Table Of ContentChumaetal.BMCPublicHealth2012,12:20
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RESEARCH ARTICLE Open Access
Does the distribution of health care benefits in
Kenya meet the principles of universal coverage?
Jane Chuma1,2*, Thomas Maina3 and John Ataguba4
Abstract
Background: The 58th World Health Assembly called for all health systems to move towards universal coverage
where everyone has access to key promotive, preventive, curative and rehabilitative health interventions at an
affordable cost. Universal coverage involves ensuring that health care benefits are distributed on the basis of need
for care and not on ability to pay. The distribution of health care benefits is therefore an important policy question,
which health systems should address. The aim of this study is to assess the distribution of health care benefits in
the Kenyan health system, compare changes over two time periods and demonstrate the extent to which the
distribution meets the principles of universal coverage.
Methods: Two nationally representative cross-sectional households surveys conducted in 2003 and 2007 were the
main sources of data. A comprehensive analysis of the entire health system is conducted including the public
sector, private-not-for-profit and private-for-profit sectors. Standard benefit incidence analysis techniques were
applied and adopted to allow application to private sector services.
Results: The three sectors recorded similar levels of pro-rich distribution in 2003, but in 2007, the private-not-for-
profit sector was pro-poor, public sector benefits showed an equal distribution, while the private-for-profit sector
remained pro-rich. Larger pro-rich disparities were recorded for inpatient compared to outpatient benefits at the
hospital level, but primary health care services were pro-poor. Benefits were distributed on the basis of ability to
pay and not on need for care.
Conclusions: The principles of universal coverage require that all should benefit from health care according to
need. The Kenyan health sector is clearly inequitable and benefits are not distributed on the basis of need.
Deliberate efforts should be directed to restructuring the Kenyan health system to address access barriers and
ensure that all Kenyans benefit from health care when they need it.
Background greaterneedforhealthcareisnotdisputed[3];theyhave
Achievinguniversal coverage currently dominates global worsehealthindicatorsandarelessinclinedtoreportill-
health debates. In 2005, the World Health Organization nessesbecausetheyperceivethemtobeanormalfeature
(WHO) resolution called for health systems to move of life [4], or to avoid taking time off income generating
towardsuniversalcoverage,whereeveryonehasaccessto activities [5]. Understanding the extent to which health
“key promotive, preventive, curative and rehabilitative carebenefitsaredistributedonthebasis ofneedforcare
health interventions for all at an affordable cost, thereby isthusanimportantpolicyquestion,whichhealthsystems
achieving equity in access” [1]. The 2010 World Health shouldaimtoaddress.
Reportwasalsodevotedtouniversalcoverage[2].Univer- BenefitIncidenceAnalysis(BIA)allowsanassessmentof
sal coverage involves among other things ensuring that the distribution of health care benefits across socio-eco-
healthcarebenefitsaredistributedonthebasisofneedfor nomic groups. Initially developed to assessthe incidence
careandnotonabilitytopay.Thefactthatthepoorhave of government spending [6], the technique has recently
beenapplied to bothpublicand private health sectors to
*Correspondence:[email protected] highlightoverallhealthsystemperformance[7].BIAstu-
1KenyaMedicalResearchInstitute(KEMRI)-WellcomeTrustResearch dies were initially conducted in low-income countries in
Programme,P.OBox230,Kilifi,Kenya
the1990s.Findingsfromthesestudiesrevealedthatpublic
Fulllistofauthorinformationisavailableattheendofthearticle
©2011Chumaetal;licenseeBioMedCentralLtd.ThisisanOpenAccessarticledistributedunderthetermsoftheCreativeCommons
AttributionLicense(http://creativecommons.org/licenses/by/2.0),whichpermitsunrestricteduse,distribution,andreproductionin
anymedium,providedtheoriginalworkisproperlycited.
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health care fundshardly reached thepoorinmostcoun- surveys collected comprehensive data on utilization of
tries [4,8,9]. While these studies were instrumental in health care services, including all visits made to health
highlightingthedistributionaspectsofvarioushealthsys- care providers in the recall period. Data on recurrent
tems, they have been criticized for using unreliable data health expenditure were sought frompublic expenditure
sources and applying crude estimation techniques, with review reports conducted by the Ministry of Health
limitedattentiontomethodsconsistency[10].Moreover, annuallyaspartoftrackinggovernmentresources.Expen-
these studies were conducted close to two decades ago, dituredatafortheprivatesectorwereestimatedfromthe
makingitimportanttoconductmorerigorousanalysisat household surveys using information on out-of-pocket
atimewhencountriesareconsideringimplementingvar- payments, mainly because private organizations are not
iousreformsto supportuniversalcoverage.Anotherlim- requiredtosubmittheirexpenditurereportstothecentral
itation of most BIA studies is that they are conducted at levelunlikethegovernmentfacilities,wherethesameare
onepointintimeanddonotallowforanyassessmentof easilyobtainedfromgovernmentreports.Itwasassumed
distribution changes over different periods. Also, most thatprivateproviderswilltransferalltheirexpensestothe
BIAstudiesdonotassesswhetherbenefitsaredistributed clientssincetheirgoalisprofitmaximization.Tovalidate
onthebasisofneed[7]. thisapproach,fourhospitals(2privateand2private-not-
This paper addresses some of these challengesby con- for profit) were approached to provide the authors with
ductingasystem-wideanalysisofthedistributionofhealth expendituredataandtherewerenosignificantdifferences
carebenefitsinKenyaandcompareschangesinthedistri- with expenditure data estimated through out-of-pocket
bution over two time periods. The paper documents the payments.Ethical approval wasobtainedfromtheKenya
distributionofhealth care benefitsacrosssocioeconomic MedicalResearchInstitute(Protocolnumber1609).
