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ANALYSIS OF DATA FROM THE CAMBODIA SOCIOECONOMIC SURVEYFINANCIAL HEALTH PROTECTION IN CAMBODIA (2009-2016)

ANALYSIS OF DATA FROM THE CAMBODIA SOCIOECONOMIC SURVEY

FINANCIAL HEALTH PROTECTION IN CAMBODIA (2009-2016)

K I N G D O M O F C A M B O D I A

N A T I O N - R E L I G I O N - K I N G

E v i d e n c e t o i n f o r m p o l i c y t o w a r d s u n i v e r s a l h e a l t h c o v e r a g e i n C a m b o d i aRegionPacificWestern

OrganizationWorld Health

World Health Organization

November 2019

FINANCIAL HEALTH PROTECTION IN CAMBODIA (2009-2016)

ANALYSIS OF DATA FROM THE CAMBODIA SOCIOECONOMIC SURVEY

E v i d e n c e t o i n f o r m p o l i c y t o w a r d s u n i v e r s a l h e a l t h c o v e r a g e i n C a m b o d i a

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Suggested citation. Financial health protection in Cambodia, (2009–2016): analysis of data from the Cambodia Socioeconomic Survey. Manila, Philippines. World Health Organization Regional Office for the Western Pacific. 2019. Licence: CC BY-NC-SA 3.0 IGO.Cataloguing-in-Publication (CIP) data. 1. Cambodia. 2. Health expenditures. 3. Healthcare financing. I. World Health Organization Regional Office for the Western Pacific. (NLM Classification: W74)

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Graphs and Figures. Source: National Institute of Statistics. Cambodia Socioeconomic Surveys 2009 to 2016. Except where stated.

CBHI community-based health insurance

CDHS Cambodia Demographic and Health Survey

CSES Cambodia Socioeconomic Survey

CTP capacity to pay

GDP gross domestic product

NHA National Health Accounts

OOP out-of-pocket (expenditure)

SDG Sustainable Development Goal

UHC universal health coverage

WHO World Health Organization

ABBREVIATIONS

FOREWORD

The Royal Government of Cambodia recognizes that out-of-pocket expenditure on health poses significant challenges to the population. To inform the design, implementation and evaluation of the social health protection system, an increased understanding of the levels and trends of out-of-pocket expenditure is critical.

This report intends to increase the evidence base by presenting the findings of a study of the most recently available data from the Cambodia Socioeconomic Survey conducted in collaboration with the World Health Organization.

The study identifies some areas of concern. For example, out-of-pocket expenditure increased considerably between 2009 and 2016 and according to the National Health Accounts study represents 60% of current health expenditure. The study also highlights signs of improvement, for example that the rich/poor gap has narrowed in relative terms. Impoverishment has fallen since 2009 from 900,000 people to 300,00 people in 2016. This is a significant reduction and Cambodia will continue to push to ensure that all people do not face any financial payments that cause hardship. Cambodia is committed to achieving universal health coverage and the goal to ensure access to quality health services without experiencing health payments that lead to catastrophe or impoverishment.

The Ministry of Health intends to continue monitoring out-of-pocket expenditure on health and its impact on equity and financial access to health and hope that this report will contribute to the evidence-base and inform dialogue within the government and with development partners to strengthen the way Cambodia’s health sector is financed.

TABLE OF CONTENTS

AcknowledgementsExecutive summaryIntroduction

1.1. Estimation of illness and health-care utilization1.2. Estimation of out-of-pocket expenditure on health1.3. Estimation of household capacity to pay1.4. Estimation of catastrophic health expenditure1.5. Estimation of impoverishment due to health-care spending1.6. Estimation of Sustainable Development Goal (SDG)

indicator for financial hardship1.7. Estimation of indebtedness due to health expenditure 1.8. Estimation of health-related transportation expenses

xixiixiv

45799

10

1011

13

1

1.Methods and data sources

2.Descriptive statistics

5.Limitations

4.Discussion

6.Annex

3.1. Summary of the main findings3.2. Illness and health-care utilization3.3. Out-of-pocket expenditure on health3.4. Health spending analysis at individual level3.5. Capacity to pay3.6. Financial protection indicators3.7. Transportation expenditures related to seeking

health services3.8 Characteristics of households with a financial burden

References and data sources

Additional data

17182123262838

39

17

51

54

43

5758

3.Results

xi

The Royal Government of Cambodia with support from the World Health Organization (WHO) conducted this study under the guidance of Dr Lo Veasnakiry, Director of the Department of Planning and Health Information, Ministry of Health. A special thanks to key officials and representatives of the Ministry of Health, including Mr Ros Chhun Eang, Chief of the Bureau of Health Economics and Financing, Department of Planning and Health Information.

To monitor progress towards universal health coverage, in accordance with the Third Health Strategic Plan 2016-2025 and the National Social Protection Policy Framework 2016-2025, the Ministry of Health commissioned a report to track financial protection and service utilization among Cambodians. The data and results aim to inform policy-making to advance the goals of the Royal Government of Cambodia. The team consists of colleagues from the WHO regional and country offices, including Dr Annie Chu, Ms Maria Pena, Ms Rochelle Eng and Mr Mo Mai. The study received management support from Dr Kumanan Rasanathan, Coordinator for Health Systems (WHO Cambodia), Mr Erik Josephson, Health Economist (WHO Cambodia), Dr Yunguo Liu, WHO Representative in Cambodia, and Dr Peter Cowley, Coordinator for Health Policy and Financing of the WHO Regional Office for the Western Pacific.

Valuable inputs in the form of contributions, reviews and suggestions were received from Dr Ke Xu (WHO), Ms Justine Hsu (WHO), Ms Kateryna Chepynoga (WHO) and Dr Bart Jacobs (GIZ).

WHO recognizes and appreciates the financial support from: the Ministry of Health, Labour and Welfare, Japan; the Ministry of Health and Welfare, Republic of Korea; and the Department for International Development, United Kingdom of Great Britain and Northern Ireland.

ACKNOWLEDGEMENTS

xii

This study aims to generate evidence to inform health sector policy and planning in Cambodia, to contribute to the monitoring and evaluation of health system reforms, to measure the progress of the country’s effort on social health protection towards universal health coverage and to identify the determinants of catastrophic health expenditure and impoverishment among households in Cambodia in 2009-2016.

A descriptive study using cross-sectional household survey data from the nationally representative Cambodia Socioeconomic Survey 2009-2016 was used for this analysis. An internationally recognized and standardized methodology developed by the World Health Organization (WHO) was used to calculate the proportion of households that faced catastrophic health expenditures and impoverishment. Multivariate regression was performed to identify the determinants of catastrophic health expenditures and impoverishment. This report presents the findings of an analysis of the nationally representative socioeconomic surveys for the period 2009-2016 on out-of-poket (OOP) expenditures. The analysis sheds light on levels of catastrophic expenditure, impoverishment and indebtedness due to health-care spending for the general population and specific subgroups in Cambodia. The study was conducted in collaboration by the Ministry of Health and WHO.

The incidence of illness in the Cambodian population decreased from 19.1% in 2010 to 15.2% in 2016. On average, 90% of the population who were ill reported seeking care at any health provider. Private providers have been the main choice of health-care providers since 2009, with more than 70% of visits in 2016 being to private providers, followed by public health providers at around 20%, while visits to other informal providers such as shops or markets selling drugs remain significant at 10%.

Throughout the period 2009–2016, OOP expenditure on health rose, from US$ 41 per person per annum in 2009 to US$ 48 in 2016, and households spent US$ 186 in 2009 versus US$ 216 in 2016. The increase in OOP spending may be attributed to more care-seeking coupled with higher costs of care associated with the lack of social health protection schemes and preference for private sector.

Since 2009, households in rural areas have consistently spent more on health. In 2016, rural households spent US$ 232, whereas those in urban areas spent US$ 156. Males and females spent about the same amount on health from 2012 to 2015. However, in 2016, females spent US$ 55 and males US$ 41, which meant that females spent 1.3 times more than males. In 2016, people aged 60 years and above constituted 8% of the population, while accounting for 30% of health spending – US$ 156 per capita. Spending for this age group is likely

EXECUTIVE SUMMARY

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to increase as the population ages and noncommunicable diseases become more prominent.

The analysis of household OOP spending by socioeconomic quintiles1 reveals that the gap between the spending by the richest and poorest quintiles is increasing. The values for OOP spending by poor households in the lowest quintiles fluctuate between US$ 35 and US$ 51. Average spending by households in quintile 5 was US$ 665 in 2016, which was more than 16 times higher than spending by the poor, reflecting a widening gap between the rich and the poor.

Translating the proportion of households experiencing catastrophic health expenditure and impoverishment to numbers, the findings indicate that annually in Cambodia, more than half a million people suffer catastrophic health expenditures and more than 300 000people are driven into poverty by health payments. Levels of catastrophic expenditure among the population decreased from more than 1.1 million persons (250 000 households) in 2009, to more than half a million persons (122 000households) in 2016. Catastrophic expenditure generally increases from the

lowest to the upper quintiles. Whereas in 2009, almost 900 000 people were impoverished due to OOP payments (160 000 households), this number had declined to around 300 000 (50 000 households) in 2016.2 Most of those impoverished were from the poorest quintiles, which meant that health payments pushed “near-poor” households below the poverty line, endangering the household’s subsistence income. A possible reason for impoverishment in the lower quintiles may be that these “near-poor” households are not covered by any social protection scheme.

It is important to continue routine monitoring of OOP spending on health, given its implications for equity and efficiency, as a measurement of performance of social health protection schemes. The results of monitoring also support assessment of progress towards universal health coverage and Sustainable Development Goal key indicators. Such monitoring may be conducted as part of the National Health Accounts and the Annual Health Financing Report by the Ministry of Health, and the results should feed into the evaluation of national policy reforms and health-related strategies and plans.

1 Households were categorized into five groups from lowest to highest known as socioeconomic quintiles, with quintile 1 being the poorest 20% of households, and quintile 5 being the richest 20% of households.2 Impoverishment estimated using the national poverty line for 2016.

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Cambodia is undergoing several reforms aimed at promoting greater social protection for health, decreasing the barriers to access and improving service quality. The recent adoption of the Third Health Strategic Plan 2016–2020 and the National Social Protection Policy Framework 2016–2025 paves the way for Cambodia to progress the agenda towards universal health coverage (UHC), where no one faces financial hardship from accessing quality health-care services. Monitoring the progress of ongoing reforms requires data on financial protection and thorough analysis that can support evidence-based policy-making. Out-of-pocket (OOP) expenditure incurred by households at the point of accessing health services represents a considerable financial obstacle for the Cambodian population. OOP payments include consultation fees, purchases of medication, and hospital bills for inpatient and outpatient care from both public and private facilities. The private health sector is largely unregulated, which makes price and quality control a challenge. OOP spending can present a major barrier to health-care access and is a frequent cause of indebtedness and impoverishment. OOP expenditure does not facilitate risk sharing among the population, which is a core function of health financing policy and a key element in progressing towards UHC. Moreover, OOP spending is not an equitable or efficient way of financing health care. Relying on OOP payments increases the likelihood of catastrophic expenditures (1), and individuals may delay or forgo seeking care simply because they cannot afford the services. The 2016

National Health Accounts (NHA) found that OOP expenditure accounted for US$ 729 million (60.4%) of Cambodia’s total health expenditure of US$ 1207 million (2). The Royal Government of Cambodia recognizes the that OOP spending poses a challenge to the population and is making efforts to expand and strengthen the social health protection system, as outlined in the National Social Protection Policy Framework 2016–2025 approved in March 2017 (3).

This report presents the findings of a study that was carried out to inform the development of policy by analysing OOP spending trends and monitoring financial protection by using a variety of indicators. This includes the World Health Organization (WHO) methodology for measuring catastrophic health expenditures, impoverishment due to health payments, catastrophic health payments (4), as well as the UHC/Sustainable Development Goal (SDG) indicator for financial protection (5), and indebtedness due to household spending on health care. These indicators can be used to measure progress on financial protection and financial risk disparities, key components of the equity dimension of UHC. This report also utilized data from and informed the NHA study.

INTRODUCTION

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3 Based on the non-food expenditure module of the Cambodia Socioeconomic Survey.

