Assessment of Health System Performance in Nepal - Ministerial ...

Health System Performance 2010Key Points• Health is both a direct component of human well-being and a form of human capitalthat increases an individual’s capabilities. Better health significantly contributes toeconomic development and to the reduction of poverty and income inequality• Nepal has made significant progress in the health sector over the past decade. Healthindicators such as life expectancy, infant/child mortality, and maternal mortality showgradual but steady improvement• Despite these achievements, there are still large inequalities in health outputs andhealth outcomes across geographic regions and socioeconomic groups• Increasing the real per capita income by 10 percent, will cause the IMR to fall by 7percent, child mortality rate (CMR) by 11 percent, and life expectancy rate (LER) willincrease by almost 2 percent. Increasing the ratio of health budget to total budget by10 percent, CMR will decrease by 4.5 percent, and LER will increase by 0.6 percent.If we provide more services by increasing health services, for example increasingnumber of beds by 10 percent, IMR will fall by 4 percent and LER increase by 1percent.• The results show that in recent years, public health institutions have less capacity toimprove intermediate health outputs because of a shortage of human resources,number of health institutions, and institution-related inputs• Equity and efficiency are not in conflict. Improvement of institutional capacity in thedelivery of health services (at least increasing the numbers of institutions andmanpower in the institutions) can shift the health production function ensuring equityin health care services across regions. Allocation of resources according to needs canimprove equity and efficiency of health outputs; however, a blanket policy will nothave such a capacity• Private providers play a complementary role in providing health services andcontributing to improvement of health outcomes. Thus, this report includes not onlypublic providers, but also how to make better use of private capacity to improvehealth outcomes• Money matters to the health care system, but it does not guarantee efficient, equitable,and effective health care services. Health care financing has the power to reformhealth care delivery and provide incentives to providers to deliver efficient andeffective health careiii

Eligibility criteria for becoming a DMP (checklist A)The DMP must be a registered medical practitioner who: has normally had at least three years recent clinical experience with a group ofpatients/clients in the relevant field of practice is in a GP practice and is either vocationally trained or has a certificate ofequivalent experience from the Joint Committee for Postgraduate Training inGeneral Practice Certificate or is a specialist registrar, clinical assistant or aconsultant within a NHS Trust or other NHS employer has the support of the employing organisation or GP practice to act as a DMP whowill provide supervision and support to the NMP student and opportunities todevelop competence in prescribing practice has some experience or training in teaching and/or supervising in practice normally works with the trainee prescriber. If this is not possible (such as in nurseledservices or community pharmacy), arrangements can be agreed for anotherdoctor to take on the role of the DMP, provided the above criteria are met and thelearning in practice relates to the clinical area in which the trainee prescriber willultimately be workingCharacteristics of a competent DMP (checklist B) 1Teaching Knowledge about teaching methods (how and when to use them)knowledgeTeaching Using teaching knowledge, giving feedback, being able to observe,skills analysing, teaching the trainee to carry responsibility, encouragingreflection, structuring, being able to teach (professional) skills, beingable to handle conflict, being able to communicate (including listening),phasing of trainingTeachingattitudePersonalitytraitsGiving the trainee latitude, giving the trainee respect, being open tocriticism, being open to criticism on his/her teaching, being interested inthe trainee, being able to separate private life and teaching, being ableto separate the different roles in the teaching-relationship (teacher,colleague), being able to cope with tension resulting from being both aDMP and an NMP trainer, being a role model, offering a safeenvironment, individualising training, being alert, being critical of thetrainee and their learning process, being open to extra training tobecome a better teacher, enjoying the role of teacher, being availableand reachable, making time for teaching, being able to see things inperspective, being stimulating, not profiting from the trainee, being loyalto the department, willing to share patients with the trainee, daring togive feedback, learning from the traineeEnthusiasm, flexibility, self-knowledge, ability to reflect, self-insight,patience, integrity, enjoying their role as a DMP1 Adapted from: Boendermarker PM, Schuling J, Meybroom-de Jong B, Zwierstra RP, Metz JCM (2000) What arethe characteristics of the competent general practitioner trainer? Family Practice, 17(6), 547-5538

Health System Performance 2010To develop an effective mechanism for resource allocation and utilization in the health sector,an analysis of the equity, efficiency, and effectiveness of resource allocation and utilization inthe health sector is crucial. Simply stated, equity is the notion that greater resources and moreservices should be made available to the most vulnerable and needy groups; efficiency looksat the cost of inputs for each unit of output produced, and effectiveness is the extent to whichactual performance compares with expected performance. A better health system advancesboth efficiency and equity. This analysis of the health system seeks to improves performanceby providing a better understanding of the health system to aid in the design of an evidencebasedpolicy.II. Efficiency analysisEfficiency is concerned with maximising health outcomes/outputs. As such, there are threetypes of efficiency: technical efficiency, cost effectiveness efficiency, and allocativeefficiency, as stated in the conceptual framework.2.1 Technical EfficiencyThe following is an analysis of the causal relationship between inputs and outputs in thehealth sector. In the health sector, inputs are both public and private expenditures, althoughpublic expenditure is the primary factor in determining health outcomes and shaping thehealth system in developing countries. Based on the available data, the input-output matrix,on the following page, shows the relationship between inputs - particularly expenditure in thehealth sector - and health outcomes for the last two decades (fiscal years 1989/90 to 2007/08).3

