FACILITATOR’SNOTESON:

“NationalHealthAccountsandtheirusein informinghealthsectorreform”

1. Objectivesofcasestudy:

•To“demystify”theprocessof NationalHealthAccounts(NHA)datacollectionand matrixcompilation;

•ToprovideinsightsintodatasourcesforNHAandtohighlightpotentialproblems withsomedatasources;

•Todevelopskillsinextrapolatingcertainexpenditureestimatesandincompiling

NHAmatrices;

•Tohighlightpotentialareasofdouble-countingwhencompilingNHAmatrices;

•TodevelopskillsinanalysingNHAdatatoassesshealthsystemperformanceto informhealthsectorreforminitiatives;

•To illustratehownon-financialdatacanassistin obtainingamorecomprehensive healthsystemanalysis.

2. Keyissuestocoverbeforeusingcasestudy:

Itisusefultoprovideabitofbackground informationonNationalHealthAccounts (NHAs)beforeusingthiscasestudy. Thisdoesnotneedtobeparticularly longor detailed,butshouldasaminimumcoverthefollowinginformation:

•WhatareNHAs–whatinformationdotheyincludeandwhataretheyusedfor;

and

•Thedistinctionbetweenhealthcarefunding‘sources’,‘financingintermediaries’ and‘uses’(andthedifferentcategoriesofpresenting‘uses’information, suchas providercategories,lineitems,geographicareas,etc.)

3. Overviewofcasestudy:

Thiscasestudytakesapproximately2hourstocomplete. Calculatorsshouldbe madeavailabletoparticipants. Theyshouldworkinsmallgroups,consistingof between 2to5people–thesizeofthegroupcanbebasedonthetotalnumber of participantsandtheavailableseatingarrangements.

Therearethreecomponentsorphasestothiscasestudy:

1. Participantsareprovidedwithexpendituredataandtheyarerequiredtocompile afinancingintermediariestoprovidersmatrix;

2. Participantsarethenrequiredtodiscussandanalysetheseresults;

3. Participantsareprovidedwithadditional,non-financial dataandrequestedto discussandanalysethisinformation.

Onecaneitherhaveaplenarydiscussionattheendofallthreecomponents ofthe casestudy,oraplenarydiscussionaftereachstage(discussingthecalculationsafter thefirststageanddiscussingtheanalysis conductedineachofthesecondandthird stages).

4. Phase1

Participantsshouldbehandedthefirst5pagesofthecasestudy,i.e.thecover sheet,thethreepageswithfinancingandexpenditure dataandtheblankfinancing intermediarytoprovidermatrix. Allowparticipantstoreadthroughthe3pagesof backgroundinformationand ask if there are any queriesaboutthe information provided. Queriesthataremostfrequently raised,andissuesthatyoumaywishto clarifyattheoutset,include:

•Ensure that all participants understand the distinction between financing intermediariesandsourcesoffinance(stressthattheyneedtoidentifywho

‘controls’themoneyorwhoactuallypaysmoneyovertoproviders);

•IndicatethattotalexpenditureinformationisprovidedfortheMinistryofHealth, i.e.expenditure onpersonnel,drugsetc.areincludedintherelevantprovider categories(e.g.academicandtertiaryhospitals);

•PointoutthattheWorkmen’sCompensationFundiscompletelydifferentand separatefromprivatehealthinsurance;

Asyouarewalkingaroundthedifferent groups, youmayneedtocheckthat participantshaveunderstoodtheformatoftheout-of-pocketpaymentdata, i.e.thatit ispercapitadatawhichtheyneedtoextrapolate uptotheentirepopulation. As differentgroupsworkatdifferentspeeds,itishelpfultohandeachgroupcopiesof theanswersheet(seelastpageofthesefacilitator’s notes)whentheyhave completedthematrixsothattheycancheckwhethertheircalculationsarecorrect andtoworkoutforthemselveswheretheymayhavegonewrong.

Keypointsofdiscussionrelatingtothecalculationsinclude:

•Potential double-countingerrors.This may occur in two places, namely in relationtothetransferpaymentfromtheMinistry ofHealthtolocalgovernment healthdepartments, andhousehold’shealthinsuranceschemecontributions (whichareestimatedinthehouseholdsurveyinformationsection,but are already incorporatedinthehealthinsuranceexpendituredata).