Goal and objectives

The overall goal of this study is to generate evidence to inform health sector policy and planning in Cambodia and to contribute to the monitoring and evaluation of health system reforms in the country. The specific objectives are:

• to estimate total OOP spending on health in Cambodia in 2009–2016;3

• to estimate the proportion of households that incur catastrophic expenditure and are impoverished as a result of spending on health care;

• to examine the determinants of catastrophic health expenditure and impoverishment due to health payments;

• to support monitoring and evaluation of health sector policy goals, including monitoring of the SDG financial protection indicator (target 3.8.2); and

• to build capacity in Cambodia to analyse OOP expenditure and related indicators using household survey data.

1


Methodsand data sourcesThe study used methods developed by the World Health Organization (WHO), which are described in detail in “Distribution of health payments and catastrophic expenditures: Methodology” (4). These methods are summarized below.

The main data source for this study is the Cambodia Socioeconomic Survey (CSES), a nationally representative survey carried out annually by the National Institute of Statistics, within the Ministry of Planning. The sampling of the CSES is a three-staged stratified sampling design, not simple random sampling. Therefore, in Stata, the dataset is declared as survey data through adjusting multistaged stratified sampling, which applies weights in each process of analysis.

1

2

The CSES collects data on demographic characteristics, housing, agriculture, education, labour force, health and nutrition, and household income and consumption. Survey sample sizes are reported in Table 1. Large samples have been surveyed every five years – 2009 and 2014. The various recall periods used for recording expenditures across items in the surveys are provided in Table 2. The annex details the major changes in the survey questionnaires from 2009 to 2016. This analysis of out-of-pocket (OOP) spending uses only the following

years: 2009, 2010 and 2013–2016. The years 2011 and 2012 were excluded from this study due to survey design differences in the 2011 and 2012 CSES health expenditure survey questions. OOP spending is taken from the non-food expenditure module in the CSES. Further details on the survey can be found in the annex.

The Demographic and Health Survey is used to complement the information from the CSES, in particular with regard to social protection schemes in Cambodia.

Table 1: Sample sizes in the Cambodia Socioeconomic Survey (2009–2016)

Survey year Number of households Number of individuals

2009 11 971 57 105

2010 3 592 16 510

2011 3 592 16 327

2012 3 840 17 644

2013 3 840 17 225

2014 12 090 53 968

2015 3 839 17 301

2016 3 839 17 055

methods and data sources1

3


Recall period Module

Food 7 days General expenditure

Beverage 7 days General expenditure

Tobacco 7 days General expenditure

Health-care utilization and spending 30 daysHealth-care seeking and

expenditure

Out-of-pocket spendinga 1 month General expenditure

Transportation, communication, personal care, rent and utilities

1 month General expenditure

Clothing and footwear 6 months General expenditure

Furniture and other expenses, education 12 months General expenditure

Table 2: Recall periods of Cambodia Socioeconomic Survey (2009–2016)

There are three sections in the CSES that contain health expenditure data: the general expenditure module, expenditure diary, and the health-care seeking and expenditure module.

For standardization and consistency across countries, data from the “non-food module” are used to estimate OOP spending. This portion of the survey collects data on all items of household expenditure, and compared to a health survey or the health section of a survey, the health expenditure estimates tend to be lower when taken from a non-health module (non-food module in the CSES). However, this tends to provide less biased estimates of the proportion of overall household spending that goes on health (6). Proportions of health spending and responses to specific

survey questions on health spending defined by individual characteristics, such as by age, residence, sex and provider are taken from the health module.

CSES sample weights were applied to generate representative data for the country, as well as for each population subgroup (socioeconomic status, urban versus rural residence, age and sex). Individual sample weights were used for individual-level analysis (e.g. illness, health-care utilization, and health expenditure by provider, sex, age and illness), and household sample weights were used for household-level analysis (e.g. OOP, catastrophic health expenditure and impoverishment due to spending on health care).

a Health-care spending proportions by illness, age group and provider are taken from the health-care module because it is on an individual basis.

4 Stores selling drugs are classified in the CSES as the non-medical sector.4

Statistical analyses were carried out in Stata version 14. However, there have been some adjustments to the surveys:

• The 2009 and 2010 surveys did not collect data on utilization of inpatient and outpatient care, while the 2011–2016 surveys included this information.

• Data on transportation costs have been collected since the 2009 survey.

• The recall periods for health utilization and expenditure are slightly different: for health-care utilization in the past 30 days and for health spending, from the non-food module, in the last month.

• Since 2011, there have been additional categories for providers, including for “overseas medical expenditures”.

Data for the estimation of illness and health-care utilization came from the health expenditure module of the CSES. The incidence of illness was calculated based on the number of individuals who reported having an illness, injury or health problem in the previous 30 days. Survey weights were applied to represent the population and estimate national figures based on the average number of episodes of illness per capita:

Average episodesof illness per capita

Total illness episodes

Total persons

The percentage of care or treatment sought for all episodes of illness was calculated based on the number of people who sought care or treatment for an illness reported in the previous 30 days:

Health-care seeking share among all those reporting illness

Total persons seeking care Total persons who fell ill

The CSES asked specifically for the place of care for the first visit and, if more than one, the last place of care. The CSES includes 18 provider categories. In this study, the provider categories from the CSES were reclassified into nine groups. The groups are:

1. health centres; 2. public national hospitals; 3. public provincial hospitals; 4. public district hospitals;5. private hospitals;6. private clinics;7. pharmacies and stores (selling drugs);4

8. overseas care in the latest year 2014–2016; and

9. others.

The data were further categorized into public, private and non-medical providers.

Summary statistics on the proportion of different providers were calculated as a proportion of overall care or treatment sought:

1.1Estimation of illness and health-care utilization


5


Provider share Total persons seeking care

at provider (m), kTotal persons seeking care, k

Where provider m = 1 , 2, 3,…9 and k = first or last visit.

1.2Estimation of out-of-pocket expenditure on health

OOP health payments are made by individuals when they receive health services. The CSES contains data on how much households spent on medical care and medical products. It is assumed that the spending reported in the survey was OOP, with no reimbursement from a health insurance provider or other source. OOP spending is calculated by adding up household spending on medical care (doctors’ fees, other medical services, hospital charges, other medical supplies, medication, drugs, vitamins, bandages, corrective eyeglasses, hearing aids, etc.) from the non-food expenditure module, while health spending proportions by age group, illness type, provider, and, whether outpatient or inpatient, is estimated from the health module. Since it is a monthly value, it is then converted to a yearly value by multiplying by 12. Proportions estimated from the CSES are applied to the OOP value taken from the National Health Accounts (NHA) study to obtain per capita values.

OOP spending based on the health module

Two levels of estimation are included: the individual level and the household level. Average OOP spending per episode of illness and type of care (outpatient or inpatient) for 2009–20165 were calculated on an individual level using individual sample weights.

Average OOP spending per episode of illness

Total OOPi for those who fell illTotal persons who fell ill

Average OOP spending per outpatient visit

Total OOPi for outpatient careTotal outpatient visits

Average OOP spending per inpatient stay

Total OOPi for inpatient careTotal inpatient stays

5 The 2010 CSES did not include questions on the type of visit, so it was not possible to calculate OOP spending by outpatient and inpatient care for that year. Data from 2011 have been excluded from this analysis.

6

The estimates of OOP on health only include payments for consultation, diagnosis, treatment, drugs and other costs. Spending on transportation to access health services is treated separately (see Section 3.7).Unfortunately the CSES only provides information on utilization at the first and, if more than one visit, the last provider. Data on expenditure are also collected for all visits in the last 1 month, which means there are no specific data on expenditure by visit. This makes it challenging to estimate OOP expenditure on health by provider. Nevertheless, an attempt was made to estimate OOP by provider as follows: the cost per visit per provider was estimated by using the average OOP payment by those who had visited a particular provider only once (since it was then clear at which provider the full expenditure was incurred). If an individual had made more than one visit and to different providers, the average of the two providers’ costs was used. OOP spending per provider was then estimated by using individual sample weights.

The 2015 and 2016 CSES included 19 categories of illness type. Spending by illness type has been included in this analysis within Annex Table A.11. This analysis makes the assumption that individuals have only one illness per month.

Average OOP spending by illness type

Total OOPi by illness type (n)Total persons suffering illness type (n)

n = 1, 2, 3, …19

OOP spending based on the non-food expenditure module

The cumulative OOP expenditure for the country and average OOP expenditure per capita were calculated at the household-level ratio of health expenditures to total household expenditures, and the household survey estimate was scaled to match the NHA estimate of household consumption.

Proportions of OOP spending by age group

The ratio of OOP spending by age group was taken from the 2009–2016 CSES and applied to the total OOP spending found in the NHA study.

Proportions of OOP spending by sex

The ratio of OOP spending by sex was taken from the 2009 and 2014 CSES (larger sample years) and applied to the total OOP spending found in the NHA study.

Proportions of OOP spending by residence

The ratio of OOP spending by urban and rural areas was taken from the 2009–2016 CSES and applied to the total OOP spending found in the NHA study.


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1.3Estimation of household capacity to pay

Catastrophic health expenditure is estimated based on households’ capacity to pay or non-subsistence expenditure.

To calculate capacity to pay, data on household consumption expenditures and food expenditures were used to estimate household subsistence spending. All consumption variables (e.g. overall consumption, food, health) were converted into a monthly figure (1 month = 30.4 days). The analysis did not adjust for inflation, as it was assumed that the inflation rate over the survey period was minimal.

The subsistence spending was estimated in four steps:

1. First, the food expenditure share (foodexph) for each household was calculated by dividing food expenditure by total household expenditure6:

foodexph foodh

exph

2. The needs of a household grow with each additional member, but due to economies of scale in consumption, not in a proportional way. A household equivalence facotor is used to adjust

household size (hhsizeh) to produce the household equivalence size (eqsizeh)

eqsizeh = hhsizehß

where hhsizeh = household size

The value of the parameter ß is 0.56, according to WHO’s estimation based on household surveys conducted in 59 countries.

3. Equivalized food expenditure (eqfoodh) was estimated by dividing the food expenditure of each household by the household equivalence size:

eqfoodh foodh

eqsizeh

4. Subsistence spending (se), which is equal to the minimum requirement to finance basic functions in life, was then calculated. The reference line (rl) is defined as equal to the food expenditure of the household whose food expenditure share of total household expenditure is equal to the 50th percentile of the sample. The weighted average of food expenditure in the 45–55th percentiles (food45 and food55, respectively) was calculated to minimize

6 Household consumption expenditure (exp) comprises both monetary and in-kind payments on all goods and services, and the monetary value of the consumption of homemade products. Household food expenditure (food) is the amount spent on all foodstuffs by the household, plus the value of the family’s own food production that is consumed within the household. Because food expenditure is used for subsistence estimation in the analysis, household consumption of alcoholic beverages, tobacco, food consumed out of the home (e.g. at hotels and restaurants) and prepared meals bought outside and eaten at home were not included in household food expenditure. However, those consumption items were included in the household consumption expenditure (exp).

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measurement error. This is equal to subsistence spending per capita, which was converted to subsistence spending for each household as follows:

seh = rl x eqsizeh

The household capacity to pay (CTP) is defined as a household’s non-subsistence spending. For households with food expenditure lower than subsistence spending (seh>foodh), non-food expenditure is used as non-subsistence spending:

ctph = exph - seh if seh ≤ foodh

ctph = exph - foodh if seh > foodh

The poverty line is the minimum level of income needed for subsistence. For this analysis, we are using the national poverty line, as this is defined based on the country’s context in terms of the specific economic and social situation. The international poverty line is meant to be used for comparability purposes and accounts for differences in purchasing power.

A household is regarded as poor (poorh) when its household expenditure is smaller than the nationally defined poverty line

(nplh), which includes both food and non-food components. The national poverty line was estimated by taking the official poverty line in 2009–2015 (7) and adjusting inflation for 2016. The national poverty line is a daily per capita rate and varies by year; however, it has been adjusted as a monthly value, and at household level.

nphh,m,y = npli,d,y x 30.4 x hhsize

The household poverty incidence was calculated using household poverty status and household weight:

poorh = 1 if exph < nplhpoorh = 0 if exph ≥ nplh

The global poverty line is used to allow for global comparisons of extreme poverty at US$ 1.90 per capita per day and of moderate poverty at US$ 3.10 using 2011 purchasing power parity. However, the national poverty line is used for purposes of this analysis (Table 3).