Health System Performance 2010Table 2.1 Input outcome matrixInputFiscal YearPublic Expenditure on HealthGDP per As % of As % ofcapita total GDP1995/96 Budget (HBGDPprice (RPI) (HBTG) )InfantmortalityRate(IMR)ChildMortalityRate(CMR)OutcomeCrudeBirthRate(CBR)LifeExpectancyRate (LER)1989/90 7895.35 4.60 0.93 128.00 197.00 41.60 53.501990/91 8222.13 3.84 0.88 107.00 197.00 39.60 54.001991/92 .8420.13 3.62 0.84 107.00 197.00 39.60 54.001992/93 8472.81 3.40 0.64 102.00 165.00 39.60 54.021993/94 8912.08 4.85 1.08 102.00 165.00 39.60 54.001994/95 8986.90 4.91 1.21 102.00 165.00 37.50 54.001995/96 9271.18 5.99 1.44 102.00 165.00 37.50 54.001996/97 9485.47 6.19 1.42 79.00 118.00 37.80 54.501997/98 9586.51 5.70 1.37 74.70 118.00 35.40 56.101998/99 9747.10 5.69 1.34 69.42 111.72 34.54 57.521999/00 10148.44 6.09 0.80 66.78 108.78 34.10 58.252000/01 13809.56 5.19 0.87 64.14 105.44 33.58 58.952001/02 13527.88 4.91 0.79 64.00 91.00 33.50 60.002002/03 13750.91 5.05 0.81 60.00 83.50 48.00 60.002003/04 14096.31 5.26 0.87 56.00 76.00 46.73 60.982004/05 14304.13 6.00 0.98 52.00 68.50 45.45 62.002005/06 14513.40 6.34 1.13 48.00 61.00 28.40 63.692006/07 14721.22 6.81 1.36 48.00 61.00 28.40 63.692007/08 15219.41 6.63 0.52 48.00 61.00 28.40 63.69Sources: Adhikari and Maskay (2004), MOHP et al, (2009), RTI, (2009)This matrix shows that health outcomes are increased as health inputs are increased. Allinputs are shown in monetary terms. These physical inputs are measured by the ratio betweenthe population and physical inputs. Extension of services (health service providers) in termsof population per service (hospitals, health centres, health posts, ayurvedic service centres,sub-health posts, and primary health centres [SP]), the population per hospital bed (BP) andpopulation per supply of skilled manpower (SMP) are also used in this analysis.All inputs are independent variables that determine the level of health outcomes (dependentvariables). The correlation coefficients between the dependent and independent variablesshow the relationships in the input-output model.4

Health System Performance 2010Table 2.2: Correlation coefficients of the given variablesIMR 1IMR CMR CBR LER RPI HBTG HBGDP SP BP SMPCMR 0.98** 1CBR 0.32 0.29 1LER -0.93** -0.93** -0.34 1RPI -0.90** -0.91** -0.23 0.96** 1HBTG -0.70** -0.74** -0.48* 0.64** 0.58* 1HBGDP 0.06 0.03 -0.16 -0.20 -0.23 0.41 1SP 0.73** 0.75** 0.26 -0.52* -0.55* -0.71** -0.31 1BP 0.18 0.16 0.14 -0.40 -0.28 0.11 0.53* -0.39 1SMP 0.90** 0.88** 0.24 -0.76** -0.73** -0.61** 0.03 0.65** 0.16 1** Significant at 1% level * Significant at 5 % levelIMR has positive correlations with CMR, SP and SMP and negative correlations with LER,RPI, and HBTG at a 1 percent level of significance. Similarly, CMR has positive correlationswith SP and SMP, and negative correlation with LER, RPI, and HBTG at a 1 percent level ofsignificance. CBR is negatively correlated with only HBTG at a 5 percent level ofsignificance. LER has a positive correlation with RPI, HBTG, SP and SMP. The coefficientsthat are significant at 1 percent or 5 percent have theoretically expected signs. The resultssuggest that there are expected relationships between the given variables.2.2 Regression analysisThe most popular method for estimating the causal relationships between health inputs andhealth outcomes was suggested by Filmer and Pritchett (1999), and Adhikari and Maskay(2004), and is used in this analysis. The following conceptual equation for the “healthproduction function” is:This equation relates the dependent variable, “M”, which is taken to be either that of childmorality rate, infant mortality rate, crude birth rate and life expectancy rate, to the log ofmean per capita income, the log of the share of public health as a fraction of total governmentbudget and the log of the share of public health as a fraction of GDP. “X” is the independentvariable which control for a variety of other socio-economic factors. Regression analysishelps illustrate the causal relationships between input and outcome variables.5

Health System Performance 2010Table 2.3: Regression analysis and interpretationsDependentvariableReal GDPper capitaRatio of healthbudget to totalgovernmentbudgetRatio ofhealthbudget toGDPNumber ofpeopleserved bythe healthcareprovidersNumber ofpeopleserved bya bedNumber ofpeopleserved byskilledmanpowerIMR -0.7180 -0.1850 -0.0093 0.1099 0.4132 0.2222Interpretations(overall modelsignificant at 1%level with highSquared (0.9684)Significantat 1% withexpectedsignExpected signbut notsignificantExpectedsign butnotsignificantExpectedsign but notsignificantExpectedsign andSignificantat 10%Expectedsign andSignificant at5%CBR 0.1085 -0.4653 0.0470 0.1083 0.4914 -0.0873Interpretations(overall modelnot significant)notsignificantnot significantnotsignificantnotsignificantnotsignificantnot significantCMR -1.0733 -0.4457 -0.0093 0.0607 0.4605 0.1913Interpretations(overall modelsignificant at 1%level with highSquared (0.9591)Significantat 1% withexpectedsignExpected signand Significantat 10%Expectedsign butnotsignificantExpectedsign but notsignificantExpectedsign but notsignificantExpectedsign but notsignificantLER 0.1975 0.0615 -0.0028 0.0053 -0.1032 -0.0180Interpretations(overall modelsignificant at 1%level with highSquared (0.9666)Significantat 1% withexpectedsignExpected signand Significantat 10%notsignificantnotsignificantExpectedsign andSignificantat 5%not significantThe regression analysis demonstrates that government health expenditure has the power tochange health outcomes, particularly CMR and life expectancy. However, it has a little powercompared to per capita income. The elasticities of the given variables determine howsensitive the output variables are to changes to the input variables.Table 2.4: Elasticity of health outcomes with respect to health inputsVariable IMR CMR LERReal per capita income -0.718 -1.07 0.198Ratio of health budget togovernment total budget - -0.45 0.062Number of people servedby a bed 0.413 - -0.103Note: This employs a double log modelThe coefficients of elasticity provide encouraging results for researchers and policymakers. Ifthe real per capita GDP increases by 10 percent, it will decrease the IMR by almost 7 percent,CMR by 11 percent, and increase LER by almost 2 percent. Similarly, if we increase the ratio6

