Health Equity and Financial Protection DATASHEET 76527 Venezuel a The Health Equity and Financial Protection datasheets provide a picture of equity and financial protection in the health sectors of low- and middle-income countries. Topics covered include: inequalities in health outcomes, health behavior and health care utilization; benefit incidence analysis; financial protection; and the progressivity of health care financing. Data are drawn from the Demographic and Health Surveys (DHS), World Health Surveys (WHS), Multiple Indicator Cluster Surveys (MICS), Living Standards and Measurement Surveys (LSMS), as well as other household surveys where available. The datasheets use a common set of health indicators for all countries. All analyses are conducted using the health modules of the ADePT software. INEQUALITIES Child health1,2,3 Q1 Q2 Q3 Q4 Q5 Total CI IN HEALTH 2000 2 OUTCOMES Diarrhea 16.7% 11.6% 8.6% 10.7% 5.5% 11.6% -0.171*** Acute respiratory infection 17.0% 15.9% 14.9% 11.8% 14.6% 15.3% -0.068* INEQUALITIES Maternal and child Q1 Q2 Q3 Q4 Q5 Total CI IN HEALTH CARE health interventions1,2 UTILIZATION 2000 2 Full immunization 20.9% 22.5% 32.3% 13.3% 24.8% 22.9% 0.026 Medical treatment of ARI 38.0% 35.9% 32.4% 41.8% 38.2% 37.0% -0.007 Adult preventive care2,3 Q1 Q2 Q3 Q4 Q5 Total CI 2000 2 Voluntary counseling and 30.3% 37.6% 44.8% 45.6% 59.5% 44.6% 0.131*** testing for HIV Note: The Health Equity and Financial Protection datasheets use a standardized selection of indicators (see Measurement of Indicators for full list). When (1) data sources are not available or (2) indicator-specific sample size is less than 250 per quintile for mortality indicators or less than 25 per quintile for all others, indicators are not reported for the country under analysis. For analysis of inequalities using WHS, DHS and MICS, quintile ranking is based on an asset index. For all other analyses, ranking is based on household consumption. Q = quintile (where quintile 1 is the poorest) CI = concentration index; ranges between -1 and 1; negative sign indicates that the health outcome takes higher values among the poor * Significant at 10%, **Significant at 5%, ***Significant at 1%. Data sources: 1=n/a Demographic and Health Survey, 2=2000 Venezuela Multiple Indicator Cluster Survey, 3=n/a World Health Survey. Recommended citation: World Bank. 2012. Health Equity and Financial Protection Datasheet - Venezuela. Washington, D.C.: World Bank. For more information and the latest versions of the Health Equity and Financial Protection reports and datasheets, see: www.worldbank.org/povertyandhealth. Photo credit: UN Photo/Pessuapa I nterpre tatIon of results InequalItIes In health outcomes, rIsky behavIor and health care utIlIzatIon the tables in this section show how health outcomes, risky behaviors and health care utilization vary across asset (wealth) quintiles and periods. the quintiles are based on an asset index constructed using principal components analysis. the tables show the mean values of the indicator for each quintile, as well as for the sample as a whole. also shown are the concentration indices which capture the direction and degree of inequality. a negative value indicates that the variable (e.g. stunting or skilled birth attendance) is more concentrated among the poor, while a positive value indicates that the variable is concentrated among the better off. the larger the index in absolute size, the more inequality there is. the statistical significance of the concentration index is also shown, at 1% (***), 5% (**) and 10% (*) significance levels. For example, if stunting has a concentration index of -0.121***, then stunting is significantly concentrated among the poor. beneFIt-IncIdence analysIs benefit-incidence analysis (bIa) shows whether, and by how much, government health expenditure disproportionately benefits the poor. there are three tables showing, respectively, the distribution of service utilization across consumption quintiles for different types of care, the distribution of user fees, and the distribution of the estimated subsidies. all tables also show the concentration indices which capture the direction and degree of inequality. a negative value indicates that the variable (i.e. utilization, fees or subsidies) is more concentrated among the poor, while a positive value indicates that the variable is concentrated among the better off. the larger the index in absolute size, the greater is the inequality. For example, if the concentration index of subsidies to hospitals is positive, the non-poor benefit more than the poor from government spending on hospital services. the distribution of subsidies depends on the assumptions made to allocate subsidies to households. under the constant unit cost assumption, each unit of utilization is assumed to cost the same and is equal to total costs incurred in delivering this type of service (i.e. subsidies plus user fees) divided by the number of units of utilization. under the constant unit subsidy assumption, the unit subsidy is assumed to be constant, equal to total subsidies for the service in question divided by the number of units of utilization of that service. under the proportional cost assumption, higher fees are indicative of a more costly type of care; specifically, it is assumed