Out-of-pocket expenditure and financial protection in the Chilean health care system—A systematic review

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Out-of-pocket expenditure and financial protection in the Chilean health care system—A systematic review Kira Johanna Koch a,∗ , Camilo Cid Pedraza b , Andreas Schmid a a b

Universität Bayreuth, Universitätsstr. 30, Bayreuth, 95447, Germany Pontificia Universidad Católica de Chile, Diagonal Paraguay 362, 2nd Floor, 8330077 Santiago de Chile, Chile

a r t i c l e

i n f o

Article history: Received 7 December 2016 Received in revised form 19 February 2017 Accepted 21 February 2017 Keywords: Out-of-pocket expenditure Financial protection Catastrophic health expenditure Impoverishment Chile AUGE reform

a b s t r a c t Background: Protection against financial risk due to medical spending is an explicit health guarantee within Chile’s AUGE health reform. This paper seeks to analyze the degree to which out-of-pocket expenditure still expose Chilean households to financial catastrophe and impoverishment, and to explore inequalities in financial protection. Methods: A systematic literature review was conducted to identify empirical studies analyzing financial protection in Chile. The search included databases as well as grey literature, i.e. governmental and institutional webpages. The indicators are based on the conceptual framework of financial protection, as portrayed in the World Health Report 2013. Results: We identify n = 16 studies that fulfill the inclusion criteria. Empirical studies indicate that 4% of Chilean households faced catastrophic health expenditure defined as out-ofpocket expenditure exceeding 30% of household’s capacity to pay, while less than 1% were pushed into poverty in 2012. In contrast to prior studies, recent data report that even publicly insured who should be fully protected from co-payments were affected by catastrophic health expenditure. Also in the private insurance system financial catastrophe is a common risk. Conclusion: Despite health reform efforts, financial protection is insufficient and varies to the disadvantage of the poor and vulnerable groups. More research is required to understand why current mechanisms are not as effective as expected and to enable according reforms of the insurance system. © 2017 Elsevier B.V. All rights reserved.

1. Introduction More than a decade ago, the Plan for Universal Access with Explicit Guarantees (AUGE: Accesso Universal a Garantías Explicitas en Salud) was introduced in Chile, providing the population with guaranteed access to health services of high quality within a reasonable time period while being protected against financial risk for currently 80 health problems. However, the case of Ricarte Soto, a

∗ Corresponding author. E-mail address: [email protected] (K.J. Koch).

journalist who deceased from lung cancer in 2013, has alerted policy makers once again that – despite considerable efforts in the last decade to improve protection against financial risk – severe problems prevail. New legislation intends to reduce high cost drug spending made by households, but the overall success of the past health reforms remains unclear. Our paper addresses this issue. Besides Chile, many other countries strive for universal health coverage. The World Health Report 2010 defines universal health coverage as “ensuring that all people can use the promotive, preventive, curative, rehabilitative and palliative health services they need, of sufficient quality to be effective, while also ensuring that the use of these

http://dx.doi.org/10.1016/j.healthpol.2017.02.013 0168-8510/© 2017 Elsevier B.V. All rights reserved.

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services does not expose the user to financial hardship” [1]. The protection against financial risk due to out-of-pocket spending (OOPS), defined as all payments that households pay directly while receiving health services, raises more and more importance, especially if these direct health payments are a major source of health financing. Such highly regressive payments cause each year financial hardship in countries at all income levels, i.e. financial catastrophe for about 150 million people worldwide while pushing 100 million people into poverty [2]. Yet, as in many other OECD countries [3–6], impoverishing and catastrophic health expenditure due to OOPS remain a core challenge. Chile is an excellent example for this global challenge and interesting to look at as it has established itself a leading position in South America over the past years. Gradual improvement in Chile’s social and economic situation resulted in a positive impact on the population’s health status [7,8]. However, the Chilean population of around 18 million inhabitants live in a society with falling birth rates and rising life expectancy, leading to an aging population, which is accompanied by a shift in the epidemiological profile to non-communicable diseases [9,10]. Social inequality expressed by a high GINI coefficient remains a key issue [11]. The AUGE reform, implemented in 2004 and gradually expanded over the years, has been promoted as the milestone to reduce inequalities by providing four explicit health guarantees; one of those being financial protection, but a clear assessment is difficult as to scare scientific evidence and very fragmented data. The aim of this paper is to provide a comprehensive overview of current scientific evidence on financial protection in Chile. It is based on a systematic review of the literature, allowing a better understanding of the impact of the latest health reform efforts and identifying specific needs for further research. For that matter, we investigate the degree to which OOPS expose households to financial hardship in the Chilean health care system and the severity of inequalities in financial protection across population subgroups. It is a first paper in English available, which enables non-Hispanic countries to compare with and draw lessons learnt from the Chilean experience. This paper starts with a brief overview of the Chilean health care system. The subsequent method section explains the conceptual framework and the search strategy for the systematic review. The main body of the paper contains an analysis of available studies on catastrophic health expenditure and impoverishment. The discussion takes a critical appraisal of the findings in the light of current reform strategies. The paper ends with a conclusion and policy implications. 2. Background In 2014, Chile spent 7.8% of GDP on health. Total health expenditure amounted to approximately $US 20.1 billion (exchange rate $US 1 = $CLP 570.35, 2014), divided into 49.5% of general governmental health expenditure and 50.5% of private spending [12]. Chileans can mainly choose between two different health insurance systems: the national health fund (FONASA: Fondo Nacional de Salud) and the for-profit private sector (ISAPREs:

Instituciones de Salud Previsional). The majority of the Chilean population (75.2%) is insured within FONASA. Another 18.5% have an individual contract with one of the ISAPREs, and the rest (6.3%) have either an insurance plan offered by the armed forces (FF.AA) or no insurance at all [13]. Further distinction is made between open and closed ISAPREs, while the latter is only accessible for people who work in a given company or in a sector of economy (predominately in state-dominated mining) and hence covers a negligible number of individuals only. For further analysis, this paper focuses solely on FONASA and open ISAPREs beneficiaries due to high enrolment numbers in these schemes. FONASA is financed through general taxes and an obligatory 7% contribution of every worker’s wage as well as out-of-pocket payments. Non-working family members as well as indigents are covered free of charge. The insureds under ISAPRE have also to pay a legally mandated 7% income based contribution (or an equivalent premium for non-working enrolees) which as of now still accounts to private health spending according to current accounting regulations [14], along with additional risk adjusted premiums. In total, insured pay on average 10% of monthly gross income on ISAPRE health insurance in addition to further OOPS [15]. Household’s per capita income affirms to be the predominant factor in either an affiliation within FONASA or ISAPREs (Annex 1 in the online version at DOI: http://dx.doi.org/10.1016/j.healthpol.2017.02.013) [16]. Furthermore, due to medical underwriting in the private sector (including risk adjusted and annually updated premiums and the option to exclude certain illnesses or services) the majority of elderly people are insured within FONASA (Annex 2 in the online version at DOI: http://dx.doi.org/10.1016/j.healthpol.2017.02.013) [17]. No restrictions hinder enrolees to switch back and forth between insurance systems picking the more favorable option depending on their current health and income status. This opt-out option enables high-income groups to leave the public system, which limits the potential of solidarity in the system and as such raises equity concerns. Since 2014, the presidential advisory commission has taken up this issue and has been debating on new models of the private health insurance system in Chile [18]. Both the public and the private sector take advantage of the financing and the steering effects of OOPS. The most popular form is a relative participation, i.e. the insured pays a proportion of total costs for instance via deductibles (franchise), co-payments or co-insurance. FONASA health services are delivered through the public (MAI: Modalidad de Atención Institucional) and private (MLE: Modalidad Libre Elección) sector. Depending on the choice of provider, OOPS vary for FONASA members. When choosing public providers, the degree of cost sharing depends on FONASA’s group classification, which is primarily based on household’s monthly gross income. The categories are A, B, C and D, with A representing indigents. Primary health care is provided in local surgeries and are free of charge. Specialist treatment and hospital visits require a co-insurance between 0% and 20%. FONASA A and B as well as all elderly over 60 years independent of their socioeconomic status are fully covered [18]. Only

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Table 1 Co-insurance and co-payment shares for FONASA and ISAPREs beneficiaries.