Health System Performance 2010of health budget to the total budget by 10 percent, CMR will decrease by 4.5 percent andLER will increase by 0.6 percent. If we increase the number of beds in hospitals, the numberof “people served by a bed” will be reduced. If we reduce the ratio of people to total beds by10 percent (in other words, increase the number of beds), it will reduce IMR by 4 percent andincrease LER by 1 percent.The literature provides indicative results based on empirical evidence of how extra spendingleads to changes in health outcomes. The World Bank has written about health expenditureeffectiveness, “In countries with “good” policies and institutions (strong property rights,absence of corruption, a good bureaucracy), an extra 10 percent of GDP in aid has beenestimated to lead to a decline in infant mortality of 9 percent. By contrast, in countries inwhich policies are only average, the impact is just 4 percent. Where policies are “bad,” aidhas no statistically significant effect on infant mortality,” (Wagstaff and Claeson, 2004, page56). Thus, the Nepalese health system can be expected to have average results; there is a lotof room for improvement.2.3 Cost EffectivenessThere are various methods to measures the cost effectiveness efficiency of health systems. Itis determined by both production function and prevailing resources. Effectiveness can bedefined as the difference between the targeted outputs, such as targeted coverage andachieved output (coverage). Obviously, targeted coverage is 100 percent; existing percentageof coverage allowed to measure the cost effectiveness with comparing their costs ofproduction. The results can be interpreted by utilizing the health production function, whichdescribes the relationship between intermediate outputs and health-related inputs. The valuesof these inputs are costs of production; therefore, all inputs are in monetary terms. In costeffectiveness analysis, intermediate outputs or activities are used to assess the causal effectsof health expenditures. It is difficult to determine the direction of the impact prior toestimation of the results. Effectiveness that is measured in natural unit is presented in theappendix A for last 13 years.All inputs are measured in monetary terms and outputs are primarily intermediate outputs(effectiveness). It measures the effectiveness of public financing to produce intermediatehealth outputs. Data for last the 13 years were collected from economic surveys and annualreports. All data are used in natural log forms to capture the non-liner relationships betweenthe dependent and independent variables. Similar to efficiency measurement, all effectivenessvariables are dependent variables and real GDP per capita income, ratio of health budget tototal government budget, ratio of health budget to GDP, ratio of population to existing publichealth care providers, numbers of beds, and skill manpower are independent variables7

Health System Performance 2010Table 2.5 Regression analysis of health inputs and intermediate outputsRealGDPpercapitaRatio of healthbudget to totalgovernmentbudgetRatio ofhealthbudgetto GDP8Number ofpeopleserved byhealth careprovidersNumberof peopleservedby a bedNumber ofpeopleserved byskilledmanpowerDependentvariableAll immunizationcoverage (BCG,DPT3, Polio3 * (-and Measles) 0.23) - - - - -Nutrition (growthmonitoringcoverage %) * (0.90) ** (1.08) - * (-1.01) - -Nutrition(proportion ofmalnourishedchildren %)*(-2.20) - - - - -ARI incidence*(2.24)**(1.17) - - - -Incidence ofpneumonia (mildand severe)*(1.7)**(0.6) -*(-0.7) - -Incidence ofdiarrhoea*(-1.9) - - - - -Somedehydrationcases - - - - - -SeveredehydrationDiarrhoea casefatality rate*(-10.4) -**(1.1) - -**(-2.5) - - -*(-1.5) - -First antenatalvisit % - - - - - -Contraceptiveprevalence rate(CPR) - - - - - -Condoms (CPRmethod mix) - - - - - -Malaria bloodexamination rate**(0.21)*(0.37) -*(-.46) - -Tuberculosiscase detectionrate - - -*(-.82) - -DOTS coverage - - - - - -Total OPD newvisits - - - - * (3.55) -Note: - = Not significant; *= significant at 5% level; **= significant at 10% level; coefficients are in parenthesisThe results show that most of the variables were not statistically significant. This costeffectiveness analysis suggests that the health system had lower performance in producingintermediate outputs since they are either constant or decreasing over time. Thus, policyreform must work to improve the effectiveness of health outputs.

Health System Performance 20102.4 Allocative efficiencyThe government has given priority to preventive services, which are related to public goods.Expenditure for medical services has fallen since 2000; conversely, expenditure on publichealth services has increased. Fiscal year 2003/04 saw nearly equal allocation of financialresources to medical services and public health services.Figure 2.1: Allocation of resources to medical versus public health servicesMoHP, (2009a)Analysis of the Public Expenditure Review of the health sector revealed that rural healthservices consumed greater financial resources than urban areas, and that the disparitybetween the two is growing.Figure 2.2: Allocation of funds to rural/urban areasMoHP, (2009a)The following graph shows that priority 1 programmes has consumed almost one third of thetotal development budget for the health sector during the review period; conversely, priority 39

Health System Performance 2010programmes consumed the majority of development health spending. The results validatedthe hypothesis that expenditure in the health sector has not been allocated based on priorities.Figure 2.3: Allocation of resources in priority programmesMoHP, (2009a)III. Factors contributing to Health production function3.1 Health production functionHealth care programmes are continuously working to produce health outputs, thus the healthoutcomes reveal the effectiveness of the programmes. For example, immunization packages(inputs) are implemented through the regular health infrastructure. Coverage, however, asmeasured by the percentage of immunized people, has remained constant, and in some caseshas even decreased. Similarly, the programme to monitor stunted children increased itscoverage until 2005/06 when coverage plateaued despite no changes in the number ofresources (inputs) devoted to the programme.10