The burden of health payments is defined as a household’s OOP spending as a percentage of the household’s CTP (oopctp):

oopctph = ooph

ctph


Table 3: National and global poverty lines, 2009–2016

2009 2010 2013 2014 2015 2016

National poverty line per capita per day (CR)*

3 874 4 076 4 728 4 919 5 128 5 319

National poverty line per capita per day (US$)

0.97 1.02 1.18 1.23 1.28 1.28

Global poverty line per capita per day (CR) 2011 PPP (based on US$ 1.90)

2 333 2 426 2 712 2 816 2 851 2 936

Global poverty line per capita per day (CR) 2011 PPP (based on US$ 3.10)

3 807 3 959 4 425 4 595 4 652 4 791

CR: Cambodian riel; PPP: purchasing power parity.Source: Royal Government of Cambodia, 2013

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1.4Estimation of catastrophic health expenditure

Catastrophic health expenditure (cata) is defined by WHO as occurring when a household’s total OOP spending equals or exceeds 40% of a household’s CTP (or non-subsistence spending). The threshold of 40% may be adapted according to a country’s specific situation, but it enables cross-country comparisons. The dummy variable on catastrophic health expenditure

was constructed with 1 indicating a household with catastrophic health expenditure, and 0 indicating a household without catastrophic health expenditure:

catah = 1 if ooph

ctph ≥ 0.4

catah = 0 if ooph

ctph < 0.4

1.5Estimation of impoverishmentdue to health-care spending

A non-poor household is impoverished by health payments when it becomes poor after paying for health services. To assess the extent of impoverishment in the population, a dummy variable on the poverty impact of health payments (impov) was created. It equals 1 when household expenditure per capita is equal to or higher than the national poverty line before spending on health care but is lower than the national

poverty line after deducting OOP, and it is 0 otherwise:

impovh = 1if exph ≥ nplh and (exph - ooph) < nplh

otherwise impovh = 0

In these analyses, we only look at the impoverishment due to health payments based on the national poverty line.

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1.6Estimation of Sustainable Development Goal (SDG) indicator for financial hardship

1.7Estimation of indebtednessdue to health expenditure

The incidence of indebtedness resulting from illness among Cambodian households was calculated from data in the CSES. One of the six alternative answers to the question “How was the treatment financed?” was “borrowing”,

and households were asked to indicate the three main sources if more than one existed. If households indicated borrowing for any of the three main sources of health finance, they were considered indebted due to illness.

SDG indicator 3.8.2 (SDG382) is defined as a household’s OOP payments being equal to or exceeding a portion of the total household expenditure (5). Two thresholds, 10% and 25%, are used in the analyses.

The SDG indicator 3.8.2 is based on a health expenditure budget share rh defined as the following ratio:

rh = household health expenditures per capita

household expenditures per capita

Health expenditures are defined as large when exceeding the thresholds 10% and/or 25%.

SDG38210,25 = Σhwh 1(rh > 10,25)

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1.8Estimation of health-relatedtransportation expenses

Within the health module, the CSES asks questions about the costs of transportation to the first and, if more than one visit, last health-care provider (in the previous 30 days). Expenditures on health-related transportation were calculated per visit using individual-level data and individual sample weights as follows:

Individual health-related transport costs per inpatient visit

Total transport costs when seeking inpatient care

Total no. of persons seekinginpatient care

Individual health-related transportcosts per outpatient visit

Total transport costs when seeking outpatient care

Total no. of persons seeking outpatient care

Ratio of spending on transport relative to total spending on health

Total transport spending Sum of total transport spending + total

OOP spending by household

13


Descriptive statistics7 The 2014 sample consisted of 12 090 households and 53 968 individuals. The sample was split into expenditure quintiles for deeper analysis by the different income groups. Households in the lowest two quintiles live predominantly in “rural” areas, 89% (Q1) and 91.8% (Q2). By contrast, half of the households in the richest quintile live in urban areas (including Phnom Penh and “other urban” areas) as compared to the poorest quintile, of which less than 2% of the households live in Phnom Penh (Table 4).

2

7 The descriptive statistics are intended to provide a snapshot of the individual and household characteristics in Cambodia. The 2014 survey is used, given that this is the latest survey with the largest sample.

14

Household level

Phnom Penh(%)

Other urban(%)

Rural(%)

Household size

Quintile 1 1.9 6.3 91.8 3.2

Quintile 2 3.0 7.9 89.0 4.2

Quintile 3 7.2 9.4 83.3 4.6

Quintile 4 12.7 14.0 73.3 5.0

Quintile 5 31.7 18.5 49.8 5.3

Total 11.3 11.2 77.5 4.5

Table 4: Household location and size by quintile

The average household size in Cambodia is 4.5 people. The poorest quintile has the fewest household members, averaging around 3.2 people per household. In comparison, the richer households tend to have bigger families, averaging around 5.3 household members. In 2015, a report by the Ministry of Planning highlighted the phenomenon of out-migration from rural to urban areas and left-behind households of those who did not migrate. This report provides details on household composition in rural areas (8). Migration patterns in Cambodia show that adults aged 15–59 years are increasingly moving to urban areas to find work. The study shows that

the characteristics of left-behind household members include children (71%) and older people aged 60 years and above (31%). These households tend to be smaller and have fewer than four members.

In terms of the composition of age groups, the poorest quintile has a larger share of members aged 60 years and above (11.8%) and more household members that are under 5 years old. In comparison, 70% of household members in the richest quintile are aged 15–59 years, meaning that just under three quarters of household members are in this age group, while less than 10% are under 5 years old (Table 5).

descriptive statistics2

15


Men(%)

Women(%)

Under 5 years (%)

5–14 years (%)

15–59 years (%)

60 years and above (%)

Quintile 1 46.1 53.9 13.6 17.5 57.0 11.8

Quintile 2 48.8 51.2 11.8 21.1 60.7 6.3

Quintile 3 49.8 50.2 10.5 21.5 61.5 6.4

Quintile 4 49.8 50.2 9.2 20.3 64.2 6.2

Quintile 5 49.3 50.7 8.8 15.4 69.6 6.2

Total 49.0 51.0 10.5 19.1 63.3 7.1

Table 5: Individual characteristics

17


3

8 Excluding 2011 and 2012.9 Gross domestic product per capita increased from US$ 407 in 2004 to US$ 1080 by 2014.

Results3.1Summary of the main findings

This section presents the results of the analysis of Cambodia’s OOP spending on health between 2009 and 2016.8 Key indicators are summarized in Table 6, while further details are provided in the following sections. From 2009 to 2016, the analysis shows that OOP spending on health per person increased from US$ 41 in 2009 to US$ 48 in 2016. Overall, total OOP spending increased from US$ 534 million in 2009 to US$ 728 million in 2016. Many factors may contribute to the high OOP spending, such as Cambodia’s economic growth9 and the increase in household disposable income to spend on health; the changing demographic profile with higher spending on health by the elderly population; the rising cost of health-care services; and a slight increase in health-care utilization for inpatient care.

Health-seeking behaviour remains consistently high: more than 90% of the population sought care when ill in the period from 2009 to 2016. The proportion of households that experienced catastrophic expenditures declined from 8.8% in 2009 to 3.7% in 2016. Impoverishment from health payments decreased from 5.7% to 1.6% in the same period.

18

results3

Table 7 presents the results of the analysis of incidence of illness and health-care utilization. The proportion of individuals who reported illness in the past 30 days from 2009 to 2016 fluctuated between 14% and 19%, and the prevalence of chronic illness ranged from 2.7% to 3.7% of the population. In 2009, an estimated 381 000 people had a chronic disease, and by 2016, this reached over half a

million people. This does not account for undiagnosed cases. There is a clear trend that the number of people with chronic diseases is increasing. Care-seeking among those suffering illness ranged between 87% and 96% in the same period. In 2016, 5.9% of individuals who reported illness received inpatient care and on average spent 5.6 days in hospital.

3.2Illness and health-care utilization

2009 2010 2013 2014 2015 2016

OOP health per capita per annum (US$) 41 44 45 45 44 48

OOP health per household per annum (US$) 186 204 210 204 197 216

Total household consumption expenditure (million US$)a 7 969 9 314 12 482 13 601 14 820 16 149

Total OOP spending (million US$)b 534 596 663 664 653 728

Incidence of households with catastrophic expenditure (%)

8.8 7.8 5.8 4.8 5.1 3.7

Incidence of households impoverished due to health payments (%)

5.7 5.3 2.5 2.1 1.4 1.6

a2011–2012 CSES data were not included because survey methodology had changed. bFrom National Accounts Database, National Institute of Statistics, Ministry of Planning.

Table 6: Summary indicators of out-of-pocket (OOP) expenditure on health, 2009-2016

19


NA: not available

Table 7: Illness and health-care utilization, 2009–2016

Table 8: Percentage of individuals who sought care by residence, 2009–2016

Indicator (last 30 days) 2009 2010 2013 2014 2015 2016

Proportion of individuals who report illness (%)

14.4 19.1 17.7 14.5 13.6 15.2

Proportion of the population with chronic illness (%)

2.9 2.8 3.7 2.7 3.4 3.7

Proportion of individuals who sought care when ill (%)

93.5 86.6 93.2 90.3 95.5 93.0

Proportion of individuals who sought inpatient care when ill (%)

NA NA 4.9 5.6 5.8 5.9

Average number of inpatient days

NA NA 5.9 6.2 5.8 5.6

2009(%)

2010(%)

2013(%)

2014(%)

2015(%)

2016(%)

Cambodia 14.4 16.6 16.5 13.1 13.0 14.1

Phnom Penh 11.3 13.6 10.2 7.2 4.6 4.8

Other urban 13.8 14.0 16.0 12.0 12.1 13.3

Other rural 14.9 17.3 17.5 14.2 14.6 15.8

Table 8 shows that during the period 2009–2016, residents of rural areas tended to seek care more frequently than urban

dwellers. The percentage of Phnom Penh’s residents seeking care halved from 11.3% in 2009 to 4.8% in 2016.

20

Fig. 1: Choice of provider for the first visit, 2009–2016a

last visits in all survey years since 2009. Annex Table A.3 shows that for all years, the predominant providers were drugstores and private clinics when individuals visited one or two providers in one month. Table A.3 illustrates a further breakdown showing which provider the individuals who reported illness consulted for their first and last visits. People sought

care more frequently from non-medical providers10 than from the public health sector during 2009 and 2010. However, the practice of visiting non-medical providers decreased significantly in 2015 (Fig. 1).

Those in the lowest quintiles tended to seek care predominantly at the home or office of a trained nurse, a private

For those who were ill and sought care, the average number of times care was sought was fewer than two times in one month. While the proportion of individuals seeking health care across quintiles did not vary significantly, those in the lowest expenditure quintile tended to seek health

care slightly less often than those in the highest quintile (results available upon request). Health-seeking behaviour when ill was high across all quintiles.

Private providers were the primary choice for health care for the first and

aDetails on the choice of provider for 2009–2016 can be found in Annex Tables A3 and A4.

10 Non-medical providers include Khmer magicians, shops/markets selling drugs, traditional medicines, religiousleaders and traditional birth attendants.

Public Private Non-medical

20102009 2013 2014 2015 20160

20

40

60

80

100%

results3

21


Fig. 2: Percentage of care sought at selected providers by quintile, 2016

pharmacy or a health centre, whereas people in the higher quintiles tended to seek care more often from private clinics and private pharmacies. People in the lower quintiles who live in rural areas were more likely to seek care from the non-medical sector than those in the higher quintile living in urban areas.11

Fig. 2 shows that individuals in the upper quintiles seek care more often from private clinics and from hospitals in both the private and the public sector. In comparison, health centres and the homes or offices of trained nurses are mostly frequented by those in the lower quintiles.

Fig. 3 indicates the OOP spending on health per year by individuals and households from 2009 to 2016. OOP expenditure on health per capita and per household increased slightly between 2009 and 2016. Note that OOP spending in the CSES includes overseas care, which

accounted for 4% in 2014, 22% in 2015 and 7% in 2016 relative to total OOP spending. Expenditure on transportation to access health services is not included in these estimates and is presented separately (see Section 3.7).

3.3Out-of-pocket expenditure on health

11 Further details on this can be found in Annex Table A.4.

5

10

15

20

25

30

35%

0

Q1 Q2 Q3 Q4 Q5

Public hospitals

Private hospitals

Private clinics Home/office of trained nurse

Health centres

8.4

3.6

9.7

23.2

15.5

8.2

3.2

12.9

18.5

14.6

8.8

4.4

19.9 21

.4

10.211

.4

3.4

26.8

16.5

8.0

14.6

8.2

30.7

11.7

6.2

22

Fig. 3: Annual out-of-pocket (OOP) expenditure on health, per household and per capita, 2009–2016 (US$)

Across all years, the highest expenditure quintile consistently spent more on health than the lowest quintile. In 2009, the highest quintile spent 12 times more than the lowest and 17 times more by 2016. The widening gap can be attributed to households from the upper quintiles seeking care overseas, and also the continuing tendency of those in the upper

quintiles to seek care in the private sector. The spending by those in the lowest quintile has not varied much since 2009, and has remained on average US$ 41. Since 2009, spending by those households in rural areas has been higher than by those living in urban areas, and the gap between them is steadily increasing (Fig. 4).

