3 Management Inpatients Nazia Peer

35

Section A: Management Inpatients Indicator Comparisons by District

3 Management Inpatients Nazia Peer

Introduction

All of the following indicators are measures of efficiency, which is defined as “the allocation and use of resources in a manner that obtains the best health service outputs at the least cost”.a All of the indicators in this section are presented for district hospitals only, unless otherwise indicated.

3.1 Average length of stay

The average length of stay (ALOS) indicator measures how long, on average, each patient spends in a hospital, expressed as a number of days. The ALOS is calculated by using the patient days (number of inpatient days plus half of the total number of day patients seen) divided by the number of separations (discharges added together with transfer-out, deaths and day patients).

ALOS is regarded as an indicator of efficiency, since a shorter stay can reduce the cost per patient and allow more patients to be treated in a given period. Moreover, a shorter stay in hospital can also make provision for treatment to be shifted from expensive inpatient care to post-acute settings. However, very short ALOS could be more service-intensive and could incur more costs per episode or costs per day. It could also have adverse effects on health outcomes, might reduce the comfort and recovery of the patient, and may lead to a rising readmission rate.b A low ALOS may also indicate inadequate quality of care.

Too long a stay is also concerning, and could be as a result of many factors, including delayed patient diagnosis, treatment and overall management, the patient’s low socio-economic status, inadequate transport and poor referral systems. A persistently high ALOS should be investigated by managers, and processes of patient care, referral procedures and quality of service need to be evaluated.

In 2012/13, the South African average for ALOS was 4.2 days. Figure 1 shows the values of ALOS per district. Frances Baard (NC) had the shortest ALOS (1.1 days) followed by Xhariep (FS) (2.1 days). In contrast, both Uthungulu and iLembe districts in KwaZulu-Natal (KZN) had the longest ALOS (6.8 days), followed by Buffalo City (6.3 days) in the Eastern Cape (EC). What becomes clear is that there are provincial patterns (Map 1). All the districts in the Northern Cape and Free State, except for JT Gaetsewe (NC) (3.6 days) and Mangaung (FS) (3.9 days) respectively, have ALOS well below the national average. Apart from Amajuba with an ALOS at 3.0 days, 10 of the 11 KZN districts reported an ALOS higher than the national average. Six of the eight EC districts were above the national average. However, it is interesting to note that the ALOS is generally low in the vast, sparsely populated districts of the Northern Cape.

Four of the 11 NHI districts have an ALOS above the national average.

The annual trends are shown in Figure 4. The ALOS in Mangaung (FS) is clearly higher than all other provincial districts, while KZN’s districts show a clear reduction with each district having a unique pattern. EC districts also show an obvious decline; however, Buffalo City trends have fluctuated, as only 13% of patient separations in Buffalo City are in district hospitals.

a Mwase T. The Application of National Health Accounts to Hospital Efficiency Analyses in Eastern and Southern Africa. Working Paper. Bethesda, MD: The Partners for Health Reformplus Project, Abt Associates Inc.; August 2006.

b Organisation for Economic Co-operation and Development (OECD). Average length of stay in hospitals. In: OECD Health at a Glance: Europe 2012. Paris: OECD Publishing; November 2012.

Average length of stay (District Hospitals) by district, 2012/13

Days [Source: DHIS]

