuscript writing, and revising.
Natalia Egorova, PhD, MPH, is an associate professor in the Department of Population Health Science and Policy, Icahn School of Medicine at Mount Sinai in New York, NY. She is expert in analysis of large healthcare survey and discharge databases. For this project, she was responsible for the data analysis, manuscript writing, and revising.
Rebeca Franco, MPH, is a project manager in the Department of Population Health Science and Policy, Icahn School of Medicine at Mount Sinai in New York, NY. She is responsible for managing several multisite studies. For this project, she participated in the execution of the study protocol and data analysis and was involved with manuscript development.
Nina A. Bickell, MD, MPH, is a professor in the Department of Population Health Science and Policy, Icahn School of Medicine at Mount Sinai in New York, NY. She is a health services researcher investigating cancer disparities. For this project, she was responsible for the design, conduct, and interpretation of study findings and manuscript writing and revising.