The Cost of Breast Cancer: A Comparison Between Private and Public Hospitals

Backgrounds: Breast cancer is the most prevalent cancer among women. Breast cancer imposes a considerable economic burden on the health system. This study aimed to compare the cost of breast cancer among patients who referred to private and public hospitals in Iran (2017). Methods: This was a prevalence-based cost of illness study. A total of 179 patients were selected from private and public hospitals using the census method. The researcher-constructed checklist was used for data collection. Data were analyzed using SPSS software version 22. Results: The estimated total mean ±SD direct cost of patients who referred to the private hospital and the public hospital was $10051.78±19484.61 and $3956.33±6783.02, respectively. Further, the total mean indirect cost of patients who referred to the private hospital was lower than those referring to the public hospital at $1870.89 (%15.69 of total costs) and $22348.5 (%84.95 of total costs), respectively. These differences were statistically signicant (P<0.05). Conclusions: Breast cancer imposes a substantial cost on patients, health insurance organizations and the whole society in Iran. Therefore, the adoption of effective measures for the prevention and early diagnosis of breast cancer is urgently needed.


Background
Cancer is a leading cause of death worldwide. The number of cancer cases and deaths is projected to grow rapidly due to population ageing and adopt lifestyle behaviours that increase cancer risk. This is especially important in low-and middle-income countries as they undergo an economic transition (1).
The estimated number of new cases and deaths of cancer was 2088849 and 626679, respectively, worldwide in 2018 (2).
Breast cancer is a major public health problem, and 1.7 million new cases are diagnosed per year. It has been shown that almost 60% of deaths from breast cancer occur in developing countries (3,4). In 2018, breast cancer was the most commonly diagnosed cancer in women (24.2%, i.e. nearly one in 4 of all new cancer cases diagnosed in women worldwide were breast cancer) (5). In 2018, it was estimated that 627,000 women died from breast cancer, contributing approximately 15% of all cancer deaths among women (5). It has been estimated that the incidence of women breast cancer worldwide will reach approximately 3.2 million new cases per year by 2050 (4).
Breast cancer in developing countries represents one-half of all breast cancer cases and 62% of cancer mortality (6). In Iran, breast cancer is the fth leading cause of cancer mortality (7)(8)(9). According to GLOBOCAN database 2018, the number of new cases, deaths and 5-years prevalence from breast cancer for women in Iran was estimated to be 13776, 3526 and 40825, respectively (10). In the last 30 years, the probability of breast cancer incidence for individuals aged 15-79 years in Iran has increased, according to the statistics (11). According to the statistics, 6160 breast cancer cases are diagnosed in the country each year, and 1063 cases result in death (12). In 2035 compared to 2012, the number of new cases will be nearly two times greater (13).
Breast cancer imposes a considerable economic burden on societies (14)(15)(16). For example, the total cost of breast cancer was more than three times the total cost of prostate cancer (17). A study by Figueiredo et al. indicated that between 2004 and 2014, public healthcare costs increased, and the correlation between breast cancer and public healthcare costs was positive, mainly in uenced by governmental strategies (18). Breast cancer imposes a signi cant nancial burden on healthcare systems of Iran (19,20). Policymakers and health planners are interested in understanding the economic burden of illnesses to assess the optimal allocation of health resources to various diseases and estimate the potential costs and bene ts of public health interventions (20).
Cost of illness (COI) studies indicate the importance of a particular disease and provide a baseline for assessing new interventions (20) and nancial losses as a result of illness (21). The aim of the COIstudies is providing an estimate of how much society spends on a particular disease and identifying different cost components (22). The COI can be used as a criterion for decision making in allocating limited budgets and resources for governmental health policies in effective control of diseases (21). A comprehensive economic analysis demands consideration of both direct and indirect costs such as productivity losses as a result of individuals unable to work because of hospitalization or outpatient visits, and also premature death arising from the illness (21).
In future, the cost of cancer care will increase as new sophisticated, expensive treatment modalities are adopted to raise the standard of care (23). Breast cancer is on the rise in Iran, and since patients are mostly diagnosed at more advanced stages of the disease (24,25), mortality resulting from breast cancer is high (26). So, the presentation of accurate data about the economic burden of the disease will allow informed decision making by health care policymakers in Iran about the prevention and treatment of the disease. Therefore, the objective of this study was to compare the cost of breast cancer among patients who referred to private and public hospitals in Iran in 2017.