•Ensuringthatfinancingintermediarieshavebeenappropriatelyidentified.For example,somemaynothaveincludedtheMinistryofHealth’scontributionto localgovernmenthealth departmentsinthelocal governmentcolumn. Thesame problemmayoccurwithWorkmen’sCompensation (someputitunder‘firms’ expenditureinsteadofWorkmen’sCompensation).

Thefirstphaseofthecasestudycanalsobeusedtohavesomediscussion ofthe potentialsourcesofNHAdata.

5. Phase2

Onceeveryoneishappywiththecalculations,groupscanbegindiscussingthe issuesraisedattheendofthefirstpartofthecasestudy. Youshouldexplainthe finalcolumninthe‘modelanswer’matrix.Whilethesecondlastcolumnindicatesthe percentagecontributionofeachprovidercategorytototalhealthcareexpenditure, thefinalcolumnpresents ananalysis withineachofthepublicandprivatesectors. Thelightershadedcellsindicatethepercentage contribution ofeachcategoryof publicproviderto expenditurewithinthepublichealthsector,whilethedarkershaded cellsindicatethepercentage contribution ofeachcategoryofprivateproviderto expenditurewithintheprivatehealthsector.

Discussionofthedistributionofexpenditurebetweenfinancingintermediaries

Keyissuesinclude:

•Theverylowcontributionofdonors,indicatingthatthiscountryisnotheavily dependentondonorfunding.

•Private insurance schemes are the single largest category of financing intermediary, andthusthattheseschemeshaveconsiderable influenceoverthe healthsysteminthiscountry.

•Householdscontributeconsiderableresourcesdirectlyout-of-pockettohealth careproviders. Out-of-pocketpaymentsareanextremelyregressiveformof financingandthisraisesequityconcerns abouthealthcarefinancing inthis country.

•Over60%ofhealthcareresourcesinthiscountryarecontrolledbyprivate financingintermediaries, indicatingthattheprivatehealthsectorissubstantialin thiscountry.

•Withinthepublicsector,theMinistryofHealthisthesinglelargestfinancing intermediary andthushascontroloverthevastmajorityofhealthfundsinthis sector.Thissuggestsahighlycentralisedpublichealthsector.

Discussionofthedistributionofexpenditurebetweenprovidercategories

Keyissuesinclude:

•Thepublicsectorisbiasedtowardshospital-basedcurativecare,with39%of publicsectorexpendituregoingtoacademicandtertiaryhospitalsand38%going tootherpublicsectorhospitals.

•Publicsectorprimarycareorbasichealthservicesonlyaccountfor13%oftotal publicsectorhealthcareexpenditure. UNICEF andUNDPrecommendthat20% ofpublichealthcareexpenditureshouldbedevotedtobasichealthservices.

•Medicinesarethebiggestexpenditureitemintheprivatesector,accountingfor overathirdofprivatesectorhealthcareexpenditure. Privately-sold medicineis the single largest category of health care expenditure in the overall health system.

•Another thirdofprivatehealth careexpenditureisdevotedtoprivatepractitioners

(specialists,GPsanddentists).

•Administrationcostsintheprivatesectorexceedthatinthepublicsector.

Discussionofadditionaldatarequiredtofullyinterpretthefinancialdata

Itisverydifficulttoassessefficiencyandequityissuesintheabsenceofnon- financialdata. Forexample,itcannotbesaidthatthedistributionofresources betweenthepublicandprivatesectorsisinequitable, unlessitisknowwhat percentageofthepopulationhasaccesstoanduseseachsector. Participants are likelytosuggestthattwoofthemostimportantpiecesofnon-financialdataare:

•Populationcoveragebythepublicandprivatehealthsectors;and

•Utilisationdata(inordertoassessefficiencyissues).

Othertypesofnon-financialdatathatmaybeusefulincludehumanresourcedata andindicatorsofneedforhealthservices(suchasmortalityandsocio-economic

data).