Uthungulu: DC28iLembe: DC29

Buffalo City: BUFUgu: DC21

Zululand: DC26Umzinyathi: DC24OR Tambo: DC15

A Nzo: DC44Amathole: DC12

Umkhanyakude: DC27Sisonke: DC43

Joe Gqabi: DC14Uthukela: DC23

uMgungundlovu: DC22Vhembe: DC34

C Hani: DC13Capricorn: DC35eThekwini: ETH

Nkangala: DC31Gr Sekhukhune: DC47

Waterberg: DC36RS Mompati: DC39

G Sibande: DC30Mopani: DC33

Ehlanzeni: DC32Mangaung: MAN

NM Molema: DC38West Rand: DC48

Cacadu: DC10N Mandela Bay: NMA

Johannesburg: JHBJT Gaetsewe: DC45

Cape Town: CPTBojanala: DC37

Fezile Dabi: DC20Sedibeng: DC42

Dr K Kaunda: DC40Central Karoo: DC5

Eden: DC4Amajuba: DC25Tshwane: TSH

Ekurhuleni: EKUCape Winelands: DC2

West Coast: DC1Siyanda: DC8

Overberg: DC3T Mofutsanyane: DC19

Lejweleputswa: DC18Pixley ka Seme: DC7

Namakwa: DC6Xhariep: DC16

Frances Baard: DC9

2 4 6

6.28

3.64

5.51

4.48

5.32

5.55

5.51

3.63

2.05

2.45

2.65

3.38

3.92

3.27

3.80

2.99

3.57

3.02

6.20

5.04

5.05

6.00

3.04

6.07

5.50

6.83

6.76

5.44

4.26

4.02

4.64

4.47

4.17

4.18

4.11

4.24

4.01

3.57

2.30

2.31

2.86

1.09

3.38

3.91

4.14

3.22

3.54

2.87

2.89

2.70

3.10

3.17

SA average

Target

ProvincesECFSGPKZNLPMPNCNWWC

36


Figure 1: Average length of stay (district hospitals) by district, 2012/13

Average length of stay (District Hospitals) by NHI district, 2012/13

Days

Umzinyathi: DC24

OR Tambo: DC15

uMgungundlovu: DC22

Vhembe: DC34

G Sibande: DC30

Dr K Kaunda: DC40

Eden: DC4

Amajuba: DC25

Tshwane: TSH

T Mofutsanyane: DC19

Pixley ka Seme: DC7

2 4 6

5.55

2.65

3.02

5.04

6.00

3.04

4.64

4.11

2.31

3.22

3.10

SA average ProvincesECFSGPKZNLPMPNCNWWC

DC6

DC7

DC8

DC10

DC5

DC36

DC39

DC1

DC16

DC13

DC19DC18

DC30

DC4

DC2

DC38

DC32

DC45

DC14

DC34

DC12

DC35

DC20

DC33

DC37

DC31

DC3

DC9

DC26

DC40

DC27

DC47

DC15

DC23

DC44

DC43

DC22

DC24

DC28

TSH

MAN

DC25

TSH

DC42

DC48 EKUJHB

Gauteng

LegendProvince

District

ALOS_DH_20121.1 - 2.4

2.5 - 3.4

3.5 - 4.3

4.4 - 5.3

5.4 - 6.8

37


Figure 2: Average length of stay (district hospitals) by NHI district, 2012/13

Map 1: Average length of stay (district hospitals) by district, 2012/13

0 1 1 2 2 3 3 4 4 5 5 6 6 7 7Indicator Value

EC N Mandela Bay: NMA

Cacadu: DC10

C Hani: DC13

Joe Gqabi: DC14

Amathole: DC12

A Nzo: DC44

OR Tambo: DC15

Buffalo City: BUF

FS Xhariep: DC16

Lejweleputswa: DC18


Fezile Dabi: DC20

Mangaung: MAN

GP Ekurhuleni: EKU

Tshwane: TSH

Sedibeng: DC42

Johannesburg: JHB

West Rand: DC48

KZN Amajuba: DC25

eThekwini: ETH

uMgungundlovu: DC22

Uthukela: DC23

Sisonke: DC43

Umkhanyakude: DC27

Umzinyathi: DC24

Zululand: DC26

Ugu: DC21

iLembe: DC29

Uthungulu: DC28

LP Mopani: DC33

Waterberg: DC36

Gr Sekhukhune: DC47

Capricorn: DC35

Vhembe: DC34

MP Ehlanzeni: DC32

G Sibande: DC30

Nkangala: DC31

NC Frances Baard: DC9

Namakwa: DC6

Pixley ka Seme: DC7

Siyanda: DC8

JT Gaetsewe: DC45

NW Dr K Kaunda: DC40

Bojanala: DC37

NM Molema: DC38

RS Mompati: DC39

WC Overberg: DC3

West Coast: DC1

Cape Winelands: DC2

Eden: DC4

Central Karoo: DC5

Cape Town: CPT

4.5

5.5

5.5

5.5

5.3

6.3

3.6

3.6 SA

: 4.2

3.9

2.7

2.4

3.4

2.1

..