Methods
This was a prevalence-based cost of illness study, which was conducted from the societal perspective using bottom-up approach costing.
The statistical population in this study included all patients with breast cancer. One hundred seventy-nine patients with breast cancer who admitted to the private hospital (N = 103) and the public hospital (N = 76) in Rasht (a city in the north of Iran) between Aug 2016 and Aug 2017 included in this study.
The cost of illness is divided into three general categories: direct costs, indirect costs, and intangible costs. Direct costs divided into two categories: direct medical costs and direct nonmedical costs. Direct medical costs involve all hospitalization and outpatient costs caused by health care procedures. Direct nonmedical costs involve transportation, food and lodging costs incurred for receiving medical treatment. Indirect costs include lost productivity due to premature deaths from illness and lost productivity due to absenteeism and presenteeism due to complications of illness as well as informal care costs. Finally, intangible costs include the cost of pain and suffering in patients and their families and relatives. In most cost of illness studies, intangible costs are often not calculated because of the methodological di culty.
In this study, the economic burden of breast cancer was assessed by calculating direct medical costs, direct nonmedical costs, and indirect costs. Data related to the hospitalization part of direct medical costs were extracted from patients' records and data related to the outpatient part of direct medical costs, direct nonmedical costs and indirect costs were obtained via an interview with patients and their family members, respectively. The researcher-made checklist was used for data collection. The checklist consists of demographic variables (age, marital status, monthly income status, educational status, job status, supplemental insurance status, and the type of basic insurance), duration of the disease and treatment type and questions of cancer-related costs.
Indirect costs were estimated using the Human Capital Approach. Indirect costs were estimated by summing two parts: 1) The costs of lost productivity due to patients and their families' missed workdays and 2) the cost of premature death due to breast cancer. First, in order to estimate the cost of missed workdays per patient, we calculated the average number of missed workdays by patients and their families because of breast cancer and then multiplied by the minimum daily wage rate (310000 (2017)), in this way we estimated the cost of missed workdays per patient. Also, by having the number and the mean age of premature death and retirement age (60 years old) in Iran, the total number of years lost due to premature death resulting from breast cancer was calculated and multiplied by the number of days of the year and the minimum daily wage rate, in this way the cost of premature death was calculated. Finally, the total cost of lost productivity calculated by summing these two parts.
The equations used for indirect costs calculation are as follows: 1. The cost of missed workdays = the mean (patients missed workdays + patient family's missed workdays) × minimum daily wage rate 2. C = the mean {(retirement age-age at premature death) × (the number of patients who died ÷ sample size)} × (minimum daily wage rate × the number days of the year) To recall bias prevention, patients' treatment process were followed up every two months for one year. All costs in this study were expressed as US Dollars based on the Exchange rate of Central Bank of the Islamic Republic of Iran (US$ 1 = 31389 Rials (2017)). Data were analyzed using SPSS software version 22 and excel (2016). Descriptive statistics (mean ± SD, frequency, and percent) were used to assess the demographic variables status. K-S test (Kolmogorov-Smirnov) was applied to assess the normality of data. Since the P-Value for all variables was less than 0.05 (P < 0.05), non-parametric tests, including Mann-Withney and Kruskal-Wallis, were used to assess the association between demographic variables and costs. The Spearman correlation coe cient also was used to examine the correlation between age at diagnosis and costs.