Discussionofdatagapsandpossibleinaccuraciesinthedata

OneofthemajorgapsinthissetofNHAdataisfinancingandexpenditure for complementary medicalpractitioners(e.g.homeopaths,chiropractorsetc.)and traditionalhealers. Asitappearsthatthesecategories ofprivateprovidersarenot coveredbyprivatehealthinsurance schemes(because theschemesdonotreport expenditureontheseproviders),thismayresultinasubstantialunderestimateofout- of-pockethouseholdexpenditure.

Anydatacollectedthroughsamplesurveysmaybeinaccurate. Inthiscasestudy, thisparticularlyappliestodataonhealthcareexpenditurebylocalgovernment

health departments,by firms on workplacehealth servicesand by households. Householdsurveysarerenownedforunderestimating healthcareexpenditure, particularly ifalongrecallperiodisused(e.g.‘howmuchmoneyhaveyouspenton healthservicesinthelastyear’comparedwithaskingaboutexpenditure inthelast month or the last two weeks). You can illustrate this by highlighting that the householdsurveyprovidesamassiveunderestimateofhouseholds’healthinsurance contributions.Eventhoughemployersmaymakesomecontributionsonbehalfof theiremployees,thehouseholdsurveysuggeststhat$3,921millionwascontributed tohealthinsurance,whereastotalhealthinsuranceexpenditureis$12,987million (i.e.only30%ofhealthinsurancecontributions werecapturedinthehousehold survey). You could have a discussion of ways of improving out-of-pocket expenditureestimatesthroughdatatriangulation, forexamplebyalsogetting information directlyfromthemajorhealthcareproviderswhoreceiveout-of-pocket paymentsfrompatients.

6. Phase3

Handoutthefinal2pages ofthiscasestudy,requestingparticipantstoreadthrough itanddiscusstheissuesraisedattheendofthissection.

Discussionofusefulnessofadditionaldata

Keyissuesinclude:

•Healthcareexpenditureaccountsfor8.5%ofGDP.Thisisarelativelyhigh proportionofGDPtodevotetohealthcareinamiddle-incomecountry. Ascan beseenfromTable3,thiscountryhasarelatively highIMR(of62per1,000live births)suggestingthatit maynotbegettingvalueformoney.

•Thepublic-privatemixishighlyskewed. While60%ofexpenditureoccursinthe privatesector,andthevastmajorityofmostcategories ofhealthpersonnel, with theexceptionofnurses,workintheprivatesector(Figure1),lessthanaquarter ofthepopulationhasroutineaccesstoprivatesectorcare.

•Withinthepublicsector,thereisclearlyaheavyemphasisonthehighestlevels ofcare. Notonlyisnearly40%ofpublicsectorhealthcareexpenditure devoted toacademic andtertiaryhospitals, over60%ofgeneralistdoctorsandmorethan halfofallpharmacistswork inthese facilities(Table1). Thereisrelativelylimited accesstodoctorsattheprimarycarelevel. Thissuggeststhattheremaybe allocativeinefficiencyinthepublichealthsector.

•Concerns about allocative efficiency are strengthened by the information presentedinTable2. Whileslightlymorethanaquarterofalloutpatient visits occuratacademichospitals,nearlyahalfofallexpenditure onpublicsector outpatientcareisattributabletothesefacilities.Althoughitmay beacceptableto spendnearly$120peroutpatient visitatanacademic hospitalwhenspecialist careisneeded,itisunlikelythat18%ofalloutpatients needtobeseenatthis levelofcare. Foreverypatienttreatedinanacademichospital’soutpatient department, 4patientscouldbetreatedinclinics. (Note:someparticipants may askwhytheexpendituredataforthedifferentcategoriesofhospitalsandclinics inTable2differfromthatinthematrix. Table2onlyreferstoexpenditure on outpatientserviceswhilethematrixreferstoexpenditure onbothinpatientand outpatient careinhospitals. Similarly, thematrixcategory ofpublicbasichealth servicesincludesnotonlyclinicservicesbutalsonon-facility basedbasichealth servicessuchasenvironmentalandschoolhealthservices).

