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Original Article

Inequities in access to health care in South Africa

Bronwyn Harrisa,*, Jane Goudgea, John E. Atagubab,Diane McIntyreb, Nonhlanhla Nxumaloa, Siyabonga Jikwanac,and Matthew Chersicha,d

aCentre for Health Policy & Medical Research Council Health Policy Research Group,School of Public Health, Faculty of Health Sciences, University of the Witwatersrand,

Johannesburg, Private Bag X3, Wits, 2050, Johannesburg, South Africa.E-mail: [email protected]

bHealth Economics Unit, School of Public Health and Family Medicine, University ofCape Town, Cape Town, South Africa.

cNational Department of Health, Pretoria, South Africa.

dDepartment of Obstetrics and Gynecology, International Centre for ReproductiveHealth, Faculty of Medicine, Ghent University, Ghent, Belgium.

*Corresponding author.

Abstract Achieving equitable universal health coverage requires the provisionof accessible, necessary services for the entire population without imposingan unaffordable burden on individuals or households. In South Africa, little isknown about access barriers to health care for the general population. We exploreaffordability, availability, and acceptability of services through a nationallyrepresentative household survey (n4668), covering utilization, health status,reasons for delaying care, perceptions and experiences of services, and health-careexpenditure. Socio-economic status, race, insurance status, and urban-rurallocation were associated with access to care, with black Africans, poor, uninsu-red and rural respondents, experiencing greatest barriers. Understanding access

barriers from the user perspective is important for expanding health-care coverage,both in South Africa and in other low- and middle-income countries.Journal of Public Health Policy (2011) 32, S102S123. doi:10.1057/jphp.2011.35

Keywords: out-of-pocket payments; access; health-care utilization; inequities;household survey; South Africa

Introduction

More than a billion people, mainly in low- and middle-income

countries (LMICs), are unable to access needed health services as theseare unaffordable.1 In South Africa, health-care access for all is

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constitutionally enshrined; yet, considerable inequities remain, largelydue to distortions in resource allocation.24 Access barriers also includevast distances and high travel costs, especially in rural areas; high out-

of-pocket (OOP) payments for care;5 long queues;6 and disempoweredpatients.7 These barriers, created by uneven social-power relationships,resonate with access hurdles experienced elsewhere in LMICs.1,8

Globally policy attention has turned to universal health coverage(UHC) as a remedy for inaccessible, unaffordable health services.

Achieving equitable UHC requires the provision of accessible,necessary services (depth) for the entire population (breadth), andaccommodating the differential needs and financial constraints of

disadvantaged groups (height).

8

Access is therefore the opportunityand freedom to use services,9 and encompasses the circumstances thatallow for appropriate service utilization, plus a sufficiently informedindividual or household (demand-side) empowered to exercise choicewithin the health system (supply-side).9,10 The degree of fit betweendemand- and supply-sides, rather than each in isolation, determinesthe degree of access achieved.9

South Africas apartheid past still shapes health, service, and resourceinequities.2 Racial, socio-economic, and rural-urban differentials in

health outcomes, and between the public and private health sectorsremain challenging.2,3,11 In 2005, spending per private medical schememember was ninefold higher than public sector expenditure, and onespecialist doctor served fewer than 500 people in the private sector butaround 11 000 in the public sector.11 Large information gaps remainabout health access in the general population in South Africa, especiallyaround utilization rates and OOP payments for health care.12

Documenting demand-side perspectives of users, too-long neglected,

could inform future policies.

8,9

We conducted a national householdsurvey to fill these gaps and to examine access barriers.

Methods

In 2008, we conducted a household survey in South Africa, withhouseholds selected using multi-stage sampling, detailed elsewhere andin this edition.13,14 The team selected five randomly-chosen householdswithin 960 enumerator areas. Within each household, we administered

the questionnaire to an adult responsible for household healthdecisions. If the health-head declined or was ineligible, the household


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was substituted by the one to the immediate left. We verified 20 percent of questionnaires telephonically and double entered the data.The Universities of Cape Town and the Witwatersrand provided ethics

approval for the study and all respondents provided informed consent.

Measurement of access and need

We collected information on: health status; utilization of outpatient(annualized number of visits/person in the last month), and inpatient(number of admissions per 1000 people/year) services; health-insurancestatus; and reasons for delaying care when someone was ill and then

the illness worsened in the previous year. We examined the accessdimensions9 of availability (distances and travel mode to facilities),acceptability (reasons for provider choice, user satisfaction and healthsystem perceptions, including reasons for delayed care), and afford-ability. For affordability, we calculated household burdens of OOPpayments (04 per cent of total household expenditure is low-moderate, 59 per cent high, and above 10 per cent catastrophic).5

We calculated the transportation burden by dividing transportationcosts for outpatient visits by total household monthly expenditure.