3.8

3.3

3.6

3.0

3.0

5.5

6.8

6.8

4.3

3.0

5.0

6.0

5.4

6.2

5.1

6.1

4.5

4.6

4.0

4.2

4.2

4.0

4.2

4.1

2.9

2.3

2.3

3.6

1.1

3.9

3.4

3.2

4.1

3.5

2.9

2.9

2.7

3.2

3.1

22

2SD 2SD1SD 1SD

Average length of stay (District Hospitals) by district, grouped by province, showing standard deviations from average, 2012/13Prov

ECFSGPKZNLPMPNCNWWC

Units: DaysSource: DHIS

38


Figure 3: Average length of stay (district hospitals) by district, grouped by province, showing standard deviations from the average, 2012/13

Annual trends: Average length of stay (District Hospitals)

Day

s

2

4

6

8

10EC FS

●

● ● ● ●● ● ● ●

●●

GP

2

4

6

8

10KZN

●● ● ● ● ● ●

● ●●

●

LP MP

2

4

6

8

10

2002

/03

2003

/04

2004

/05

2005

/06

2006

/07

2007

/08

2008

/09

2009

/10

2010

/11

2011

/12

2012

/13

NC

2002

/03

2003

/04

2004

/05

2005

/06

2006

/07

2007

/08

2008

/09

2009

/10

2010

/11

2011

/12

2012

/13

NW20

02/0

320

03/0

420

04/0

520

05/0

620

06/0

720

07/0

820

08/0

920

09/1

020

10/1

120

11/1

220

12/1

3●

● ● ● ● ● ●

●● ● ●

WC

EC A NzoEC AmatholeEC Buffalo CityEC C HaniEC CacaduEC Joe GqabiEC N Mandela BayEC OR TamboFS Fezile DabiFS LejweleputswaFS MangaungFS T MofutsanyaneFS Xhariep

GP EkurhuleniGP JohannesburgGP SedibengGP TshwaneGP West RandKZN AmajubaKZN eThekwiniKZN iLembeKZN SisonkeKZN UguKZN uMgungundlovuKZN UmkhanyakudeKZN Umzinyathi

KZN UthukelaKZN UthunguluKZN ZululandLP CapricornLP Gr SekhukhuneLP MopaniLP VhembeLP WaterbergMP EhlanzeniMP G SibandeMP NkangalaNC Frances BaardNC JT Gaetsewe

NC NamakwaNC Pixley ka SemeNC SiyandaNW BojanalaNW Dr K KaundaNW NM MolemaNW RS MompatiWC Cape TownWC Cape WinelandsWC Central KarooWC EdenWC OverbergWC West Coast

●

●

●

39


Figure 4: Annual trends: Average length of stay (district hospitals)

40


3.2 Inpatient bed utilisation rate

This indicator measures the occupancy of the beds available for use in district hospitals, and represents how efficiently a hospital uses its available capacity. This rate is expressed as a percentage and is calculated by dividing the number of inpatient days by the usable bed days. In a district which has more than one hospital, these data can mask inequities and conceal variations between the individual hospitals.

The SA average for bed inpatient utilisation rate (BUR) has been about 65% over the last five years, with a low of 64.7% in 2010/11 and a high of 68% in 2008/09. The 2012/13 BUR is 67.3% which is a minimal rise from 67.2% in 2011/12. The distribution of BUR by district is shown in Figure 5.

Nine districts – City of Cape Town (WC) (94.3%), Namakwa (NC) (87.9%), Ekurhuleni (GP) (87.1%), Siyanda (NC) (84.0%), West Coast (WC) (83.7%), Fezile Dabi (FS) (83.6%), Eden (WC) (82.6%), Mangaung (FS) (82.5%) and Bojanala (NW) (81.2%) – had BURs of over 80%. This was a clear increase from the previous year, when five districts had BURs of 80% or higher.

The highest BUR was 94.3% for the City of Cape Town (WC) and the lowest was Frances Baard District (NC) at 43.6%. The difference is more than two-fold. Sixteen districts had BURs lower than 60%, a deterioration from 2011/12 when there were 12 districts with BURs under 60%.

In the Western Cape, all the districts have BURs that are greater than the national average. The Northern Cape is of particular interest, as its districts show the most intra-provincial variation. Namakwa (87.9%) and Siyanda (84.0%) have the second and fourth highest BURs respectively, while Frances Baard (43.6%) and Pixley ka Seme (54.0%) are among the lowest. In Mpumalanga, all the districts had narrow intervals between each other, showing a uniform provincial picture.

In the North West Province, two districts, Mompati (55.8%) and NM Molema (47.6%) are among the 10 districts with the lowest BUR. It is of concern that both these districts have dropped from 2011/12.

Johannesburg Metropolitan District (GP) has a BUR of 53.0%, which is the fourth lowest nationally. Given that there is a drastic shortage of district-level beds in Johannesburg, this low BUR is difficult to understand.