•Table 3 highlights the inequitable distribution of public sector health care resources (financial, human and facilities) between geographic areas. The

provinceswiththehighestIMRandpovertyratestendtohavethelowestlevelsof publicsectorhealthcareresources.

•Overall,theadditionaldataprovided,especiallythenon-financialdata,enables participantstoundertakeamuchmoreextensive analysisofthiscountry’s health system, particularly in relation to equity and efficiency. This highlights the importanceofnotsimplyfocussingonfinancialdatainaNHAstudy.

Discussionofkeychallengesfacingthehealthsector

Fromtheaboveanalysis,thekeychallengesinclude:

•Arelativelyhighlevelofoverallhealthcareexpenditure,suggestingthatthekey challengeisnotthatoflackofresources,butratherusingexistingresources moreefficientlyandequitably;

•Majordisparitiesintheresourcingofthepublicandprivatehealthsectors,relative tothepopulationdependentoneachsector;

•Veryhighlevelsofmedicineexpenditureintheprivatehealthsector,suggesting thatthepriceofmedicines and/orprescribinganddispensingpractices ofprivate providersrequirereview;

•Alikelymaldistributionofresourceswithinthepublicsectorbetweenlevelsof care, with a need to reduce expenditureat the higher levels and increase expenditureonprimarycareservices;and

•Massive disparities in the distribution of health care resources between geographic areas, implying the need to redistribute resources in favour of relativelypoorly-resourcedprovinceswithhighlevelsofmortalityandpoverty.

7. Concludingremarks

Inconcludingthiscasestudy,it isusefultohighlightthreekeyissues:

•NHAisnotsomethingthatoneneedsateamofhighlypaid‘experts’todo.

Instead,healthmanagersand/orresearcherswhoarecommittedtogatheringthe appropriatehealthcarefinancingandexpenditure datacanconductaNHAand usetheinformationit contains.

•NHAisnotjustadatacollectionexercise.Itcanprovideextremelyvaluable information tocriticallyevaluateahealthsystemandtoinformhealthpolicy development,particularlywherefinancialdataissupplemented witharangeof non-financialdata.

•Whilethiscasestudyhasfocussedoncollectingandanalysingnationallevel data,thesameprinciplesandmethodscanbeusedtocompileandanalyse healthcarefinancingandexpendituredataatadecentralised levelofthehealth system(e.g.ataprovincial,regionalordistrictlevel).

Facilitator’s Notes for NHA

PROVIDERS / FINANCING INTERMEDIARIES
Ministry of Health / Ministryof
Education / Ministries for
Security
Forces / Local
Government / Donors / Private
Insurance / Workmen's
Compensation
Fund / Firms / Households
(Out-of- pocket) / TOTAL / %of total / %of sector
total
Public sector administration / 843 / 843 / 2.8% / 6.7%
Public academic & tertiary
hospitals / 4,636 / 320 / 31 / 6 / 4,993 / 16.6% / 39.4%
Other public hospitals / 3,897 / 466 / 130 / 101 / 191 / 4,785 / 15.9% / 37.7%
Public basic health services / 821 / 117 / 563 / 68 / 93 / 1,662 / 5.5% / 13.1%
Education and training / 330 / 63 / 393 / 1.3% / 3.1%
Private administration / 1,709 / 1,709 / 5.7% / 9.9%
Private hospitals / 2,602 / 437 / 80 / 3,119 / 10.4% / 18.0%
Private GPs and dentists / 2,906 / 1,302 / 4,208 / 14.0% / 24.3%
Private specialists / 1,890 / 1,890 / 6.3% / 10.9%
Privatelysold medicines / 3,430 / 2,512 / 5,942 / 19.8% / 34.3%
Workplace hospitals / 340 / 340 / 1.1% / 2.0%
Workplace clinics / 132 / 132 / 0.4% / 0.8%
TOTAL / 10,197 / 330 / 583 / 563 / 131 / 12,987 / 569 / 472 / 4,184 / 30,016
%of total / 34.0% / 1.1% / 1.9% / 1.9% / 0.4% / 43.3% / 1.9% / 1.6% / 13.9%

Di McIntyre & Charlotte Muheki, Health Economics Unit, University of Cape Town6

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