Background
The implementation of the SPSS in 2004 initially arose with the purpose of providing public health services to the population without social security in Mexico. This plan became the health insurance system that guarantees access to health services to everyone regardless of their employment or socioeconomic status. The SPSS, which operates through the Seguro Popular (SP-entity that operates as an insurer), covers a specific catalog of health interventions through the Catálogo Universal de Servicios de Salud (CAUSES-Universal Catalog of Health Services) and a high cost interventions package called Fondo de Protección contra Gastos Catastróficos (FPGC-Fund for Protection against Catastrophic Expenditure). In addition, the Seguro Médico Siglo XXI (SMSXXI-21st Century Medical Insurance) was created, and provides additional coverage of what would be considered in CAUSES and FPGC for children under 5 years old [
1]. Among the main objectives of the SP was to offer health coverage for vulnerable population, besides reducing catastrophic and impoverishing expenditures. High cost diseases (cancers, lysosomal diseases, HIV, etc.) represented a significant financial burden for households that lacked access to health insurance, most of the population without access to health services suffering from a highcost disease did not receive medical attention. Therefore, the FPGC was created; the objective of this fund is to cover highcost diseases for population affiliated to the SP, and includes an explicit catalog of interventions. An important part of the FPGCs resources is spent on breast cancer treatment [
2]. Breast cancer is globally classified among the main public health problems [
3], the most frequent occurring in women; each year 1.38 million of new cases are detected and 458,000 deaths are caused by this disease. It is estimated that about half of cancer cases and 60
\(\%\) of the deaths are reported in developing countries [
4]. According to data from the Pan American Health Organization (PAHO) in 2012, in Latin America and the Caribbean, 27
\(\%\) of new cancer cases and 15
\(\%\) of deaths caused by cancer are due to breast cancer. In North America, 30
\(\%\) of new cases and 15
\(\%\) of deaths caused by cancer in women are attributed to breast cancer [
5]. In Mexico, breast cancer currently is ranking first in terms of incidence of neoplasms in women, accounting for 11.43
\(\%\) of all cancers. The most affected group is between 40 and 59 years old [
6]. The number of breast cancer cases in Mexico was estimated at 20,444 and fatal cases were 5595 for the year 2012 [
7]. There is a strong relation between age and mortality in breast cancer, the number of patients having this disease is significantly increasing from 30 to 64 years old. On the other hand, and for obvious reasons, mortality increases with age [
8].
The coverage of breast cancer on the FPGC
TThe FPGC has as objective to cover financially the attention of diseases of high specialty and high cost, which may endanger peoples lives and families heritage. Because of agreements signed with the 32 federal entities, it provides monetary resources through a trust. It operates through a group of health units providing health services, which are accredited to offer interventions covered by the FPGC. The coverage of breast cancer by the FPGC started in 2004. At the end of the fiscal year 2015, the catalog of the FPGC ended up with 61 interventions that cover nine groups of high cost diseases. According to the information of the Comisión Nacional de Protección Social en Salud (CNPSS-National Commission for Social Protection in Health) [
2], from 2004 to 2015 the FPGC financed 1,082,805 served cases that represent $48,782.7 million pesos [
9]. It is important to highlight that more than 50
\(\%\) of the FPGCs resources is spent in breast cancer treatments, intensive neonatal care, colon and rectum cancer, and a large proportion for financing antiretroviral drugs for HIV/AIDS care. In order to consider the attention cost of a disease as a catastrophic expenditure, it requires that the Consejo de Salubridad General (CSG-General Board of Health Standards) issues a protocol; such protocol highlights the process of clinical care given by medical experts in terms of disease care, as well as the treatment duration and necessary medicines. Within the portfolio of the FPGC medical services, there is a subset of diseases for which there is a maximum period of attention or maximum age covered. This group of diseases, which has a maximum period of attention with resources of the FPGC, represents a challenge for the SPSS as to fulfill the maximum period of attention; there is not a mechanism to ensure access to health care with resources from the SPSS for this specific population. One of the diseases that is in this situation is breast cancer: monitoring must be performed every 4–6 months for the first 5 years, as indicated by the care protocol issued by the CSG. On the other hand, the SPSS generates a tariff and sets the payment rate, which includes the cost for each care stage, the tariffs of each intervention in the catalog of the FPGC are revealed to service providers [