There is a wide range in the BUR among the NHI districts, which probably highlights the differences among these districts across factors such as socio-economic status, geographic context, disease burden, management and resources.

Inpatient bed utilisation rate (District Hospitals) by district, 2012/13

Percentage [Source: DHIS]

Frances Baard: DC9NM Molema: DC38

Uthungulu: DC28Johannesburg: JHB

Amajuba: DC25Pixley ka Seme: DC7

T Mofutsanyane: DC19RS Mompati: DC39

Lejweleputswa: DC18Uthukela: DC23

Umzinyathi: DC24C Hani: DC13

OR Tambo: DC15JT Gaetsewe: DC45

Amathole: DC12Umkhanyakude: DC27

Sisonke: DC43Cacadu: DC10iLembe: DC29

Waterberg: DC36Zululand: DC26Tshwane: TSH

A Nzo: DC44West Rand: DC48

N Mandela Bay: NMASedibeng: DC42

Buffalo City: BUFJoe Gqabi: DC14G Sibande: DC30Capricorn: DC35Ehlanzeni: DC32

Xhariep: DC16Mopani: DC33

Nkangala: DC31uMgungundlovu: DC22

Central Karoo: DC5Ugu: DC21

Dr K Kaunda: DC40Gr Sekhukhune: DC47

eThekwini: ETHCape Winelands: DC2

Vhembe: DC34Overberg: DC3

Bojanala: DC37Mangaung: MAN

Eden: DC4Fezile Dabi: DC20West Coast: DC1

Siyanda: DC8Ekurhuleni: EKUNamakwa: DC6

Cape Town: CPT

20 40 60 80 100

68.2

62.6

59.5

59.2

68.5

59.4

66.2

67.1

70.2

55.9

54.3

83.6

82.5

67.9

66.7

87.1

53.0

66.2

74.6

73.5

56.4

57.7

53.5

66.0

59.8

52.3

63.9

60.9

76.5

70.8

78.5

69.4

64.8

75.0

69.3

70.8

70.0

59.5

87.9

54.0

84.0

43.6

81.2

47.6

55.8

74.7

94.3

83.7

78.4

78.7

82.6

73.6

SA average

Target


41


Figure 5: Inpatient bed utilisation rate (district hospitals) by district, 2012/13

Inpatient bed utilisation rate (District Hospitals) by NHI district, 2012/13

Percentage

Amajuba: DC25

Pixley ka Seme: DC7


Umzinyathi: DC24

OR Tambo: DC15

Tshwane: TSH

G Sibande: DC30

uMgungundlovu: DC22

Dr K Kaunda: DC40

Vhembe: DC34

Eden: DC4

20 40 60 80 100

59.4

54.3

66.2

73.5

57.7

53.5

78.5

69.3

54.0

74.7

82.6

SA average


DC6

DC7

DC8

DC10

DC5

DC36

DC39

DC1

DC16

DC13

DC19DC18

DC30

DC4

DC2

DC38

DC32

DC45

DC14

DC34

DC12

DC35

DC20

DC33

DC37

DC31

DC3

DC9

DC26

DC40

DC27

DC47

DC15

DC23

DC44

DC43

DC22

DC24

DC28

TSH

MAN

DC25

TSH

DC42

DC48 EKUJHB

Gauteng

LegendProvince

District

BUR_DH_201244 - 54

55 - 63

64 - 71

72 - 79

80 - 94

42


Figure 6: Inpatient bed utilisation rate (district hospitals) by NHI district, 2012/13