The team assessed equity by considering whether access was equalamong those with equal need for health care, by contrasting levels ofneed with service use in different population groups, such as socio-economic quintiles. We used two indicators of need: self-assessed healthstatus as poor or very poor in main respondents;12 and, among thetotal population, any household member experiencing recent illness orinjury.

Data analysis

We analyzed the data using STATAs 11 and weighted it for differentialprobability of participant inclusion. To detect differences amongcategorical variables we used the RaoScott F statistic to determineP-values.15 Given the large sample size, virtually all associationswere significant. Using principal component analysis, we developeda composite index of socio-economic status based on variablesincluding access to water and sanitation, housing characteristics,

and age and gender of household heads, which are strongly relatedto socio-economic status in South Africa.16 We then categorized

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respondents into five socio-economic quintiles, from poorest (quintile 1)to wealthiest (quintile 5).

Results

The health decision-maker declined participation or was ineligible in238 households (5 per cent), 223 of which were substituted. The 4668households sampled contained 21 159 individuals. Four-fifths wereblack Africans, almost half had only primary schooling or less, and39.9 per cent inhabited rural areas (Table 1). A quarter were employed,a similar proportion unemployed, and the remainder either pensioners

(8.3 per cent), or children and students (44.3 per cent). Median percapita expenditure (for everything, including, but not restricted to,health services) was US$26.7/month (IQR$13.3$53.3; $1R7.5),with 28.9 per cent spending below $15/month. Conversely, 5.4 per centspent $250/month or more. Most did not have health insurance (88.4per cent).

Need and utilization

We assumed that the 17.8 per cent of main respondents who reportedpoor health and the similar proportion of the total population whoexperienced illness or injury in the preceding month were in need ofcare. Need was unevenly distributed, although patterns varied betweenthese measures (Table 2). For main respondents, over 20 per cent of thosein the poorest three quintiles needed care compared to just 5.6 per centof the richest; yet, the socio-economic status of those ill or injured wasfairly evenly distributed. Similarly, need was higher among main

respondents with only primary education or less (31.7 per cent) thanthose with tertiary qualifications (3.5 per cent), but education was notassociated with recent illness or injury. Almost 20 per cent of women inboth groups needed care: 1.31.6-fold more than males. Relative toother groups, more black Africans (20.2 per cent) reported poor health.In contrast, a third of Indians or Asians, decreasing to 16.6 per cent ofblack Africans, were recently ill or injured among the total population.While almost 20 per cent of the uninsured in both groups needed care,6.2 per cent of insured main respondents reported poor health, and

23.6 per cent of the total insured were recently ill or injured. Withinboth groups a third of those above 65 years needed care.




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Table

1:Populationcharacteristicsan

dhealthserviceutilizationinth

egeneralpopulationinSouthA

frica

Variable(%

ofstudypopulation)

Outpatientvisits(perperson/year)

Totaloutpatient

Inpatientadmissions(per1000people/year)

C

linic/CHC

PublichospitalP

rivate

Public

Priv

ate

Age o1

8(37.9)

1.8

0.4

0.7

2.9

30.5

5.8

18

24(15.1)

1.3

0.6

0.7

2.7

84.4

8.6

25

49(31.1)

2.1

1.1

1.5

4.7

113.1

20.1

50

64(10.4)

4.1

1.7

2.2

8.0

109.6

51.5

65

(5.4)

4.6

2.1

2.0

8.7

176.2

27.5

Sex

Fem

ale(55.7)

2.7

1.1

1.2

5.1

101.6

13.8

Male(44.3)

1.5

0.6

1.1

3.3

53.8

20.0

RaceBlackAfrican(82.2)

2.4

1.0

0.9

4.2

76.3

9.2

Colored(9.5)

2.1

0.7

1.2

4.0

97.4

28.9

IndianorAsian(2.2)

1.2

1.2

3.8

6.2

59.3

50.7

Wh

ite(6.1)

0.5

0.4

3.5

4.4

116.6

84.7

Areatype

Rural(39.9)

2.8

1.0

0.7

4.6

58.3

4.0

Info

rmal-urban(17.2)

2.2

0.9

0.9

4.0

100.1

3.5

Formal-urban(42.9)

1.6

0.8

1.7

4.1

93.9

33.6

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Educa

tion

Non-primary(47.1)

2.7

0.9

0.7

4.4

61.2

5.9

Som

esecondary(31.7)

1.9

1.1

1.0

4.0

101.2

14.8

Completesecondary(16.7)

1.5

0.8

1.7

4.o

84.7

35.9

Tertiary(4.6)

0.8

0.4

4.2

5.3

153.1

71.0

Employment

Employed(23.9)

1.3

0.8

2.0

4.1

105.1

41.3

Unemployed(23.5)