Results
A total of 179 patients with breast cancer were included in the analysis. The majority of patients were covered by the basic insurance (98.9%), and only 36.3% of patients were covered by supplemental insurance. Most of the patients (64.2% ) held a diploma degree and more than half of the patients were non-natives (54.2%). A statistically signi cant difference was found between supplemental insurance status and total medical direct cost (P < 0.05) Table 1.
The mean ± SD of age at diagnosis, age and age at death estimated at 45.41 ± 9.38, 47.98 ± 10.08 and 49.94 ± 11.80, respectively. The estimated mean ± SD number of hospital admission and the length of hospital stay of patients who referred to the private hospital was 1.35 ± 0.50 and 2.71 ± 2.49, respectively whereas those who referred to the public hospital was higher at 1.48 ± 085 and 8.63 ± 1049, respectively. Additionally, 10.7% of patients who referred to the private hospital and 6.6% of those referring to the public hospital postponed their treatment process for more than two months due to nancial barriers.     (27). So it can be concluded that the age of breast cancer onset has decreased in Iran in recent years. The average mortality age of breast cancer is still lower than other cancers, and the economic burden of this disease will rise in the predictable future, according to one study in Japan (21).
In this study, the total mean cost of breast cancer among patients who referred to the public hospital estimated at $ 22972.37 (76632.08 PPP current international $) ( The difference between direct and indirect costs in patients referred to private and public hospitals may be due to several reasons. First, premature death was the major component of the total indirect cost of breast cancer patients who referred to the public hospital, whereas that did not occur among breast cancer patients in the private hospital. This may be because private hospitals offered better services which resulted in a higher survival rate and a lower mortality rate. Besides, given that the mean age of patients with breast cancer referring to the public hospital (49.776.66 ± 9.89) was higher as compared with those referring to the private hospital (46.66 ± 10.06), and this difference was statistically signi cant (p < 0.05), the high mortality rate in the public hospital can be because most of the older patients referred to the public hospital. On the other hand, it is likely that patients with advanced-stage cancer referred more to public hospitals for receiving services. Second, None of the patients who referred to the public hospital had supplementary insurance, while most of the patients who referred to the private hospital, in addition to basic health insurance, were covered by supplemental insurance. Supplemental insurance has increased patients access to more advanced and expensive treatment services and has made services more inelastic by reducing the patients' co-payment or have led to increased induced demand. Also, in Iran, only people who had better socio-economic status and better income level were able to afford supplemental health insurance and subsequently received more expensive and advanced services, which in turn postponed their death. Third, tariffs in the private sector are 2-4 times higher than that of the public sector. Therefore, direct medical costs are higher in patients referring to the private sector. Finally, it can be concluded that those who referred to the private sector had better access to more advanced and expensive treatment services due to their better socio-economic status and supplemental insurance coverage, which caused the mortality rate and indirect costs among these patients to be lower, but due to more treatment services utilization, they incurred higher direct medical costs.
Since the present study was performed at cross-sectional and prevalence-based method, matching was not conducted between patients referring to the public and the private hospitals in terms of age, income level and disease stage and also the effect of confounding variables was not controlled. Since it is not possible to conclude with any certainty, it is necessary to investigate the cause of this difference in costs and mortality rate between patients referring to the public and the private hospitals in future studies using a perspective and controlled design.
Of the direct medical costs, outpatient costs were higher than hospitalization costs in both private and public hospitals.  (21), which the results of these studies are in line with our results.
The total cost of missed workdays for patient and patient's family who referred to the private hospital was 1.7 times greater than those referring to the public hospital, and the difference was not statistically signi cant (P > 0.05). Both in the private and the public hospital, the cost of missed workdays of patient's family members was greater than patients themselves. These costs (opportunity cost) are imposed on patients' families in real terms but are hidden from policymakers' view.
In our study, basic insurance played an important role in the reimbursement of direct medical costs and reducing the proportion of out-of-pocket expenses in direct medical costs. The majority of breast cancer costs in public hospitals was paid by basic insurance (%90.68), %6.39 of the costs was paid by the patient, and only a small proportion was paid from the targeted subsidy plan by the government (%2.92).
To the contrary, in the private hospitals, %35.36 of costs was reimbursement by supplemental insurance, %37.85 of costs was reimbursement by basic insurance, and the remaining %26.77 of costs (6.04 greater than those referring to the public hospitals) was paid by patients. The total out of pocket payments in the private hospital estimated at $3881.23 (approximately 0.38 of total direct costs and 2.83 times higher than in the public hospital), while in the public hospital was $1367.19 (about 0.34 of total direct costs).
Although most of the cancer patients in the private sector were covered by supplemental insurance, they paid higher co-payments. Since tariffs in the private sector are 2-4 times higher than that of the public sector, patients referring to private hospitals paid more out of pocket payments despite supplemental insurance. Therefore, these patients are likely to have better socio-economic status, more nancial capacity (purchasing power) and more ability to pay. On the other hand, despite higher costs, these patients may prefer to go to private hospitals because of the shorter waiting time and better service quality.