Proportion of population (2014) Gross monthly income $USD (2015) Group classification

FONASA A

FONASA B

FONASA C

FONASA D

ISAPREsa

18.4%

26.5%

12.9%

17.4%

18.5%

Indigents

≤394

394–570

≥570

Not relevant

Family allowance beneficiaries (Law 18.020)

Basic solidarity pensions beneficiaries

If the contributor has more than 3 dependents beneficiaries pass to Group B

If the contributor has more than 3 dependents beneficiaries pass to Group C

No groups, premiums based on age, gender and medical history

Co-payment MAI: institutional providers (public health sector) Primary health care 0% 0% 0% 0% Inpatient and specialist 0% 0% 10% 20% consultations 0% 30% 50% 80% Oral health Co-payment MLE: private providers (free choice) Outpatient care Not allowed 40–60% Inpatient care Not allowed Large range of OOPS, FONASA covers 50% (Level 1)b AUGE/GES 0% 0% 10% maximum annual 20% maximum annual deductiblec deductiblec

Deductibles, co-payments, ceilings and exclusion depending on plan of the insured

20% maximum annual deductiblec

Source: Based on [13,20,65,66]. Note: exchange rate $US 1 = $CLP 654.24, annual 2015 [39]. a Open and closed ISAPREs. b Shares may change in the specific case of the diagnostic program (in Spanish: programa de pago asociado a diagnóstico). c The sum of OOPS over any 12-month period cannot exceed two monthly wages, if the household has an AUGE problem, and three monthly wages if the household has two or more AUGE problems.

enrolees in FONASA categories B, C, and D are eligible for subsidies when choosing providers in the private MLE sector, enrolees in category A are supposed to stay within the public system. As a rule, FONASA covers 50% of total costs incurred by private providers based on level 1, which is the lowest and rarely charged tariff out of three price levels. FONASA members tend to prefer the private MLE sector for medical examinations or diagnostic testing, as they wish to avoid long waiting lists within the public MAI sector and hope for better quality of health care [17,19]. In ISAPREs, the amount that finally has to be paid out of pocket depends on the chosen plan. There are variable deductibles, co-payments, ceilings and exclusions depending on plans [20]. Generally, ISAPREs contract with providers in the ambulatory and inpatient sector, establishing a preferred provider network. In some cases, health providers belong to the same holding as the private health insurance company. According to ISAPREs companies, 97.2% of commercialized plans in 2014 cover equal or higher than 70% of expenditure in the ambulatory sector, while in the inpatient sector 95% of commercialized plans held coverage equal or higher than 90%. However, in reality there are health services that are not covered by or are not specified in said plans. The effective coverage rate is thus lower as stated above, currently estimated to be around 65% only [21]. In 2004, the Plan for Universal Access with Explicit Guarantees (AUGE), also known as GES, was introduced. It was the first attempt to overcome the deeply separated system by introducing a plan which is accessible for both FONASA and ISAPREs beneficiaries and to cover gaps of coverage (e.g. regarding certain pharmaceuticals, medical treatment, waiting lists) that were mostly prevalent in the public system. There are four explicit guarantees: (1) access to health services, (2) quality of care through accreditation of health

providers and facilities, (3) opportunity understood as a maximum waiting time and (4) financial protection against OOPS. In the public sector, AUGE is financed through public funding (predominately via general taxes and FONASA’s 7% contribution rate), and is obligatory for its enrolees. By contrast, in the private sector AUGE is financed through a per capita premium (freely defined by ISAPREs) which is part of the total agreed upon premium. It is the enrolees’ choice whether to use conditions of his or her ISAPRE plan or to enter the AUGE program. Since 2013, AUGE lists 80 health problems for which coverage is guaranteed by law. Patients are protected to pay not more than 20% of the reference price defined by the health authority. The new legislation attempt is the Ricarte Soto Law, which is financed through general tax. Approved in January 2015, the law strives for financial protection by free supply of high cost treatments, with costs exceeding 40% of households’ average capacity to pay, accessible to both FONASA and ISAPREs enrolees [22]. A list of selected treatments will be updated, based on three criteria: high costs, effectiveness and seldom usage due to low prevalence, and thus applies to those rare diseases that per definition do not fulfill the criteria of the AUGE plan. From 2017 onwards, the list will contain 14 high cost drug treatments [23]. Table 1 summarizes the current cost-sharing mechanisms in both the public and private system. 3. Methods 3.1. Concept of financial protection We apply the conceptual framework of financial protection released by the World Health Organization (WHO) in the World Health Report 2013. The concept assesses if existing cost-sharing mechanisms in a country, as outlined

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Records identified through PubMed n = 61

Records identified through Science Direct n = 206

Records identified through Google Scholar n = 100*

Records after duplication removed n = 342 Records added through grey literature n=3

Title and abstract screening n = 342

Excluded based on title and abstract n = 278

Full text review n = 67

Excluded based on full text n = 51

Studies included for review n = 16 (4 in English, 12 in Spanish) * Google Scholar rendered a list of 8.940 results, with the first 100 results considered due to a considerable decrease of relevant papers thereafter Fig. 1. Flow diagram for systematic literature review.

in Table 1 for Chile, are adequate or if people are at risk to financial harm. Financial protection is achieved when households’ resources ensure the utilization of health services without inordinate sacrifice of present or future necessities of well-being such as poor nutrition or inadequate education. Indicators to measure financial protection are well established, underpinned by multi-country survey data, and can be categorized into indirect and direct indicators (Annex 3 in the online version at DOI: http://dx.doi.org/10.1016/j.healthpol.2017.02.013). Indirect indicators are aggregated data on a national level that help to understand the whole picture of current country’s health care performance. Direct indicators refer to disaggregated OOPS data on a household level. Of the latter, two concepts – catastrophic health expenditure and impoverishment – have gained international acceptance [24,25]. Catastrophic health expenditure (CATA) occur when a household’s OOPS exceed a certain percentage of household’s available resources [26]. The methods of calculating household’s available resources and how much of these resources have to be spent on health to face financial catastrophe varies greatly. We follow Xu [27] who defines the household’s capacity to pay as a household’s non-subsistence spending, i.e. household’s consumption expenditure (EXP) minus subsistence spending (SE). Subsistence spending is the minimum requirement of a household in order to guarantee the most basic standard of living. The average food expenditure of households, whose food share is in the 45th to 55th percentile, is used to estimate subsistence spending. This value is adjusted for household size and can also serve as a relative poverty line [28]. Alternatively, total expenditure is often used as a denominator [3]. The dynamic indicator, mean positive overshoot, aims at measuring the average amount by which households affected by catastrophic payments spent more than the threshold point used to define financial catastrophe [29]. The decisive advantage of the overall concept is that households from all income groups can be affected

[24]. However, the concept does not capture the degree of financial hardship caused, and certainly poorer households are more likely to fall into poverty [25]. Impoverishment (IMPOOR) occurs when a household whose level of expenditure was above the poverty line falls below the poverty line due to OOPS [27]. A poverty line, either absolute or relative, represents a threshold to the level where basic needs of life cannot be met. In this case, we use the aforementioned subsistence spending as a relative poverty line. The incidence measure however does not capture households who were already below the poverty line and were pushed even further into poverty due to OOPS. In these cases, dynamic indicators such as poverty gap are required which measures the extent to which a households’ pre-existing level of poverty deteriorates further and thus how far, on average, the poor are from the established poverty line due to OOPS [24,29]. Furthermore, a limitation of the concept is the assumption that the function of wellbeing consists of health consumption and others. Coping strategies, such as borrowing and selling assets, may also indicate a lack of financial protection. Nonetheless, combined the two consumption related measures are still described as the best indicators of financial hardship [25]. It is worth noting that financial protection should not only be measured as a population average, but also within different subpopulation groups in order to assess inequitable distribution of financial protection [30,31]. Health inequity is defined as the differences between subgroups of a population that may be linked to forms of disadvantage such as poverty, discrimination and lack of access to health care services. As it is a normative concept, health inequality defined as observable health differences serves as an indirect mean [32]. This multidimensional concept requires the consideration of several dimensions, such as household’s income, place of residence, gender, age, education [30,33]. Generally, both absolute (magnitude) and relative (proportional) measures of inequality as well as disaggregated data should be presented. National averages

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Table 2 Selection of studies n = 16. Author (Year)

Household survey, sample used for estimations

Periods under review

Indicators analyzed Method

Agacino (2009) [67]

EPF, Metropolitan Region of Santiago

1997, 2007

OOPS

Arpón et al. (2015) [38]