groupsandassessestheappropriatenessofthedistribution
(i.e.whetherbenefitsaredistributedonthebasisofneed). Data analysis
Thestudypresentsthemostcompleteperspectiveonthe Standard BIA studies estimate the value of subsidy
distribution ofhealthcarebenefitsinKenya andplaysan received from use of public health services. Benefits are
important role in highlighting inequities in the Kenyan estimated in this study using the approach described by
healthsystem. O’Donnell et al. (2008), with some adjustments to allow
for analysis of private sector services [7]. Briefly, BIA
Health care financing and deliveryin Kenya involvesthreesteps:(1)estimatingannualutilizationrates
HealthservicesinKenya are providedbyboth the public in relation to socioeconomic groups; (2) estimating unit
andprivatesector.The government isthe mainprovider costsperhealthservice(bothoutpatientvisitsandinpati-
ofhealthservicesowning 51% ofallhealthfacilities [11]. entdays), andmultiplyingtheunitcostsbyservicesused
The privatefor-profitowns34.3%oftotalfacilities, while todeterminethemonetarybenefitofeachservice;(3)the
theprivatenot-for-profit(largelyfaith-basedinstitutions) distribution of health benefits across socioeconomic
owns 14.8%. Households are the largest source of health groups is examined. Where the focus is on the govern-
funds in Kenya, contributing about 35.9% of total health mentsubsidy,out-of-pocket-paymentspaidbytheservice
expenditure [12]. Donor funds account for 31% of total usersaresubtractedfromtotalbenefits.Table2presents
healthcarefunding,whilegovernmentspendingaccounts theestimatedunitcostsfordifferentlevelsofcare.
for 29.3% [13]. About 50% of the public health budget is Households were classified into five socioeconomic
spent at the hospital level [14]. All government health groupsusingpercapitaexpenditure.Outpatientutilization
facilitieschargeuserfeesforservice.In2004,userfeesat rateswereconvertedintoannualutilizationbymultiplying
dispensaries and healthcenterswere replaced witha flat by thirteen [7,10]. Unit costs were estimated by dividing
consultation fee of Kenya shillings 10 (US$0.13) and 20 recurrentexpenditureforeachtypeoffacilitybyweighted
(US$0.26)respectively. utilizationrates.Forhospitalsthatprovidedinpatientand
outpatientcare,outpatientvisitswereconvertedintoinpa-
Methods tientdaysbydividingbythree.Thisratiohasbeenwidely
Data sources appliedintheliterature[15].
Datawereobtainedfrom nationallyrepresentative cross- Thereisnosingle acceptedmeasureofneed forhealth
sectionalhouseholdsurveysconductedbytheMinistryof care,althoughitiswidelyrecognizedthathealthcareneed
Healthin2003and2007.Thetwocross-sectionalsurveys varies acrosssocio-economic groups,ageandgender[3].
were designed in a similar way and used the same ques- Mortalityandmorbidityindicatorshavebeenwidelyused
tionnaire.Keyfeaturesofthesurveysaresummarizedon to indicate need, but their application in BIA is limited
Table 1. Data on outpatient visits were collected using a becausemostsurveysthatcapturemortality rarelyincor-
four-week recall period, while hospital admissions were poratehealthcareutilizationdata[7].Othervariablesfre-
collected for the one year preceding the surveys. Both quentlyusedtoindicateneedincludeutilizationofhealth
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Table 1Key featuresofthe household surveys
2003 2007
Numberofhouseholdsinterviewed:
(cid:129)Ruralhouseholds(%) 5,852(69.6) 5,810(68.7)
(cid:129)Urbanhouseholds(%) 2,552(30.4) 2,643(31.3)
Numberofindividuals
(cid:129)Male(%) 18,765(49.2) 18,787(49.2)
(cid:129)Female(%) 19,225(50.5) 19,436(50.9)
Individualsreportingillnessinthelastfourweeks(%) 6,279(16.5) 5621(14.7)
Individualshospitalizedinthelast12months(%) 504(1.5) 764(20.)