that unit costs and fees are proportional to one another. If the concentration index is negative, then the subsidy to the particular level of care is pro-poor and if the concentration index is positive, then the subsidy is pro-rich. the column labeled “share� shows the distribution of the total subsidy across different levels of care. FInancIal protectIon: catastrophIc and ImpoverIshIng expendIture measures of financial protection relate out-of-pocket spending to a threshold. one approach is to classify spending as ‘catastrophic’ if it exceeds a certain fraction of household income or consumption or nonfood consumption. catastrophic payments are defined as health care payments in excess of a predetermined percentage (i.e. 5% to 40%) of their total household spending or nonfood spending. the first line of the first table shows the catastrophic payment “headcount�, i.e. the proportion of households with a health payment budget share greater than the given threshold. For example, if the “headcount� figure given in the last column of the first table is 6%, then 6% of households spend more than 40% of their pre-payment income on health payments. the concentration indices in the second line of each table show whether there is a greater tendency for the better off to have out-of-pocket spending in excess of the payment threshold (in which case it takes on a positive value), or whether the poor are more likely to have out-of-pocket spending exceeding the threshold (in which case it takes on a negative value). another approach is to classify health spending as ‘impoverishing’ if it is sufficiently large to make the household cross the poverty line, i.e. the household would not have been poor had it been able to use for general consumption the money it was forced to spend on health care. the extent of impoverishment due to health care expenditure is measured by comparing the extent of poverty computed using household consumption gross and net of out-of-pocket health spending. the table shows three measures of poverty. the first line of the table shows the percentage of the population living below the poverty line, i.e. the poverty “headcount�. the second line shows the population’s average shortfall from the poverty line, i.e. the “normalized poverty gap�; the normalization is useful when making comparisons across countries with different poverty lines and currency units. Finally, the last line shows the average shortfall from the poverty line, among those who are poor, i.e. the normalized mean positive poverty gap. the last column shows the percentage increase in poverty, the percentage increase in the average shortfall from the poverty line and the percentage increase in the average shortfall from the poverty line among the poor due to out-of-pocket health spending, respectively. progressIvIty oF health FInancIng the table in this section reports whether overall health financing, as well as the individual sources of finance, is regressive (i.e. a poor household contributes a larger share of its resources than a rich one), progressive (i.e. a poor household contributes a smaller share of its resources than a rich one) or proportional. the 1st through 5th columns show the distribution of consumption and different sources of health care financing. the 6th column shows the summary measures of inequality; in the case of consumption, this is the gini coefficient and in the case of other sources of financing it is the concentration index. In the 7th column, the kakwani index (defined as the concentration index less the gini coefficient) takes on a positive value, then payments are more concentrated among the better off than consumption, and is a sign that payments are progressive. If the kakwani index is negative, then payments are regressive. the last column shows the contribution of each financing source to total health care financing (obtained from national health accounts data). For more guIdance on InterpretatIon oF results, see: o’donnell, o., e. van doorslaer, a. Wagstaff and m. lindelow. (2008). analyzing health equity using household survey data: a guide to techniques and their implementation. Washington, d.c.: World bank. Wagstaff, a., m. bilger, z. sajaia and m. lokshin. (2011). health equity and financial protection: streamlined analysis with adept software. Washington, d.c.: World bank. Me asureMent of I ndIcators INdIcator MeasUreMeNt data chIld health Number of deaths among children under 12 months of age per 1,000 live births (Note: mortality Infant mortality rate rate calculated using the true cohort life table approach; the dhs reports use the synthetic cohort dhs life table approach) Number of deaths among children under 5 years of age per 1,000 live births (Note: mortality rate Under-five mortality rate calculated using the true cohort life table approach; the dhs reports use the synthetic cohort life dhs table approach) % of children with a height-for-age z-score <-2 standard deviations from the reference median stunting dhs, MIcs (Note: z-score calculated using Who 2006 child Growth standards) % of children with a weight-for-age z-score <-2 standard deviations from the reference median Underweight dhs, MIcs (Note: z-score calculated using Who 2006 child Growth standards) diarrhea % of children with diarrhea (past two weeks) dhs, MIcs