3.0

1.4

1.1

5.5

112.5

11.0

Pen

sioner(8.3)

5.2

2.4

1.8

9.4

163.9

20.5

Student/child(44.3)

1.7

0.5

0.6

7.9

34.7

5.6

Healthinsurance

None(88.4)

2.4

1.0

0.7

4.1

88.2

3.3

Insured(11.6)

0.4

0.4

4.7

5.5

25.5

118.6

Healthstatusa

Exc

ellent(22.7)

1.5

0.7

1.5

3.7

136.3

32.5

Good(32.9)

2.5

1.3

2.0

5.8

121.2

21.7

Ave

rage(26.5)

5.5

2.3

2.7

10.4

190.2

44.1

Poo

r(14.7)

7.8

3.6

2.6

14.0

291.4

23.7

Verypoor(3.1)

5.6

6.7

2.7

14.9

406.8

36.8

aRestrictedtomainrespondent(n=46

68).




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Table

2:Differentialsinneed,utilization,andhealthsystemaccessbetweensocio-economicquintiles

Variable

Category%a

Quintile1

Quintile2

Quintile3

Quintile4

Quinti

le5

Total

Need

Poororverypoorhealthb

21.3

25.0

20.8

16.2

5.6

17.8

Illorinjured

19.7

16.2

15.9

16.9

19.6

17.6

Utilization

Outpatienttotalpopulation

Public

clinic/CHC

68.8

64.3

61.4

51.4

21.6

54.7

Districthospital

17.9

15.8

9.8

8.1

3.9

11.6

Regionalhospital

8.1

9.4

9.7

9.7

5.3

8.5

Tertiaryhospital

1.7

2.5

7.2

7.6

5.6

4.8

Privat

enon-hospitalfacility

15.7

19.8

22.8

31.3

60.8

28.8

Privat

ehospital

3.1

1.7

1.6

4.5

12.2

4.4

Public

sectorvisits(mean/year)

3.7

3.2

3.3

3.0

2.3

3.1

Public

sectorvisitsifill/injured(mean

/year)c

15.9

12.6

11.2

10.2

6.2

10.9

Privat

esectorvisits(mean/year)