EPF, Metropolitan Region of Santiago and regional urban zones ENSGS, national

2007, 2012

OOPS, CATA, IMPOOR

2005

OOPS, CATA, IMPOOR OOPS (focus on FONASA/ISAPREs)

˜ (2012) Bitran and Munoz [45] Castillo and Villalobos (2013) [41] Cid (2013) [68] Cid and Prieto (2012) [15] Correa-Browns (2012) [43] Cuadrado and Silva-Illanes (2015) [44] Freile (2015) [42]

ISP (2015) [37] Knaul et al. (2011) [47]

Larraín (2014) [69]

Cuadrado and García (2015) [48] Pérez (2009) [46] Perticara (2008) [40] Rompentin (2013) [49]

EPF, Metropolitan Region of Santiago and regional urban zones EPF, Metropolitan Region of Santiago EPF, Metropolitan Region of Santiago EPF, CASEN EPF, Metropolitan Region of Santiago and regional urban zones EPF, Metropolitan Region of Santiago and regional urban zones EPF, Metropolitan Region of Santiago ENSGS, national

2007

Type of paper

No information

Language

Government document (unpublished) Based on Xu (2005) Government document

Spanish

Based on Xu (2005) Hand book

English

Based on Xu (2005) Journal article

Spanish

Based on Xu (2005) Power point presentation Based on Xu (2005) Journal article

Spanish Spanish

Spanish

1997, 2007, 2012

OOPS

1997, 2007

OOPS, CATA

2007 (EPF), 2009 (CASEN) 2012

OOPS (focus on chronically ill) OOPS, CATA (focus on value added tax on imaging tests) OOPS (focus on elderly)

Based on Xu (2005) Journal article

English

Based on Xu (2005) Journal article

English

Based on Xu (2005) Academic thesis

Spanish

1997, 2007, 2012

OOPS, CATA

Based on Xu (2005) Journal article

Spanish

2005

Journal article CATA rel. to a) households’ CTP net of food spend. (30%), b) int. pov. line of $US 1 PPP OOPS, CATA Three different Academic thesis ways of measuring CTP CATA (focus on Based on Xu (2005) Government non-communicable document diseases) OOPS, CATA, Based on Xu (2005) Academic thesis IMPOOR OOPS, IMPOOR Based on Xu (2005) Journal article

English

OOPS, CATA, IMPOOR

Spanish

2012

EPF, Metropolitan Region of Santiago and regional urban zones EPF, Metropolitan Region of Santiago and regional urban zones ENSGS, national

2007, 2012

EPF, Metropolitan Region of Santiago EPF, Metropolitan Region of Santiago and regional urban zones

1997

2012

2005

2007

OOPS, CATA

Based on Xu (2005) Academic thesis

Spanish

Spanish

Spanish Spanish

of population groups help to capture changes over time [30]. In this way governmental bodies obtain the appropriate information to derive policy implications and to protect vulnerable groups [24].

of Health, FONASA and Superintendence of Health. Additionally, data was collected from WHO Global Health Expenditure Database (GHED). Fig. 1 outlines the flow diagram for the systematic literature review.

3.2. Search strategy

4. Results

The literature was screened via PubMed, Science Direct and Google Scholar to identify all available studies that deal with protection against financial risk due to OOPS in Chile. See Annex 4 in the online version at DOI: http://dx.doi.org/10.1016/j.healthpol.2017.02.013 for full information on the search string. Titles through the search process were reviewed, and if found to be relevant the abstract or executive summary was read. In Google Scholar, the first 100 results were considered due to a considerable decrease of relevant papers thereafter. Grey literature was also included, i.e. screening of governmental and institutional websites, such as those from the Ministry

The literature review renders a list of n = 16 studies, with three-quarters written in Spanish (Table 2). Primary data sources of these studies are household surveys. Mostly cited is Chile’s EPF budget survey (Encuesta de Presupuestos Familiares) conducted now every five years and covering the Metropolitan Region of Santiago and regional urban zones. EPF 2012, EPF 2007 and EPF 1997 are the most recent surveys while the latter is limited to the Metropolitan Region of Santiago. The ENSGS survey (Estudio Nacional sobre Satisfacción y Gasto en Salud) is a nation-wide health expenditure survey available from 2005. A nation-wide survey on socioeconomic determinants (CASEN: Encuesta

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de Caracterización Socioeconómica Nacional) conducted every two to three years covers also factors related to inequity. 4.1. General observations on the basis of indirect indicators According to WHO GHED [12] based on national health accounts data, OOPS amount to approximately $US 6.3 billion (exchange rate $US 1 = $CLP 570.35, 2014), respectively 2.5% of GDP, or 31.5% of total health expenditure in 2014 (see Palacios and Leal for background on adjustment and projection methods [34]). By contrast, FONASA estimates OOPS to be 38.9% of total health expenditure in 2014 [13]. This approach is confronted with overestimation concerns driven by the data used [35]. Aside from this discrepancy, OOPS in absolute terms have increased from 1997 while in relative terms OOPS as a share of total health expenditure have declined, keeping in mind that this is partly due to methodological adjustments [34]. Moreover, WHO GHED [12] reports general government expenditure on health to be $US 9,9 billion (exchange rate $US 1 = $CLP 570.35, 2014), respectively 3.9% of GDP, or 49.5% of total health expenditure in 2014. Over the last decade Chile’s public funding was fairly stable, while the focus shifted in favor of the subcomponent of public health spending [36]. Direct indicators further help to understand the distribution pattern within a country. An initial analysis of OOPS is imperative before assessing financial catastrophe and impoverishment. Each of these three aspects is also analyzed addressing inequality concerns. 4.2. Households’ burden of out-of-pocket health spending Cid and Prieto [15] and ISP [37] analyze OOPS based on EPF data only for the Metropolitan Region of Santiago and outline that household’s average OOPS per month increase from 1997 to 2007 but slightly decline in 2012. Arpón et al. [38] base their study on the full EPF 2007 and 2012 sample covering the Metropolitan Region of Santiago and regional urban zones. Rural areas are not covered. Regional urban zones reach the same level of OOPS as the metropolitan area for the first time in 2012, which lead to an overall increase of OOPS between 2007 and 2012 amounting to $US 104 (exchange rate $US 1 = $CLP 486.00, April 2012 [39]). In relative terms, households spend on average between 4% and 11% directly on health, with higher shares calculated on a ENSGS basis (Table 3). ENSGS, unlike EPF, holds a national coverage but specific surveys with a focus only on health tend to overestimate health expenditure [35]. Main cause of OOPS are drug purchases. For the first time in 2012, outpatient medical and dental services surpass hospital services [38]. Yet, the inpatient care related burden on individual households can be significant due to high amounts of OOPS per case [40]. 4.3. Inequality pattern in out-of-pocket health spending across subpopulation groups The higher the socioeconomic status of the household the higher is the total amount and the relative proportion

spent directly on health; also confirmed by a high GINI coefficient for household’s OOPS [15]. In 2012, households in Q5 (richest) spend 26 times more directly on health than those in Q1 (poorest) in the Metropolitan Region of Santiago [37]. In relative terms, a fairly progressive distribution across quintiles is reported, i.e. higher OOPS shares in higher quintiles. Nevertheless, Cid and Prieto [15] reveal and ISP [37] confirms that when only households are considered who actually spend on health, poor households spend most OOPS on drugs, revealing an undesirable regressive pattern for the main component of OOPS. By contrast, a progressive pattern applies for medical services and diagnostic tests. Another good indicator for assessing socioeconomic differences is the insurance type of the head of the household, since income has proven to be a predominately factor for choosing either system. ISAPREs households are overrepresented in higher quintiles, spending on average $US 236 per month directly on health in 2012. Vice versa, FONASA households are overrepresented in lower quintiles, with considerably lower spending, ranging from $US 99 (FONASA D) to $US 28 (FONASA A), and hence emphasizing a steep gradient across and within the two systems (exchange rate $US 1 = $CLP 486.00, April 2012 [39]). In relative terms, FONASA D has the highest proportion of OOPS on household’s average monthly expenditure, followed by ISAPREs. The high OOPS shares in FONASA C and particularly in FONASA B stand out in contrast to a lower share in FONASA A [38]. Likewise, poor ISAPREs households spend considerably more directly on health than do richer ISAPREs households or even comparable FONASA households [41]. Looking at vulnerable groups, study results clearly report rising amounts of OOPS for elderly people over the period 1997–2012. The effect rises even more if the household head comes into a higher age group [15,38,40]. OOPS of said group is nearly the double of the rest of the population [42]. Furthermore, Correa-Burrows [43] supports the hypothesis that non-communicable diseases increase OOPS. 4.4. Households’ burden of catastrophic health expenditure In the literature, incidence rates on financial catastrophe vary greatly depending on survey type and analytical method. Latest data from 2012 indicate rates around 4% [15,37,38,44]. Unfortunately, no analysis on the mean positive overshoot exists which is a significant gap in the Chilean monitoring system. The majority of studies choose household’s capacity to pay as a denominator to determine household’s available resources, following Xu’s method (Table 4). Thresholds of 30% and 40% are commonly used. We outline data for a 30% threshold in the text and provide figures for a 40% threshold (if any) in Table 4. Generally, the higher the threshold chosen the lower is the incidence of financial catastrophe but cases are more severe as OOPS claim an even higher share of household’s monthly expenditure. According to Arpón et al. [38], 121,439 households suffer catastrophic health expenditure, which make up 4.0% of all households in 2012. Analysis is limited to the Metropoli-