Fig. 4: Out-of-pocket (OOP) expenditure on health per household by wealth quintile and residence, 2009–2016 (US$)a

aOOP spending on health per individual by wealth quintile can be found in Annex Table A.7

OOP per household OOP per capita

50

100

150

200

250

2009 2010 2013 2015 201620140

40.6

185.6

43.8

204.4

45.4

209.7

44.9

203.7

43.6

197.5

48.1

215.9

Q1 Q2 Q3 Q4 Q5 Urban Rural Average0

100

200

300

400

500

600

700

2009 2010 2013 2014 2015 2016

results3

23


OOP spending for households in the highest quintile grew from US$ 502 to US$ 665 between 2009 and 2016 (Fig. 4, Table 9). Members of the poorest quintile spent an average of US$ 41 across the six years. During the same period, households living in rural areas consistently spent more on health-care services than urban dwellers.

In 2016, urban households spent US$ 156 on health, while rural households spent US$ 232. The difference in health-care spending between rural and urban dwellers is widening. The difference was less than US$ 10 in 2009 and 2010 and began to increase in 2013 (US$ 42). The gap was approximately US$ 70 in 2014, 2015 and

Table 9: Household out-of-pocket spending by quintile and residence, 2009–2016 (US$)

2009 2010 2013 2014 2015 2016

Quintile 1 41 40 51 38 35 40

Quintile 2 72 81 85 75 76 71

Quintile 3 120 106 117 110 88 125

Quintile 4 193 191 214 204 136 178

Quintile 5 502 605 581 592 653 665

Urban 176 194 176 148 143 156

Rural 188 207 218 219 212 232

Average 186 204 210 204 197 216

3.4Health spending analysis at individual level

2016.Health spending by provider

Fig. 5 presents the distribution of health spending by provider from 2009 to 2016. Those who received care at private clinics accounted for the highest share of health spending. This was followed by spending

at hospitals including national hospitals and private hospitals. In 2015, spending on medical care overseas accounted for a significant share of total health spending. Spending on private providers has accounted for more than half of health spending since 2009 and had increased to over 65% of total health spending by 2016.

24

12 Including shops and markets selling drugs.

Fig. 5: Distribution of out-of-pocket spending by provider, 2009–2016a

The primary choices of provider were private clinics and drugstores12; however, in 2016, spending at drugstores only made up 13% of total OOP payments, whereas private clinics made up 45%. Overseas health care was not a primary choice; nevertheless, it accounted for a substantial amount of total OOP health spending, 22% in 2015 and 7% in 2016.Across the different quintiles, within the category of private clinics, visits to the home/office of a trained health worker/nurse is among the most commonly frequented providers, and 18% of respondents gave this

as their first place for consultation. In 2016, among the lowest three quintiles, around 23% of care-seekers went to trained health workers, while this was only reported by 11% in the highest quintile.

OOP payments per outpatient and inpatient consultation

Table 10 presents OOP payments per outpatient consultation and inpatient day. This information was available from the 2013 CSES onwards and indicates that the

Private hospital

2009 20132010 2014 2015 2016

20

40

60

80

100%

0

Health centre

National hospital

Otherpublic

District hospital

Provincial hospital

Privateclinic

Drugstore Other private Overseas Other

4.3 %18.6 %

8.7 %

4.3 %

35.1 %

9.6 %

8.9 %

7.4 %

4.1 %

5.3 %

4.9 %

13.7 %

42.7 %

12.6 %

4.6 %

8.4 %

4.8 %

9.7 %

8.0 %

3.6 %

15.7 %

39.3 %

9.3 %

4.3 %

3.9 %

17.7 %

7.8 %

8.0 %

28.8 %

7.6 %

22.1 %

15.0 %

4.1 %

10.3 %

44.8 %

13.1 %

7.1 %

12.5 %

6.7 %

7.6 %

8.1 %

34.1 %

8.5 %

5.2 %

11.3 %

0.8 %

0.1 %

1.2 %

2.4 %

Other1.2 %

Health centre

District hospital

Other public

Other private0.8 %

0.0 %

1.3 %

Other 1.8 %

District hospital

Other public

Other private0.5 %

3.2 %District hospital

Other public1.3 %

2.9 %District hospital

3.0 %Health centre

Other public1.8 %

Other public

1.6 %

0.5 %

Other3.2 %

Other public

Other private

results3

a. The share of OOP spending by provider is different than that of the National Health Accounts 2012-2016 because the overseas category was lumped into the private clinic category.

25


Table 10: Out-of-pocket (OOP) cost of outpatient consultation and inpatient day, 2013–2016 (US$)

Table 11: Annual health spending by sex, 2009–2016 (US$)

2013 2014 2015 2016

OOP payment per outpatient visit, average 10 13 16 19

OOP payment per inpatient case, average 151 174 339 177

OOP payment per inpatient case, median 63 50 68 63

OOP payment per inpatient day, average 34 41 64 46

2009 2010 2013 2014 2015 2016

Female 42 46 48 51 50 55

Male 39 42 43 38 37 41

Average 41 44 45 45 44 48

cost of each outpatient visit and inpatient day increased from 2013 to 2016. In 2014, the average OOP payments were US$ 13 for outpatient visit, US$ 41 for inpatient care per day, and US$ 174 per inpatient case (average length of hospital stay

was 5.8 days). In 2016, the median OOP spending per inpatient case was US$ 63, which shows that there was a large variation in spending on inpatient care between individuals.

Spending by illness type

The 2015 and 2016 CSES incorporated additional illness categories, which have given insight on the health-care spending by disease in Cambodia. Annex Table A.11 presents how much was spent on health by disease by assuming that individuals only had one illness in the previous month. Given the small share of respondents to this question, the disaggregated results of these findings may not be representative of the population. However, these preliminary findings show us that OOP spending is much higher

for those individuals who sought care for heart diseases, liver cancer and respiratory diseases.

Health spending by sex

Table 11 illustrates OOP spending on health by sex from 2009 to 2016. Females spent more OOP on health than males in all years. In absolute terms, the spending gap between males and females is widening. In 2009, females spent 1.1 times more than males, while from 2014 onwards women spent 1.3 times more than males.

26

Health spending across age groups

Since 2009, the average OOP spending has increased from US$ 41 to US$ 48; however, across age groups, variations have occurred. OOP spending per capita for those under 5 years and those aged 15–59 years remained relatively stable. However, OOP spending per capita for the age group 5–14 years decreased, and

for those 60 years and above it increased almost fourfold between 2009 and 2016. People aged 60 years and older had the highest average health expenditure compared across all age groups during 2009–2016 (Fig. 6).

The high average OOP spending in this age group could be due to greater frequency of care13 and more costly services.

13 Across all years, the average number of visits was higher for this group.

Fig. 6: Average out-of-pocket expenditure on health by age group, 2009–2016 (US$)

3.5Capacity to pay

Table 12 presents an overview of total household expenditure, capacity to pay (CTP), and OOP spending on health as a share of CTP (Fig. 7). Household CTP is

defined as the remaining income left after subsistence spending. (In this analysis, food expenditure was used as a proxy for subsistence spending.) Household CTP

0

25

50

75

100

125

150

175

200

225

Under 5Average 15 to 595 to 14 60 and above

2009 2010 2013 2015 20162014

results3

27


Fig. 7: Out-of-pocket (OOP) spending as a share of capacity to pay (CTP) by quintile, 2009–2016

significantly increased from US$ 1873 in 2009 to US$ 3169 in 2016, which is consistent with a similar increase in total household expenditure. From 2009 to 2016, OOP on health as a proportion of total household expenditure and CTP decreased from 6.7% to 4.5% and from 12.7% to 7.2%, respectively.

This study looked at OOP payments as a share of CTP to factor in each household’s subsistence spending. For the lower quintiles, on average, subsistence spending makes up more than 50% of their total household spending, which means their CTP is much lower than that of households in the upper quintiles for which subsistence spending makes up less than 25% of their total spending.

OOP spending as a share of CTP is a reflection of the potential burden of health spending on a given household’s disposable income. OOP spending on health as a share of total household expenditure and CTP have decreased since 2009. OOP spending tended to be higher in the highest quintiles, and CTP

also tended to be greater for the highest quintiles. Table 12 shows that OOP/CTP tends to be greater for the upper quintiles.14 The declining ratio of OOP spending as a share of CTP reflects that CTP in Cambodia is growing faster than health-care spending.

14 Details by quintile can be found in Annex Table A.7.

2009 2010 2013 2015 20162014

Q1 Q2 Q3 Q4 Q5 Average

0

3

6

9

12

15%

28

Table 12: Out-of-pocket (OOP) spending per household on health as a share of capacity to pay (CTP), by expenditure quintile, 2009–2016

Table 13: Catastrophic expenditure and impoverishment, 2009–2016 (%)

2009 2010 2013 2014 2015 2016

Average household expenditure (US$) 3 118 3 175 3 820 4 071 4 658 4 875

OOP spending on health as a share of total household expenditure (%)

6.7 6.4 5.1 4.5 4.6 4.5

Household capacity to pay (US$) 1 873 1 939 2 371 2 598 3 004 3 169

OOP spending on health as a share of CTP (%)

12.7 11.7 8.7 7.5 7.7 7.2

2009 2010 2013 2014 2015 2016

Incidence of large household expenditure on health at 40% of non-subsistence spending (capacity to pay)

8.8 7.8 5.8 4.8 5.1 3.7

Incidence of large household expenditure on health at 25% of household total consumption

6.5 6.4 5.3 4.7 4.8 3.9

Incidence of large household expenditure on health at 10% of household total consumption

20.4 19.1 16.3 14.4 13.8 14.9

Incidence of household impoverishment due to health payments

5.7 5.3 2.5 2.1 1.4 1.6

3.6Financial protection indicators, including catastrophic, impoverishing health expendituresand the SDG 3.8.2 indicators, and sources of financing

Table 13 illustrates trends across financial protection indicators, including catastrophic expenditure and impoverishment rates due to OOP spending during 2009–2016. Incidence of household impoverishment has shown a decreasing trend since 2009, and reached 1.6% (300 000 people/50 000

households) in 2016. Incidence of catastrophic expenditure has followed a similar pattern, decreasing from 8.8% (1.1 million persons, 250 000 households) to 3.7% (more than half a million persons, 122 000 households) during the same period.

results3

29


Catastrophic health spending by quintile

Fig. 8 shows the incidence of catastrophic expenditure by expenditure quintile during 2009–2016. Catastrophic expenditure is defined as OOP payments exceeding 40% of a household’s CTP. The incidence of catastrophic expenditure had decreased since 2009 from 8.8% of the total households in Cambodia to 3.7% in 2016. There remains more than half a million persons (122 000 households) experiencing catastrophic expenditure. The tendency in Cambodia is for the incidence of catastrophic spending to be higher for those in the upper quintiles.

However, catastrophic expenditure is a relative measure, and the absolute amount left after health expenditure also matters. This is reflected in the proportion of households that were impoverished due to OOP spending, which is higher for the poorest expenditure quintiles than for the upper quintiles (Fig. 8). Incidence of catastrophic expenditure among the middle quintiles (Q2–Q4) remains high between 4% and 6%. This reflects a burden on this segment of the population that may potentially apply to groups like the near-poor, self-employed or informal sector who are not currently covered by any social protection scheme.

Fig. 8: Incidence of catastrophic household health expenditures by quintile, using 40% capacity to pay indicator, 2009–2016

2009 2010 2013 2015 20162014

Q1 Q2 Q3 Q4 Q5 Average Rural Urban

0

3

6

9

12

15%

30

Fig. 9: Catastrophic health expenditures by quintile using WHO methodologya for selected countries in the Western Pacific Region

a Using 40% as a threshold of capacity to pay.