0.4

0.5

0.7

1.3

2.9

1.2

Privat

esectorvisitsifill/injured(mean/year)c

2.1

2.1

2.7

5.1

8.7

4.4

Inpatienttotalpopulation

Districthospital

51.1

48.5

35.1

17.7

5.7

31.0

Regionalhospital

31.5

34.5

33.8

33.2

15.4

29.5

Tertiaryhospital

12.3

16.4

28.2

30.5

17.1

21.1

Privat

ehospital

5.2

0.7

2.9

18.6

61.9

18.4

Public

sectorvisits(mean)d

74.2

74.3

105.7

70.8

76.2

80.5

Public

sectorvisitsifill/injured(mean

)d

224.0

206.4

264.5

248.7

200.2

227.7

Privat

esectorvisits(mean)d

5.1

0.5

3.4

13.5

74.2

16.6

Privat

esectorvisitsifill/injured(mean)d

13.7

3.4

9.9

32.3

192.8

44.7

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Availa

bility

Transporttofacility

Walke

d

41.1

38.6

45.5

41.0

13.9

37.0

Public

transport

54.1

55.6

45.7

42.1

22.2

45.2

Privat

evehicle

2.5

3.6

6.2

15.2

63.6

15.9

Other

2.4

2.3

2.6

1.7

0.3

2.0

Traveltime

Mean

minutes

38.2

34.2

30.6

26.5

20.2

30.7

Chosefacilityasitsclosest

Outpa

tient

57.0

59.9

54.8

55.2

41.2

54.0

Inpatient

51.4

62.6

42.7

48.0

34.6

47.5

Affordability

Chosefacilityasdont

havetopay

Outpa

tient

37.7

41.6

39.9

35.8

14.7

34.5

Inpatient

23.2

38.0

29.4

31.7

9.0

26.2

Del

ayedcareas

Transportunaffordablee

21.1

17.0

11.4

9.9

1.1

12.2

Unabletogettimeoffworke

1.7

3.8

7.4

7.3

15.9

7.1

OO

Phouseholdburden

f

Transport59%

26.2

18.1

12.2

8.4

2.3

13.9

X10%

19.0

11.7

10.3

6.2

2.5

10.3

Outpa

tientpublicservice59%

2.8

1.4

1.8

1.4

0.9

1.8

X10%

2.3

2.5

0.5

1.0

0.9

1.5

Outpa

tientprivateservice59%

13.3

17.6

9.6

15.2

5.2

10.2

X10%

59.5

46.7

40.2

21.2

5.2

23.7

Inpatientpublicservices59%

10.2

4.8

3.4

5.5

4.3

5.6

X10%

7.1

5.2

4.7

7.2

7.7

6.2

Inpatientprivateservices59%

7.2

0.0

6.3

0.0

1.7

1.9

X10%

21.4

50.0

0.0

5.4

8.6

8.4




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Table

2

continued

Variable

Category%a

Quintile1

Quintile2

Quintile3

Quintile4

Quinti

le5

Total

Accep

tability

Chosefacilityasrespectful

service

Outpa

tient

6.4

6.2

8.7

13.2

19.4

10.4

Inpatient

8.8

6.0

7.0

11.6

15.4

9.7

Del

ayedcareas

Queuestoolonge

8.1

6.7

7.7

11.8

9.2

8.5

Carelikelytobeineffectivee

9.6

6.1

7.0

3.0

4.5

6.1

Wont

betreatedrespectfullye

5.3

0.4

3.2

3.2

3.1

2.9

Illness

notseriouse

56.1

62.0

71.7

75.6

79.9

68.9

aAmongwholepopulationunlessstatedotherwise.

bMain

respondentonly.

cThoseillorinjuredinthelastmonth

(ofwholepopulation).

dMeanadmissions/1000people/year.

eDidnotseekcarewhenill,thenillne

ssworsened(inpastyear).

f04%

burdenislowtomoderate,5

9%

high,above10%

catastrophic.

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Utilization

Outpatient care

While total utilization was similar across socio-economic groups(2.33.7 visits/year), the poorest mainly visited primary health care(PHC) facilities (in quintile 1, 68.8 per cent attended clinics, and 17.9per cent district hospitals), while the richest were thrice as likely to usetertiary hospitals (including national central, academic, and specialisthospitals) (Table 2). Patients with only primary education or less,made 3.4 times as many visits to public clinics as those with tertiaryqualifications (Table 1).

Outpatient visits in the private sector were concentrated in the richer

quintiles. For ambulatory private care (including general practitioners,private dentists, and pharmacies), utilization rose steadily from 15.7per cent of the poorest to 60.8 per cent of the wealthiest; a group thatalso used private-hospital outpatients four times more than those inquintile 1 (Table 2). In addition, use of private-outpatient services washigh among those with tertiary education (4.2 visits), Indians or Asians(3.8 visits), Whites (3.5 visits), and the insured (4.7 visits).

Inpatient careFor the total population, the mean days admitted per 1.000 people/yearwas 80.5 in the public sector and 16.6 in the private sector, risingto 227.7 public and 44.7 private admissions for the ill or injured. Mostinpatient care took place in public, rather than private facilities for allbut the richest, with 61.9 per cent admitted privately compared to just5.2 per cent in quintile 1, and 0.7 per cent in quintile 2 (Table 2). Forpublic sector admissions, people in the lowest quintile mostly used

district facilities (53.8 per cent), with only 13.0 per cent admitted to atertiary facility. Conversely, public sector admissions among the richestquintile were predominantly at tertiary (44.8 per cent) or regional(40.3 per cent) hospitals. Main respondents in very poor healthexperienced threefold as many public admission-days as those reportingexcellent health (406.6 versus 136.3) almost double that of those whowere ill or injured.

Insurance status was associated with differential utilization ofinpatient care, especially in the private sector, with a mean 118.6

admission-days for the insured versus only 3.3 for those withoutinsurance. For rural-dwellers and those living in informal-urban areas,




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total utilization of inpatient private facilities was just a tenth of urban-formal residents (33.6 admissions). Similarly large differentialsoccurred in private admissions between those in the poorer, more rural

provinces of Limpopo (2.3 admissions), Mpumalanga (6.7 admissions),and Eastern Cape (6.9 admissions) versus the urban, better-resourcedprovinces of Gauteng (32.5 admissions), and the Western Cape (32.8admissions). While womens total inpatient utilization was higher thanmen (115.4 versus 73.8), men were 1.5-fold more likely to be admittedto private hospitals.

Availability

The majority used public transport (45.2 per cent) or walked tooutpatient health services (37.0 per cent), although two-thirds (63.6per cent) of the richest used private means. People in formal-urbanareas were sevenfold more likely to use private transport than ruralresidents, and only 6.6 per cent of whites used public means. Averagetravel time to a facility was 30.7 min, but almost twice as long for thepoorest (38.2 minutes) than the richest (20.2 min) (Table 2). Similarly,

travel times in rural areas were long (38.2 min). Travel was shortest forwhites (17.5 min), followed by Indians or Asians (22.4 min), coloreds(25.8 min), and black Africans (32.5 min).