Individualsseeingpreventivecareinthelastfourweeks(%) 2,464(6.5) 1,644(4.3)
care services and self-reported illnesses, but these 2007 respectively (Table 1). Hospital admissions were
approacheshavebeencriticizedforfailingtocaptureneed reported among 1.5% of individuals in 2003 and 2.0% in
amongthepoorestpopulationwhodonotusehealthcare 2007. Preventive care was sought by 6.5% of individuals
servicesduetofinancial,geographicalandculturalbarriers in 2003 and 4.3% in 2007. Table 3 shows the distribu-
andwhotend to underreport illnessesdue todifferences tion of treatment seeking actions taken in the formal
in perceptions on ill health [5]. To address these limita- health sector. A total of 4,484 outpatient visits were
tions,needinthisstudywasmeasuredusingSelf-Assessed made to formal health care providers in 2003 compared
Health Status (SAHS). Individuals in the survey were to 4,736 in 2007. Government health facilities accounted
askedtoratetheirhealthcomparedtoothersoftheirage for 57.6% of all outpatient visits in 2003 and 74.3% in
and gender. Four categories of SHAS ranging from very 2007. Private clinics were the second largest source of
goodtopoorwereprovided.BorrowingfromAtagubaand outpatient care, accounting for 21.1% of visits in 2003
McIntyre2009,individualswereclassifiedintotwogroups and 12.1% in 2007. Inpatient care followed a similar pat-
ofneed:goodhealth(indicating no need forcare) ifthey tern with the majority of hospitalizations occurring in
reportedtheirhealth statusto beverygoodorgood; and government hospitals (72.4% in 2003; 67.5% in 2007).
poor health (indicating need for care) if they reported
theirhealthstatustobesatisfactoryorfair. Distribution of outpatient and inpatient benefits by
sector
Results The distribution of health care benefits is presented in
Self reported illnesses and treatment seeking patterns Table4.Publicprimaryhealthcareservices(PHC)bene-
Illnesses in the four weeks preceding the survey were fits showed a pro-poor distribution, with the poorest
reported by 16.5% and 14.7% of individuals in 2003 and quintile receiving 25.4% share of benefits in 2003 and
Table 2Unitcosts by facility type in KenyaShillings
2003 2007
Facilitytype
Outpatient Inpatient Outpatient Inpatient
Governmentfacilities
(cid:129)PHCfacilities 97.5 - 114.1 -
(cid:129)Districtandprovincialhospitals n.a* n.a 366.4 1099.6
(cid:129)Teachingandreferralhospitals n.a n.a 963.2 2889.5
(cid:129)Allgovernmenthospitals 508.5 1523.0 435.2 1306.1
Privatenot-for-profit
(cid:129)PHCfacilities 266.8 - 276.3 -
(cid:129)Hospitals 413.6 1240.9 463.9 13918
Privateforprofit
(cid:129)Clinics 382.6 - 540.9 -
(cid:129)Hospitals 568.7 1706 551.5 1670.6
*n.a.meansthatdatawerenotavailabletodistinguishbetweengovernmentfacilities
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Table 3Distribution ofhealth careactions formalcare hospitals outpatient and inpatient benefits in 2003,
2003 2007 while in the same year they received 15.6% and 19.7% of
outpatient and inpatient benefits respectively from the
Actionsn(%) Outpatient Inpatient Outpatient Inpatient
private not-for-profit hospitals. Private for-profit sector
GovernmentPHC 1,418(31.6) n.a* 1,726(37.7) n.a
benefits showed a wider pro-rich distribution with the
Governmenthospitals 1,169(26.0) 333(72.4) 1,672(36.5) 583(67.5)
richest quintile receiving 40.5% and 45.5% of outpatient
Private-not-for-profit 278(6.2) n.a 162(3.5) n.a
and inpatient benefits in 2007.
PHC
To assess differences within the public health sector,
Private-not-for-profit 182(4.1) 58(12.7) 191(4.2) 127(14.7)
hospitals the 2007 results were categorized into different levels of
care. Results show a positive relationship between the
Privateclinics 947(21.2) n.a 554(12.1) n.a
pro-rich distribution and level of care (Figure 1). The
Privatehospitals 490(10.9) 68(14.9) 431(9.4) 153(17.7)
richest quintile received 63.5%, 23.5% and 26.0% share
Totalactions 4,484(100) 457(100) 4,763(100) 863(100)
of outpatient benefits for tertiary, provincial and district
*n.a.meansfacilitydoesnotprovideinpatientservices
level facilities respectively. In contrast, the poorest quin-
tile received 2.5%, 4.7% and 14.8% share of tertiary, pro-
25.7% in 2007. The concentration index indicates a vincial and district level outpatient benefits respectively.