Map 2: Inpatient bed utilisation rate (district hospitals) by district, 2012/13

0 10 20 30 40 50 60 70 80 90 100Indicator Value

EC C Hani: DC13

OR Tambo: DC15

Amathole: DC12

Cacadu: DC10

A Nzo: DC44

N Mandela Bay: NMA

Buffalo City: BUF

Joe Gqabi: DC14

FS T Mofutsanyane: DC19

Lejweleputswa: DC18

Xhariep: DC16

Mangaung: MAN

Fezile Dabi: DC20

GP Johannesburg: JHB

Tshwane: TSH

West Rand: DC48

Sedibeng: DC42

Ekurhuleni: EKU

KZN Uthungulu: DC28

Amajuba: DC25

Uthukela: DC23

Umzinyathi: DC24

Umkhanyakude: DC27

Sisonke: DC43

iLembe: DC29

Zululand: DC26

uMgungundlovu: DC22

Ugu: DC21

eThekwini: ETH

LP Waterberg: DC36

Capricorn: DC35

Mopani: DC33

Gr Sekhukhune: DC47

Vhembe: DC34

MP G Sibande: DC30

Ehlanzeni: DC32

Nkangala: DC31

NC Frances Baard: DC9

Pixley ka Seme: DC7

JT Gaetsewe: DC45

Siyanda: DC8

Namakwa: DC6

NW NM Molema: DC38

RS Mompati: DC39

Dr K Kaunda: DC40

Bojanala: DC37

WC Central Karoo: DC5

Cape Winelands: DC2

Overberg: DC3

Eden: DC4

West Coast: DC1

Cape Town: CPT

59.5

68.5

62.6

59.4

59.2

66.2

68.2

67.1

SA

: 67.

3

82.5

55.9

54.3

83.6

70.2

55

.

67.9

66.7

53.0

66.2

87.11

53.5

73.5

76.5

59.8

60.9

63.9

52.3

57.7

74.6

66.0

56.4

55

5

.

78.5

64.8

70.8

75.0

69.4

77

70.8

69.3

70.0

59.5

87.9

43.6

54.0

84.0

33

.

00

55.8

74.7

47.6

81.2

55

78.7

83.7

94.3

73.6

82.6

78.4

77

77

2SD 2SD1SD 1SD

Inpatient bed utilisation rate (District Hospitals) by district, grouped by province, showing standard deviations from average, 2012/13Prov

ECFSGPKZNLPMPNCNWWC

Units: PercentageSource: DHIS

43


Figure 7: Inpatient bed utilisation rate (district hospitals) by district, grouped by province, showing standard deviations from the average, 2012/13

Annual trends: Inpatient bed utilisation rate (District Hospitals)

Perc

enta

ge

40

60

80

EC FS

●

●● ●

● ●●

●

●

●●

GP

40

60

80

KZN

●

●

●

● ● ● ●●

●●

●

LP MP

40

60

80

2002

/03

2003

/04

2004

/05

2005

/06

2006

/07

2007

/08

2008

/09

2009

/10

2010

/11

2011

/12

2012

/13

NC

2002

/03

2003

/04

2004

/05

2005

/06

2006

/07

2007

/08

2008

/09

2009

/10

2010

/11

2011

/12

2012

/13

NW

2002

/03

2003

/04

2004

/05

2005

/06

2006

/07

2007

/08

2008

/09

2009

/10

2010

/11

2011

/12

2012

/13

● ● ● ●

●

●

● ●●

●

●

WC





●

●

●

44


Figure 8: Annual trends: Inpatient bed utilisation rate (district hospitals)

45


3.3 Expenditure per patient day equivalent

Hospitals consume a large proportion of the healthcare budget. A hospital bed is both a scarce and an expensive commodity in health care, and efficient bed management is known to bring about significant financial benefit to the hospital. Expenditure per patient day equivalent (PDE) is a composite indicator because it links financial data with service-related data from the hospital admissions and outpatients records. All values in this section are adjusted for the effects of inflation and are reported in real 2012/13 prices.

Expenditure per PDE reflects whether a particular hospital is being optimally managed. It measures and compares the inputs (total financial resources available to the hospital) with the outputs (volume of patients seen). It is important for managers to understand the breakdown of their costs and to ensure that they benchmark their hospitals against similar district hospitals in the province.

In 2012/13, the average expenditure per PDE in South Africa for all district hospitals was R1 823, which is higher than the 2011/12 value of R1 740. Figure 9 shows a wide range of expenditure per PDE across the 52 districts, from R2 573 in Nelson Mandela Bay (EC) to R1 020 in Siyanda (NC) – an almost three-fold difference. The second highest is Frances Baard (NC) at R2 504.

There have been very wide fluctuations in values in the Northern Cape over several years, as illustrated in Figure 12. The Eastern Cape also showed a large variance with Alfred Nzo (R1 586) and Chris Hani (R1 594) districts having the lowest expenditure per PDE, and Nelson Mandela Bay (R2 573) having the highest. Gauteng districts had high values on the whole, and the Western Cape (apart from the City of Cape Town) showed a low expenditure per PDE. KwaZulu-Natal and Mpumalanga have all their districts in the middle and low ranks of expenditure.