Two-thirds using public sector outpatient primary care and 53.5per cent using public sector hospital outpatients chose the facility becauseit was close. The wealthiest quintile appeared more willing to travel, withonly 30.4 per cent of users selecting private-outpatient services for theirproximity. Closest service was also important for half (49.8 per cent) ofthose using public-inpatient facilities, while this influenced just a quarterof private inpatients. Referral was the commonest reason for selectingprivate hospitals (38.4 per cent), compared to 28.5 per cent in the publicsector. Of inpatients, 28.9 per cent in the public sector and 14.3 per centin the private, were taken there in an emergency.

Affordability

In the public sector, not having to pay informed the choice of over halfusing primary care, 30.4 per cent using hospitals as outpatients, and

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29.0 per cent of inpatients. Less than 5 per cent gave this reason forusing private services.

Of household members who delayed seeking care, 21.1 per cent of

the poorest versus 1.1 per cent of the richest said this was due tounaffordable transport costs (Table 2). Transport costs were similarly aproblem for 42.5 per cent living in Eastern Cape and 19.5 per cent inLimpopo. Unaffordable transport also obstructed immediate care for18.2 per cent of children under 6, and 13.8 per cent of the uninsured,but only 1.0 per cent of insured. Inability to leave work preventedimmediate care-seeking for 10.6 per cent of the insured, as well as 15.9per cent of the richest, declining step-wise across quintiles to 1.7 per cent

of the poorest.For those who sought outpatient care, transport costs werecatastrophic (X10 per cent of household expenditure) for 19.0 percent of the poorest, falling to 2.5 per cent of the wealthiest (Table 2).Financially catastrophic transport costs occurred in 15.3 per cent ofthose living in rural areas, 14.7 per cent of the unemployed, and12.0 per cent of those uninsured (Table 3). This also affected moreblack Africans (11.8 per cent) than other groups, and only few whites(1.6 per cent).

OOP payments for outpatient care in the public sector were low-to-moderate (04 per cent) for most households across the differentvariables, catastrophic only in a very small minority (except 5.3 per cent inLimpopo Province). In contrast, these levels were 23.7 per cent forhouseholds that sought private-outpatient care, varying markedly byrace (from 36.3 per cent for black Africans to 3.3 per cent for Indians/Asians); area type (54.1 per cent for rural, through 30.7 per cent forinformal urban to 14.4 per cent for formal urban); and socio-economic

status (59.5 per cent for the poorest, compared to 5.2 per cent for thewealthiest; Table 2). Over two-fifths of those above 65, and 35.1 per centof pensioners faced financially catastrophic costs following private-outpatient visits.

Unsurprisingly, insurance status was strongly linked with financialcatastrophe, experienced by 43.0 per cent of the uninsured versusjust 4.0 per cent of the insured utilizing private-outpatient care(Table 3). Similarly, for private inpatients, five times as many uninsuredrespondents faced catastrophic costs than those with insurance. OOP

payments were also catastrophic for 14.2 per cent of pensioner privateinpatients and 16.2 per cent of those aged above 65, compared to




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Table 3: Factors associated with high and catastrophic out-of-pocket payments for health care asa percentage of household expenditure

Variable OOP

transport tooutpatient care

OOP outpatienta OOP inpatientb

Public Private Public Private

Burden on householdc 59 X10 59 X10 59 X10 59 X10 59 X10

Ageo18 13.6 8.7 1.7 0.6 9.4 20.5 10.8 6.1 0.0 3.91824 13.5 13.7 3.5 2.5 11.7 31.1 4.9 4.6 0.0 10.52549 14.9 11.2 3.1 1.9 10.3 23.9 7.0 8.7 2.4 7.65064 13.8 9.1 1.8 1.8 11.0 22.5 5.7 6.3 3.0 7.765 13.1 12.0 0.2 1.4 8.9 41.5 2.3 3.2 0.0 16.2

SexFemale 15.0 10.6 1.9 1.4 10.4 25.9 6.5 5.3 2.5 8.6Male 12.1 10.4 2.6 1.6 10.0 23.7 6.8 9.8 0.9 7.2

RaceBlack African 16.5 11.8 2.4 1.7 12.2 36.3 7.3 6.8 1.8 7.0Colored 3.7 7.9 0.4 0.2 6.5 8.5 3.7 5.1 1.7 7.7Indian or Asian 0.5 2.7 1.2 0.0 10.4 3.3 5.1 9.1 4.5 9.8White 0.3 1.6 0.0 0.0 6.2 5.4 0.0 4.7 1.1 8.9

Area typeRural 22.4 15.3 2.9 2.1 11.5 54.1 10.1 8.2 9.7 17.9Informal-urban 8.6 10.6 1.7 1.3 16.6 30.7 4.1 5.2 0.0 1.2