2]. There is a debate in terms of the optimum monitoring period, for example, the monitoring recommended by the Instituto Nacional de Cancerología (National Institute of Cancerology) is 20 years, the main objective is to detect local, regional or systemic relapse and the presence of a second primary cancer. Thus, such monitoring should consider mammography and thorax teleray, as well as a biannual bone densitometry in postmenopausal women or those treated with aromatase inhibitors [
6]. Recent studies show that the overall survival of the 202 women monitored in the first 3 years was 82
\(\%\) and the disease-free survival 63
\(\%\). Moreover, a second work with longer monitoring data showed an overall survival of 10 years of 60
\(\%\) and a disease-free survival of 22
\(\%\) [
10]. In the research performed on similar women with breast cancer, that had clinical monitoring for more than 10 years, the survival rate was 69.0
\(\%\) in those with infiltrating ductal carcinoma and 84.0
\(\%\) of those affected with the classic lobular disease type. The latter proves that life expectancy is larger for those having classic lobular carcinoma receiving more clinical monitoring [
11]. The international evidence shows that the recommended monitoring period varies between 5 and 25 years, depending the stage when breast cancer was detected, there are still differences in terms of monitoring resulting in an increase of patients survival. However, it is clear that the more monitoring there is for patients, the greater likelihood of timely detection of the disease recurrence. Given that the FPGC covers a clinical protocol for breast cancer monitoring in a defined interval of time (5 years), and due to the positive response to the treatment, there is a segment of women with higher survival rate as specified in the care protocols, which represents a gap in financing to ensure the continuity of follow-up and treatment for the covered population. Table
1 shows the general protocol for breast cancer treatment per state, diagnosis, treatment and follow-up.
Table 1
Protocol to treatment breast cancer.
Source: Ministry of Health
Clinical examination | Surgery: conservative, mastectomy | Medical consultation and clinical examination |
Self-exploration | Chemotherapy | Mammography |
Image studies | Radiotherapy: brachytherapy, external radiotherapy | Gynecological follow-up in case of treatment with tamoxifen |
Biopsy | Biological therapies | Bone densitometry in case of treatment with aromatase inhibitors |
Immunohistochemistry | Endocrine therapy | |
Tumor pathology | | |
Others | | |
The main objective of this research is to determine the financial impact and the financial risk quantification that would represent an increase on the follow-up for women with breast cancer that exceed monitoring time covered through the FPGC. It seeks to quantify the financial impact in short and medium terms, and financial sustainability of the FPGC, in order to monitor women with breast cancer that have persistence after covering the 5 year monitoring established in the protocol issued by CSG. The following section presents the sources of information and methods used for the analysis. Subsequently, the evolution of breast cancer cases and those covered by the FPGC are presented, the demographic structure of the population served is analyzed and the epidemiological profile is determined using a micro-simulation model to follow-up on a cohort of women. The probable cost scenarios are assessed in medium term, using the Monte Carlo simulation model and the financial impact is estimated through the Value-at-Risk (VaR) of the maximum expected expenditure of the monitoring expansion. In the last section, we presented the conclusions; financing alternatives are proposed to cope with the expected additional cost as a result of the estimated scenarios.
Methods
We estimated the financial impact derivative from the extension of the monitoring period for breast cancer in women who require it at the end of the 5 year period covered by the protocol of current care, and which is financed by the FPGC. The estimate of sensitive population who are meant to receive attention, with the monitoring expansion, was carried out through a micro-simulation model following-up a cohort of women looked after by the SPSS for the period 2013–2026. The expected number of breast cancer cases was projected per year, taking into account the expected annual incidence rates and demographic change.