greaterpro-poordistributionin2007(CI=-0.148),com-
pared to 2003 (CI = -0.105). Private not-for-profit PHC Distribution of total health care benefits
benefits showed a pro-rich distribution in 2003 (CI = Whenbenefitsforeachsectorarecombinedtoarriveatan
0.021)andpro-poorin2007(CI=-0.115).Benefitsfrom overall sector distribution, results reveal similar patterns
privateclinicsshowapro-richpatterninbothtimeperi- forthepublic,private-not-for-profitandprivate-for-profit
ods, although the pro-rich distribution was greater in sectorsin2003; althoughsomedifferenceswerenotedin
2007thanin2003(CI=0.051in2003;0.102in2007). 2007(Figures2and3).Overall,in2003, about50%ofall
Hospital level out-patient (OP) and inpatient (IP) ben- hospitallevelbenefitsineachsectorwerereceivedbythe
efits in all sectors were pro-rich in 2003, but in 2007, richesttwoquintiles(CI=0.105forpublicfacilities;0.088
private not-for-profit service benefits were pro-poor. forprivate-not-for-profit;0.117forprivate-for-profitfacil-
The poorest quintile received 13.4% and 9.5% of public ities).In2007,thisproportionreducedto42.1%forpublic
Table 4Distribution ofhealth carebenefits across socioeconomic groups
Publichealthfacilities Private-not-forprofitfacilities Private-for-profitfacilities
PHC Hospital Hospital PHC Hospital Hospital PHC Hospital Hospital
outpatient inpatient outpatient inpatient outpatient inpatient
2003survey
1 25.4 13.4 9.5 16.5 15.6 19.7 17.1 11.7 13.0
(Poorest)
2 21.6 15.7 18.5 19.0 17.0 9.0 23.0 15.1 13.1
3 18.4 15.5 23.1 19.9 10.0 27.0 15.4 17.8 10.2
4 20.8 26.4 29.4 26.6 26.6 29.7 20.1 27.0 28.5
5 13.8 29.0 19.5 18.0 30.8 14.7 23.9 28.5 35.3
(Richest)
CI -0.105 0.166 0.119 0.021 0.186 0.025 0.051 0.177 0.279
p-value 0.003 0.000 0.04.3 0.699 0.031 0.804 0.262 0.000 0.038
2007survey
1 25.7 11.5 14.0 23.4 25.3 30.7 13.4 12.2 11.0
(Poorest)
2 25.7 9.9 21.3 18.7 16.8 16.7 19.7 14.3 7.2
3 20.5 20.2 20.8 32.6 20.7 9.8 14.8 15.5 21.4
4 16.2 25.5 20.8 15.3 15.2 29.8 27.9 17.3 14.9
5 12.0 32.9 23.0 10.3 22.0 12.5 24.2 40.3 45.5
(Richest)
CI -0.148 0.221 0.068 -0.115 -0.055 -0.095 0.102 0.253 0.312
p-value 0.000 0.000 0.103 0.144 0.484 0.379 0.025 0.000 0.000
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Figure1Distributionofpublicsectorbenefitsbyhospitalcategory(2007).
sectorbenefitsand36.8%forprivate-not-for-profitbene- the subsidy derived from public health care spending
fits,whileitincreasedto55.6%forprivate-for-profitbene- and the mean per capita subsidy across socioeconomic
fits.Whenbenefitsforeachsectorarecombinedtoarrive groups. The results reveal a similar pattern as previously
attotalhealthsystemdistribution,theresultsindicatethat observed before out-of-pocket payments were subtracted
theKenyanhealthsystemisgenerallypro-rich.Therichest from health care benefits. Public health care benefits
two quintiles received a 50.2% share of total health sys- were pro-poor in 2003 (CI = -0.098) and 2007 (CI =
temsbenefitsin2003(CI=0.109)and46.7%shareoftotal -0.17), although differences across socioeconomic status
healthsystembenefitsin2007(CI=0.077). in 2003 were not statistically significant (p = 0.139).
Hospital level subsidy was mainly pro-rich for both time
Distribution of government subsidy periods, except the inpatient subsidy that indicated a
Estimating the incidence of public health spending pro-poor pattern in 2007 (CI = -0.031). Total govern-
requires that out-of-pocket payments are subtracted ment subsidy for all levels of care were pro-rich in 2003
from total benefits. Table 5 shows the distribution of (CI = 0.08; p = 0.035), but differences across socio-
(cid:1005)(cid:1004)(cid:1004)
(cid:1012)(cid:1004) (cid:28)(cid:395)(cid:437)(cid:258)(cid:367)(cid:349)(cid:410)(cid:455)(cid:3)(cid:367)(cid:349)(cid:374)(cid:286)
(cid:286)(cid:296)(cid:349)(cid:410)(cid:400)
(cid:374)
(cid:286)
(cid:381)(cid:296)(cid:3)(cid:271) (cid:1010)(cid:1004) (cid:272)(cid:437)(cid:373)(cid:373)(cid:437)(cid:367)(cid:258)(cid:410)(cid:349)(cid:448)(cid:286)(cid:3)(cid:400)(cid:346)(cid:258)(cid:396)(cid:286)(cid:3)(cid:381)(cid:296)(cid:3)
(cid:258)(cid:396)(cid:286)(cid:3) (cid:410)(cid:381)(cid:410)(cid:258)(cid:367)(cid:3)(cid:3)(cid:393)(cid:437)(cid:271)(cid:367)(cid:349)(cid:272)(cid:3)(cid:400)(cid:286)(cid:272)(cid:410)(cid:381)(cid:396)(cid:3)