Health System Performance 2010Figure 3.1: Coverage of ImmunizationSource: MoHP, (2009b); Annual reports, various yearsFigure 3.2: Monitoring of stuntingSource: Annual reports, various yearsThese two graphs begin to explain why the desired results have not been achieved in thehealth system; the government has continuously increased funding for health programmes,but institutional capacity has remained the same. The health results are remarkably consistent,showing an initial improvement in outcomes followed by a drop in results and eventualdecline, as in Figure 3.2. The fact sheets from various annual reports covering 13 years arepresented in appendix A, and they bear out the same conclusion.It is difficult to show the relationships between all health programmes and health outputs inFigures, but we have presented an econometric analysis in the cost effectiveness section.Figure 3.3 is the representative curve for all health programmes and health outputs.Obviously, if there are no health programmes, health outputs will be zero. As health11

Health System Performance 2010programmes P 1 , P 2 , P 3 , and so on are implemented, health outputs are improved H 1 , H 2 , H 3 .Clearly, there is a positive relationship between health programmes and health results(outputs); results increase as health care packages or programmes are increased. During theinitial phase of implementation, the rate of improvement in outcomes is proportional toincreases in the health programmes. Over time, however, the rate of change falls off. If weincrease health programmes, P 3 to P 4 , health outputs remain constant (H 3 ). This is the point ofstagnation. The data from the last 13 years suggests that now are now almost at this point ofstagnation.Figure 3.3: Health production function3.2 Determining factors for health production functionHealth programmes (service packages), the allocated budget, human resources, and healthinstitutions determine health production function. When health outputs fail to increase despiteincreases to the health budget and health programmes, health institutions and humanresources – that is to say capacity - may be critical to increasing health.3.2.1 Public health institutionsThe population per public health institution is defined as the ratio of people to health careinstitutions. It is one of the indicators measuring distribution of public health serviceproviders in relation to the size of the population. The data on health institutions andpopulation size are derived from the Ministry of Health and Population 2007Annual Report.The results, as seen in Figure 3.4, demonstrate that public health institutions (hospitals,primary health care centres, health posts, and sub-health posts) serve almost equal numbers ofpeople in each region.12

Health System Performance 2010Figure 3.4: Ratio of population to public health institutions by regionSources: MoHP, (2007)The ratio of population to public health institutions appears to be evenly distributed byregion; however, the absolute distribution of public health institutions by development regionis quite unequal. Public health institutions are skewed towards the relatively developedEastern, Central, and Western regions (Figures 3.5 and 3.6). Hospitals and primary healthcare centres (PHCCs) are significantly lower in the Mid-western and Far Western regions.Figure 3.5: Distribution of hospitals and PHCCsSources: MoHP (2007 ), and estimated13

Health System Performance 2010Figure 3.6: Distribution of health posts (HPs) and sub-health posts (SHPs)Sources: MoHP (2007 ), and estimatedThe establishment of health care institutions based on population distribution might beappropriate from the perspective of cost effectiveness, but would be questionable in terms ofequity and fundamental human rights. It might be more appropriate to consider bothpopulation distribution and distance from an institution since distance is an important factorin determining access to health services. The health care institution density index (HID)developed by the Central Bureau of Statistics (2003) depicts public health institutions andaccess to health care services by development regions. The results demonstrate that the Midwesternand Far Western regions have less access to health care services than the other threeregions.Figure 3.7: Health care institution density index (mean)Sources: CBS (2003)Distribution of health institutions and health institution density are concerned with supplyside analysis of health institution. The adequacy of public health institutions based onpeople’s perceptions is the demand side indicator that measures the distribution of institutionsand access to health care services. If people feel that public health institutions are adequate, it14

Health System Performance 2010indicates that these institutions are delivering services adequately. Overall, the percentage ofhouseholds reporting government health facilities as “good” is only 14 percent, while 64percent reported that they were only “fair.” In the Mid-western region, up to 35 percent ofhouseholds reported facilities as “poor.”Figure 3.8: Reported adequacy of health care services by regionSource: CBS (2004)3.2.2 Private health institutionsBoth public and private health institutions contribute to the delivery of health services. Wehave very limited data on private providers, but their contributions can be seen in theutilization of services. The following figures compare the numbers of public health providerswith private health providers by ecological belt. Overall, there are more public than privateinstitutions. The Mountain region has fewer private hospitals than the other two ecologicalbelts. In the Terai, a greater number of people have utilized private health care providers,while people in the Mountain region are more likely to use public institutions. In the Hillregion utilization of public and private hospitals appears to be nearly equal. To calculateutilization, “private provider” includes hospitals, clinics, and pharmacies. Public providersinclude hospitals, primary health care centres, health posts, and sub-health posts.Figure 3.9 (a) and (b): Public/private health care institution utilization by ecologicalbelt15

Health System Performance 2010Source: MoHP (2008) Source: CBS (2004)The results shown below suggest that private hospitals are concentrated in the Central region,and in urban areas. And it is only in the Far Western region, which only has one privatehospital, that there is greater utilization of public institutions than private institutions.Figure 3.10 (a) and (b): Public/private health institution utilization by developmentregionSource: MoHP (2008) Source: CBS (2004), NLSS (2003/04)3.2.3 Human resourcesHuman resources are the active factors of health production that are responsible for theeffective implementation of the programmes. Motivational factors, including trainings,promotions, and monetary incentives for employees of the health care system are alsoimportant to strengthening institutional capacity. The data published in the government’seconomic survey (MoF, 2009) shown in Figure 3.11 shows that human resources in healthinstitutions has remained very low throughout the past decade or so.Figure 3.11: Trends in human resources in health institutionsSource: MoF (2009)16