diarrhea % of children with diarrhea (past two weeks; youngest child) Whs acute respiratory infection % of children with an episode of coughing and rapid breathing (past two weeks) dhs, MIcs acute respiratory infection % of children with an episode of coughing and rapid breathing (past two weeks; youngest child) Whs Fever % of children with fever (past two weeks) dhs, MIcs Fever % of children with fever (past two weeks; youngest child) Whs Malaria % of children with an episode of malaria (past year; youngest child) Whs adUlt health tuberculosis % of adults who reported tuberculosis symptoms (past year) Whs obesity among non-pregnant women % of women aged 15 to 49 with a BMI above 30 dhs obesity among all women % of women aged 18 to 49 with a BMI above 30 Whs road traffic accident % of adults involved in a road traffic accident with bodily injury (past year) Whs % of adults who suffered bodily injury that limited everyday activities, due to a fall, burn, poisoning, Non-road traffic accident Whs submersion in water, or by an act of violence (past year) angina % of adults ever diagnosed with angina or angina pectoris Whs arthritis % of adults ever diagnosed with arthritis Whs asthma % of adults ever diagnosed with asthma Whs depression % of adults ever diagnosed with depression Whs diabetes % of adults ever diagnosed with diabetes Whs difficulty with work and household % of adults who have severe or extreme difficulties with work or household activities (past 30 days) Whs activities (Note: this indicator was created from an ordinal variable with five categories) % of adults who rate own health as bad or very bad (Note: this indicator was created from an Poor self-assessed health status Whs ordinal variable with five categories) hIV positive Percentage of adults aged 15 to 49 whose blood tests are positive for hIV 1 or hIV 2. dhs rIsk Factors smoking (all) % of adults who smoke any tobacco products such as cigarettes, cigars or pipes Whs smoking (women) % of women aged 15 to 49 who smoke cigarettes, pipe or other tobacco dhs smoking (women) % of women aged 18 to 49 who smoke cigarettes, pipe or other tobacco Whs Insufficient intake of fruit and vegetables % of adults who have insufficient intake of fruit/vegetables (less than 5 servings) Whs Insufficient physical activity % of adults who spend < 150 minutes on walking/ moderate activity/vigorous activity (past week) Whs drinking % of adults who consume ≥5 standard drinks on at least one day (past week) Whs concurrent partnerships % of women aged 15 to 49 who had sexual intercourse with more than one partner (past year) dhs, MIcs concurrent partnerships % of women aged 18 to 49 who had sexual intercourse with more than one partner (past year) Whs % of women aged 15 to 49 who had more than one partner in the past year and used a condom condom usage (more than one partner) dhs, MIcs during last sexual intercourse % of women aged 18 to 49 who had more than one partner in the past year and used a condom condom usage (more than one partner) Whs during last sexual intercourse Mosquito net use by children % of children who slept under an (ever) insecticide treated bed net (ItN) (past night) dhs, MIcs % of pregnant women aged 15 to 49 who slept under an (ever) insecticide treated bed net (ItN) Mosquito net use by pregnant women dhs (past night) MaterNal aNd chIld health INterVeNtIoNs % of children aged 12-23 months who received BcG, measles, and three doses of polio and dPt, Full immunization dhs, MIcs either verified by card or by recall of respondent treatment of diarrhea % of children with diarrhea given oral rehydration salts (ors) or home-made solution dhs, MIcs % of children with a cough and rapid breathing who sought medical treatment for acute respiratory Medical treatment of arI dhs, MIcs infection (past 2 weeks) % of mothers aged 15 to 49 who received at least 4 antenatal care visits from any skilled personnel skilled antenatal care (4+ visits) dhs (Note: definition of skilled personnel is country-specific) % of mothers aged 15 to 49 that were attended by any skilled personnel at child’s birth skilled birth attendance dhs (Note: definition of skilled personnel is country-specific) contraceptive prevalence % of women aged 15 to 49 who currently use a modern method of contraception dhs, MIcs adUlt PreVeNtIVe care tB screening % of adults who were tested for tuberculosis (past year) Whs Voluntary counseling and testing for hIV % of women aged 18 to 49 who were tested for hIV and were told the results of the test Whs,MIcs cervical cancer screening % of women aged 18 to 69 who received a pap smear during last pelvic examination (past 3 years) Whs Breast cancer screening % of women aged 40 to 69 who received a mammogram (past 3 years) Whs adUlt cUratIVe care Inpatient or outpatient (12 months) % of adults who used any inpatient or outpatient health care (past year) Whs Inpatient (12 months) % of adults who used any inpatient health care (past year) Whs Inpatient (5 years) % of adults who used any inpatient health care (past 5 years) Whs % of adults who used any outpatient health care (past year; conditional on having not used any outpatient (12 months) Whs inpatient care past 5 years) Note: Unless otherwise noted, all children are under the age of 5 and all adults are aged 18 and older