(cid:346)
(cid:286)(cid:3)(cid:400) (cid:1008)(cid:1004)
(cid:448)
(cid:258)(cid:410)(cid:349) (cid:272)(cid:437)(cid:373)(cid:373)(cid:437)(cid:367)(cid:258)(cid:410)(cid:349)(cid:448)(cid:286)(cid:3)(cid:400)(cid:346)(cid:258)(cid:396)(cid:286)(cid:3)(cid:381)(cid:296)(cid:3)
(cid:437)(cid:367) (cid:410)(cid:381)(cid:410)(cid:258)(cid:367)(cid:3)(cid:3)(cid:393)(cid:396)(cid:349)(cid:448)(cid:258)(cid:410)(cid:286)(cid:882)(cid:374)(cid:381)(cid:410)(cid:882)(cid:296)(cid:381)(cid:396)(cid:3)
(cid:373) (cid:1006)(cid:1004)
(cid:373) (cid:393)(cid:396)(cid:381)(cid:296)(cid:349)(cid:410)(cid:3)
(cid:437)
(cid:18)
(cid:272)(cid:437)(cid:373)(cid:373)(cid:437)(cid:367)(cid:258)(cid:410)(cid:349)(cid:448)(cid:286)(cid:3)(cid:400)(cid:346)(cid:258)(cid:396)(cid:286)(cid:3)(cid:381)(cid:296)(cid:3)
(cid:1004) (cid:410)(cid:381)(cid:410)(cid:258)(cid:367)(cid:3)(cid:3)(cid:393)(cid:396)(cid:349)(cid:448)(cid:258)(cid:410)(cid:286)(cid:882)(cid:296)(cid:381)(cid:396)(cid:3)(cid:393)(cid:396)(cid:381)(cid:296)(cid:349)(cid:410)(cid:3)
(cid:1004) (cid:1006)(cid:1004) (cid:1008)(cid:1004) (cid:1010)(cid:1004) (cid:1012)(cid:1004) (cid:1005)(cid:1004)(cid:1004)
(cid:18)(cid:437)(cid:373)(cid:373)(cid:437)(cid:367)(cid:258)(cid:410)(cid:349)(cid:448)(cid:286)(cid:3)(cid:400)(cid:346)(cid:258)(cid:396)(cid:286)(cid:3)(cid:381)(cid:296)(cid:3)(cid:393)(cid:381)(cid:393)(cid:437)(cid:367)(cid:258)(cid:410)(cid:349)(cid:381)(cid:374)(cid:3)(cid:396)(cid:258)(cid:374)(cid:364)(cid:286)(cid:282)(cid:3)(cid:296)(cid:396)(cid:381)(cid:373)(cid:3)(cid:393)(cid:381)(cid:381)(cid:396)(cid:286)(cid:400)(cid:410)(cid:3)(cid:410)(cid:381)(cid:3)(cid:396)(cid:349)(cid:272)(cid:346)(cid:286)(cid:400)(cid:410)
Figure2Distributionoftotalbenefitsbysector(2003).
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(cid:1005)(cid:1004)(cid:1004)
(cid:286)(cid:296)(cid:349)(cid:410)(cid:400) (cid:1012)(cid:1004) (cid:28)(cid:395)(cid:437)(cid:258)(cid:367)(cid:349)(cid:410)(cid:455)(cid:3)(cid:367)(cid:349)(cid:374)(cid:286)
(cid:374)
(cid:286)
(cid:271)
(cid:258)(cid:396)(cid:286)(cid:3)(cid:381)(cid:296)(cid:3) (cid:1010)(cid:1004) (cid:272)(cid:437)(cid:373)(cid:373)(cid:437)(cid:367)(cid:258)(cid:410)(cid:349)(cid:448)(cid:286)(cid:3)(cid:400)(cid:346)(cid:258)(cid:396)(cid:286)(cid:3)(cid:381)(cid:296)(cid:3)
(cid:448)(cid:286)(cid:3)(cid:400)(cid:346) (cid:1008)(cid:1004) (cid:410)(cid:381)(cid:410)(cid:258)(cid:367)(cid:3)(cid:3)(cid:393)(cid:437)(cid:271)(cid:367)(cid:349)(cid:272)(cid:3)(cid:400)(cid:286)(cid:272)(cid:410)(cid:381)(cid:396)
(cid:258)(cid:410)(cid:349)
(cid:437)(cid:367) (cid:272)(cid:437)(cid:373)(cid:373)(cid:437)(cid:367)(cid:258)(cid:410)(cid:349)(cid:448)(cid:286)(cid:3)(cid:400)(cid:346)(cid:258)(cid:396)(cid:286)(cid:3)(cid:381)(cid:296)(cid:3)
(cid:373)
(cid:373) (cid:1006)(cid:1004) (cid:410)(cid:381)(cid:410)(cid:258)(cid:367)(cid:3)(cid:3)(cid:393)(cid:396)(cid:349)(cid:448)(cid:258)(cid:410)(cid:286)(cid:882)(cid:374)(cid:381)(cid:410)(cid:882)(cid:296)(cid:381)(cid:396)(cid:3)
(cid:18)(cid:437) (cid:393)(cid:396)(cid:381)(cid:296)(cid:349)(cid:410)
(cid:272)(cid:437)(cid:373)(cid:373)(cid:437)(cid:367)(cid:258)(cid:410)(cid:349)(cid:448)(cid:286)(cid:3)(cid:400)(cid:346)(cid:258)(cid:396)(cid:286)(cid:3)(cid:381)(cid:296)(cid:3)
(cid:1004)
(cid:410)(cid:381)(cid:410)(cid:258)(cid:367)(cid:3)(cid:3)(cid:393)(cid:396)(cid:349)(cid:448)(cid:258)(cid:410)(cid:286)(cid:882)(cid:296)(cid:381)(cid:396)(cid:3)(cid:393)(cid:396)(cid:381)(cid:296)(cid:349)(cid:410)(cid:3)
(cid:1004) (cid:1006)(cid:1004) (cid:1008)(cid:1004) (cid:1010)(cid:1004) (cid:1012)(cid:1004) (cid:1005)(cid:1004)(cid:1004)
(cid:18)(cid:437)(cid:373)(cid:373)(cid:437)(cid:367)(cid:258)(cid:410)(cid:349)(cid:448)(cid:286)(cid:3)(cid:400)(cid:346)(cid:258)(cid:396)(cid:286)(cid:3)(cid:381)(cid:296)(cid:3)(cid:393)(cid:381)(cid:393)(cid:437)(cid:367)(cid:258)(cid:410)(cid:349)(cid:381)(cid:374)(cid:3)(cid:396)(cid:258)(cid:374)(cid:364)(cid:286)(cid:282)(cid:3)(cid:296)(cid:396)(cid:381)(cid:373)(cid:3)(cid:393)(cid:381)(cid:381)(cid:396)(cid:286)(cid:400)(cid:410)(cid:3)(cid:410)(cid:381)(cid:3)(cid:396)(cid:349)(cid:272)(cid:346)(cid:286)(cid:400)(cid:410)
Figure3Distributionoftotalbenefitsbysector(2007).