Sources: WHO Regional Office for the Western Pacific (forthcoming)

Q1 Q2 Q3 Q4 Q5 National

0

1

2

3

4

5

6

7%

Mongolia, 2012

Philippines, 2012

Lao People’s Democratic Republic, 2007/2008

Cambodia, 2016

Viet Nam, 2010

results3

Catastrophic health spending across countries in the Western Pacific Region

Comparisons across countries in Asia – Lao People’s Democratic Republic, Mongolia, Philippines and Viet Nam – show that Cambodia’s incidence of catastrophic health expenditure is higher than that of the other countries. Cambodia’s pattern of catastrophic health expenditure shows higher expenditure in the middle quintiles

with a very high incidence for the highest quintile. This is similar to other countries (Mongolia and Philippines) that show a general increase of expenditures from the lowest to the highest expenditure quintiles. In the Lao People’s Democratic Republic, the catastrophic expenditure rates are highest for the middle quintiles, and in Viet Nam they are concentrated in the lowest quintiles and gradually decrease across the higher quintiles (Fig. 9).

31


Impoverishment due to health payments by quintile

Fig. 10 presents the incidence of household impoverishment due to health payments from 2009 to 2016, across income quintiles. In 2009, impoverishment was less than 2% for the highest expenditure quintile and had reduced to 0.2% by 2016. Following a similar pattern, impoverishment in the third and fourth quintiles decreased significantly since 2009. In comparison, the incidence of

impoverishment in the lowest two quintiles also decreased. However, around 2–4% were still suffering in 2016. In 2010 and 2014, those in the second quintile suffered higher impoverishment rates due to health payments than the lowest quintile, which could reflect gaps in financial protection for those in the middle quintiles, or near-poor population groups. Households in the first and second quintiles were more vulnerable to OOP spending, given the higher rates of impoverishment.

Fig. 10: Impoverishment due to health payments, by quintile and residency

Table 14 shows the catastrophic spending and impoverishment due to health spending for specific population groups Further analysis was carried out on sub-group population selected data in 2014, which involved a larger sample size.

Incidence by population group shows that catastrophic health expenditures and impoverishment due to health payments were significantly higher for household members with disabilities, those above 60 years and those who had a chronic disease.

2009 2010 2013 2015 20162014

Q1 Q2 Q3 Q4 Q5Average Rural Urban

0

2

4

6

8

10%

32

Table 14: Catastrophic expenditures and impoverishment due to health-care payments, percentage of households, 2014 (%)

General population

A household member with a

disability

An elderly household member

A household member who

suffered a chronic disease

Catastrophic expenditure

4.8 7.5 5.3 14.9

Impoverishment due to health-care payments

2.1 3.8 3.2 5.3

Sustainable Development Goal (SDG) indicator 3.8.2 – large expenditures on health as a budget share (5)

Fig. 11 and Fig. 12 highlight the UHC indicators for the SDGs, which are the proportion of the population with large household expenditures on health, using 10% and 25% as thresholds, as a share of total household expenditures. The incidence of catastrophic spending based on the 10% threshold was 11.7% globally and 12.8% in Asia. For Cambodia,

the incidence of catastrophic spending at the 10% threshold was 14.5% in 2016, which is higher than the global incidence of catastrophic spending (9). Based on the 25% threshold, incidence of catastrophic spending was 2.6% globally and 3.1% in Asia. Incidence was lower at the 25% threshold, at 3.8% of the population. Therefore, it is estimated that in 2016, 2.2 million Cambodians incurred OOP payments exceeding 10% of total household spending, and over half a million incurred such payments at the 25% threshold.

results3

Source: Jacobs, de Groot & Fernandes Antunes, 2016

33


Fig. 11: SDG indicator 3.8.2: Incidence of large household expenditure on health at 10% of household total consumption, 2009-2016

Fig. 12: SDG indicator 3.8.2: Incidence of large household expenditure on health at 25% of household total consumption, 2009-2016

2009 2010 2013 2015 20162014


0

5

10

15

20

25%

0

3

6

9

12

15%

2009 2010 2013 2015 20162014


34

Table 15: Source of financing for out-of-pocket spending on health, 2010–2016a (%)

Source of financing 2010 2013 2014 2015 2016

Household income 69 72 69 55 55

Savings 20 22 23 38 39

Borrowing 3 3 3 4 3

Selling assets 2 2 2 0 0

Selling household products in advance

5 2 1 1 1

Other sources 1 1 2 2 3

Source of financing for health spending

Table 15 shows the sources of financing for 2010 and 2013–2016. Most households in Cambodia rely on household income and savings to pay for health care. However,

annually, 3% of households borrow money to pay for health care and fall into debt. Selling assets and household products as a source of financing for health payments has declined and constituted less than 1% in 2016, whereas it was 7% in 2010.

Social health protection

The Cambodia Demographic and Health Survey (CDHS) provides further insight into additional sources of income used to pay for health services. Similarly to the CSES findings, the 2014 CDHS found that most individuals financed their health services from their household income (10).

This section of the OOP expenditure analysis is based on information from the CDHS, which provides detailed information on social health protection, specifically: (1) the households identified as poor through the “Identification of poor households”;15 (2) households with members receiving free or subsidized care that other people would normally have to pay for; (3) the source or

a 2009 CSES did not collect this information.

15 20.7% responded that they have been identified as poor and hold an equity card; 2.4% hold a priority access card.

results3

35


means of the free care including the Health Equity Fund (HEF), community-based health insurance (CBHI), maternity vouchers or another source; (4) at the individual level, women and men aged 15–49 years covered

by any health insurance and type; and (5) for those who sought care in the 30 days prior to the interview, the source of income to pay for transportation and treatment (Table 16).

Table 16: Percentage of households with members receiving free or subsidized care, 2014

Population segment Percentage

Whole population Whole population 16.8

ResidenceUrban 12.5

Rural 17.6

Wealth quintile

Quintile 1 29.1

Quintile 2 20.9

Quintile 3 16.1

Quintile 4 11.0

Quintile 5 6.6

The CDHS provides information on the percentage of households receiving free care (Table 16); findings show that 16.8% of households receive free or subsidized care – 17.6% of rural households and 29.1% of households in the lowest quintile. With regard to the source of the free or subsidized care (Table 17), 14.3% of households received free care through the HEF. The HEF is a government transfer mechanism that subsidizes the poor,

providing them with quality and equitable access to health-care services. According to the findings, 27.1% of households in the lowest quintile and 18.2% of those in the second quintile receive free care from the HEF. These findings show a higher rate of coverage for the targeted groups – such as the rural populations, and the lowest three quintiles than of urban dwellers and the two upper quintiles.

36

Table 17: Percentage of households with members receiving free or subsidized care by source, 2014 (%)

Health Equity Fund

Community-based health

insurance

Maternal health

voucherOther

Total 14.3 1.5 0.1 1.3

ResidenceUrban 8.0 1.3 0.3 3.2

Rural 15.4 1.5 0.1 1.0

Wealthquintile

Quintile 1 27.1 2.0 0.2 0.5

Quintile 2 18.2 1.9 0.1 1.2

Quintile 3 13.5 1.5 0.0 1.7

Quintile 4 8.7 1.2 0.2 1.1

Quintile 5 3.7 0.6 0.1 2.1

In the 2014 CDHS, women and men aged 15–49 years were asked whether they were covered by any health insurance and if so, which type. In 2014, most Cambodians (84% of women and 87% of men) did not have any form of social health protection. However, this was a slight improvement over the 2010 CDHS, when the percentages were 89% and 92%, respectively. This means a segment of the population is benefiting from being covered by some form of health insurance or other government subsidy. In 2016, social health insurance for the private

sector was introduced. Of those insured, 11.8% of women and 8.5% of men were insured through the HEF (Table 18). The share of women covered through the maternal health voucher was 0.5% and 0.9% through CBHI. By comparison, 1.1% of men were covered through CBHI and 2.8% through an employer-based health insurance. Overall findings show that both men and women in rural areas and those in the lower quintiles are more likely to be covered through the HEF than those in urban areas and those in other income quintiles.

results3

37


Table 18: Health insurance coverage – men and women, 2014 (%)

Women

Health Equity Fund

Maternal health

voucherCBHI Employer

basedPrivate

insurance Other None

ResidenceUrban 5.9 0.2 1.0 7.0 0.6 0.0 85.6

Rural 13.1 0.5 0.9 1.5 0.1 0.0 84.1

Wealthquintile

Q1 24.3 0.4 1.7 0.5 0.1 0.1 73.5

Q2 17.8 0.7 0.6 0.6 0 0.0 80.6

Q3 9.8 0.9 0.9 1.3 0.1 0.1 87.3

Q4 6.9 0.2 0.9 2.3 0.2 0.0 89.9

Q5 3.3 0.2 0.7 6.8 0.6 0.0 88.6

Total 11.8 0.5 0.9 2.5 0.2 0.0 84.4

Men

Health Equity Fund

CBHI Employer based

Private insurance Other None

ResidenceUrban 4.7 0.7 10.8 1 0.0 82.8

Rural 9.3 1.2 1.2 0.3 0.0 88.2

Wealthquintile

Q1 17.6 1.1 0.1 0 0.1 81.5

Q2 12.6 1.3 0.5 0.2 0.0 85.4

Q3 7.5 1.2 0.7 0.1 0.0 90.5

Q4 5.2 1.2 2.5 0.6 0.0 90.8

Q5 2.3 0.7 9.1 0.9 0.0 87.2

Total 8.5 1.1 2.8 0.4 0.0 87.3

CBHI: community-based health insurance.

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Table 19: Annual transportation expenditures for accessing health services, 2009–2016

2009 2010 2013 2014 2015* 2016

Transport spending as a share of total health-related spending (%)

11 11 10 12 12 11

Ratio of transport costs to OOP (US$) 0.24 0.20 0.19 0.24 0.37 0.20

Transport spending per household for those spending on transport per year (US$)

76 67 73 90 97 69

Transport spending on inpatient visits as a share of total spending on inpatient visits (%)

NA NA 13 19 24 18

Transport costs per outpatient visit (US$) NA NA 1 1 1 1

Transport costs per inpatient visit (median) (US$) NA NA 3 4 8 5

3.7Transportation expenditures relatedto seeking health services

Table 19 shows average spending on transport to access health services from 2009 to 2016. Transport spending is not considered part of OOP spending for health care and is not considered in the incidence of catastrophic spending. However, transport spending is significant in Cambodia. Since 2009, on average, for every US$ 1 spent on OOP more than US$ 0.20 is spent on health-related transport costs. Annual transport spending, in 2016, for health-related purposes was on average US$ 70 for those households who sought care, and accounted for around 11% of total spending on health-related expenses. The burden of transport spending on a household is highest for those in the lowest quintiles, as 13.4% of total health-related spending was due to transport costs, as compared to 9.4% for the

highest quintile. The transportation expenses per inpatient visit are much higher than the expenses per outpatient visit. Access to outpatient care may be easier and closer to the vicinity of the households, for instance pharmacies. Inpatient care, however, can only be provided at higher levels, such as the hospital level, which may require travelling longer distances. Spending on transport for outpatient visits as a share of total spending (including OOP spending) was around 10%, and for inpatient visits, it was 18% in 2016.Fig. 13 shows transportation spending as a share of total spending for an inpatient visit. The expenditure on transport per visit tends to increase with quintiles (Annex Table A.10). However, the relative burden of transport spending as a share of total spending for each visit has been higher

* On average households who sought care overseas spent US$1,401 on transport, and two of these households spent over US$400 on transport for one inpatient visit.

results3

39


for the lower quintiles since 2014. In 2016, the poorest quintile spent 47% on transport relative to total spending on an inpatient visit, in addition to the payment at the facility.

In 2014–2016, less than 1% of the population made payments for transportation overseas. The 1% of households that sought care overseas were from the upper quintiles. The households in the upper quintile spent on average one third more on transport than an average household in a given month.

Fig. 13: Transport spending on inpatient visits as a share of total spending on inpatient visits by quintile, 2009–2016a

a Total spending = the sum of total transport spending for health and total out-of-pocket expenses for health.

0

10

20

40

30

50

60%

Q1 Q2 Q3 Q4 Q5

2013 2015 20162014

3.8Characteristics of households with a financial burden

When comparing households that experienced catastrophic expenditure and impoverishment, households across all quintiles are mainly in rural areas and a small share of households live in other urban

areas (Table 22). Households in Phnom Penh did not suffer impoverishment due to health payments in any quintile, which can be attributed to the low percentage of the poorest population living in Phnom Penh.