Subsequently, based on the simulations of the susceptible population, the costs of monitoring care for this population was estimated using the micro costing methodology, as well as the maximum expected cost in attention of a medium-term horizon using the Monte Carlo simulation. This method has the vantage of following a cohort of patients. The estimations were based on scenarios and trends of morbidity and mortality of patients covered by the SPSS in health units of the Ministry of Health. This can be limited because there is a group of patients who attend social security and private institutions, and a group of patients who has not received timely detection of cancer, underestimating the national reality. However, the perspective of the study focuses on knowing the financial sustainability of the expansion of the monitoring period exclusively for the SPSS, based on the best available information. estimates will allow knowing a future outlook of the disease and the possible costs scenarios of increasing the monitoring period, which should be an input for public policy decision-making. Estimations were made based on the historical information of population covered, cases attended, morbidity and mortality of the SP and the Ministry of Health for the 2007 to 2013 period. Based on the number of women covered by the SPSS, and taking into account the observed incidence in the Ministry of Health, the expected total breast cancer cases for the following years were estimated (see Eq.
1). In addition, the number of cases that were diagnosed in previous years was identified and that in 2013 were monitored. With the latter, the total number of served cases (prevalence) was obtained. It is important to remember that the SPSS includes in its FPGC service portfolio the attention of this intervention since 2007, which is why there is a record of the number of cases that will require monitoring in short term. The susceptible population was determined by performing a distribution of the average population from the Consejo Nacional de Población (CONAPO-National Population Council) regarding the population affiliated to the SPSS per age group in 2013.
$$\begin{aligned} C_{i,e}&=\left[ \sum _{i,e}Io_{e}(Ps_{i,e}+\sum _{j,e}Cs_{j,e})\right]; \quad i=2013,\ldots,2026\nonumber \\ e&=0,\ldots,100; \quad j=2007,\ldots ,2013 \end{aligned}$$
(1)
where
\(C_{i,e}\) are the number of cases per year and age.
\(Io_e=\frac{\sum _{k,e}\frac{Cn_{k,e}}{Pr_{k,e}}}{n}; k=2007,\ldots ,2013;e=0,\ldots ,100\) are the average incidences observed per age; \(C_{n},\) are the new cases and \(P_{r}\), is the population at risk of contracting the disease. \(Ps_{i,e}=PC_{i,e}(PA_{l,e}); i=2013,\ldots ,2026\); \(k=0,\ldots,100\); \(l=2013,\) is the susceptible population per year and age; \(PC_{i,e},\) is the average population of CONAPO per year and age; \(PA_{l,e},\) is the distribution of the population affiliated to the SPSS per year and age in 2013, with \(e=0,\ldots,100\) and \(l=2013\). \(Cs_{j,e}\) is the population diagnosed in previous years per age, and that in 2013 were monitored during the treatment, with \(j=2007,\ldots , 2013.\)
To evaluate the survival, 14 monitoring cycles were estimated based on the historical fatality rate, considering a time horizon of 2013–2026. For each cycle, the number of new identified cases was taken into account, based on the estimated incidence, and the corresponding fatality rate was applied per age in order to obtain the expected deaths. Such estimations were performed in order to determine the survival after a year of treatment and 5 years of monitoring covered by the SPSS (see Eq.
2),
$$\begin{aligned} S_{i,e}=\sum _{i,e}\left[ C_{i,e}-C_{i,e}(L_e)\right] ; \quad i=2013,\ldots ,2026;\;\; e=0,\ldots ,100 \nonumber \\ \end{aligned}$$
(2)
where
\(S_{i,e}\) are surviving cases per year and age;
\(C_{i,e}\) is the number of cases per year and age.
\(L_e=\frac{\sum _{k,e}\frac{M_{k,e}}{D_{k,e}}}{n}\);\(k=2007,\ldots,2013;e=0,\ldots,100,\) is the average fatality rate observed per age; \(M_{k,e}\), are deaths per year and age; \(D_{k,e}\), are the diagnosed cases per year and age; and n is the number of years considered.