Figure 9 shows that there are wide intra-provincial variations in 2012/13 – and over the past four years – in the trends of expenditure per PDE. As most districts contain a number of district hospitals, these district variations conceal the much greater variations that exist between individual hospitals. To illustrate this point, in Uthungulu (KZN), the district average expenditure per PDE in 2012/13 was R1 791. Within the district there are six district hospitals, where expenditure per PDE varies in range from KwaMagwaza (R2 530), to Eshowe Hospital at R1 015 – a difference of over 100% between the lowest and highest expenditure per PDE by hospital. Similar and even greater differences between the expenditure per PDE values can be seen in most districts. These differences require investigation by hospital, district, provincial and national managers.

In terms of the NHI districts, six of the 11 are above the national average, as illustrated in Figure 10.

Expenditure per patient day equivalent (District Hospitals) by district, 2012/13

Rand (real 2012/13 prices) [Source: BAS, DHIS]

Siyanda: DC8West Coast: DC1

eThekwini: ETHCape Winelands: DC2

Eden: DC4Amajuba: DC25

Central Karoo: DC5Mangaung: MAN

Ugu: DC21G Sibande: DC30

A Nzo: DC44C Hani: DC13

T Mofutsanyane: DC19OR Tambo: DC15

Overberg: DC3Amathole: DC12Zululand: DC26Cacadu: DC10

Uthungulu: DC28Umkhanyakude: DC27

Ehlanzeni: DC32Sisonke: DC43

Bojanala: DC37iLembe: DC29

Cape Town: CPTUthukela: DC23

uMgungundlovu: DC22Umzinyathi: DC24Buffalo City: BUF

Namakwa: DC6Xhariep: DC16Vhembe: DC34

Joe Gqabi: DC14Nkangala: DC31

JT Gaetsewe: DC45Mopani: DC33

Fezile Dabi: DC20Dr K Kaunda: DC40RS Mompati: DC39

Pixley ka Seme: DC7Lejweleputswa: DC18

Tshwane: TSHGr Sekhukhune: DC47

Capricorn: DC35Ekurhuleni: EKU

Johannesburg: JHBWest Rand: DC48

Sedibeng: DC42Waterberg: DC36

NM Molema: DC38Frances Baard: DC9

N Mandela Bay: NMA

500 1000 1500 2000 2500

2504

1020

2016

1891

1463

2234

2147

1923

1586

1827

2321

1987

1389

2011

2425

1835

2346

2148

1905

1924

1824

1913

1561

1660

1836

1791

1815

1779

1428

1882

1857

1863

1548

1979

1382

1628

2035

1895

1645

1912

1594

1695

1790

1298

1857

1890

2174

1348

2198

1535

2573

2111

SA average


46


Figure 9: Expenditure per patient day equivalent (district hospitals) by district, 2012/13

Expenditure per patient day equivalent (District Hospitals) by NHI district, 2012/13

Rand (real 2012/13 prices)

Eden: DC4

Amajuba: DC25

G Sibande: DC30


OR Tambo: DC15

uMgungundlovu: DC22

Umzinyathi: DC24

Vhembe: DC34

Dr K Kaunda: DC40

Pixley ka Seme: DC7

Tshwane: TSH

500 1000 1500 2000 2500

2016

1987

1389

1905

1561

1428

1882

1863

1628

1645

2111

SA average


DC6

DC7

DC8

DC10

DC5

DC36

DC39

DC1

DC16

DC13

DC19DC18

DC30

DC4

DC2

DC38

DC32

DC45

DC14

DC34

DC12

DC35

DC20

DC33

DC37

DC31

DC3

DC9

DC26

DC40

DC27

DC47

DC15

DC23

DC44

DC43

DC22

DC24

DC28

TSH

MAN

DC25

TSH

DC42

DC48 EKUJHB

Gauteng

LegendProvince

District

EXPPDE_DH_20121020 - 1428

1429 - 1695

1696 - 1987

1988 - 2234

2235 - 2573

47


Figure 10: Expenditure per patient day equivalent (district hospitals) by NHI district, 2012/13

Map 3: Expenditure per patient day equivalent (district hospitals) by district, 2012/13

0 200 400 600 800 1,000 1,200 1,400 1,600 1,800 2,000 2,200 2,400 2,600 2,800Indicator Value