Health System Performance 2010The figure below illustrates which percentage of sanctioned doctor posts at public health careinstitutions are currently staffed, according to development region. The Mid-western regionhas the lowest percentage while the Central region has the highest percentage. Surprisingly,“other health professionals” are the most likely to be filled in all regions.Figure 3.12: Percentage of filled sanctioned posts by regionSources: HMIS 2009 and estimatedFigure 3.13: Percentage of filled sanctioned posts by professionSource: MoHP (2009), and estimatedMonitoring and supervision of the health care institutions can improve institutional capacityand lead to improved health outputs. The data on the number of supervised institutions aswell as a number of health output indicators (e.g. coverage of immunization, pregnant womanreceiving anti-helminths, 4 th ANC visits, etc.) is available. The correlation coefficient can17

Health System Performance 2010give an indicative measurement of institutional capacity using this data from all 75 districts.The hypothesis is that there should be positive relationships between supervision and healthoutputs. A supervision index that specifically measures the ratio of supervised institutions tototal number of institutions including PHCCs, HPs, SHPs, outreach clinics, and EPI clinicshas been developed for this purpose. The degree of correlation between supervision andhealth outcomes is presented in the following table.Table 3.1: correlation coefficients of supervision and health outcomesHealth outputCoverage ofBCGCoverage ofDPTCoverage ofPolio 3Coverage ofMeasles% ofpregnantwomanreceivingantihelminthes4th ANCvisits as %of expectedpregnanciesSupervisionindex 0.22 0.14 0.15Source: estimated0.23(significantat 5 %) -0.080.33(significant at 1%)The correlation coefficient yields the result that only two health outputs show a positiveimpact because of supervision, suggesting that supervision of health institutions has only aminimal impact on improving institutional capacity to deliver health care services.3.3 Possible synergic effects in health productionThe difficulties of working to make a meaningful impact on health care services arecompounded when dealing with the dual issues of inadequate health institutions on the onehand, and inadequate human resources within these institutions on the other. When these twodeficiencies are combined, the negative impact on health outcomes is greater than either onewould be on its own. The lower health outcomes seen in the Mid-western and Far Westernregions and described in Section 3 are the result of just such a negative synergic effect. Thesesynergic effects can be observed through the gap between the percentage of vacant positionsand distribution of institutions. If the percentage of vacant position is higher than thepercentage distribution of institution, this creates negative synergic effects; otherwise, therewill be positive synergic effect in production of health services. The size of negative synergiceffect is shown by the shaded area in the diagram.18

Health System Performance 2010Figure 3.14: Differences in institutional capacity by regionSource: estimated3.4 Changes to the health production functionInstitutional capacity and management is critical to the successful implementation of healthcare services and is determined by a number of factors, including human resources, thenumber of health institutions, and monitoring and supervision, among others. The analysissuggested that health institutions because of uneven geographic distribution (includinginstitutional capacity, such as monitoring and supervisions) and human resources have lesscapacity to produce health outputs in the health system.If we increase the number of health institutions in both the public and private sectors andexpand human resources, we can produce additional health outputs. The health productionfunction will be shifted as shown by the dotted lines in Figure 3.15. The additional publichealth institutions could be more evenly distributed to better service underserved populations,while private institutions provide people with additional options. The government canmotivate private institutions including community hospitals, teaching hospitals, and NGOhospitals through introducing incentive packages, including for example, tariff exemptions onimported instruments or exemption from levying the 5 percent service charge. Humanresources can be expanded in two ways: through increasing the number of available positionsat institutions and by making it mandatory for all medical students to spend a certain periodof time working at local health institutions.19

Health System Performance 2010Figure 3.15: Shift in health production functionIV. Equity analysis4.1 Child health outcomesAs we discussed in Section 2, child health outcomes in terms of infant mortality and underfivechild mortality rates are improving, but the trend in improvements for under-five childhealth outcomes is higher than for infant health outcomes.4.1.1 Child health outcomes by locationThe following figures (Figures 4.1 and 4.2) show that despite some improvements, theMountain, Western, and Far Western regions still have high infant mortality rates (IMRs).Furthermore, the graphs illustrate quite clearly that the Hill area continues to have betterperformance than the Mountain or Terai areas. Even more worrying than the disparity amongecological regions, the Mid-Western region has witnessed a 33 percent increase in infantmortality, more than double the national average. Nonetheless, rates of infant mortality havefallen over time.20

Health System Performance 2010Figure 4.1: Infant mortality by ecological beltSource: MoHP et al (2007), (2002) and (1997)Figure 4.2: Infant mortality rate by development regionSource: MoHP et al (2007 ), (2002) and (1997)4.1.2 Child health outcomes by socioeconomic statusWhile every wealth quintile showed progress from 2001 to 2006, improvements in childhealth outcomes appear to be strongly correlated to socioeconomic status, with the wealthiestquintile displaying nearly twice as much progress in child health than the lowest quintileduring the same survey period. That being said, however, child health among the middlewealth quintile did not improve as much as for other income groups, according to the 2006survey, and we see that the greatest gains were made by the second-poorest quintile.21

Health System Performance 2010Figure 4.3: Infant mortality rate by wealth quintileSource: MoHP et al (2007) and (2002)Figure 4.4: Under-five mortality, by wealth quintileSource: MOHP et al (2007) and (2002)The under-five mortality rate has decreased among all wealth quintiles, as has the disparitybetween the poorest and richest quintiles. The difference between the richest and poorestquintiles was 87 per 1,000 live births in 1996, but fell to a difference of 51 per 1,000 livebirths in 2006, indicating a marked improvement in the health outcome of children underfive.22