Taking into consideration an average duration of a 1-year treatment, the last monitoring financed by the SPSS for women diagnosed in 2013 and that would be entitled to, according to the care protocol, would be 2018. In order to establish public policy recommendations, the decision was to start the analysis in 2013 and to follow-up during 3 periods of federal government (18 years), it allows assessing the relevance of contemplating this situation in the budgets of the following administrations and link the financial impact directly with the budget. The estimated cost for expanding the monitoring period covered by the SPSS was obtained as the result of the number of cases requiring monitoring multiplied by the cost of monitoring (see Eq.
3).
$$\begin{aligned} C_i=Cs_i*Ks_i;\quad i=2013,\ldots ,2026 \end{aligned}$$
(3)
where
\(C_{i}\) the cost of expanding the period of monitoring per year;
\(CS_{i}\) cases requiring monitoring per year are cases that exceed the period of coverage currently provided by the SPSS;
\(Ks_i=M_i+AC_i\) is the cost of monitoring per year, which is updated every year with an inflation of 3%;
\(M_{i}\) is the cost of medicines (see Appendix
1);
\(AC_{i}\) is the cost of clinical analysis (see Appendix
2).
The costing methodology is based on a micro-costing approach, it is important to emphasize that in case of the FPGC the finance coverage of interventions is made per event, for which an integral cost of care considered, for more details about the costing methodology see [
12]. For evaluating the financial impact generated by the additional cost of extending the monitoring period of the breast cancer treatment in women who exceed the period financed by the SPSS a maximum expected cost was estimated, as a modified version of VaR through the Monte Carlo method by performing 5000 simulations, the estimation of VaR was performed with a confidence level of 95
\(\%\) [
13‐
16].
$$\begin{aligned} \int _{V_c}^{+\infty }r(s)ds=\alpha \end{aligned}$$
(4)
where
r is the monitoring cost;
\(\alpha\) is the significance level;
\(V_{c}\) is the cut-off point based on the established confidence level
\((1-\alpha ).\)
It is important to mention that in this case for implementing the VaR, the objective is to determine the maximum expected cost of monitoring patients with breast cancer, so the integration interval is inverted with respect to a traditional VaR estimation. In this case we seek to estimate the maximum expected cost, so we take the right tail of the distribution of possible monitoring cost values. The cut-off value is the value for which there is a probability that the monitoring cost ends on top of this, which corresponds to finding the maximum cost ensuring that only 5 out of 100 iterations may end in this value (
\(\alpha =0.05\)) (see Eq.
5).
$$\begin{aligned} P\left[ c(W)\ge V_c\right] =(1-\alpha ) \end{aligned}$$
(5)
The considered risk factors for the Monte Carlo simulation and their probability distributions were as follows (Table
2).
Table 2
Risk factors for the Monte Carlo simulation.
Source: The Authors
Incidence | lnN(\(\mu\),\(\sigma ^{2}\)) |
Fatality | lnN(\(\mu\),\(\sigma ^{2}\)) |
Costs | lnN(\(\mu\),\(\sigma ^{2}\)) |
The variable of interest for estimating the VaR is the cost per increase in the monitoring period covered by the SPSS; for this, the evolution of such cost was modeled through a stochastic lognormal process (see Eq.
6).