economic groups in 2007 were not statistically signifi- total expenditure, the results indicate a progressive dis-
cant (CI = -0.001; p = 0.960). tribution (i.e. the poor received a subsidy that was a lar-
Mean per capita subsidy was higher in 2007 than in ger proportion of their expenditure compared to that
2003 for all socioeconomic groups. In 2003, the poorest received by the richest population).
quintile received the lowest per capita subsidy of KES
125.6 but in 2007, mean per capita subsidy was lowest Distribution of benefits according to need
among the richest population (KES 170.6). Although the A limitation of most BIA studies is their failure to assess
distribution of government subsidy was pro-rich, when the extent to which benefits are distributed according to
the subsidy is expressed as a proportion of household need. Figure 4 compares the distribution of total health
Table 5Distribution ofgovernment subsidy (percentage share)
PHC Hospitals Hospitals Total Meanpercapitasubsidyin Subsidyas%ofconsumption
outpatient inpatient subsidy KES expenditure
2003survey
1 25.2 16.8 11.2 15.8 125.6 3.0
(Poorest)
2 18.7 17.1 14.3 16.4 130.3 1.4
3 21.8 15.1 26.0 19.6 155.9 1.1
4 22.6 28.0 30.9 28.4 225.8 0.9
5 11.6 23.0 17.5 19.8 157.9 0.2
(Richest)
CI -0.098 0.092 0.120 0.080 0.080 -0.375
p-value 0.139 0.000 0.174 0.035 0.032 0.000
2007survey
1 26.7 12.8 19.4 19.4 194.9 4.7
(Poorest)
2 26.2 11.2 21.7 19.5 195.9 2.2
3 19.7 20.2 20.1 19.8 197.1 1.3
4 16.2 28.5 23.1 23.5 232.6 0.9
5 11.3 27.3 15.7 17.8 170.6 0.2
(Richest)
CI -0.17 0.176 -0.031 -0.001 -0.001 -0.461
p-value 0.000 0.000 0.430 0.960 0.741 0.000
Chumaetal.BMCPublicHealth2012,12:20 Page7of9
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Figure4Distributionofbenefitsandneedforcare.
system benefits with the need for care (based on SAHS). implementedtoensurethatprimaryhealthcarefacilities
The results show that the share of self-assessed need offer quality services (including transferring funds
differed significantly across socioeconomic groups (p < directly from the treasury to facilities’ bank accounts to
0.001 in 2003; 0.08 in 2007). The poorest quintile minimize delays experienced when they are channeled
reported the highest share of need for care in both time through the health ministry). While these funds are
periods (27.1% and 21.6% in 2003 and 2007 respec- expectedto promote accesstoPHCservicesforall,care
tively), but received the lowest share of benefits (14.6% should be taken to ensure that the poorest populations,
in 2003 and 17.1% in 2003 and 2007). In contrast, the who bear the greatest burden of ill-health, continue to
richest quintile received benefits that were significantly benefitfromtheseservices.