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The poorer households suffering catastrophic expenditure had an average of 2.8 people per household, which is lower than the average for that quintile – 3.2 household members. Of the households which experienced impoverishment, those in the richest quintile had on average

8.1 members and the poorest only 3.7 members. Households that experience impoverishment tend to have more family members than the average for household members in their respective quintile, and this becomes more apparent in the richest quintile (Table 23).

Table 22: Characteristics of households with a financial burden due to health payments, 2014 (%)

Table 23: Household size by quintile for those households with a financial burden due to health payments, 2014

All households (with and without financial burden)

Households with catastrophic expenditure

Households that experienced impoverishment

Phnom Penh

Other urban

RuralPhnom Penh

Other urban

RuralPhnom Penh

Other urban

Rural

Quintile 1 1.9 6.3 91.8 0.0 3.3 96.7 0.0 1.0 99.0

Quintile 2 3.0 7.9 89.0 0.0 7.9 92.1 0.0 1.0 99.0

Quintile 3 7.2 9.4 83.3 0.9 5.4 93.7 0.0 2.1 97.9

Quintile 4 12.7 14.0 73.3 0.8 4.2 95.0 0.0 4.6 95.4

Quintile 5 31.7 18.5 49.8 6.5 7.6 85.9 0.0 12.7 87.3

Total 11.3 11.2 77.5 2.5 5.9 91.6 0.0 2.5 97.5

2014All households

Households with catastrophic expenditure

Households experience impoverishment

Household size Household size Household size

Quintile 1 3.2 2.8 3.7

Quintile 2 4.2 3.6 5.1

Quintile 3 4.6 4.3 6.7

Quintile 4 5.0 4.6 7.2

Quintile 5 5.3 5.6 8.1

Total 4.5 4.5 5.6

results3

41


Among households that spend catastrophic amounts on health, within each respective quintile, the household composition by age group changes and there is a higher number of children under 5 years and members aged 60 years and above. For households that are impoverished, a similar trend is observed across all quintiles, where there is a higher number of members aged under 5 years. For example, of those in the poorest quintile falling into poverty from health spending, 20% of the household members are aged under 5 years in comparison to the average poor households where members aged under 5 years make up 13.6%. This trend is similar across all wealth quintiles. For households that are impoverished due to health spending, the share of household members aged 60 years and above is generally less than the average of households within their respective quintile, with the exception of quintile 4.

This, however, is the contrary for households that experience catastrophic expenditure. The share of household members aged 60 years and above is higher for households with catastrophic expenditure in comparison to the average household across each respective quintile. In the poorest households with catastrophic expenditures, 18.2% of their household members are 60 years and above versus 11.8% in this age group in the average poor household. The share of individuals with chronic diseases is higher in households suffering catastrophic expenditures and impoverishment due to health payments (Table 24): 8.6% of households with high expenditures on health have members with chronic illness. This finding is consistent with the determinants analysis demonstrating that catastrophic spending and impoverishment increase when households have members with chronic diseases.

Table 24: Chronic disease prevalence, 2014 (%)

All individuals

Individuals in households suffering

from catastrophic expenditure

Individuals in households suffering from impoverishment

due to health payments

Quintile 1 2.8 10.4 6.3

Quintile 2 1.8 7.4 3.3

Quintile 3 2.3 9.7 6.1

Quintile 4 3.0 9.3 6.5

Quintile 5 3.3 7.7 6.0

2.7 8.6 5.2

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DiscussionOOP expenditure on health remains high in Cambodia. It accounts for 60% of total health expenditure and US$ 48 per capita according to the NHA study (2). As Cambodia is in transition in the development of its social health protection system and its progress towards UHC, it is important to routinely monitor health service utilization and the financial burden of health payments, with a focus on their equity, to assess the performance of social health protection schemes and effects of changes in health policy. Together with the NHA study and the Annual Health Financing Report by the Ministry of Health, the findings should feed into national policy and planning processes.

4

44

discussion4

Illness and health-care utilization

Health-seeking behaviour when ill is high across all quintiles, and residents living in rural areas tend to seek care more frequently than urban dwellers. The burden of chronic disease rose from 2.9% to 3.7% from 2009 to 2016. This, however, does not take into account the undiagnosed cases of chronic disease and only includes individuals who have had a diagnosed disease for more than a year. Noncommunicable disease services at primary health care facilities are still limited. These services are currently accessed at hospitals. As screening services at health centres are scaled up, more cases of chronic disease may be diagnosed. Health services have been provided predominantly by the private sector since 2009. The preference for those who fall ill is to access care from the private sector for the first and last visits, particularly at private clinics and pharmacies or drugstores. From 2009 to 2013, the preferred providers included shops selling drugs from the non-medical sector; however, there was a shift towards seeking more care from private providers in recent years. There are differences across quintiles: at the health centre level care is mainly sought by those in the lowest quintiles, whereas the majority of those who sought care at private hospitals were from the upper quintile.

Proximity was one possible reason for Cambodians’ preference for private providers (11), and a more recent study

in 2014 found that Cambodian patients tended to view public facilities as being too far away and as having long waiting times (12). Ozawa and Walker identified trust as a key factor in deciding which provider to select (11). Furthermore, the findings from their study show that the lack of services at night and during weekends at health centres was a barrier to access, in contrast to the availability of 24-hour care at private facilities. Perception of what constitutes effective care can influence choice. There is an observed bias towards certain interventions (e.g. IV drips), which may impact the decision on where to seek care.

According to Cambodia’s rural health markets and quality of care, only 54% of private providers had formal training, which gives cause for concern given the Cambodian health-seeking behaviour, which favours private providers (13). However, in 2017, the Government and medical councils made efforts to register all health-care professionals, including those in the private sector. Ozawa and Walker, furthermore, showed that the public health providers were respected for their medical skills, and utilization of public providers increased with the availability of health insurance and a fee exemption card (11). This is in line with earlier findings that one of the most common providers for the lowest quintiles, who have increased access through social health protection, was health centres. Rapid economic growth and expansion of social protection

45


schemes have possibly contributed to the increase in health service utilization across all quintiles.

Financial protection

Health-care spending (OOP)

OOP expenditure on health remains high in Cambodia and accounts for 60% of total health expenditure. High OOP spending can be linked to the high costs of care, specifically from user fees and high medication costs at both private and public health facilities, increasing access to care and/or rapid economic growth allowing for greater CTP for health care. The analysis of OOP spending by expenditure quintiles shows that the higher quintiles are spending more on health. Those in the highest quintiles have shown an upward spending trend since 2009. While health service utilization is generally high for those who report illness, there may be a small percentage of the population that forgoes care due to the expected OOP expenditures on health and transportation-related expenditures, information which is not captured in the household survey.

The health expenditure gap between rural and urban residents has widened over time. In 2016, rural residents spent 1.5 times more than urban dwellers. This trend is possibly attributable to a greater prevalence of poor health status and more limited access to preventive services, which may then lead to the need for more

costly interventions. Rural households also tend to seek care more frequently: in 2016, 15.8% of rural residents sought care in comparison to 13.3% from urban households, which can contribute to the higher spending by the former group.

The study findings show the importance of private providers in the provision of health care and the rising costs of health care in Cambodia. Private health-care providers remain the first choice for the majority of the population. Since 2010, private providers have accounted for the (increasing) majority of OOP spending on health, reflecting the increasing importance of the private sector as a source of health care, which is problematic in a health system where there is limited enforcement or regulation of private providers.

OOP expenditure at overseas providers account for a larger-than-desired amount of OOP spending. The costs of overseas medical treatment are generally higher than those of other providers, but they affect only a small percentage of households, mostly households belonging to the upper income quintiles. Cambodians are choosing to go abroad to seek care, which can have some unintended impacts on the domestic health system. Challenges can arise in the long term if this trend continues to grow. A two-tier system of health care could be created, in which affluent patients can choose to go abroad for care, decreasing the incentive to invest in the public system and to potentially

46

push for improved investments (14). However, there may be some unintended consequences, such as the local private sector providers feeling more pressure to improve and keep their services financially competitive. However, understanding the impact of overseas care on the public sector is still in its early stages.

People aged 60 years and above are, on average, the highest spending age group and incurred 30% of total OOP spending while making up only 8.2% of the population (7). This share is likely to increase over time as the population ages (the share of older people is projected to increase to just above 20% by 2050), and the prevalence of noncommunicable diseases is rising concurrently (15). Among this age group in 2014, 45% experienced some form of disability and there is a greater need for specialized health care (10). Having an elderly member in a household significantly increases the odds of incurring catastrophic health payments. The recent publication Health care utilization of persons with disabilities in Cambodia also provides an in-depth analysis of the vulnerability of older people. Health systems, therefore, need to be geared to address their needs and avoid causing financial hardship to this population group when accessing care. The relevant policies should also include provisions on coordination across health and other social sectors and financing of long-term

care. The National Social Protection Policy Framework 2016-2025 discusses the need to cover vulnerable groups such as people with disabilities, children under 5 years old and older people, which may reduce the burden of OOP spending and improve the livelihoods for these groups in the near future.

On average, since 2009, women have spent more on health than men. This could be attributed to the finding that on average women sought care more often than men16 as well as to the fact that women seek care for reasons other than illness and injury including antenatal care, delivery, postnatal care and health checks, which could contribute to higher spending by women, and cause them to incur higher spending on health. According to the Cambodian NHA, by source of funds for reproductive, maternal and child health, 48% comes from OOP spending (US$ 47.2 million) (2). However, findings from the CDHS (10), may show that even if the utilization rates are relatively high for women, their needs are not being met, as they are still facing numerous problems in accessing care. It found that 64% of women are concerned with finding money for treatment, 45% report not wanting to go alone, and 35% were concerned about the distance. This suggests that some women could have forgone care due to high transport costs and user fees.

16 On average, in 2014 and 2015, women sought care more often than men.

discussion4

47


Sources of financing

The findings for 2009 showed that poor and near-poor households tended to take out more loans and borrow more from informal lenders, with high interest rates due to low income levels and higher numbers of loans (17). Unproductive loans for food and medical expenses increase the vulnerability of the poor and near-poor to becoming trapped in the vicious cycle of poverty. Rural households fall more often in debt than urban households although borrowing is greater in urban areas.

Capacity to pay

A household’s CTP is defined by separating those essential and non-essential household expenditures. Essential household expenditures could include expenditures on food, rent, housing and other basic necessities, which will vary according to the country context and excludes spending on restaurants, tobacco or alcohol, and other non-essential items. CTP is defined as the household spending that is non-essential. For the purposes of this analysis, a household’s essential expenditures are equal to a household’s spending on food, and the leftover amount is a household’s “capacity to pay”. This is used as a “proxy” or alternate measure to the disposable income of a household to

pay for health care. In Cambodia, gross domestic product per capita is increasing at a rapid rate, which has translated to an increase in CTP, which means Cambodians have more available income to cover any unexpected economic shocks or spending of an unpredictable nature, such as a hospitalization or sudden unemployment. An increase in household CTP has possibly contributed to an increase in access to health services, as it is removing the financial barrier while increasing household’s CTP spending. However, even with growing CTP, OOP expenditure is also increasing at a rapid rate, which shows the need for more social health protection coverage, especially for the poorer quintiles.

As Cambodia moves towards the development of prepayment mechanisms to pay for health services, information on CTP and defining a CTP indicator based on the Cambodia context, including the CTP across quintiles, may be useful to understand how contributions are determined and to acquire a clearer understanding of potential options for collection of prepayments for health. Prepayment and risk pooling are fundamental to building a stronger financial safety net to prevent catastrophic and impoverishing health payments and ultimately to progress towards UHC (18).

48

Transportation expenditures related to seeking health care

Transport costs remain a barrier to access to health services and the burden of these costs on households is increasing, especially in the lowest quintiles. The financial burden is especially high for those households seeking inpatient care and care overseas. High expenditures on transport may deter households to seek care and could increase the tendency of Cambodians to seek care at local private pharmacies or drugstores especially in more remote areas. Due to the potential burden on those seeking care, social health protection schemes such as the HEF cover transportation expenses incurred by the patient.