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Table 3 Out-of-pocket health spending [67,38,45,41,15,37,68,43,44,42,69,46].

Study

Household survey, sample Main results: OOPS as a share of household’s average monthly used for estimation expenditure

Agaciono (2009) [67] Arpón et al. (2015) [38]

EPF, Metropolitan Region of 2007: Ø OOPS share: 6.7%; progressive increase, with a peak in Q3 Santiago EPF, Metropolitan Region of 2007 2012 2012 Santiago and regional urban Q1 3.2% 3.9% FONASA A 3.5% zones Q2 4.1% 5.0% FONASA B 6.1% 5.2% 5.6% FONASA C 6.4% Q3 Classification of quintiles Q4 6.2% 7.0% FONASA D 7.1% 5.8% 7.0% FONASA, unknown 6.5% according to household’s Q5 Ø 5.3% 6.3% ISAPRE 6.7% income per capita Others: FF.AA. and other systems Most OOPS on drugs (29%), followed by outpatient medical (19%), dental services (15%) and hospital services (14%) High education and good employment increase OOPS, but group with no employment follows in third position Households increase OOPS up to a number of two people aged 65 years or older; number of elderly people living in a household and age group of the household head increase household’s OOPS burden in 2012 Bitrán and Muñoz ENSGS, national 2005: Ø OOPS share: 9.1%; progressive distribution across quintiles (2012) [45] Castillo and EPF, Metropolitan Region of 2007: Ø OOPS share around 5%; progressive increase, with a peak in Q4 Villalobos Santiago and regional urban Poor ISAPREs households spend more on health than do richer ISAPREs (2013) [41] zones households or even comparable FONASA households Cid and Prieto EPF, Metropolitan Region of 1997 2007 2012 Q1 2.0% 2.1% 2.4% (2012) [15]; ISP Santiago (2015) [37] Q2 3.2% 3.1% 3.9% 4.3% 4.2% 4.7% Q3 Classification of quintiles 5.1% 5.6% 6.5% according to household’s Q4 7.0% 7.1% 7.7% Q5 expenditure per capita Ø 4.3% 4.4% 5.0% Progressive distribution across health care groups but if only households were considered who actually spent directly on health, regressive distribution for drugs, while a progressive distribution applies for medical services and diagnostic tests Cid (2013) [68] EPF, Metropolitan Region of Ø OOPS shares: 5.5% (1997), 5,6% (2007), 6.3% (2012) Santiago Progressive distribution but the gap narrows in 2012: OOPS shares in Q1 and Q2 increase considerably, with a share in Q1 that more than doubled from 2007 (2.1%) to 2012 (5.0%) Correa-Burrows EPF 2007, CASEN 2009 2007: The number of non-communicable diseases increases OOPS. Age (2012) [43] does not turn out to be significant. Households in Q2,Q3 and Q4 have higher OOPS shares than those in Q5, while those in Q1 indicate a reduced magnitude of OOPS Cuadrado and EPF, Metropolitan Region of 2012: Ø OOPS share: 5.23%, progressive distribution across quintiles Silva-Illanes Santiago and regional urban (2015) [44] zones Freile (2015) [42] EPF, Metropolitan Region of 2012: OOPS for elderly (11.95%) is nearly double than for the rest of the Santiago and regional urban population (5.82%). Proportion on drugs: 40% elderly; 28%: rest of the population) is major source of spending zones Larrín (2014) EPF, Metropolitan Region of 2007: Ø OOPS shares based on three different ways of measuring CTP: [69] Santiago and regional urban 6.2%, 3.2% and 5.5%; fairly progressive distribution 2012: Ø OOPS shares based on three different ways of measuring CTP: zones 6.8%, 4.4% and 4.6%; fairly progressive distribution Pérez (2009) [46] ENSGS, national 2005: Ø OOPS share: 10.7%; progressive distribution across quintiles

tan Region of Santiago only. Due to the uptake of OOPS in regional urban zones, the actual number might even be higher. Over time, Cid and Prieto [15] and ISP [37] indicate incidence rates that decline from 3.8% (1997) to 3.6% (2007) but increase again to 4.3% (2012). Estimations based on ENSGS survey in 2005 even report rates higher than 10% [45–47].

Among households with catastrophic expenditure, most OOPS is spent on outpatient care [38]. Drugs, the principal component of OOPS, do not appear to be as significant, while the burden of hospital spending increases when comparing households with and without catastrophic health expenditure [48].

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Table 4 Catastrophic health expenditure [38,45,15,37,48,44,47,69,46,49].

Household survey, Main results: Incidence rates of catastrophic health expenditure sample used for estimation Arpón et al. (2015) EPF, Metropolitan 30% threshold 2012: 40% threshold 2012: Region of Santiago Number of CATA households Number of CATA households [38] (% of population) (% of population) Quintiles according Q1 19,714 (3.3%) Q1 12,189 to household’s 19,564 (3.3%) Q2 11,282 Q2 income per capita 26,506 (4.4%) Q3 15,352 Q3 28,322 (4.7%) Q4 13,483 Q4 27,334 (4.5%) Q5 10,188 Q5 121,439 (4.0%) Total 62,494 Total Study

FONASA A FONASA B FONASA C FONASA D FONASA, unknown ISAPREs Others Total

18,513 (3.3%) FONASA A 32,321 (4.9%) FONASA B 14,582 (4.6%) FONASA C 9,519 (3.4%) FONASA D 7,990 (4.9%) FONASA, unknown 21,248 (3.7%) ISAPREs 17,267 ( - ) Others 121,439 (4.0%) Total

10,924 17,574 7,799 5,019 6,075 7,797 7,307 62,494

(2.0%) (1.9%) (2.6%) (2.2%) (1.7%) (2.1%) (1.9%) (2.7%) (2.4%) (1.8%) (3.8%) (1.4%) ( - ) (2.1%)

FONASA incidence rate: 4.2% (drugs: 21%, hospital services: 21%, dental services: 19%, outpatient care: 30%, others: 9%) ISAPREs incidence rate: 3.7% (drugs: 19%, hospital services: 25%, dental services: 22%, outpatient care: 30%, others: 5%) 55% (60%) of total CATA households have at least one elderly person as a member if a 30% (40%) threshold is considered Econometric model: at least one elderly person living in a household (+1.7 percentage points), household head moving up another age group (+0.2 percentage points), number of people living in a household (-0.5 percentage point), poor household (-1.6 percentage point) 40% threshold 2005: 6.4%