EC A Nzo: DC44

C Hani: DC13

OR Tambo: DC15

Amathole: DC12

Cacadu: DC10

Buffalo City: BUF

Joe Gqabi: DC14

N Mandela Bay: NMA

FS Mangaung: MAN


Xhariep: DC16

Fezile Dabi: DC20

Lejweleputswa: DC18

GP Tshwane: TSH

Ekurhuleni: EKU

Johannesburg: JHB

West Rand: DC48

Sedibeng: DC42

KZN eThekwini: ETH

Amajuba: DC25

Ugu: DC21

Zululand: DC26

Uthungulu: DC28

Umkhanyakude: DC27

Sisonke: DC43

iLembe: DC29

Uthukela: DC23

uMgungundlovu: DC22

Umzinyathi: DC24

LP Vhembe: DC34

Mopani: DC33

Gr Sekhukhune: DC47

Capricorn: DC35

Waterberg: DC36

MP G Sibande: DC30

Ehlanzeni: DC32

Nkangala: DC31

NC Siyanda: DC8

Namakwa: DC6

JT Gaetsewe: DC45

Pixley ka Seme: DC7

Frances Baard: DC9

NW Bojanala: DC37

Dr K Kaunda: DC40

RS Mompati: DC39

NM Molema: DC38

WC West Coast: DC1

Cape Winelands: DC2

Eden: DC4

Central Karoo: DC5

Overberg: DC3

Cape Town: CPT

1,593.8

1,644.9

2,572.9

1,911.7

1,585.6

1,695.2

1,790.2

1,890.1

SA

: 1,8

23.3

1,894.5

1,534.8

1,978.7

2,034.7

1,628.4

.

2,233.5

2,173.9

2,197.8

2,111.0

2,321.11

1

1,814.9

1,862.9

1,881.9

1,347.7

1,428.3

1,827.3

1,857.3

1,778.6

1,836.0

1,548.1

1,791.1

88

1,904.8

2,146.8

2,147.7

1,924.4

2,346.1.

22

22

1,560.7

1,912.6

1,824.1

1,922.9

1,019.7

1,891.0

2,504.4

2,016.111

1,987.3

2,010.6

2,424.6

1,835.1

4

66

1,462.6

1,389.0

1,660.0

1,298.4

1,382.1

1,857.1

4

00

1

2SD 2SD1SD 1SD

Expenditure per patient day equivalent (District Hospitals) by district, grouped by province, showing standard deviations from average, AllProv

ECFSGPKZNLPMPNCNWWC

Units: Rand (real 2012/13 prices)Source: BAS, DHIS

48


Figure 11: Expenditure per patient day equivalent (district hospitals) by district, grouped by province, showing standard deviations from the average, 2012/13

Annual trends: Expenditure per patient day equivalent (District Hospitals)

Ran

d (re

al 2

012/

13 p

rices

)

500

1000

1500

2000

2500

3000EC FS

●

● ●

● ● ●

●●

●

GP

500

1000

1500

2000

2500

3000KZN

● ●

● ●

●●

●● ●

LP MP

500

1000

1500

2000

2500

3000

2004

/05

2005

/06

2006

/07

2007

/08

2008

/09

2009

/10

2010

/11

2011

/12

2012

/13

NC

2004

/05

2005

/06

2006

/07

2007

/08

2008

/09

2009

/10

2010

/11

2011

/12

2012

/13

NW20

04/0

520

05/0

620

06/0

720

07/0

820

08/0

920

09/1

020

10/1

120

11/1

220

12/1

3

● ●

●

●●

●

●

●●

WC





●

●

●

49


Figure 12: Annual trends: Expenditure per patient day equivalent (district hospitals), real 2012/13 prices

50


3.4 Ratio ambulatory to inpatient days

This indicator is new in the profile of DHB reporting, and compares outpatient visits with inpatient days (including half of day patients). The indicator is calculated by dividing the total Outpatient Department (OPD) headcount (including emergencies) – as the numerator – by the sum of the total inpatient days plus 50% of the total day patients, which constitutes the denominator. A value greater than 1 would indicate that more outpatient and casualty patients are seen than are those who are admitted.

In an ideal setting, all patients coming to the OPD should be referred from a PHC facility. In some cases, hospitals even have clinics on their premises or very close by, known as gateway clinics, to provide a filtering service and prevent unreferred patients from arriving in the OPD. Therefore, a lower ratio is relatively better than a higher ratio.

The 2012/13 value for ratio of ambulatory to inpatient days was 1.3. This means that there are 1.3 times more OPD and casualty patients than there are patient days. The highest ratio (7.9) is Amajuba (KZN) which is a clear outlier and requires further investigation of the one hospital in the district. The lowest ratios were found in JT Gaetsewe (NC) 0.5 and Nelson Mandela Bay (EC) 0.6.