$$\begin{aligned} C_i=C_{o}e^{\left( \mu -\frac{\sigma ^2}{2}\right) \Delta _i+\sigma \sqrt{\Delta _i\xi }} \end{aligned}$$
(6)
where
\(\xi \sim N(0,1); \Delta _i=i-i_0.\)
Three scenarios were estimated (base, pessimistic and optimistic) for generating the VaR. For the base scenario, the parameters taken into consideration, were incidence, mortality and costs observed for the pessimistic and optimistic scenarios expected values of such parameters were generated using a normal distribution standard. The pessimistic scenario considered a range of expected increase of the observed incidence of up to 10
\(\%\), also a cost variation was simulated in the same proportion. This variation of up to 10
\(\%\) in incidences and costs was considered taking as reference the historical behavior of such parameters [
2]. The optimistic scenario considered a decrease in incidence and costs, allowing to evaluate a floor for the expected total cost taking into consideration that the expected incidence in the coming years decreases, as a result of the breast cancer prevention campaigns. Even when it is an unlikely scenario, it is important to have a range of maximum cost expected to be able to make decisions regarding the consideration of future budget. In terms of costs, there is the possibility of maintaining a policy of promoting generic drugs, as some of the molecules used in the breast cancer treatment will lose their patent in coming years, so it would be feasible to reduce the monitoring cost. In addition, there is a policy of containment and price reduction for medicines with patent in force or single source, through the negotiation of public procurement prices and consolidated purchases, which will make possible that in short term treatment costs will not increase. Regarding the sources of information, registered breast cancer cases (incidence) in the Ministry of Health were used, which were financed by the FPGCs portfolio of services and estimated costs for monitoring treated patients. At the same time, the specific cause mortality was used for population treated in the Ministry of Health, and CONAPO projections of average population for the period 2013–2050 were utilized in order to use the demographic structure of population covered by the SPSS in a long term horizon. The estimations presented consider current information regarding the care protocol and the current FPGC coverage. The objective is to evaluate if increasing monitoring is financially viable, in case it allows to detect relapses, their attention and treatment would be financed as a new case. The financial impact of possible relapse requires additional estimates of the sustainability of the FPGC, taking into account the evolution of all diseases covered in this fund.
Conclusions
Thanks to the implementation of the FPGC, the SPSS has accomplished its objective of reducing the catastrophic and impoverishing expenditures, yet there still are future opportunity areas. This policy should be accompanied at all times by the homogenization of medical services quality, provided by highly qualified staff, with standardized care protocols and clinical practice guidelines for each intervention that supports the care provided. Financing interventions included in the FPGC represents a big challenge because the necessary resources depend on demographic, epidemiological and financial factors. Hence, the importance of conducting an in-depth analysis to manage the potential risks for the SPSS of including interventions or modifications to existing protocols. An important segment of the resources of the FPGC is destined for breast cancer treatment, because it was presented as the first cause of death for women between 40 and 59 years old. There is a debate about the need of extending the monitoring period as a measure to increase the probability of survival and life quality of patients, prevent local, regional or systemic relapse and the presence of a second primary tumor. Due to the fact that including breast cancer in the FPGC was in 2007, from 2012 cases of patients who exceed the monitoring financed period are happening and will be left without coverage, that is the reason why it is essential to evaluate the financial impact for the SPSS to extend that period. Currently, the SPSS does not have a mechanism that guarantees continuity and access to medical care for population that exceeds the maximum period of financed care with resources from the SPSS. The results obtained in this work indicate that the population of women diagnosed with breast cancer presents a survival rate after 5 years of monitoring to approximately 30\(\%\) of the diagnosed cases. However, the incidence rate is not proportional to the fatality rate, which can be produced by the little monitoring given to patients. It is important to emphasize that the FPGC finances the interventions per event, so that a patient who was treated for breast cancer once her treatment was completed and the monitoring period contemplated in the protocol, lacks funding to continue with the monitor in later years. The estimation of three scenarios of maximum expected cost (base, pessimistic and optimistic) through a micro-simulation and the Monte Carlo method, allowed to determine the necessary financial resources to provide monitoring from 10 to 23 years to women diagnosed with breast cancer at a confidence level of 95\(\%\), which rises up to $3607.40 million pesos for every period in the base scenario ($4151.79 million pesos in the pessimistic scenario and $3414.85 million pesos in the optimistic scenario). Such expenditure would be amortized in the following 18 years which would represent approximately an annual increase of 9.1\(\%\) of the resources destined to the disease care and would use the 3.0\(\%\) of the availability of resources of the FPGC taking into consideration the base scenario estimations (2.8\(\%\) in the pessimistic scenario and 3.4\(\%\) in the optimistic scenario). According to estimates made of the additional cost for extending the monitoring period of breast cancer cases would be financially viable taking into consideration the available resources of the FPGC, considering that there are no significant changes in the epidemiology and costs of the rest of the interventions covered by the FPGC.