Bitrán and Muñoz ENSGS, national (2012) [45] EPF, Metropolitan 30% threshold Cid and Prieto 1997 2007 2012 Q1 3.2% 2.5% 2.3% (2012) [15]; ISP Region of Santiago (2015) [37] Q2 2.8% 2.2% 4.1% Q3 3.8% 3.3% 3.8% Quintiles according Q4 4.0% 4.3% 5.2% to household’s Q5 expenditure per 5.1% 5.7% 5.9% Ø 3.8% 3.6% 4.3% capita 2012: CATA households spend 28.2% on drugs out of total OOPS, highest shares in Q3 (D5: 36.2%, D6: 39.2%) Presence of elderly people living in a household increases the likelihood of financial catastrophe Cuadrado and EPF, Metropolitan 30% threshold, 2012: 4.09%, i.e. 44,241 households with catastrophic expenditure García (2015) [48] Region and regional caused by non-communicable diseases which make up 36% of CATA households urban zones or 1.5% of all households. Principal components of out-of-pocket spending are hospital services and drugs EPF, Metropolitan 30% threshold 2012: 4.09% Cuadrado and Region and regional Silva-Illanes urban zones (2015) [44] Knaul et al. (2011) ENSGS, national 2005: 15.4% CATA 1: relative to household’s CTP net of food spending (30%) [47] 2005: 11.1% CATA 2: relative to an international poverty line of $US1 PPP Larrín (2014) [69] EPF, Metropolitan 30% threshold; Region and regional 2007: 13% (Xu method); 2007: 5% (CTP measure differs from Xu (2005) method) urban zones 2012: 12% (Xu method); 2012: 4% (CTP measure differs from Xu (2005) method) Pérez (2009) [46] ENSGS, national 40% threshold 2005: 10.5% Progressive distribution with highest incidence rates in Q5 for FONASA enrolees but a regressive distribution with highest rates in Q2 (since Q1 is barely represented) for ISAPREs enrolees Rompentin (2013) EPF, Metropolitan 30% threshold; 2007: Number of households facing CATA through expenditure on Region and regional drugs decline with ascending quintiles, highest share in D1 (7.6%) vs. D6-D10 [49] urban zones (0.5%) while the number of households increase for elderly people

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4.5. Inequality pattern in catastrophic health expenditure across subpopulation groups Higher income groups are more likely to be confronted by financial catastrophe. ISP [37] reports increasing incidence rates in all quintiles, expect of the lowest quintile, with highest rate in Q5. By contrast, Arpón et al. [38] find the peak in Q4, emphasizing that the richest households are not the most severely affected. This is an interesting observation and links to similar findings across insurance types. It seems that there has been a shift in the group of households’ exposure. Older data from ENSGS 2005 report that affected FONASA households belong mostly to Q3–Q5, with peak in Q5, while affected ISAPREs households are mostly attributable to Q2 (since they are barely represented in Q1) [46]. In later years, this general statement is questionable, at least for FONASA households. Arpón et al. [38] reveal with new EPF 2012 data that the majority, i.e. 68% of households with catastrophic health payments are in FONASA and 17% belong to ISAPREs. This makes up 4.2% of all households in FONASA and 3.7% of all households in ISAPREs. This time, contrary to prior findings, the highest incidence rate does not occur in FONASA D but in FONASA B. 4.9% of all households in FONASA B, i.e. around 32,000 households have catastrophic health expenditure, revealing increased inequality in the system. FONASA C follows second if the incidence rates within each insurance group are compared (see Table 4 for detailed information). Age has a large impact on the probability of a catastrophic event, with more than half of total households affected having at least one elderly person. Econometric models confirm that the probability of suffering a catastrophic event increases if at least one elderly person lives in the household. Said probability increases further if the household head moves up into a higher age group. The fact that this effect seems to have increased over the years is a political concern [15,38]. Similar situation appears for the chronically ill. Around 44.000 households suffer catastrophic health expenditure due to non-communicable diseases, which make up 36% of households confronted with financial catastrophe, or 1.5% of all households [48]. Main components are hospital services and drugs. In Chile the probability of being confronted by financial catastrophe due to drug purchases declines the wealthier the household is, and as such is consistent with the regressive distribution pattern of drug spending for households who actually spend directly on health [49]. Further research is needed to understand what OOPS items (high cost rare event or cumulated lower cost frequent event) cause financial catastrophe. 4.6. Households’ burden of impoverishment Discrepancy in incidence rates of impoverished households [27] is minor, and depends on survey type and analytical method. It remains unclear, however, how many already impoverished households are driven even further into poverty due to OOPS, since no analysis on the indirect indicator – depth of poverty – is available. Furthermore, a very careful interpretation is warranted, as the results

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very much depend on the chosen level of the poverty line. According to Arpón et al. [38], 12,955 households are pushed into poverty due to OOPS in 2012. This makes up 0.43% of total housholds. Incidence rates based on ENSGS data from 2005 are slightly above 1% [45,46], indicating – despite survey type differences – that the incidence rate of impoverishment has declined over the period 2005–2012 (Table 5). 4.7. Inequality pattern in impoverishment across subpopulation groups Contrary to results on financial catastrophe, lower income groups are more likely to be driven into poverty due to OOPS. This is logical, as near poor are more likely to fall below the poverty line. According to Arpón et al. [38], the majority, around 80% of impoverished households, belong to the first two quintiles. Same picture is observed when comparing insurance type systems. FONASA households account for nearly 90% of impoverished households. Among them, around half belong to FONASA A and nearly one-fifth to FONASA B. By contrast, no ISAPRE household is impoverished, going along with the fact that the income of an average ISAPREs household more than doubles that of an average FONASA household [18]. ENSGS data lead to similar results [45,46]. However, studies are missing that control for other socioeconomic determinants such as education, household size and age of the household head, or analyze those severe cases of households who have been in Q3 or Q4 before falling into impoverishment. Still, Rompentin [49] analyzes may serve as a lead, as the author reports that the number of elderly people in a household is associated with a higher probability of facing high cost drug spending defined as the average percentage of drug spending of an impoverished household. This goes along with the fact that demand rises with age, and hence said group is more likely to be impoverished. Likewise, no evidence exists for a relationship to non-communicable diseases in Chile, but international evidence supports that the incidence of these diseases pushes households, especially those who live close to the poverty line, into impoverishment [50]. Rompentin [49] further states that for a household the probability of impoverishment due to OOPS on drugs decline as income grows. Yet there remains need for research to the question by which health services households are impoverished. 5. Discussion 5.1. Linking results on financial protection to current health reform efforts The results show that Chile still struggles with high OOPS and in particular with catastrophic health expenditure and to a lesser degree with impoverishment. The AUGE plan and the Ricarte Soto Ley aim at reducing OOPS with improved financial protection of the population. However, since the AUGE plan restricts demand for care to a set of health problems and thus limits access to a defined ˜ group of patients, some authors such as Román and Munoz [51] argue that this violates the ethical principles of soli-

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10 Table 5 Impoverishment [38,45,46,40,49].

Study

Arpón et al. (2015) [38]

Household survey, sample used for estimation EPF, Metropolitan Region of Santiago

2012: Number of households impoverished (% of total population) Q1 5,407 (0.90%) 5,077 (0.84%) Q2 Quintiles according to Q3 1,236 (0.21%) household’s income Q4 1,235 (0.20%) per capita Q5 0 (0.00%) Total 12,955 (0.43%)

Bitrán and ENSGS, national Muñoz (2012) [45] Pérez (2009) ENSGS, national [46] Perticara (2008) [40] Rompentin (2013) [49]

Main results: Incidence rates of impoverishment

EPF, Metropolitan Region of Santiago EPF, Metropolitan Region of Santiago and regional urban zones

2012: Number of households impoverished (% of households impoverished) FONASA A 6,770 (52.3%) 2,518 (19.4%) FONASA B 1,055 (8.1%) FONASA C 49 (0.4%) FONASA D FONASA, unknown 1,183 (9.1%) 0 (0.0%) ISAPREs 1,380 (10.6%) Others Total 12,955 (100%) 2005: 1.2% Nearly all households are in the lowest quintile ISAPREs households do not fall into poverty 2005: 1.15% Probability is highest within the first two quintiles 0.09% of ISAPREs households are pushed into poverty and attributable to Q2 1997: 0.9% 2007: Number of households facing IMPOOR through expenditure on drugs decline with ascending quintiles: D1: 21%, D2:19%, D6-D10: 0.12% Number of elderly people in a household is associated with a higher probability of facing high cost drug spending defined as the average percentage of drug spending of an impoverished household