Social health protection schemes

The analysis of the social protection scheme is based on the 2014 CDHS report (10), which showed that the share of households receiving free or subsidized care through the HEF was 14.3%. Since 2010, the percentage of the population covered by health insurance had increased, including the HEF, CBHI and voucher coverage. However, the percentage of the population without coverage remained above 80% (men 87.3% and women 84.4%). These findings also show that there are households receiving subsidized care that are still incurring high OOP payments.Cambodia has made significant progress in reducing catastrophic spending and

17 The IDPoor programme was established in 2006 within the Ministry of Planning. The IDPoor cards are issued to identified poor households in Cambodia to provide access to various social assistance services by the Government.

discussion4

49


impoverishment as well as in expanding coverage, but there are still persistent barriers to access. Physical barriers like access to IDPoor cards17 and distance to be travelled to access health facilities may discourage use and hence encourage the use of local vendors such as drugstores. Waiving fees for services may not be sufficient to increase utilization of public health-care services. The HEF provides transport subsidies and food subsidies for family members of ill patients. Increased safeguards, such as additional subsidies, may encourage earlier care-seeking behaviour. Education and awareness of benefits and mechanisms among providers, health staff and patients covered by social protection schemes may impact utilization patterns and usage of such schemes. Additionally, the HEF accounts only for 1% of total health expenditure, which means that expenditure outside the HEF scheme is still significant, 60% of total health spending continues to come from OOP payments.

Social health insurance for the private sector is planned to cover 1.2 million people. Registration of members and collection of premiums from companies is ongoing. As members and providers become better informed about the benefits, and how the reimbursement system works, this may change and have an impact on OOP spending. The recently introduced civil servant scheme and select informal workers, and the scheme for the private sector are growing, but are still in their infancy.

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LimitationsSeveral important limitations need to be considered when drawing conclusions from the results presented in this report. Firstly, the health service utilization variable only includes utilization for an injury or illness, and not for other reasons to seek health care. Forgone utilization due to potential financial barriers to access services is not captured in the household survey data.

5

52

limitations5

Secondly, the CSES collects information on expenditure and consumption on an annual basis. The large sample-size surveys are conducted every five years: 2004, 2009 and 2014 covering more than 10 000 households and 70 000 individuals. By comparison, in 2010, 2013, 2015 and 2016, the sample sizes for households were around 3500 and 16 000 individuals. Disaggregation in the years with a smaller sample size may not be representative of the population. Therefore, for the section on the determinants, the 2014 CSES was used.

Regarding the survey design limitations, information is collected on only one type of illness, discounting the reporting of co-morbidities. The assumption is that individuals only have one illness per month, which may not be true for all individuals. In terms of the provider, information is collected only on the first and last provider visited, which can be considered a fair assumption because most individuals sought care less than two times per month. However, when estimating how much was spent per provider it was assumed that individuals spent an equal amount at each provider if they visited more than one, which may not be the case.

This survey also included a question on households obtaining free care and how they obtained this care. This is important because the Cambodian Government has now expanded coverage: in addition to the 3 million poor, some of the non-formal workers (around 2.5 million) will be eligible through the HEF, and the details of this scheme are under discussion. However, the response rate to this question in the survey was quite low. On average, around 6–7% of the sample responded to this question. Therefore, we have based the findings on the 2014 CDHS report (10), which attained coverage of 14.3%. However, given that it is a health survey, there is a tendency to overreporting of events and expenditure (6), and this bias should be taken into account. A combination of challenges could explain the lack of access to free care: the first is the understanding that the IDPoor cards are generally only issued every three years, but there will be a new on-site identification of the poor. This means that any person who does not have an IDPoor card but may be eligible can be assessed at the health facility and if qualified can access subsidized health-care services.

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In terms of the limitations of the methodology used to produce this report, the CTP definition can refer to the portion of the household budget that remains following subsistence spending (4).However, the CTP may be overestimated because households have other basic needs aside from food expenditure. Other subsistence spending such as on housing, transportation and clothes, if deemed significant in the Cambodian context, could be incorporated to avoid overestimating households’ CTP.Following on from this report, there is an opportunity to further analyse some of the results from this survey. It would be useful to do the quintile analysis based on per capita expenditure excluding OOP

payments, because OOP payments may place households in the upper quintiles, due to their high expenditures on health, and this may be misleading. Furthermore, additional analyses on the high-spending households and whether these high expenditures are tied to a certain illness or due to other factors would be useful. Regarding transportation spending, it would be informative to examine more closely the link to specific health facilities given that some households spend more on transport than on health services. More analysis on illness type, and spending drivers linked to noncommunicable diseases over time would also be useful.

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1. Xu, K. (2003) Household catastrophic health expenditure: a multicountry analysis. Lancet. [Online] 362. Available from: doi:10.1016/S0140-6736(03)13861-5.

2. World Health Organization Regional Office for the Western Pacific (2018) Cambodia national health accounts, 2012-2016: health expenditure report.

3. Royal Government of Cambodia (2017) National Social Protection Framework 2016–2025. [Online]. Available from: http://www.rcrcresilience-southeastasia.org/wp-content/uploads/2018/01/2017-National-Social-Protection-Policy-Framework-2016-2025-NSPPF.pdf.

4. Xu, K. (2005) Distribution of health payments and catastrophic expenditures: Methodology. [Online]. Available from: http://apps.who.int/iris/handle/10665/69030 [Accessed: 12 September 2018].

5. World Health Organization & International Bank for Reconstruction and Development / The World Bank (2017) Tracking universal health coverage: 2017 global monitoring report. [Online]. Available from: http://apps.who.int/iris/bitstream/10665/259817/1/9789241513555-eng.pdf.

6. World Health Organization (2010) Estimating out-of-pocket spending for national health accounts. [Online]. Available from: www.who.int/health-accounts/documentation/estimating_OOPs_ravi_final.pdf.

7. Royal Government of Cambodia (2013) Poverty in Cambodia - A New Approach: Redefining the Poverty Line. [Online]. Available from: http://www.mop.gov.kh/DocumentKH/New%20Poverty%20Line-FINAL%20APR%202013.pdf.

8. Zimmer, Z. & Van Natta, M. (2015) Migration and left-behind households in rural areas in Cambodia: structure and socioeconomic conditions. [Online]. Available from: https://cambodia.unfpa.org/sites/default/files/pub-pdf/MigrationandLeftBehindHouseholds-Final.pdf [Accessed: 19 October 2018].

9. Wagstaff, A., Flores, G., Hsu, J., Smitz, M.-F., et al. (2017) Progress on catastrophic health spending in 133 countries: a retrospective observational study. The Lancet Global Health. [Online] Available from: doi:10.1016/S2214-109X(17)30429-1 [Accessed: 23 December 2017].

10. Statistics/Cambodia, N.I. of, Health/Cambodia, D.G. for & International, I.C.F. (2015) Cambodia Demographic and Health Survey 2014. [Online] Available from: https://dhsprogram.com/publications/publication-FR312-DHS-Final-Reports.cfm [Accessed: 13 September 2018].

11. Ozawa, S. & Walker, D.G. (2011) Comparison of trust in public vs private health care providers in rural Cambodia. Health Policy and Planning. [Online] 26 (suppl_1), i20–i29. Available from: doi:10.1093/heapol/czr045.

12. Liverani, M., Nguon, C., Sok, R., Kim, D., et al. (2017) Improving access to health care amongst vulnerable populations: a qualitative study of village malaria workers in Kampot, Cambodia. BMC Health Services Research. [Online] 17. Available from: doi:10.1186/s12913-017-2282-4 [Accessed: 14 November 2018].

REFERENCES AND DATA SOURCES

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13. Sanjoaquin, M. (2014) Cambodia’s rural health markets and the quality of care. [Online]. pp.1–4. Available from: http://documents.worldbank.org/curated/en/514181468213569828/Cambodias-rural-health-markets-and-the-quality-of-care [Accessed: 13 September 2018].

14. Lunt, N., Smith, R., Exworthy, M., Horsfall, D., et al. (n.d.) Medical Tourism: Treatments, Markets and Health System Implications: A scoping review. [Online]. p.55. Available from: https://www.oecd.org/els/health-systems/48723982.pdf.

15. Zimmer, Z. & Khim, F. (2013) Ageing and Migration in Cambodia. [Online]. Available from: http://www.mop.gov.kh/DocumentKH/Ageing%20&%20Migration%20in-Cambodia.pdf [Accessed: 19 October 2018].

16. World Health Organization Regional Office for the Western Pacific (2017) Health care utilization of persons with disabilities in Cambodia. [Online]. Available from: http://iris.wpro.who.int/bitstream/handle/10665.1/13694/9789290618263-eng.pdf [Accessed: 19 October 2018].

17. Asian Development Bank (2014) Cambodia: Country Poverty Analysis 2014. [Online]. p.57. Available from: https://www.adb.org/sites/default/files/institutional-document/151706/cambodia-country-poverty-analysis-2014.pdf.

18. World Health Organization (ed.) (2010) Health systems financing: the path to universal coverage. The World Health Report 2010. Geneva.

DATA SOURCES AND REFERENCE DOCUMENTS FOR THE PRODUCTION OF NHA DATA

• Jacobs, Bart, Richard de Groot, and Adélio Fernandes Antunes. “Financial Access to Health Care for Older People in Cambodia: 10-Year Trends (2004-14) and Determinants of Catastrophic Health Expenses.” International Journal for Equity in Health 15 (June 17, 2016). https://doi.org/10.1186/s12939-016-0383-z.

• National Institute of Statistics. Cambodia Socioeconomic Survey (CSES). Years 2009 to 2016. Available from: http://www.nis.gov.kh/index.php/en/national-statistical-systems/official-statistics-of-cambodia/14-cses

• Royal Government of Cambodia (2013) Poverty in Cambodia - A New Approach: Redefining the Poverty Line. [Online]. Available from: http://www.mop.gov.kh/DocumentKH/New%20Poverty%20Line-FINAL%20APR%202013.pdf.

• WHO Regional Office for the Western Pacific (Forthcoming). Access to care and the financial burden of health payments for selected countries in the Western Pacific.

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Annex

6

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1

CSES 2004 CSES 2007 CSES 2009 CSES 2010 CSES 2011

Interview periodOct 2003 to Dec 2004

Jan 2007 to Dec 2007




Sample size

Households 15 000 3 593 11 971 3 592 3 592

Individuals 74 719 17 439 57 105 16 510 16 327

Recall period

Foods, beverages, tobacco 7 days 7 days 7 days 7 days 7 days

Health-care utilization and expenditure (health module)

4 weeks 4 weeks 30 days 30 days 30 days

Health expenditure (in general expenditure module)

Last 1 month

Last 1 month

Last 1 month

Last 1 month

Last 1 month


1 month 1 month 1 month 1 month 1 month

Clothes and footwear 6 months 6 months 6 months 6 months 6 months

Furniture and other expenses 12 months 12 months 12 months 12 months 12 months

Free/subsidized treatment 12 months 12 months 12 months 12 months 12 months

Illness Yes Yes Yes Yes Yes

Type of illness 41 cat 41 cat 5 cat 5 cat 5 cat

Type of provider First and

lastFirst and

lastFirst and

last

Hospitalized? Yes Yes N/A NA Yes

Days hospitalized NA NA NA NA Yes

Health-care expenditures Yes Yes Yes YesIncludes overseas spending

Health-related transport expenses

NA NA Yes Yes Yes

Insurance? NA NA Yes Yes Yes

Provider disaggregation 14 cat 14 cat 18 cat 18 cat 18 cat

Table A.1: Summary table of sample sizes and recall periods for Cambodia Socioeconomic Surveys (CSES), 2004, 2007 and 2009–2016

annex6

cat: categories; NA: not available.

Additional data

59


CSES 2012 CSES 2013 CSES 2014 CSES 2015 CSES 2016

Interview periodJan 2012 to Dec 2012



Sample size

Households 3 840 3 840 12 090 3 839 3 839

Individuals 17 644 17 225 53 968 17 301 17 058

Recall period

Foods, beverages, tobacco 7 days 7 days 7 days 7 days 7 days

Health-care utilization and expenditure (health module)

30 days 30 days 30 days 30 days 30 days

Health expenditure (in general expenditure module)

Last 1 month

Last 1 month

Last 1 month

Last 1 month

Last 1 month


1 month 1 month 1 month 1 month 1 month

Clothes and footwear 6 months 6 months 6 months 6 months 6 months

Furniture and other expenses 12 months 12 months 12 months 12 months 12 months

Free/subsidized treatment 12 months 12 months 12 months 12 months 12 months

Illness Yes Yes Yes Yes Yes

Type of illness 5 cat 5 cat 5 cat 19 cat 19 cat

Type of providerFirst and

lastFirst and

lastFirst and

lastFirst and

lastFirst and

last

Hospitalized? Yes Yes Yes Yes Yes

Days hospitalized Yes Yes Yes Yes Yes

Health-care expendituresIncludes overseas spending

Includes overseas spending




Health-related transport expenses

Yes Yes Yes Yes Yes

Insurance? Yes Yes Yes Yes Yes

Provider disaggregation 18 cat 18 cat

19 cat (incorporated overseas as a

provider)

19 cat 19 cat

Table A.1(continued)

60

2009 2010 2011 2012 2013 2014 2015 2016

Mean no. of times care was sought (conditionalon seeking care)

2.4 1.9 1.8 2 1.9 1.8 1.7 1.7

Proportion who sought care less than two times in one month (%)

67 79 81 75 77 84 84 83

Table A.2: Number of times care was sought including the distribution and average, 2015

1 annex6

00 2 4 6 8 10 12 14 16 18 20 22 24 26

5

10

15

20

25

30

35

40

45

50

55

60%

(sum

) see

knum

Number of times care was sought for illness/injury, last 30 days

0

5

10

15

20

25

Note: On average Cambodians seek care less than 2 times in a given year. A few people seek care up to 15 times, but this is rare.