Health System Performance 2010Table 4.1: Trends in Under-five mortality per 1,000 live births by wealth quintileWealth quintile 1996 2001 2006PercentChangeFirst (poorest) 166 135 98 -40.1Second 157 121 83 -47.1Third 159 109 91 -42.8Fourth 106 92 63 -40.6Fifth (wealthiest) 79 59 47 -40.5Total 118 91 61 -48.3Difference between poorest and richest quintiles 87 76 51 -41.4Source: RTI International, (2008)4.1.3 Child health outcomes by caste/ethnicityTable 4.2 depicts inequalities between castes/ethnic groups in the under-five mortality rate.The disparity between Brahmins/Chhetris and Dalits has narrowed to 14 per 1,000 live birthsin 2006 from 45 in 1996, a 69 percent decrease. Under-five mortality among Dalits was cutby almost half from 1996 to 2006. The disparity between Newars and Janajatis, bycomparison, decreased by only 14 percent. The largest decrease in under-five mortality wasamong Muslims, a 57 percent decrease from 158 per 1,000 live births in 1996 to 68 in 2006.Table 4.2: Trends in under-five mortality per 1,000 live births by caste/ethnic groupCaste/ethnic group 1996 2001 200623PercentChangeBrahmins/Chhetris 125 98 76 -39.2Dalits 170 129 90 -47.1Janajatis 126 108 80 -36.5Other Terai Groups/Madhesis 164 130 86 -47.6Newars 83 84 43 -48.2Muslims 158 99 68 -57.0Total 118 91 61 -48.3Difference between Brahmins/Chhetris and Dalits 45 31 14 -68.9Difference between Newars and Janajatis 43 24 37 -14.0Source: RTI International, (2008)Figure 4.5 describes infant mortality rates by caste/ethnic group, illustrating a sharp declinein the IMR among Dalits, from 103 per 1,000 live births in 1996 to 68 in 2006. A similarreduction in the IMR is seen among Muslims. The greatest decline, however, was among the

Health System Performance 2010Others group (Marwari, Jaine, Punjabi/Sikh, Bengali, and unidentified), who make up onepercent of the population. The IMR for this group plummeted from 132 per 1,000 live birthsin 1996 to 44 in 2006. There was a slower rate of decline in the IMR among Newars andBrahmins/Chhetris. The second-highest reduction in infant mortality was among the OtherTerai Groups/Madhesis, for whom the IMR decreased by 39 percent. These trends indicate amove towards more equitable health outcomes.Figure 4.5: Infant mortality per 1,000 live births by caste/ethnic groupSource: RTI International, (2008)24

Health System Performance 20104.2 Maternal health outcomesThe results of the analysis suggest that maternal health outcomes have improved as a result ofthe collective effort of different sectors of the government.Figure 4.6: National maternal mortality rate (MMR)Source: MoHP et al (2007)The maternal mortality rate (MMR) is the aggregate measure of maternal health outcomes.While an analysis of MMR by socioeconomic and geographical criteria might be useful forpolicy analysis, the current data does not permit such analysis. Instead, as suggested by AbouZahr and Wardlaw (2001), we took the data on deliveries by skilled birth attendants (SBAs)and caesarean sections (C-sections) to serve as proxy indicators of maternal health.4.2.1 Deliveries assisted by a skilled birth attendantThe percentage of deliveries assisted by SBAs, including a doctors, nurses, or midwives, isone of the indicators of maternal health. The results show that the percentage of birthsdelivered under the supervision of an SBA increased from 9 percent in 1996 to 19 percent in2006. Similarly, the number of C-sections being performed has also risen. There is an inverserelationship between the MMR and the rate of SBA use and C-sections performed. IncreasedSBAs and C-sections reduce the possible death.Figure 4.7: Deliveries assisted by a skilled attendant and C-sectionsSource: MoHP et al (2007), (2002) and (1997)25

Health System Performance 2010SBA and C-section by development regionsThe data shows that the percentages of both SBA use and C-sections were higher in theCentral regions and lower in the Midwestern and Far Western regions. This would suggestthat the latter regions might have a higher MMR than other regions.Figure 4.8 SBA use as a percentage of total births, by development regionSource: MoHP et al (2007), (2002) and (1997)Figure 4.9: C-sections as a percentage of total births, by development regionSource: MoHP et al (2007), (2002) and (1997)SBA use and C-section by socioeconomic groupMaternal health outcomes in terms of the percentage of births assisted at delivery by an SBA andpercentage of C-sections performed show disparities among socioeconomic groups. Maternal healthoutcomes are more than twice as good as among the second-wealthiest quintile26

Health System Performance 2010Figure 4.10: SBA use and C-sections by wealth quintileSource: MoHP et al (2007)4.3 Nutritional statusNutritional status is an important indicator of children’s overall health and well-being. Thenutritional status of young children is an indicator directly related to the health andproductivity of people as adults. A number of factors determine the nutritional status ofchildren in developing countries including low dietary intake, infectious disease, lack ofappropriate health care, and inequitable distribution of food within the household.The nutritional status of children under five years of age is determined by two indices:percentage of stunted children (whose height-for-age is below minus two standarddeviations), and percentage of underweight children (whose weight-for-age is below minustwo standard deviations). The prevalence of low weight has decreased slightly over time,while the percentage of stunted children appears to have remained virtually unchanged.Figure 4.11: Trends in the nutritional status of childrenSource: MoHP et al (2007), (2002) and (1997)27

Health System Performance 20104.3.1 Nutritional status by geographic regionRegional variations are substantial, with 62 percent of children in the Mountain regionexhibiting stunted growth, a number far above the national average, and one that is increasingover time. Stunting among children is highest in the Mid-western region (58 percent) andlowest in the Eastern region (40 percent), and while stunting is becoming more common inthe Mid-western region, other regions exhibit little to no change.Figure 4.12 Prevalence of stunted children by development regionSource: MoHP et al (2007), (2002) and (1997)Figure 4.13 Prevalence of underweight children by development regionSource: MoHP et al (2007), (2002) and (1997)28