darity and equity. Besides no financial protection, patients who suffer from a disease, which is not included on the list of 80 health problems may even have to wait longer in the public sector as AUGE guarantees are to be completed within a certain time. Furthermore, ISAPREs beneficiaries are privileged to access good quality care faster [10,20,51]. Extensive studies [52–57] have been conducted to analyze AUGE’s impact on access, timeliness and quality of care, anticipating significant improvements for AUGE-patients in these areas, however little is known about the financial protection impact. No study is available so far that compares the situation of households’ prior to and post health reforms in this specific matter. Nevertheless, outlined studies in the result section do provide key information to draw conclusions about the impact of recent health reforms concerning the reliance on OOPS and financial protection mechanisms in place. Until now, Chile relies with more than 30% of total health expenditure heavily on OOPS as a financing mean, while general government expenditure on health remain below 4% of GDP. As such, WHO recommendations cannot be fulfilled in either case, indicating that there is a high probability for households to suffer from financial harm [58,59]. On a household level, OOPS in absolute and relative terms continue to increase, although one positive aspect is the decline in OOPS on drugs and hospitaliza-

tion. Arpón et al. [38] argue that this effect can be partly explained by AUGE’s success. Yet, Chile’s economic growth and increased households’ income, current problems in public provision linked to a rise in choosing the private MLE sector, demographic aging and the shift toward non-communicable diseases are all further aspects that influence OOPS. Further increases in OOPS might also be a sign that the needs of insured people are not fully met so that they see themselves forced to spend money directly on health. Generally, higher income groups spend more directly on health than do lower income groups. Highest OOPS shares occur for FONASA D, followed by ISAPREs. This recognizes that driven by the idea to foster redistribution, FONASA D has to bear the greatest burden with 20% of co-insurance for services within the public MAI sector, making ISAPREs insurances even more attractive especially for young healthy affiliates. Still, high OOPS shares for FONASA B and C occur, even though, levels of guarantees have already been assured beyond AUGE as to different co-insurances depending on FONASA group [60]. Within ISAPREs population, households in lower quintiles have a less favorable share of monthly expenditure devoted to health, even aggravated since ISAPREs has levied an additional AUGE surcharge on total premiums of each insured [20]. This group can be identified of particular

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need to benefit from AUGE’s guarantees, but utilization rate by ISAPREs households is low, fluctuating around 5% of AUGE services p.a. [60]. Generally, ISAPREs are not actively encouraging the use of AUGE services, as this implies higher financial protection guarantees and thus higher responsibilities from their side. Due to the current low uptake, the additional AUGE surcharge serves more as a subsidy for administration costs and consequently leads to higher profits for ISAPREs [18,61]. Households might also feel restricted in their free choice of providers as AUGE services are exclusively available with providers that ISAPREs dictate and which are usually not the providers they attend [56]. Drug purchases remain principal component of OOPS. The more resource the household has available the higher is the amount spent directly on drugs. However, if only those who actually spend on health are considered, poorer households have highest proportions of drug expenses, revealing an undesired regressive pattern and recognizing this group in particular need to benefit from reduced drug spending [15,37]. It will be interesting to see if the Ricarte Soto Ley, the new reform strategy in the series of universal health coverage efforts, is able to tackle this issue by improved access to high cost drugs free of charge. In terms of catastrophic health expenditure, study results reveal that the positive trend of reduced incidences of households with catastrophic health expenditure cannot be continued in 2012. Instead, the incidence rate increases again to around 4%. Disaggregation by income quintiles shows households within higher quintiles to be more confronted by financial catastrophe. Aguilera et al. [62] argue that higher catastrophic events among the more affluent households could be related to the exception of co-insurance for the poorest quintiles, but also to equity gaps in complex health services. However, according to Arpón et al. [38], the majority of households confronted with catastrophic health expenditure was insured within FONASA in 2012. Among them, it was not the group of FONASA D that bears highest burden but FONASA B, which is exempted from co-insurance in the public MAI sector. Certainly, this is a new understanding about (missing) financial protection. By contrast, the incidence rate among FONASA A households is considerably lower. This might in part be explainable by the fact that said group, contrary to FONASA B, is excluded from choosing providers in the private MLE sector (where considerably higher OOPS are requested); yet existing household surveys do not allow further subdividing these spending into the public MAI and the private MLE sector. Furthermore, it has to be taken into account that nearly half of the Chilean population belong to either FONASA A or B (Table 1). Even though FONASA A is also protected by 0% co-insurance within the public MAI sector, said group still reaches high absolute numbers of households with financial catastrophe. Even more aggravated by the fact that this group accounts for an even higher share of total households affected when a higher threshold is chosen – and thus more severe cases of hardship are considered (Table 4). Among ISAPREs population, it seems that the likelihood of suffering financial catastrophe is higher for poorer households, revealing inequality in the private system.

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Further equity concerns arise when looking at elderly people, who are usually insured with FONASA, as they simply cannot afford premiums based on personal risk profiles since health demand increases with age. The presence of elderly people in a household increases the likelihood of suffering financial catastrophe. Even more, said effect seems to have increased over time. Similar to FONASA A and B, elderly people aged 65 or older are protected from co-insurance within the public MAI sector. Once again, the questions arise why still a large part of this vulnerable group – despite protection mechanisms – suffers financial catastrophe and whether and to what extent they might see themselves enforced to choose private provider while risking financial harm. In addition, chronically ill face a higher probability of exposure, as they often have to purchase drugs on a regular basis, and may even be forced to consult private providers to overcome long waiting lists in the public MAI sector, or to benefit from higher quality consultation and supervision. Within the group that is in need to purchase drugs, the group with limited resources pays the highest share on drugs out of total OOPS. This implies that richer households can access to better financial protection mechanisms than poorer households. A focus on chronic diseases was desired while selecting AUGE health problems. However, it remains unclear how great the impact is on financial pro˜ [51] argue that tection of such people. Román and Munoz care of acute phase may be guaranteed within the AUGE package, but not the subsequent treatment procedure. This may exclude possible complications that require surgical interventions or complex treatments. The same applies for preventive measures. Further research in this field is very much needed, especially in the light of the growing importance of non-communicable diseases in the future. Unlike financial catastrophe, results to the incidences of impoverishment are more positive. Incidence rate is below 1% and a declining trend is observed. This also explains why research focuses primarily on catastrophic health expenditure. Arpón et al. [38] estimate only 0.43% of all households being impoverished due to OOPS in 2012. Yet, low-income groups that belong to FONASA A or B are most severely affected. This is an interesting observation, as those two groups are protected by 0% co-insurance within the public MAI sector. This undesirable regressive distribution pattern also applies for direct drug spending. Rompentin [49] concludes that the fact that said households have suffered the most severe effects reveal problems with availability of drugs in the public system, or problems with access to public provision. Valdiviesco and Montero [56] agree and criticize further that in some cases free drug provision within AUGE has been irregular both in frequency and quality. Moreover, vulnerable groups such as elderly people and chronically ill have a higher probability to be pushed into poverty, emphasizing inequalities in financial protection. It is worth noting that catastrophic health expenditure and impoverishment as indicators of progress to universal health care coverage refer to OOPS made by households, but these payments are only one of various causes that lead to financial harm. Especially poor households may be forced to use savings, borrow money or sell assets to pay for care [63]. Other factors such as loss of income, transport costs,

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poor quality and time costs may also play an important role in social protection, even though they are excluded from financial protection measures. There is an on-going discussion whether or not common indicators should be extended to incorporate any non-use of health care services [59,64]. 5.2. Limitations This systematic review focuses on the concept of financial protection against OOPS. However, for a full understanding of the situation in a country striving for universal health coverage the concept of service coverage including studies on service utilization and quality of care assessments in public and private facilities needs to be monitored alongside [52–57]. Thus, this study covers only one of multiple relevant dimensions. Furthermore, the basis of the systematic review is limited with regard to the number of articles published in peer-reviewed journals. About one-fifth of relevant studies are grey literature, i.e. primarily government reports. Moreover, the identified empirical studies themselves face several limitations that are strongly linked to the availability of current data on financial protection in Chile. First, differences exist regarding survey types (EPF vs. ENSGS), survey year, representation of survey sample, different ways of how capacity to pay is measured, different ways of extrapolating consumer price index provided by the Central Bank of Chile and classifying quintiles according to household’s expenditure per capita or household’s income per capita. Second, comparability within EPF versions was complicated as EPF 1997 only covers the Metropolitan Region of Santiago. EPF 2007 and 2012 have been extended to cover regional urban zones. Anyhow, analysis of financial catastrophe and impoverishment were limited to the Metropolitan Region, a mayor limitation, since regional urban zones experienced a significant rise in OOPS. Expanding the sample to a national level would improve current methods to estimate total OOPS on a national scale, as an income adjustment of rural areas using CASEN data is no longer needed. The non-sampling error, which is linked to the design of the survey, still needs to be considered [35]. Third, the EPF survey was conducted, prior to 2007, every ten years, which limits conclusion over time. A five-year rhythm has enhanced robust monitoring of financial protection. To identify the effects of policy measures, however, a yearly database is needed. Otherwise, confounding factors cannot sufficiently be controlled. Robust monitoring further allows analyzes of how households have coped with health shocks. Individual households who were pushed below the poverty line could be tracked over time. Such information is not yet available. Lastly, data gaps were identified at several times throughout the analysis (mean positive overshoot, poverty gap, distribution across health care groups etc.) which infringe a comprehensive assessment of the situation. 6. Conclusion and policy implications The results of this systematic review confirm that financial protection in the Chilean health care system is not

