Introduction

Previous studies have showed that breast cancer patients treated by low volume providers have inferior outcomes and survival than those treated by high volume providers [1,2]. Several studies have revealed predictors for low-volume providers among cancer patients. Among these factors, socioeconomic status was an important determinant. Several studies have showed that breast cancer patients of low SES, living in rural areas, far away from high volume hospitals were more likely to be treated at low-volume hospitals and by low-volume surgeons [3,4]. Low-SES patients might have less access to a high-volume provider due to their insurance status and live far away from a high volume hospital, which might be another important reason for survival disparities in breast cancer. However, most studies explore the association of individual SES and the access to a low-volume provider on a hospital or surgeon level [3–5]. Also, no large-scale study has explored the combined effect of patients’ individual and neighborhood SES on their access to a low-volume provider for breast cancer surgery. Moreover, it has not been fully understood that under a nationwide universal health insurance system, patients are able to seek care with any hospital or physician, how significant the breast cancer patients’ individual and neighborhood SES influences their choices on where to undergo breast cancer surgery.

The purpose of this study was to explore whether breast cancer patients from a lower individual and neighborhood SES are disproportionately receiving breast cancer surgery from low-volume providers under a nationwide universal health insurance system by using the Taiwan National Health Insurance Research Database (NHIRD).

Materials and Methods

Results

A total of 5,750 patients who received breast cancer surgery were included in the study. The cutoff point of breast cancer surgery for high-volume hospital and high-volume surgeon was 91 and 21 cases. Table 1 shows their baseline characteristics. The mean age at diagnosis differed by individual socioeconomic status. The mean age was 57 years in low-SES patients, 51 years in moderate-SES patients, and 48 years in high-SES patients.

Low-volume hospital

Breast cancer patients in disadvantaged neighborhood were more likely to visit low-volume hospitals (Figure 1). Table 2, in multivariate analysis, Model A shows patients with a moderate/low-SES in advantaged/disadvantaged neighborhood had the odds ratios ranging from 1.29 to 2.12 (p<0.05) to receive breast cancer surgery at a low-volume hospital, compared with high-SES patients in advantaged neighborhood. In Model B, after adjustment for patients' age, CCIS, geographic region and urbanization level of residence, only patients with a moderate- and low-SES in disadvantaged neighborhoods had an odds ratio of 1.47 (95% CI=1.19-1.81) and 1.31 (95% CI=1.05-1.64) respectively, compared with high-SES patients in advantaged neighborhood. Predictors of surgery at a low-volume hospital were moderate- and low-SES in disadvantaged neighborhoods, increased age, and not living in urban areas.

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Figure 1. The proportion of receiving breast cancer surgery at a low-volume hospital in breast cancer patients by individual and neighborhood SES.

https://doi.org/10.1371/journal.pone.0081801.g001

Variable	Model A				Model B*
	Odds ratio	95% CI	p value		Odds ratio	95% CI	p value
Neighborhood socioeconomic status
High SES in Advantaged Neighborhood	1				1
High SES in Disadvantaged Neighborhood	1.27	0.99-1.62	0.056		0.92	0.71-1.19	0.514
Moderate SES in Advantaged Neighborhood	1.34	1.09-1.66	0.006		1.20	0.97-1.49	0.093
Moderate SES in Disadvantaged Neighborhood	2.12	1.75-2.56	<0.001		1.47	1.19-1.81	<0.001
Low SES in Advantaged Neighborhood	1.29	1.06-1.58	0.012		1.13	0.92-1.40	0.240
Low SES in Disadvantaged Neighborhood	1.89	1.54-2.32	<0.001		1.31	1.05-1.64	0.016
Patients' age					1.01	1.01-1.02	0.002
CCIS					1.01	0.99-1.03	0.170
Geographic region
Northern					1
Central					1.07	0.91-1.27	0.401
Southern					1.42	1.22-1.66	<0.001
Eastern					5.87	3.59-9.61	<0.001
Urbanization level
Urban					1
Suburban					1.34	1.17-1.54	<0.001
Rural					1.48	1.21-1.80	<0.001
Hosmer-Lemeshow goodness-of-fit test					4.16		0.842

Table 2. Odds ratios of individual SES for low-volume hospital in advantaged and disadvantaged neighborhoods.