Health System Performance 20104.3.2 Nutritional status by socioeconomic groupFigure 4.14: Prevalence of stunted children by wealth quintileSource: MoHP et al (2007)V. Utilization of Health Care ServicesHealth care service utilization is conditional upon illness: higher levels of acute illness lead toa higher possibility of health care utilization. Some parts of health care utilization arediscussed in section three. Utilization of health services is presented in the following figures.5.1 Disparities in health care utilizationPoor people report lower utilization of health services compared to the rich, with the resultthat there is lower reporting of illness among the poor (only 10 percent). This does not mean,however, that they are healthier than the rich; in fact they have a greater incidence of disease,but because of they have less access to health care services - be that due to financialconstraints, geographical obstacles, social hindrances, or any other number of factors thatprevent the poor from seeking medical attention - their illness is far less likely to be officiallyrecorded.Nonetheless, poor people still prefer private health care providers. This suggests that privatefacilities play a complementary role in providing health services to the people.29

Health System Performance 2010Figure 5.1: Percentage self-reporting acute illness, by wealth quintileSource: CBS (2004)Figure 5.2: Utilization of all health facilities, by wealth quintileSource: CBS (2004)5.2 Antenatal care utilizationTable 5.1 describes the changes, by wealth quintile, in 4 th antenatal care (ANC) visitsprovided to new mothers. As can be seen by the disparity between the richest and poorestquintiles, inequality has gradually grown between 1996 and 2006, increasing from 29 to 50percent, despite a nearly four-fold increase in utilization by the poorest quintile.Table 5.1: Percentage of mothers making 4 or more ANC visits, by wealth quintileWealth quintile 1996 2001 200630Change in% pointsFirst (poorest) 2.7 5.1 10.5 7.8Second 3.4 6.0 20.2 16.8Third 5.8 9.5 27.7 21.9Fourth 9.6 18.0 38.0 28.4Fifth (richest) 31.5 46.8 60.0 28.5Total 8.8 14.3 29.4 20.6Difference between poorest and richest quintiles 28.8 41.7 49.5 20.7

Health System Performance 2010Figure 6.2: Access to health care services by wealth quintileSource: CBS, (2004)6.1 Access to immunizationUniversal immunization of children against the six vaccine-preventable diseases -tuberculosis, diphtheria, whooping cough, tetanus, polio, and measles - is crucial to reducinginfant and child mortality. Disparities in immunization coverage among subgroups of thepopulation are integral to informing programme planning and targeting resources to the areaswith the greatest need. Additionally, information on immunization coverage is important formonitoring and evaluation of the expanded programmes for Immunization (EPI). As the datain Figures 6.3 and 6.4 suggest, there is still a high percentage of children that have not beenimmunized, particularly in the Mid-western region specifically, and in the Mountain region ingeneral (CBS, 2004). In terms of socioeconomics, the poorest wealth quintile has the highestproportion of children who have not been immunized (CBS, 2004).Figure 6.3: Percentage of immunized children by regionSource: CBS, (2004)32

Health System Performance 2010Figure 6.4: Percentage of immunized children by ecological beltSource: CBS, (2004)The NDHS 2006 found that in total, 83 percent of children aged 12-23 months were fullyimmunized at the time of the survey. With regard to specific vaccines, 93 percent of childrenaged 12-23 months had received the BCG vaccination and 85 percent had been immunizedagainst measles. Coverage for the first dose of DPT was relatively high (93 percent), but only89 percent went on to receive the third dose of DPT. Ninety-seven percent of childrenreceived the first dose of the polio vaccine, and 91 percent went on to receive the third dose.Even though DPT and polio vaccines are often administered at the same time, polio coverageis higher than DPT coverage primarily due to the administration of polio vaccines duringnational immunization day campaigns. Nevertheless, the dropout between the first and thirddoses of polio is notable at 6 percent. Seventy-six percent of children aged 12-23 monthsreceived the first dose of the hepatitis B vaccine, but coverage dropped to 69 percent for thethird dose (NDHS 2006).The data also revealed that immunization coverage has grown over time. Unfortunately, thepercentage of children who did not receive any of the six basic immunizations fell from 20percent to 1 percent in 2001, but then tripled to 3 percent in 2006.Figure 6.5: Percentage of fully immunized childrenSource: MoHP et al (2007), (2002) and (1997)33

Health System Performance 2010Figure 6.6: Percentage of children never immunizedSource: MoHP et al (2007), (2002) and (1997)VII. ConclusionsPerforming an assessment of health system performance is critical to addressing health policyissues, and defines a set of measurable and reliable indicators. Careful consideration of thepossible approaches to measuring health system performance provides the basis forimproving outcomes. Health indicators such as life expectancy, infant/child mortality, andmaternal mortality, among others, show gradual but steady improvement. Overall healthsystem performance in terms of health production is quite encouraging in Nepal becauseunlike many developing countries, per capita income and government spending has provedeffective in changing health outcomes (Wagstaff & Claeson, 2004). Public spending plays amajor role in the planning, regulation, motivation, facilitation, and shaping of the health careservice delivery system. The evidence suggests that money matters in health care, but thatmoney alone is no guarantee of efficient, equitable, and effective health care. There are stilllarge inequalities in access, utilization, and coverage of health services across geographicalregions and socioeconomic groups. Intermediate outputs, particularly immunizationcoverage, services coverage, safe motherhood, and utilization of public health services havenot shown encouraging progress in recent years. Improvement of institutional capacity indelivery of health services can shift the health production function and ensure equity in healthcare services across the regions. Institutional capacity includes not only public providers, butalso how to make better use of private capacity to improve health outcomes.Relatively low efficiency in health production function with negative synergic effects occursin the Mid-western and Far Western regions. Similarly, health inequalities are relativelyhigher where less efficiency of health production appears. The evidence clearly shows thatequity and efficiency are not in conflict in the Nepalese health system. Allocation ofresources according to need can improve both the equity and efficiency of health outputs;however, a blanket policy may not have such capacity. Health care financing has the power toreform health care delivery organizations and provide incentives to providers to deliver moreefficient and effective health care.34