adequate to prevent financial hardship reliably – despite recent health reform efforts. Improving universal health coverage goals of equitable access with financial protection requires systems that reduce the reliance on OOPS to a level of less than 20% of total health expenditure (Chile: 31.5% in 2014), and increase at the same time its governmental revenues on health to at least a proportion of 5–6% of GDP (Chile: 3.9% in 2014) [12,58]. As a result, in 2012, around 4% of Chilean households suffered from catastrophic health expenditure defined as OOPS equal or exceeding more than 30% of household’s capacity to pay, while less than 1% of the Chilean households were driven into poverty due to OOPS. Due to the according insurance setup, higher income groups were more exposed to financial catastrophe, while lower income groups were more likely to be driven into poverty. In contrast to prior studies, recent data report that even publicly insured who should be fully protected from co-payments in the public system were affected by catastrophic health expenditure. Also in the private insurance system, financial catastrophe is a common risk. Moreover, vulnerable groups such as elderly people and people with chronic disease were particularly suffering from financial hardship. Health reforms, such as the AUGE plan and the Ricarte Soto Law, were introduced to improve financial protection of the Chilean population. Improvements have been achieved, but due to an insufficient database, it is currently difficult to quantify the effect of such measures. This is unfortunate since a well-functioning health information system is crucial to generate the full set of disaggregated information to derive adequate policy implications. In addition, comparison of study results was difficult due to different methodological approaches, and gaps in the data often set limits on the evidence. More research is required to understand why current mechanisms are not as effective as expected and to enable according reforms of the insurance system on the path toward universal health coverage, which is of vital importance in the light of economic slowdown, globalization, demographic aging and growing prevalence of chronic diseases. Conflict of interest None to declare. Funding This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors. Acknowledgement We gratefully acknowledge helpful remarks from the 2016 DIBOGS workshop participants, held on 18th and 19th November and hosted by the Ludwig Maximilian University in Munich. We are also grateful for valuable comments from Florian Rinsche. The authors are responsible for all remaining errors.

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References [1] World Health Organization. What is universal coverage? [December 05, 2016]; Available from: http://www.who.int/health financing/universal coverage definition/en/. [2] World Health Organization. The World Health Report 2010 health systems financing: the path to universal coverage. Geneva: World Health Organization; 2010. [3] World Health Organization, World Bank. Tracking universal health coverage: first global monitoring report. World Health Organization, World Bank; 2015. [4] Baird KE. The incidence of high medical expenses by health status in seven developed countries. Health Policy 2016;120(1):26–34. [5] Yardim MS, Cilingiroglu N, Yardim N. Catastrophic health expenditure and impoverishment in Turkey. Health Policy 2010;94(1):26–33. [6] Kronenberg C, Barros PP. Catastrophic healthcare expenditure—drivers and protection: the Portuguese case. Health Policy 2014;115(1):44–51. [7] World Health Organization. World Health Statistics, 2015. Geneva: World Health Organization; 2015. [8] Sumah AM, Baatiema L, Abimbola S. The impacts of decentralisation on health-related equity: a systematic review of the evidence. Health Policy 2016;120(10):1183–92. [9] Instituto Nacional de Estadísticas Chile. Demográficas y vitales: Población, país y regiones: Actualización población 2002–2012 y proyecciones 2013–2020. [December 05, 2016]; Available from: http://www.ine.cl/canales/chile estadistico/familias/demograficas vitales.php. [10] Missioni E, Solimano G. Towards universal health coverage: the Chilean experience. World Health Report (2010) background paper, 4. Geneva: World Health Organization; 2010. [11] United Nations Development Programme. Human Development Report 2014 sustaining human progress: reducing vulnerabilities and building resilience. New York: United Nations Development Programme; 2014. [12] World Health Organization. Global health expenditure database. [November 28, 2016]; Available from: http://apps.who.int/nha/database/Select/Indicators/en. Nacional de Salud. Boletín Estadístico [13] Fondo 2013–2014. [November 30, 2016]; Available from: http://www.fonasa.cl/sites/fonasa/adjuntos/Boletin%202013 %20-%202014. [14] Organisation for Economic Co-operation and Development, eurostat, World Health Organization. A system of health accounts. OECD Publishing; 2011. [15] Cid C, Prieto L. El gasto de bolsillo en salud: el caso de Chile, 1997 y 2007. Revista Panamericana de Salud Pública 2012;31(4):310–6. [16] Ministerio de Desarrollo Social. CASEN 2013: Una medición de la pobreza moderna y transparente para Chile. Santiago de Chile: Ministerio de Desarrollo Social; 2013. [17] Fondo Nacional de Salud. Boletín Estadístico [November 30, 2016]; Available from: 2012–2013. https://www.fonasa.cl/sites/fonasa/adjuntos/Boletin%202012 %20-%202013. [18] Comisión Asesora Presidencial para el Estudio y Propuesta de un Nuevo Modelo y Marco Jurídico para el Sistema Privado de Salud. Informe: Estudio y propuesta de un nuevo modelo y marco jurídico para el sistema privado de salud. Santiago de Chile: Comisión Asesora Presidencial; 2014. [19] Cid C, Torche A, Bastías G, Herrera C, Barrios X. Bases para una reforma necesaria al seguro social de salud chileno. In: Pontificia Universidad Católica de Chile, editor. Propuestas para Chile. Concurso Políticas Públicas; 2013. p. 183–219. [20] Bitrán R. Explicit health guarantees for Chileans: the AUGE benefits package. Universal health coverage studies series No. 21. Washington, D.C: The World Bank; 2013. [21] Sanchez M. Análisis de los planes de salud del sistema Isapre: Enero de 2014. Departamento de Estudios y Desarrollo. Santiago de Chile: Superintendencia de Salud; 2014. [22] Gobierno de Chile. Ley Ricarte Soto: Así funcionará el Sistema de protección financiera para diagnósticos y tratamientos de alto costo. [December 05, 2016]; Available from: http://www.gob.cl/2015/06/02/ley-ricarte-soto-asi-funcionara-elsistema-de-proteccion-financiera-para-diagnosticos-y-tratamientos -de-alto-costo/. [23] Ministerio de Salud. Ley Ricarte Soto. [December 05, 2016]; Available from: http://web.minsal.cl/leyricarte.