61


Table A.3: Provider consulted for first and last treatment of the episode

2009 2010 2013 2014 2015

Provider First Last First Last First Last First Last First Last

National hospital 2.6% 2.6% 1.4% 2.2% 2.1% 1.9% 2.6% 2.7% 3.1% 2.3%

Provincial hospital 2.3% 2.2% 1.7% 1.8% 2.4% 1.4% 3.1% 2.7% 3.0% 2.7%

District hospital 2.9% 2.8% 2.6% 1.8% 2.2% 1.8% 3.0% 2.9% 4.2% 2.6%

Health centre 10.8% 9.2% 9.7% 7.5% 8.9% 6.5% 14.0% 8.6% 10.8% 9.5%

Health post 0.5% 0.2% 0.2% 0.1% 0.0% 0.0% 0.3% 0.4% - -

Provincial rehabilitation centre

0.1% 0.1% 0.1% - - 0.1% 0.1% 0.0% 0.1%

Other public provider 0.8% 1.0% 1.3% 1.3% 0.1% 0.1% 0.4% 0.3% 0.1% 0.1%

Private hospital 2.7% 2.6% 2.2% 2.4% 2.6% 2.6% 4.5% 4.9% 4.5% 3.6%

Private clinic 12.8% 14.6% 9.9% 9.5% 16.9% 16.9% 17.5% 17.9% 20.3% 21.0%

Private pharmacy 18.8% 19.6% 20.5% 22.0% 24.8% 24.8% 23.0% 23.3% 26.3% 30.0%

Home/office of trained nurse 13.4% 12.9% 11.6% 10.5% 14.7% 14.7% 15.9% 17.9% 18.2% 16.8%

62

2009 2010 2013 2014 2015

Visit by trained health worker/nurse

0.2% 0.3% 0.1% 0.1% 0.4% 0.4% 0.2% 0.3% 0.6% 0.7%

Other private medical

6.4% 5.0% 8.7% 7.9% 6.6% 6.6% 1.9% 2.0% 1.0% 0.9%

Shop selling drugs/market

22.1% 21.5% 27.7% 29.5% 20.0% 20.0% 12.4% 14.6% 6.0% 6.8%

Magician 1.6% 2.5% 1.5% 2.4% 1.4% 1.4% 0.5% 0.7% 1.0% 2.0%

Monk/religious leader

0.5% 0.3% 0.2% 0.3% – – – 0.1% 0.1% –

Traditional birth attendant

0.0% 0.1% – 0.0% – – – 0.0% –

Other 1.5% 2.7% 0.7% 0.6% 0.8% – 0.2% 0.4% – –

Overseas – – – – – – 0.4% 0.3% 0.7% 0.9%

1 annex6

Table A.3 (continued)

63


Table A.4: Provider consulted for first treatment of the episode by residence, 2016

Provider Rural Urban

National hospital 2.6% 5.8%

Provincial hospital 2.9% 3.3%

District hospital 4.4% 2.8%

Health centre 11.8% 5.1%

Provincial rehabilitation centre 0.0% –

Other public provider 0.1% 0.1%

Public 21.9% 17.1%

Private hospital 4.3% 5.6%

Private clinic 19.1% 27.4%

Private pharmacy 23.7% 40.4%

Home/office of trained nurse 20.4% 5.8%

Visit by trained health worker/nurse 0.7% 0.2%

Other private medical 1.2% 0.1%

Private 69.5% 79.5%

Shop selling drugs/market 6.8% 1.7%

Magician 1.1% 0.5%

Monk/religious leader 0.1% –

Traditional birth attendant 0.0% –

Other 0.0% –

Non-medical 8.0% 2.3%

Overseas 0.7% 1.1%

64

Provider Quintile 1 Quintile 2 Quintile 3 Quintile 4 Quintile 5

National hospital 1.3% 1.4% 2.7% 4.1% 5.9%

Provincial hospital 3.3% 2.6% 1.2% 3.1% 4.9%

District hospital 3.8% 4.2% 4.9% 4.2% 3.8%

Health centre 15.5% 14.6% 10.2% 8.0% 6.2%

Provincial rehabilitation centre – – – 0.2% –

Other public provider – 0.1% – 0.1% 0.1%

Public 23.9% 22.9% 19.0% 19.7% 20.8%

Private hospital 3.6% 3.2% 4.4% 3.4% 8.2%

Private clinic 9.7% 12.9% 19.9% 26.8% 30.7%

Private pharmacy 27.1% 28.9% 26.2% 27.2% 22.0%

Home/office of trained nurse 23.2% 18.5% 21.4% 16.5% 11.7%

Visit by trained health worker/nurse 0.4% 1.3% 0.2% 0.8% 0.4%

Other private medical 1.2% 2.5% 0.9% 0.4% 0.3%

Private 65.2% 67.4% 72.9% 75.1% 73.3%

Shop selling drugs/market 10.2% 7.2% 6.9% 3.5% 2.9%

Magician 0.5% 2.0% 1.2% 1.0% 0.1%

Monk/religious leader 0.3% – – 0.3% –

Traditional birth attendant – 0.1% – – –

Other – – – 0.1% –

Non-medical 10.9% 9.3% 8.1% 4.9% 3.0%

Overseas – 0.4% – 0.3% 3.0%

Table A.5: Provider consulted for first and last treatment of the episode by quintile, 2016

1 annex6

65


Table A.6: Average household expenditure in US$, 2009–2016

Table A.7: Out-of-pocket spending on health as a share of CTP, by quintile

2009 2010 2013 2014 2015 2016

Annual 3118 3175 3820 4071 4658 4875

Quintile 1 1172 1252 1714 1728 1973 2086

Quintile 2 1803 1858 2507 2564 2902 3116

Quintile 3 2406 2383 3159 3317 3734 4062

Quintile 4 3312 3211 4079 4434 4979 5348

Quintile 5 6899 7179 7645 8313 9713 9768

Rural 2592 2552 3224 3539 4077 4394

Urban 5520 5854 6090 6027 6790 6705

Indicator 2009 2010 2013 2014 2015 2016

Average 12.7% 11.7% 8.7% 7.5% 7.7% 7.2%

Quintile 1 10.8% 8.7% 7.2% 5.6% 6.2% 5.8%

Quintile 2 12.3% 11.6% 8.0% 6.8% 8.5% 6.2%

Quintile 3 13.7% 11.4% 8.0% 7.2% 7.4% 7.8%

Quintile 4 13.9% 13.2% 9.8% 8.7% 7.7% 7.7%

Quintile 5 12.7% 13.4% 10.4% 9.0% 8.6% 8.6%

66

Table A.9: Incidence of impoverishing health expenditure by wealth quintile and by residence using the national poverty line, 2009–2016

Table A.8: Incidence of catastrophic expenditure by wealth quintile using WHO methodology, 2009–2016

Year 2009 2010 2013 2014 2015 2016

Average 8.8% 7.8% 5.8% 4.8% 5.1% 3.7%

Wealth quintile

Quintile 1 5.8% 4.0% 3.7% 3.6% 2.7% 2.1%

Quintile 2 7.4% 5.3% 3.8% 4.0% 5.7% 2.9%

Quintile 3 9.9% 7.1% 4.2% 4.0% 4.4% 3.8%

Quintile 4 10.7% 9.7% 7.6% 5.1% 4.7% 3.0%

Quintile 5 10.4% 12.7% 9.6% 7.0% 8.0% 6.9%

ResidenceRural 10.2% 8.9% 6.7% 5.5% 6.1% 4.2%

Urban 2.7% 2.7% 2.2% 1.8% 1.4% 1.8%

Year 2009 2010 2013 2014 2015 2016

Average 5.7% 5.3% 2.5% 2.1% 1.4% 1.6%

Wealth quintile

Quintile 1 9.4% 7.9% 4.6% 2.7% 3.0% 3.8%

Quintile 2 8.1% 8.6% 3.8% 4.3% 2.2% 2.8%

Quintile 3 7.9% 7.4% 2.6% 1.9% 1.8% 1.3%

Quintile 4 4.2% 4.6% 1.5% 1.4% 0.3% 0.4%

Quintile 5 1.7% 0.3% 0.5% 0.6% 0.1% 0.2%

ResidenceRural 6.9% 6.4% 3.1% 2.6% 1.7% 2.0%

Urban 1.1% 1.4% 0.3% 0.2% 0.3% 0.3%

1 annex6

67


Table A.10: Spending on transport for inpatient and outpatient visits by quintile, 2013–2016 (US$)

Spending on transport per outpatient visit, 2013 to 2016

Year Quintile 1 Quintile 2 Quintile 3 Quintile 4 Quintile 5

2013 0 1 1 1 1

2014 1 1 1 2 3

2015 1 1 1 1 2

2016 1 1 1 1 3

Spending on transport per inpatient visit, 2013 to 2016 (US$)

Year Quintile 1 Quintile 2 Quintile 3 Quintile 4 Quintile 5

2013 2 5 3 7 16

2014 6 5 5 8 28

2015 3 6 9 7 67

2016 7 12 6 4 15

Table A.11: Spending on health per person who sought care by illness type per month, 2015 and 2016 (US$)

Lung cancer

Liver cancer

Heart diseases

Cervical cancer

TB

Other diseases

Diabetes

Meningitis

Typhoid

Dengue fever

Malaria

Respiratory

Cholera

Diarrhoea

H1N1

H5N1

HIV/AIDS

High blood pressure

Chikungunya

0 50 100 150 200

2015 2016

68

Table A.12: Proportion of households by location from each quintile, and proportion of individuals by gender, age, and having a chronic illness from each quintile, 2009 and 2016

Household level Individual level

Phnom Penh(%)

Other urban

(%)

Rural(%)

Men(%)

Women(%)

Under 5 years

(%)

5–14 years

(%)

15–59 years

(%)

Above 60 years

(%)

Chronic illness

(%)

Quintile 1 1.2 10.1 23.2 14.6 14.6 15.1 15.6 14.3 13.7 15.4

Quintile 2 2.9 12.4 22.8 18.8 18.3 19.3 19.6 18.0 18.2 16.9

Quintile 3 7.3 17.3 21.7 20.3 20.5 20.8 21.3 20.1 19.9 18.1

Quintile 4 17.2 20.7 20.2 22.6 22.1 23.3 22.0 22.1 23.5 20.8

Quintile 5 71.4 39.5 12.1 23.7 24.5 21.6 21.4 25.5 24.7 28.8

2009

Household level Individual level

Phnom Penh(%)

Other urban

(%)

Other rural(%)

Men(%)

Women(%)

Under 5 years

(%)

5–14 years

(%)

15–59 years

(%)

Above 60 years

(%)

Chronic illness

(%)

Quintile 1 1.9 8.1 24.3 12.8 15.0 17.6 13.8 12.3 23.1 17.6

Quintile 2 9.3 13.9 22.4 18.3 18.2 20.8 19.5 17.3 20.0 13.4

Quintile 3 13.8 20.9 20.8 20.6 20.7 20.0 22.5 20.2 20.2 22.2

Quintile 4 26.9 22.7 18.6 23.0 21.8 19.8 23.3 23.1 16.5 20.3

Quintile 5 48.2 34.4 13.9 25.3 24.3 21.9 20.8 27.0 20.3 26.5

2016

1 annex6

727 8 9 2 9 0 6 1 8 7 0 6

WHO Western Pacific RegionPUBLICATION

ISBN-13 978 92 9061 870 6

financial health protection in cambodia (2009-2016) · suggested citation. financial health...

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