Formal-urban 6.7 5.1 1.4 0.7 8.6 14.4 4.8 5.2 1.2 7.5

EducationNon-primary 18.8 11.9 1.6 1.7 11.7 34.5 7.8 7.2 0.0 15.6Some secondary 10.9 10.7 2.6 1.0 13.4 27.2 5.9 6.2 1.6 7.6Complete secondary 9.6 10.3 3.6 2.2 8.3 20.4 6.1 6.5 1.8 7.0Tertiary 6.2 2.2 1.7 0.0 5.7 8.2 6.3 8.4 3.4 5.3

EmploymentEmployed 11.3 7.6 4.0 2.1 9.0 19.4 7.1 12.0 1.3 6.6Unemployed 16.0 14.7 2.5 2.4 14.4 33.7 5.9 5.2 6.6 12.8Pensioner 13.9 9.6 0.5 0.7 9.7 35.1 2.8 3.7 0.0 14.2Student/child 14.0 8.9 1.9 0.8 9.4 22.7 9.5 5.8 0.0 3.5

Health insuranceNone 16.0 12.0 2.1 1.5 17.4 43.0 6.6 6.6 2.7 25.2Insured 4.1 2.4 2.5 0.0 2.0 4.0 9.5 7.7 1.6 4.6

Health statusExcellent 15.2 5.4 3.9 1.4 3.7 22.7 4.8 6.3 2.4 6.1Good 12.2 9.3 2.3 1.7 11.7 15.8 4.9 6.4 0.0 7.1Average 13.9 14.7 2.9 1.6 14.4 28.1 6.5 6.4 5.7 14.6Poor 19.9 13.7 2.0 2.2 15.6 46.9 5.7 8.9 5.5 6.1Very poor 16.6 11.6 0.0 1.6 12.9 25.3 6.5 0.0 17.1 0.0

aMost recent visit, excludes transportation.bMost recent admission, excludes transportation.c04% burden is low to moderate, 59% high, X10% catastrophic.OOP: Out-of-pocket payments.

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3.9 per cent below 18. A fifth of the poorest, and half in quintile 2,experienced catastrophic costs as private inpatients, while for the upperthree quintiles this burden was low-to-moderate.

Most (88.2 per cent) encountered low-to-moderate OOP burdens aspublic sector inpatients. However, almost twice as many men (9.8per cent) than women (5.3 per cent) experienced catastrophic costs,as did rural (10.1 per cent) relative to urban-formal dwellers (4.8per cent). Catastrophic payments for public inpatients were also borneby 9.1 per cent of Indians or Asians, falling to 4.7 per cent of Whites, aswell as 12.0 per cent of the employed, 10.4 per cent of those living inthe largely rural Limpopo Province, and 8.2 per cent of rural-dwellers.

Despite free PHC services and hospital user fee exemptions foruninsured children under 6,2,17 OOP were made by 17.0 per cent ofchildren under 6 as public sector inpatients and 7.7 per cent of uninsu-red patients attending a PHC facility.

Acceptability

Long queues (8.5 per cent), perceived ineffective care (6.1 per cent),

and anticipated disrespectful treatment (2.9 per cent) partly accountedfor delayed care-seeking. Most commonly, delays were due to a beliefthat the illness was not serious enough to warrant immediate care(68.8 per cent), highest among the richest and insured (Table 2).

Desire for respectful treatment influenced the health-seekingbehavior of almost a quarter (22.3 per cent) attending private-outpatient services, but only 4.1 per cent accessing public PHCservices, and 5.7 per cent using public hospitals. For inpatients,

anticipation of respectful treatment was twofold as important forprivate (17.1 per cent) than public patients (7.5 per cent). Around four-fifths of main respondents who used public-inpatient services in thepast year reported being treated respectfully by health providers,compared to 92.9 per cent of private inpatients (Table 4). Over half ofall respondents (54.7 per cent) felt that patients at public hospitals arerarely treated with respect and dignity. Perceptions, however, variedby source, with 46.3 per cent of those actually admitted to a publichospital in the past year holding this view, compared to 54.7 per cent

who had never been admitted, and 54.2 per cent basing their views onmedia reports.




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Dissatisfaction levels were high regarding the time taken to receiveservices: 37.5 per cent of public outpatients, 17.7 per cent of privateoutpatients, and 25.5 per cent of public inpatients (Table 4). Otheracceptability factors that evoked dissatisfaction included cleanliness,privacy, and confidentiality.

Finally, confidence in the effectiveness of care received influencedoutpatient facility choice for almost half (43.5 per cent) of those inthe private sector, but only 9.6 per cent using PHC, and 13.7 per cent

using public hospitals, although slightly higher in public inpatients(18.8 per cent). Among public sector patients, between a third and aquarter were dissatisfied with the overall quality of care received, whilefewer were dissatisfied with overall quality of private care (9.0 per centoutpatients, 5.1 per cent inpatients).