13

[24] Saksena P, Hsu J, Evans DB. Financial risk protection and universal health coverage: evidence and measurement challenges. PLoS Medicine 2014;11(9):e1001701. [25] Boerma T. Monitoring universal health coverage: summary report of a meeting in Bellagio, 11–13. March 2014. Geneva: World Health Organization; 2014. [26] O’Donnell O, van Doorslaer E, Wagstaff A, Lindelow M. Analyzing health equity using household survey data. The World Bank; 2007. [27] Xu K. Distribution of health payments and catastrophic expenditures: methodology. Discussion paper, No. 2. Geneva: World Health Organization; 2005. [28] Xu K, Klavus J, Kawabata K, Evans DB, Hanvoravongchai P, Ortiz JP, et al. Household health system contributions and capacity to pay: definitional, empirical and technical challenges. In: Murray CJL, Evans DB, editors. Health systems performance assessment: debates, methods and empiricism. Geneva: World Health Organization; 2003. p. 533–42. [29] World Health Organization. The World Health Report 2013 research for universal health coverage. Geneva: World Health Organization; 2013. [30] Hosseinpoor AR, Bergen N, Koller T, Prasad A, Schlotheuber A, Valentine N, et al. Equity-oriented monitoring in the context of universal health coverage. PLoS Medicine 2014;11(9):e1001727. [31] Boerma T, Eozenou P, Evans D, Evans T, Kieny M-P, Wagstaff A. Monitoring progress towards universal health coverage at country and global levels. PLoS Medicine 2014;11(9):e1001731. [32] World Health Organization. Handbook on health inequality monitoring: with a special focus on low- and middle-income countries. Geneva: World Health Organization; 2013. [33] Vega J, Frenz P. Integrating social determinants of health in the universal health coverage monitoring framework. Revista Panamericana de Salud Pública 2013;34(6):468–72. [34] Palacios A, Leal R. Gasto de bolsillo en salud: metodología y resultados 1997–2012. Boletín Semestral Economía y Salud 2014;8(2):19–26. [35] Cid C. Sistematización de las metodologías del gasto de bolsillo en salud y propuesta metodológica para Chile. Santiago de Chile: Ministerio de Salud; 2013. [36] Cid C, Matus M. Efecto de la crisis en el gasto en salud en siete países sudamericanos: Avance de investigación en curso. [November 30, 2016]; Available from: http://actacientifica.servicioit.cl/biblioteca/gt/GT19/GT19 CidPedraza MatusLopez.pdf. [37] Instituto de Salud Público. Revisión y actualización de los datos de gasto de bolsillo en salud y medicamentos en Chile. Santiago de Chile: Instituto de Salud Público; 2015. ˜ C. Informe final: Gasto catas[38] Arpón P, Acevedo R, Inostroza X, Ibánez trófico y de bolsillo en salud para el período 1997–2012. Agosto 2015. Santiago de Chile: Ministerio de Salud (MINSAL); Gobierno de Chile; 2015. [39] Banco Central de Chile. Base de datos estadísticos: Tipos de cambios. [December 01, 2016]; Available from: http://si3.bcentral.cl/siete/secure/cuadros/arboles.aspx. [40] Perticara M. Incidencia de los gastos de bolsillo en salud en siete países latinoamericanos. CEPAL – Serie Políticas Sociales No. 141. Santiago de Chile: United Nations; 2008. [41] Castillo C, Villalobos P. Caracterización del gasto de bolsillo en salud en Chile: una mirada a dos sistemas de protección. Revista Medica De Chile 2013;141(11):1456–63. [42] Freile B. Estimación del gasto de bolsillo en salud para los adultos mayores residentes en zonas urbanas de Chile. Tesis para optar al grado de magister en salud pública. Santiago de Chile: Univeridad de Chile. Facultad de Medicina. Escuela de Salud Pública; 2015. [43] Correa-Burrows P. Out-of-pocket health care spending by the chronically ill in Chile. Procedia Economics and Finance 2012;1:88–97. [44] Cuadrado C, Silva-Illanes N. Impact of the application of the value added tax to imaging tests on out-of-pocket health expenses of households in Chile. Medwave 2015;15(11):e6333. ˜ [45] Bitrán R, Munoz R. Health financing and household health expenditure in Chile. In: Knaul FM, Wong R, Arreola-Orneles H, editors. Household spending and impoverishment: volume 1 of financing health in Latin America series. Cambridge: Harvard University Press; 2012. p. 129–51. [46] Pérez P. La justicia financiera del sistema de salud Chileno. Tesis para optar al grado de Magíster en Políticas Públicas. Santiago de Chile: Universidad de Chile, Facultad de Economía y Negocios; 2009. [47] Knaul FM, Wong R, Arreola-Ornelas H, Oscar Méndez A. Household catastrophic health expenditures: a comparative analysis of twelve Latin America and Caribbean countries. Salud Pública de México 2011;(Suppl. 2):S85–95.

Please cite this article in press as: Koch KJ, et al. Out-of-pocket expenditure and financial protection in the Chilean health care system—A systematic review. Health Policy (2017), http://dx.doi.org/10.1016/j.healthpol.2017.02.013

G Model HEAP-3700; No. of Pages 14

14

ARTICLE IN PRESS K.J. Koch et al. / Health Policy xxx (2017) xxx–xxx

[48] Cuadrado C, García JL. Estudio sobre el cálculo de indicatores para el monitoreo del impacto socioeconómico de las enfermedades no transmisibles en Chile: Informe final. Santiago de Chile: Ministerio de Salud (MINSAL); Pan American Health Organization (Paho); Comisión Económica para América Latina y el Caribe; 2015. [49] Rompentin PJ. Acceso a medicamentos de alto costo en Chile. Tesis para optar el grado de Magister en Economía. Santiago de Chile: Universidad de Arte y Ciencias Soicales de Chile, Escuela Latinoamericana de Estudios de Postgrado; 2013. [50] Saksena P, Xu K, Evans DB. Impact of out-of-pocket payments for treatments of non-communicable diseases in developing countries: a review of literature. Geneva: WHO; 2011. ˜ [51] Román O, Munoz F. Una mirada crítica en torno al plan AUGE. Algunos aspectos generales y valóricos. Revista Medica De Chile 2008;136(12):1599–603. [52] Frenz P, Delgado I, Kaufman JS, Harper S. Achieving effective universal health coverage with equity: evidence from Chile. Health Policy Planning 2014;29(6):717–31. ˜ A, Chi C. Equity in health care utilization in Chile. International [53] Núnez Journal for Equity in Health 2013;12(58):1–16. [54] Vásquez F, Paraje G, Estay M. Income-related inequality in health and health care utilization in Chile, 2000–2009. Revista Panamericana de Salud Pública 2013;33(2):98–106. [55] Paraje G, Vásquez F. Health equity in an unequal country: the use of medical services in Chile. International Journal for Equity in Health 2012;11(81):1–16. [56] Valdivieso V, Montero J. El plan AUGE: 2005 al 2009. Revista Medica De Chile 2010;138(8):1040–6. [57] Fondo Nacional de Salud. Manuel informativo AUGE 80: En Fonasa exige tus derechos. Santiago de Chile: Fondo Nacional de Salud; no date. [58] Xu K, Saksena P, Matthew J, Indikadahena C, Kutzin J, Evans DB. Exploring the thresholds of health expenditure for protection against financial risk. World Health Report (2010) background paper, 19. Geneva: World Health Organization; 2010. [59] Xu K, Evans DB, Carrin G, Aguilar-Rivera AM, Musgrove P, Evans T. Protecting households from catastrophic health spending. Health Affairs 2007;26(4):972–83.

˜ 2008. [60] Cid C. Financiamiento agregado de la salud en Chile: Ano Cuadernos Médico Sociales (Chile) 2011;51(3):143–50. [61] Cid C, Uthoff A. ¿Es necesaria una nueva reforma a la salud en Chile? ˜ de la propuesta de la Comisión Asesora PresReflexiones a dos anos idencial; unpublished. ˜ C. Full case study: [62] Aguilera X, Castillo C, Nájara M, Delgado I, Ibanez monitoring and evaluating progress towards universal health coverage in Chile. PLoS Medicine 2014;11(9):1–26. [63] Wagner AK, Graves AJ, Reiss SK, Lecates R, Zhang F, Ross-Degnan D. Access to care and medicines, burden of health care expenditures, and risk protection: results from the World Health Survey. Health Policy 2011;100(2–3):151–8. [64] Wagstaff A. Measuring financial protection in health. Policy research working paper 4554, development research group, human development and public services team. Washington, D.C: The World Bank; 2008. [65] Fondo Nacional de Salud. Clasificación asegurados según tramos (A, B, C o D). [December 01, 2016]; Available from: https://fonasaweb.fonasa.cl/portal fonasa/site/artic/20140621 /pags/20140621192134.html. Nacional de Salud. Cobertura plan de [66] Fondo [December salud. 01, 2016]; Available from: https://fonasaweb.fonasa.cl/portal fonasa/site/artic/20160518/pags /20160518120753.html. [67] Agacino R. El gasto de bolsillo en servicios médicos y en fármacos: Análisis de resultados de la Encuesta de Presupuestos Familiares, EPF, 2007. Santiago de Chile: Departamiento de Economía de la Salud; 2009, unpublished. [68] Cid C. Problemas y desafíos para un financiamiento solidario de la salud. [December 05, 2016]; Available from: http://www.epes.cl/wp/wp-content/uploads/Presentaci%C3%B3n-Camilo -Cid-Pedraza.pdf. [69] Larraín N. Análisis de la equidad en el financiamiento del sistema de salud Chileno. Seminario de Título para optar al Título de Ingeniero Comercial. Santiago de Chile: Universidad de Chile, Mención Economía; 2014.

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