*Adjusted for patients' age, Charlson Comorbidity Index Score, geographic region and urbanization level of residence.

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Low-volume surgeon

Breast cancer patients with lower SES were more likely to visit low-volume surgeons (Figure 2). Table 3, in Model B multivariate analysis, after adjustment for patients' age, CCIS, geographic region and urbanization level of residence, patients with a moderate- and low-SES in advantaged/disadvantaged neighborhoods had the odds ratios ranging from 1.51 to 1.80 (p<0.001) to receive breast cancer surgery from a low-volume surgeon, compared with high-SES patients in advantaged neighborhoods. Predictors of surgery by a low-volume surgeon were moderate- and low-SES in advantaged/disadvantaged neighborhoods, and increased age.

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Figure 2. The proportion of receiving breast cancer surgery from a low-volume surgeon in breast cancer patients by individual and neighborhood SES.

https://doi.org/10.1371/journal.pone.0081801.g002

Variable	Model A				Model B*
	Odds ratio	95% CI	p value		Odds ratio	95% CI	p value
Neighborhood socioeconomic status
High SES in Advantaged Neighborhood	1				1
High SES in Disadvantaged Neighborhood	1.47	1.15-1.88	0.002		1.25	0.97-1.62	0.087
Moderate SES in Advantaged Neighborhood	1.60	1.29-1.98	<0.001		1.51	1.22-1.87	<0.001
Moderate SES in Disadvantaged Neighborhood	2.05	1.69-2.49	<0.001		1.75	1.42-2.16	<0.001
Low SES in Advantaged Neighborhood	1.79	1.47-2.19	<0.001		1.55	1.26-1.91	<0.001
Low SES in Disadvantaged Neighborhood	2.21	1.80-2.72	<0.001		1.80	1.44-2.25	<0.001
Patients' age					1.01	1.01-1.02	<0.001
CCIS					1.02	0.99-1.04	0.092
Geographic region
Northern					1
Central					1.06	0.90-1.25	0.464
Southern					1.12	0.96-1.31	0.152
Eastern					4.64	2.90-7.44	<0.001
Urbanization level
Urban					1
Suburban					1.15	1.01-1.32	0.047
Rural					1.01	0.82-1.23	0.956
Hosmer-Lemeshow goodness-of-fit test					7.88		0.445

Table 3. Odds ratios of individual SES for low-volume surgeons in advantaged and disadvantaged neighborhoods.

*Adjusted for patients' age, Charlson Comorbidity Index Score, geographic region and urbanization level of residence.

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In Hosmer-Lemeshow goodness-of-fit test for low-volume hospital and low-volume surgeon, both p values >0.05 that shows the model has a good fit to the data.

Table 4 shows patients in disadvantaged neighborhoods had lower healthcare resources, such as physicians per 10,000 residents and pharmacists. High-SES patients in advantaged neighborhoods were more likely to have higher median household income. This data supported the reason for using six individual and neighborhood SES groups.

	High individual SES			Moderate individual SES			Low individual SES
	Advantaged neighborhood	Disadvantaged neighborhood		Advantaged neighborhood	Disadvantaged neighborhood		Advantaged neighborhood	Disadvantaged neighborhood	p value
Number of patients	858	518		891	1401		1176	906
Mean age, mean±SD	47±8	49±8		49±9	52±11		58±13	56±13	<0.001
Education ≥ high school, %	98.0	87.5		96.4	74.7		98.1	86.0	<0.001
Median household income, NT$1000	647±76	507±35		615±58	494±41		628±68	502±35	<0.001
Health care-related resources
Physicians per 10,000 persons, mean±SD	28±23	17±17		23±17	13±14		26±21	13±14	<0.001
Pharmacists per 10,000 persons, mean±SD	11±13	5±4		8±10	4±4		10±12	4±4	<0.001

Table 4. Sociodemographic characteristics by individual and neighborhood socioeconomic status (n=5750).