Discussion

In 1971, the inverse-care law was coined, because the availability ofgood medical care varied inversely with population health needs.18

Forty years on, many poor or disadvantaged social groups are deniedequal access to good-quality services, despite their greater need.1,8

Delineating access barriers is a first-step towards reversing inequitiesand is a prerequisite for achieving UHC.1,8

This study is strengthened by the use of two need measures: self-reported health status among main respondents; and recent illness

or injury within all household members. When gauged by healthstatus, need varied predictably by socio-economic status, gender, and

Table 4: Service dissatisfaction among main respondents

Variable (% dissatisfied with service used in past month) Outpatient service Inpatient service

Public Private Public Private

Clean facility 10.0 6.2 10.9 4.5Consultation in private 13.8 8.2 15.3 4.5Health problems kept confidential 10.3 6.8 15.9 3.3Treated with respect and dignity 19.6 9.7 21.2 7.1Drugs received improved their health 17.5 9.1 13.3 3.9Timely medical attention 37.5 17.7 25.5 5.1Overall quality of care 22.4 9.0 19.3 5.1

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residence. However, need assessed by the second measure was lessclearly differentiated across such variables. It is well documented thatlow-income groups cannot afford to be ill, and therefore under-report

or ignore illness.12,19,20 Further, remembering recent illness in otherhousehold members may incur recall bias, or recent illnesses of othermembers may be conflated with service utilization.

Need for health care is difficult to measure as it is embedded withinsocial norms and constructions of illness and perceptions of health.20 Inour results, a perception that illness was not serious enough to warrantmedical attention was the commonest reason for delayed treatment.This perception was especially prominent among the rich and insured,

suggesting that they might have had less serious illnesses than thepoor and uninsured. Unaffordable transport, anticipation of disrespect-ful providers, and a belief that care would be ineffective were moreprominent access barriers for these latter groups.

For care seekers, total utilization was similar across socio-demo-graphic groups. Marked disparities were, however, noted between thetype of care accessed, both between private and public sectors, andwithin the public sector itself. Utilization of higher-level public facilitieswas greatest among richer, urban, and insured. Because tertiary

hospitals are concentrated in the largely urban, wealthier provincesof Gauteng and Western Cape, and are better resourced and specializedthan district facilities,2 this finding raises equity concerns. As elsewhere,access to specialized, doctor-led curative services within the publicsector illustrates the inverse-care law.8 This emphasizes the need forconsidering depth dimensions of UHC (type of services offered)alongside the breadth (coverage for all). The finding also raisesquestions around referral systems that may unfairly privilege certain

groups, and why some groups of people appear to by-pass the districthealth system a cornerstone of efforts to address access inequities.2

Costs of accessing services can be crippling for poor households.21

Our results suggest that the poorest bear disproportionate cost burdens.OOP burdens of outpatient care also fall on uninsured members,largely from their use of private providers. Although the poorestquintiles make more use of public PHC services, around a fifth ofquintiles 1 and 2 also used private-outpatient care. Considerableprivate sector use across all socio-economic quintiles is not unique to

South Africa, and accounted for over 20 per cent of outpatient visits forthe poorest groups in 39 LMICs.22 However, in South Africa this




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burden on the poor bears vivid testimony to the countrys distinctiveprivate-public sector split, which severely limits cross-subsidizationfrom wealthy to poor, and from healthy to sick. It emphasizes the need

for reforming the private health sector in South Africa.12,23As in many other LMIC contexts,1,22 transportation costs and travel

distance emerged as key access barriers, especially for black Africans,poor, and rural residents. Although the Clinic Upgrading and BuildingProgramme has improved service availability,3 we found that accessbarriers relate to the geographic inaccessibility of health facilities,particularly in largely rural and poorly resourced provinces. However,within the same geographical setting, different households cope diffe-

rently with illness.

5

This suggests a need for holistic and inter-sectoralapproaches to support worse-off households, including mobile services,grants, and user fee exemptions.1,5

We found that a considerable portion of the groups exempted fromuser fees still pay for services. This undermines the equity-objectives ofthe governments exemption policies2,17 and risks undoing thisimportant financial protection for poor households and vulnerablegroups.5 It also illustrates the discretionary power of providers andbureaucrats who determine who ultimately qualifies for exemptions.24

Understanding how frontline staff shape acceptability of health careis crucial.25 Respectful treatment, especially in the private sector withfinancial incentives to influence user choice, attracts users to certainfacilities. Fewer public service users felt they were treated with respectand dignity. Provider respect engenders trusting patient-providerinteractions, which sustain access, particularly for socially disadvan-taged groups who generally bear the brunt of unacceptable care.25,26

Strengthening interventions to change organizational culture and

management practices,

25

and ensuring compliance with the PatientsRights Charter,24 are important for addressing the differential accept-ability needs of disadvantaged groups (the height of UHC).8

Finally, our results show that perceptions about health care varyaccording to whether respondents had recently used public sectorservices (more positive) or not (more negative); a reminder thatthe acceptability of health care is socially ingrained,25 and shapedby the media, and experiences of family and friends. Policy-makerstherefore need to challenge negative perceptions and stereotypes,

while simultaneously addressing legitimate concerns about the qualityof care on offer.13 Improved acceptability, stimulating a shift from

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private to public services, would diminish the adverse financial burdensincurred through private providers.