Limitations
This study had several limitations. First, since some patients refused to answer the questions asked of them, the selection bias (sampling bias and attrition) of respondents in reviewing the costs could not be avoided. Second, the indirect costs consisted of only the missed workdays and premature mortality, which would greatly undervalue the indirect economic burden of illness. The lack of data on permanent leaving the job by patients and caregivers during the recovery period could also underestimate the indirect cost estimates. Third, the cost of breastfeeding was not calculated due to the paucity of data. Fourth, intangible economic costs of breast cancer patients and their families, including the pain, sorrow, were not included because they are di cult to convert into a monetary value (33). Given this was a crosssectional and prevalence-based study, matching was not conducted between patients referring to the public and the private hospitals in terms of age, income level and disease stage and also the effect of confounding variables were not controlled. An additional limitation is that this study conducted in only two private and public hospitals that can limit the generalization of study ndings to all private and public sector.

Policy Implications
Given that the cost of premature death in the private hospital was zero, it is not possible to conclude with certainty whether cancer patients who referred to the public hospital were at the nal stage of the disease or bene ted from better services or both? If the low mortality rate and low indirect costs in patients referred to the private hospital be attributed to the quantity and quality of services provided to cancer patients referring to the private sector and considering the high share of indirect costs of total costs in patients referred to the public hospital, it is necessary that health policymakers take the necessary measures to improve the quantity and quality of public sector services. Also, despite the insurance coverage, patients suffer a high amount of OOP payment, and a substantial and wide-ranging effort is needed to support breast cancer patients. This suggests that insurance policies need to be revised to increase nancial support among cancer patients, especially for those who are currently uninsured. It is recommended that the results of this study to be used in future studies to evaluate the cost-effectiveness of screening interventions, early detection and preventive interventions, and health policymakers take an appropriate policy to reduce the economic burden of this disease.

Conclusion
Breast cancer imposes a substantial economic burden on patients at private and at public hospitals, healthcare system and society. Indirect costs were considerably higher for breast cancer patients and their caregivers referring to the public hospital, especially in terms of premature mortality than those referring to the private hospital, which can show a signi cant proportion of the total costs. Because indirect costs do not impose on the health system and health insurance organizations, health policymakers do not pay enough attention to these costs. Therefore, these costs must be addressed at the macro level of economic policymaking. Support strategies also should be adopted for cancer patients and their family members at parliament and government level, and unemployment insurance, improved for cancer patients.

Declarations Ethics declarations
Ethics approval and consent to participate This study was approved by the Deputy of Research and Technology, the Guilan University of Medical Sciences [grant number; 690320003]. Written consent was obtained from the authorities of the hospital prior to the start of the study. The questionnaire was completed by an in-person interview. Besides, prior to conducting the study, study objectives were explained to the participants, and informed consent was obtained from them. They were informed that the data was kept con dential and anonymous.

Consent for publication
All authors have approved the nal version of the manuscript.

Availability of data and materials
The datasets analyzed during the current study are not publicly available due to data protection regulations.

Competing interests
The authors have indicated that they have no con icts of interest regarding the content of this article.

Funding
This study was supported by the Deputy of Research and Technology, the Guilan University of Medical Sciences.

Author contributions
Somayeh Heydari, Abolghasem Pourreza, Abolhasan Afkar, and Abdolhosein Emami Sigaroudi contributed to the study design. Somayeh Heydari and Habib Jalilian contributed to the development of the economic model, the interpretation of the results and the drafting of the manuscript. Habibeh Mir contributed to this article by conducting interviews with patients. All authors have approved the nal version of the manuscript to be published and agree to be accountable for all aspects of the work.