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Discussion

From a national database study of 5,750 patients who received breast cancer surgery under a nationwide universal health insurance system in 2006, we explored the association of the combined effect of individual and neighborhood SES on the access to a low-volume provider for surgical treatment in cases of breast cancer. Our series revealed that breast cancer patients with moderate/low SES in disadvantaged neighborhoods were more likely to receive breast cancer surgery at low-volume hospitals, while individuals with moderate/low SES were more likely to receive breast cancer surgery from low-volume surgeons. Even under a nationwide universal health insurance system, disparities in access to healthcare exist. The authorities may provide more breast cancer treatment information to these vulnerable groups and the public health policies should keep focusing on them.

The strengths of our study are based on the fact that it was a large population-based cross-sectional study (n=5,750), with nearly complete follow-up information of access to healthcare institutes among the whole study population (99%), as well as the fact that the dataset is routinely monitored for diagnostic accuracy by the National Health Insurance Bureau of Taiwan. The trend in access to a low-volume provider among the surgeons and hospitals showed a positive association between combined SES and low-volume providers.

The SES of a patient played a key factor in receiving breast cancer surgery. Inequalities in the utilization of medical resources may affect patients from different SES. High-SES breast cancer patients, either living in advantaged or disadvantaged neighborhoods, have a lower rate of visiting a low-volume provider. High-SES breast cancer patients may use their knowledge, information, money, social connections, and other available resources to improve their health status even they live in disadvantaged neighborhoods. On the contrary, lower-SES patients even in advantaged neighborhoods where possessed more health-related resources were associated with higher odds to receiving breast cancer surgery from low-volume surgeons. A lower SES may cause stress, depression, and isolation on patients [10], which made it harder for lower-SES patients to obtain useful information or advice from relatives, friends, or acquaintances.

Our previous study showed that low-SES breast cancer patients had a higher risk of mortality [11]. In the current study, we found such patients were more likely to be treated by low-volume providers, a factor for survival disparities [2,12–14] this correlation may be one of the reasons for the survival disparities across breast cancer patients with different SES.

Our findings can be applied to policy intervention to reduce healthcare disparities. It has been suggested that the referral of patients to high-volume hospitals will provide a better application of recommended processes of care [13,15]. Our study showed that in addition to referring breast cancer patients to a high-volume hospital, referring patients to a high-volume surgeon may be another consideration.

However, under a universal insurance coverage lower-SES patients in disadvantaged neighborhoods were still more likely to receive breast cancer surgery at a low-volume hospital. Inconvenience and a considerable amount of expenses to traveling for surgery may be one of the reasons. Therefore, a more important point for lower-SES breast cancer patients other than referring them to a high-volume provider is the difference in their treatment quality comparing to high-SES patients. Research organizations and payers may conduct clinical quality improvement research to identify care, treatment strategies, and process differences between providers of different volumes. It has been suggested that there are some low-volume providers who get good results, and therefore referral to relative low-volume providers should be supported if good outcomes can be demonstrated [15]. This may be more convenient for older and lower-SES breast cancer patients to be treated close to home and may be less controversial than referring every patient to high-volume providers without considerations of their age, lower-SES and geographical factors.

Our study has limitations. First, our database does not contain address information that the distance from each patient residence to the nearest high-volume hospital and surgeon cannot be obtained. But we collected the neighborhood health care-related resources as a reference of their nearest access to medical service providers. Second, the diagnosis of breast cancer, and any comorbidity, was completely dependent on ICD codes. Nonetheless, the National Health Insurance Bureau of Taiwan randomly reviews the charts and interviews patients in order to verify diagnosis accuracy. Third, the relationship of the stages of breast cancer patients could not be assessed because cancer stage data was not included in the database. However, Begg et al. revealed that cancer stage was independent of caseload volume in a SEER-Medicare linked database [16].

In summary, even under a nationwide universal health insurance system, our findings indicate that disparities in access to healthcare exist. Breast cancer patients from a lower individual and neighborhood SES are more likely to receive breast cancer surgery from low-volume providers. The authorities should provide more breast cancer treatment information to these vulnerable groups and help these groups from receiving inadequate treatment. The public health policies should keep focusing on lower SES groups to reduce health disparities.

Supporting Information

Acknowledgments

This study is based in part on data from the National Health Insurance Research Database provided by the Bureau of National Health Insurance, Department of Health and managed by the National Health Research Institutes (registration number 101115). The interpretation and conclusions contained herein do not represent those of the Bureau of National Health Insurance, Department of Health, or the National Health Research Institutes.