higher than their share of need. Differences in the share
of benefits received across socio-economic groups were Hospital level services are pro-rich, but larger disparities
statistically significant (p < 0.001). are recorded in outpatient compared to inpatient services
Hospitallevelservices werepro-rich,excepttheprivate-
Discussion not-for-profitsectorthatshowedapro-poordistribution
Primary health care facilities are pro-poor in 2007. Outpatient services were more pro-rich than
Thetwopoorestquintilesreceivedabouthalfofthepub- inpatientservicesinthepublicandprivate-not-for-profit
licsectorPHCbenefitsinbothtimeperiods.Therewere sectors. These findings differ from others that have
nosignificantdifferencesinthedistributionofPHCben- reportedamorepro-richdistributionforinpatientcom-
efits in the private-not-for-profit sector between 2003 pared to outpatient services [4,16,17]. The richest quin-
and 2007, although the 2007 results suggest a shift tile received two-thirds and about a quarter of tertiary
towardspro-poordistribution.Thegreaterpro-poordis- leveloutpatientandinpatientbenefitsrespectively,while
tribution of public PHC benefits reported in 2007could provincial and district hospitals mainly served middle-
beattributedtoauserfeereductionpolicyintroducedin income groups. Healthcare resourcesin Africaare con-
2004, where variable user fees in government dispen- centrated at the hospital level [4,14,18]. Kenya spends
saries and health centers were abolished and replaced over 50% of the public health budget on hospitals ser-
withaflatrateofKenya Shillings10and20respectively. vices[14];theseresources,asclearlydemonstratedbythe
Studiesinlowand middleincomecountrieshaveshown findings, mainly benefit the two richest quintiles. Pre-
thatthepoorestpopulationtendstousePHCmorethan viousstudieshavearguedthatincountrieswherethepri-
the rich [4,10]. These results have led for calls to direct vate sector is well developed, government subsidies can
additionalfunds toprimaryhealthcareservicesasaway be better targeted towards the poor, by diverting the
of promoting equity. The Kenyan government regards demandforhealthcarefortherichpopulationtothepri-
primary health care facilities as an important part of vatesector[4].Ourfindingssuggestthatthisisnoteasily
the health system and various reforms have been achieved. Kenya has had a very developed private sector
Chumaetal.BMCPublicHealth2012,12:20 Page8of9
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for the last two decades, but public hospital services country like Kenya, where there is a significant private
remain pro-rich. Alternative strategies to ensure that sector, and where people access public services on the
resources allocated to public hospitals benefit everyone basis of ability to pay, questions regarding the role
whoneedsthemarerequired. played by the public health system in addressing inequi-
ties remain.
The public and private health sector recorded a similar
magnitude of inequalities in 2003 but differences across The distribution of benefits is inappropriate
sectors were observed in 2007 The poorest population is in greater need of health ser-
Thedistributionoftotalbenefitsin2003revealedasimilar vices than the richest population, and should therefore
magnitude of inequalities across the three sectors under receive the largest share of health system benefits [3].
consideration. The richest two quintiles received more Results confirm that the poorest Kenyans have greater
thanhalfoftotalbenefitsineachsector.However,thedis- health needs, but they receive the least share of total
tribution of health care benefits in 2007 clearly distin- health system benefits. Few studies assess whether the
guished between the three sectors; the private not-for- distribution of health system benefits match need for
profitsectorshowedapro-poordistribution,publicsector care. A study conducted in the United States reported
benefits approachedequality,while the private for-profit that the distribution of public spending favored those
sectorwas very pro-rich. Few studies have compared the with higher need for care and increased strongly with
distribution of benefits for the entire health system. The health need [19], while in South Africa the distribution
onlystudythatdocumentsdistributionofbenefitsinboth of health sector benefits did not match need for care
publicandprivatesectorsrevealwiderinequalitiesinthe [16]. Countries should work towards restructuring their
privatesectorcomparedtothepublicsector[16].Private health systems in a manner that removes the main bar-
healthcarefacilitiesareperceivedtohavegreaterinequi- riers of access (including but not limited to affordability,
ties than the public health system [3]. Our findings availability and acceptability) to ensure that all people
demonstratethatinsomecases,thedegreeofinequalities can access care when they need it.
canbesimilarinallsectors.Itisnotclearwhythispattern
was observed in 2003, considering that private services Limitations
oftenchargehigherfeesthangovernmentfacilities.What This study has several limitations. First, BIA does not
is clear though is that neither the public nor the private account for differences in quality of care. Quality differ-
sectorscateredfortheneedsofthepoorin2003,although ences exist between facilities. The poorest population
the 2007 data suggest some improvementsinpublic and might be using lower quality services than the richest
private-not-for-profitsectors. population, suggesting that benefits received by the poor
would be much lower if quality differences were
Government subsidy records a similar distribution accounted for. Second, seasonality is an important factor
The distribution of government subsidy follows a pat- influencing levels of self reported illnesses, treatment
tern similar to the benefits, with the poorest population seeking behavior and health care costs [20,21]. The ana-
receiving a larger share of PHC subsidy compared to lysis did not account for seasonal variations and there-
hospital level subsidy. When the subsidy is expressed as fore annual utilization rates may be overestimated
a percentage of households’ consumption expenditure (underestimated) depending on the household surveys
the poor receive a subsidy that accounts for a higher timings. Thirdly, outpatient days were converted into
proportion of expenditure compared to the richest inpatient day by divided by three. This approach can
population. Although governments subsidize health ser- have implications for cost levels. Fourthly, need in this
vices in many countries, evidence suggests that the rich study is measured through SAHS. This measure does
benefit from government subsidies more than the poor. not tell the equidistance between categories, although it
A study conducted in 21 countries revealed that the has been shown that standardized measures of need
richest 20% of the population received 26% of total gov- compare well with SAHS categories [22]. Finally, multi-
ernment subsidies, compared to 16% received by the ple measures of need exist, some of which suggest that
poorest 20% [8]. In a review of the distribution of gov- the rich might have greater need in relation to non-
ernment subsidy on health, Chu et al. 2000 reported communicable diseases. Future studies should compare
that public health expenditure was well targeted in 21 appropriateness of health system benefits distribution
out of 38 studies and that the poorest 20% received using different indicators of need.
more than the richest 20% when the subsidy is
expressed as a percentage of their income or expendi- Conclusions
ture (i.e. progressive distribution). Sub-Saharan African The principles of universal coverage require that all
countries performed poorly for all levels of care. In a should benefit from health care according to need [23].