Limitations

Poor recall might account for the total OOP payments in this surveybeing approximately $66 million below other recent estimates,triangulated from the Medical Schemes Council, Treasury and NationalHealth Accounts.11 Monthly premiums paid to medical schemes werenot considered in our OOP calculations, yet these pose substantialcost burdens. Although we enquired about preventative and related

non-curative services, responses were restricted largely to curative care.Further, methodologically, temporal relationships cannot be establishedbetween variables within cross-sectional surveys,27 where, for example,high OOP payments might account for present socio-economic status.Future cohort and qualitative analyses might define the order of suchevents.

Conclusion

To achieve equitable UHC, the right to access health must be realizedacross society so that those who need care are able to access itregardless of who or where they are, or their ability to pay.1,28 Ourfindings concur with previous South African studies, confirming thatpoor, uninsured, black Africans, and rural groups have inequitableaccess.2,3,5,7 These inequities mirror the South African context,signaling the limited power of vulnerable social groups to claim anduse entitlements and opportunities,8 and resonating strongly with

studies in other LMICs.

1,8,21,22

Undoing this status quo requires acomprehensive approach to UHC, which considers the breadth,depth, and height of access, rather than financing reform alone.1,8

A financing-centered approach to National Health Insurance mayreduce some of the affordability barriers, but will not deal with otheraccess barriers found in this survey. Indeed, given the choice, manyprefer using the private sector, even if it incurs catastrophic payments.This results in greater resources flowing to private facilities, thusworsening the public sector. Similarly, efforts to revitalize PHC and

district systems which might enhance affordability and availability need to consider acceptability, whether intended users will actually




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access these services. Improving public sector service quality andperceptions thereof, and creating equitable access to different levels ofpublic care, could reduce use of private providers and thus minimize

financially catastrophic charges. These steps would create a closer fitbetween the equity-seeking objectives of present policies and theinequitable, unhealthy realities that many continue to face.

Acknowledgements

For their highly valued contribution to the data collection, managementand analysis, we would like to thank our colleagues, including VanessaDaries, Veloshnee Govender, Okore Okorafor, Robert Moeti, AdelaideMaja, Natasha Palmer, Anne Mills, and Olufunke Alaba. Forconceptual guidance, we would like to thank Duane Blaauw andLaetitia Rispel. SACBIA survey was a collaborative initiative betweenHealth Economics Unit, University of Cape Town; Centre for HealthPolicy, University of the Witwatersrand; South African NationalDepartment of Health (NDoH); and the London School of Hygiene

and Tropical Medicine. NDoH funded the survey through a EuropeanUnion grant. The Community Agency for Social Enquiry collected thedata. Diane McIntyre is supported by the South African ResearchChairs Initiative of the Department of Science and Technology andNational Research Foundation.

About the Authors

Bronwyn Harris, MA, is a researcher at the Centre for Health Policy,School of Public Health, University of the Witwatersrand, Johannesburg.She conducts research on access, equity, and patientprovider relation-ships in health systems.

Jane Goudge, PhD, is Director of the Centre for Health Policy, Schoolof Public Health, University of the Witwatersrand, Johannesburg

researching access to health care, equitable financing, and compre-hensive primary health care.

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John E. Ataguba, BSc, MPH, is a lecturer and researcher at the HealthEconomics Unit, University of Cape Town. He has been involved inseveral research projects on health and poverty across Africa.

Diane McIntyre, PhD, is the South African Research Chair in Healthand Wealth and is a professor in the Health Economics Unit,Department of Public Health and Family Medicine, University ofCape Town.

Nonhlanhla Nxumalo, MPH, is a researcher at the Centre for HealthPolicy at the School of Public Health, University of the Witwatersrand,

Johannesburg. She is part of the Consortium for Health Policy andSystems Analysis in Africa.

Siyabonga Jikwana, MA, MPH, is currently a Director in the HealthFinancial Planning & Economics Unit in the South African NationalDepartment of Health.

Matthew Chersich, MBBCh, PhD, is Associate Professor at the Centrefor Health Policy, University of Witwatersrand, Johannesburg and

Visiting Professor in the Department of Obstetrics and Gynecology atGhent University, Belgium.

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