Health System Performance 2010ReferencesAbouZahr C and Wardlaw T (2001) Bulletin of the World Health Organization, 2001, 79:61–568.Acharya L and Cleland J (2000) Maternal and Child Health Services in Rural Nepal: DoesAccess or Quality Matter More? Health Policy and Planning; 15(2): 223–229.Adhikari S. R. and Maskay, N. M. (2004) Health Sector Policy in the First Decade of Nepal’sMultiparty Democracy; Does Clear Enunciation of Health Priorities Matter? Health Policy,68 (2004) 103-112.Central Bureau of Statistics (CBS), International Centre for Integrated MountainDevelopment (ICIMOD/MENRIS) with the support of SNV-Nepal (2003) Districts Of NepalIndicators Of Development , Kathmandu Nepal.Central Bureau of Statistics (CBS, 2004) Nepal Living Standards Survey 2003/04: StatisticalReport Volume one and two Central Bureau of Statistics, National Planning CommissionSecretariat, Government of Nepal, December 2004.Ensor T. and Cooper S. (2004) Overcoming barriers to health service access: influencing thedemand sideHealth Policy and Planning; 19(2): 69–79.Filmer, Deon and Lant Pritchett. “The impact of public spending on health: does moneymatter?” Social Science & Medicine. 49 (1999) 1309 - 1329.Government of Nepal, Ministry of health (1999) Second Long Term Health Plan (1997-2017), HMG/N, Ministry of Health, Kathmandu, Nepal.____. (2003), Health Sector Strategy: An agenda for reform HMG/N, Ministry of Health,Kathmandu, Nepal.____.(2004)Nepal Health Sector Programme- Implementation Plan” (NHSP-IP), HMG/N,Ministry of Health, Kathmandu, Nepal.______, National Planning Commission, 2003, The Tenth Plan (2002-07), National PlanningCommission/His Majesty’s Government of Nepal.Jamison, D T (2006) Investing in Health Disease Control Priorities in Developing Countriessecond edition, Oxford University Press and The World Bank.Ministry of Finance (MOF) (2009) Economic Survey Kathmandu, Nepal: Ministry ofFinance, Government of Nepal.Ministry of Health and Population (MoHP) (2007), Department of health services AnnualReport 2062/063 (2005/2006) Ministry of Health and Population, Department of HealthServices.Ministry of Health and Population (MoHP) (2008), Department of health services AnnualReport 2061/062 (2004/2005) Ministry of Health and Population, Department of HealthServices.35

Health System Performance 2010Ministry of health and population (MoHP) (2009a) Public expenditure review on the healthsector Kathmandu, Nepal: Ministry of Health and Population, Government of Nepal.Ministry of Health and Population (MoHP) (2009b), Department of health services AnnualReport 2064/065 (2007/2008) Ministry of Health and Population, Department of HealthServices.Ministry of Health and Population (MoHP) [Nepal], New ERA, and Macro InternationalInc.(2007) Nepal Family and Health Survey 1997. Kathmandu, Nepal: Ministry of Health andPopulation, New ERA, and Macro International Inc.Ministry of Health and Population(MoHP) [Nepal], New ERA, and Macro InternationalInc.(2007) Nepal Demographic and Health Survey 2002. Kathmandu, Nepal: Ministry ofHealth and Population, New ERA, and Macro International Inc.Ministry of Health and Population(MoHP) [Nepal], New ERA, and Macro InternationalInc.(2007) Nepal Demographic and Health Survey 2006. Kathmandu, Nepal: Ministry ofHealth and Population, New ERA, and Macro International Inc.RTI International, ( 2008)Equity Analysis of Health Care Utilization and Outcomes.Research Triangle Park, NC, USA.RTI International, (2009) Cost and Equity Implications of Public Financing for HealthServices at District Hospitalsbudget analysis in Nepal. Research Triangle Park, NC, USA.Wagstaff A and Claeson M (2004) the Millennium Development Goals for Health: Rising Tothe Challenges World Bank. Washington DC.36

Health System Performance 2010AppendixEffectiveness of health system (intermediate health outputs) 1996/97 to 2007/08Intermediate HealthOutputs, 1996/97 to 2007/08 (Page 1 of 3)Fiscal YearExpanded Programme on Immunization Nutrition Acute Respiratory InfectionsBCGcoverage (%)DPT-3coverage (%)Polio-3coverage (%)Measlescoverage (%)Growthmonitoringcoverage as %of

Health System Performance 2010Intermediate Health Outputs, 1996/97 to 2007/08 (Page 2 of 3)Control of Diarrhoeal Diseases Safe Motherhood Family PlanningMalaria annual parasite incidence(API) per 1,000FiscalYear% of somedehydrationamong totalnew cases% of severedehydration amongtotal new casesCase fatalityrate/1,000

Health System Performance 2010Intermediate Health Outputs, 1996/97 to 2007/08 (Page 3 of 3)Tuberculosis Control ProgrammeLeprosy Control ProgrammeFiscal YearCase detectionrate* (%)Treatment success rate onDOTS* (%)New casedetection rate(NCDR) /10,000** Prevalence rate (PR)/10,000 **1996/97 48 50 3.5 5.9 101997/98 50 53 3.17 3.9 11.71998/99 62 64 7.8 8.7 8.71999/00 67 89 3.18 3.88 7.182000/01 69 89 2.44 3.43 8.432001/02 70 89 5.73 4.41 4.312002/03 71 90 3.24 3.04 3.952003/04 71 88 2.84 2.41 3.482004/05 70 88 2.41 2 3.522005/06 65 88 1.96 1.65 4.812006/07 70 89 1.65 1.45 5.562007/08 71 88 1.67 1.42 4.15Sources: Annual reports, various yearsDisability rate Grade 2 amongnew cases**39

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