Chumaetal.BMCPublicHealth2012,12:20 Page9of9
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The Kenyan health sector is clearly inequitable and ben- 10. O‟DonnellO,vanDoorslaerE,R-EP,SomanathanA,AdhikariS,
efits are not distributed on the basis of need. Deliberate HarbiantoD,GargC,HanvoravongchaiP,HuqM,KaranA,etal:The
IncidenceofPublicSpendingonHealthcare:ComparativeEvidencefrom
efforts should be directed to restructuring the Kenyan
Asia.WorldBankEconomicReview2007,21:93-123.
health systems to address access barriers and ensure 11. MinistryofMedicalservices:Factsandfiguresonhealthandhealth
that all Kenyans benefit from health care when they relatedindicators.2008.
12. GovernmentofKenya,HealthSystems2020Project:KenyaNationalHealth
need it.
Accounts2005/2006.Bethesda,MD:HealthSystems20/20project,Abt
AssociatesInc;2009.
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expenditurereview2009.2010.
1These are small clinics, usually operating in one or two
14. GlenngardAH,MainaTM:Reversingthetrendofweakpolicy
rooms by a single health professional, either a nurse, implementationintheKenyanhealthsector?-astudyofbudget
clinical officer and in few cases medical officers. A few allocationandspendingofhealthresourcesversussetpriorities.Health
ResPolicySyst2007,5:3.
have laboratories operated by a technician who has
15. BarnumH,KutzinJ:PublicHospitalsinDevelopingCountries:Resource
some ‘partnership’ with the owner of the clinic. Use,Cost,Financin.Baltimore,MD:JohnsHopkinsUniversityPressforthe
2Data on hospital category were not available for the WorldBank;1993.
16. AtagubaJ,McIntyreD:FinancingandbenefitincidenceintheSouth
2003 survey.
Africanhealthsystem:Preliminaryresults.WorkingPaper09-1CapeTown:
HealthEconomicsUnit,UniversityofCapeTown;2009.
17. Castro-LealF:Theimpactofpublichealthspendingonpovertyandinequality
Acknowledgements inSouthAfricWashingtonDC:PovertyandSocialPolicyDepartment,World
JCissupportedbytheWellcomeTrust,UK(#084516).Wearegratefulto Bank;1996.
ProfessorDianeMcIntyreforhersupportinthestudydesignandfor 18. DiderichsenF:Resourceallocationforhealthequity:issuesandmethods.
commentingondrafts.Thispaperispublishedwiththepermissionofthe InHNPDiscussionPaperWashington,DC:WorldBank;2004.
directorKEMRI. 19. SeldenTM,SingM:Thedistributionofpublicspendingforhealthcarein
theUnitedStates,2002.HealthAff(Millwood)2008,27:w349-359.
Authordetails 20. ChumaJM,ThiedeM,MolyneuxCS:Rethinkingtheeconomiccostsof
1KenyaMedicalResearchInstitute(KEMRI)-WellcomeTrustResearch malariaatthehouseholdlevel:evidencefromapplyinganewanalytical
Programme,P.OBox230,Kilifi,Kenya.2CentreforTropicalMedicine,Nuffield frameworkinruralKenya.MalarJ2006,5:76.
DepartmentofClinicalMedicine,UniversityofOxford,Headington,Oxford, 21. SauerbornR,NougtaraA,HienM,DiesfeldHJ:Seasonalvariationsof
UK.3MinistryofMedicalServices,Kenya.4HealthEconomicsUnit, householdcostsofillnessinBurkinaFaso.SocSciMed1996,43:281-290.
DepartmentofPublicHealthandFamilyMedicine,UniversityofCapeTown, 22. O’DonnellO,vanDoorslaerE,WagstaffA,LindelowM:AnalyzingHealth
Rondebosch,7701CapeTown,SouthAfrica. EquityUsingHouseholdSurveyData:AGuidetoTechniquesandTheir
ImplementationWashington,D.C:TheWorldBank;2008.
Authors’contributions 23. WorldHealthOrganisation:Sustainablehealthfinancing,universal
JCwasresponsiblefortheoveralldesignofthestudy.TMassistedin coverageandsocialhealthinsurance.InEB115R132005.
sourcingthedata,cleaningandanalysis.JCandJAwereinvolvedinthe
analysisandwritingup.Allauthorsreadandapprovedthemanuscript. Pre-publicationhistory
Thepre-publicationhistoryforthispapercanbeaccessedhere:
Competinginterests http://www.biomedcentral.com/1471-2458/12/20/prepub
Theauthorsdeclarethattheyhavenocompetinginterests.
doi:10.1186/1471-2458-12-20
Citethisarticleas:Chumaetal.:Doesthedistributionofhealthcare
Received:16August2011 Accepted:10January2012
benefitsinKenyameettheprinciplesofuniversalcoverage?BMCPublic
Published:10January2012
Health201212:20.
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