With this indicator there will be intra- and inter-provincial variation because district hospitals provide different levels of care. A ratio below 1 means that fewer clients were seen at the emergency unit/OPD clinics than were admitted into hospital. For example in the Cape Town Metro the larger district hospitals provide a significant quantum of level 2 services which impacts on inpatient days.

Ratio Ambulatory to Inpatient days (District Hospitals) by district, 2012/13

Number [Source: DHIS]

Amajuba: DC25T Mofutsanyane: DC19

G Sibande: DC30Ekurhuleni: EKUNkangala: DC31

uMgungundlovu: DC22Mopani: DC33iLembe: DC29

Waterberg: DC36Pixley ka Seme: DC7

Capricorn: DC35Bojanala: DC37eThekwini: ETH

Gr Sekhukhune: DC47Uthukela: DC23Tshwane: TSH

Uthungulu: DC28Ehlanzeni: DC32

Vhembe: DC34West Coast: DC1

Lejweleputswa: DC18Namakwa: DC6

Fezile Dabi: DC20Ugu: DC21

Johannesburg: JHBCape Winelands: DC2

Mangaung: MANCentral Karoo: DC5

Umkhanyakude: DC27Eden: DC4

Overberg: DC3A Nzo: DC44

Sisonke: DC43Umzinyathi: DC24

Zululand: DC26Buffalo City: BUFSedibeng: DC42

RS Mompati: DC39C Hani: DC13

Frances Baard: DC9Cape Town: CPT

Cacadu: DC10Joe Gqabi: DC14

NM Molema: DC38West Rand: DC48OR Tambo: DC15Amathole: DC12

Siyanda: DC8Dr K Kaunda: DC40

Xhariep: DC16N Mandela Bay: NMA

JT Gaetsewe: DC45

2 4 6 8

1.05

0.83

0.73

0.92

0.80

0.76

1.08

0.55

0.67

1.27

2.54

1.26

1.18

1.01

0.76

1.89

1.23

1.46

1.23

1.76

1.48

1.06

7.92

1.06

1.15

1.45

1.70

1.07

1.51

1.75

1.34

1.60

1.69

1.50

1.94

1.89

1.34

0.51

1.27

1.60

0.71

0.92

1.55

0.78

1.00

0.67

0.92

1.30

1.20

1.12

1.14

1.15

SA average


51


Figure 13: Ratio ambulatory to inpatient days (district hospitals) by district, 2012/13

Ratio Ambulatory to Inpatient days (District Hospitals) by NHI district, 2012/13

Number

Amajuba: DC25


G Sibande: DC30

uMgungundlovu: DC22

Pixley ka Seme: DC7

Tshwane: TSH

Vhembe: DC34

Eden: DC4

Umzinyathi: DC24

OR Tambo: DC15

Dr K Kaunda: DC40

2 4 6 8

0.76

2.54

1.46

1.76

1.06

7.92

1.34

1.94

1.60

0.67

1.14SA average Provinces

ECFSGPKZNLPMPNCNWWC

DC6

DC7

DC8

DC10

DC5

DC36

DC39

DC1

DC16

DC13

DC19DC18

DC30

DC4

DC2

DC38

DC32

DC45

DC14

DC34

DC12

DC35

DC20

DC33

DC37

DC31

DC3

DC9

DC26

DC40

DC27

DC47

DC15

DC23

DC44

DC43

DC22

DC24

DC28

TSH

MAN

DC25

TSH

DC42

DC48 EKUJHB

Gauteng

LegendProvince

District

AMBOPD_DH_20120.5 - 0.8

0.9 - 1.2

1.3 - 1.6

1.7 - 2.5

2.6 - 7.9

52


Figure 14: Ratio ambulatory to inpatient days (district hospitals) by NHI district, 2012/13

Map 4: Ratio ambulatory to inpatient days (district hospitals) by district, 2012/13

-1 -1 0 1 1 2 2 3 3 4 4 5 5 6 6 7 7 8 8 9Indicator Value


Amathole: DC12

OR Tambo: DC15

Joe Gqabi: DC14

Cacadu: DC10

C Hani: DC13

Buffalo City: BUF

A Nzo: DC44

FS Xhariep: DC16

Mangaung: MAN

Fezile Dabi: DC20

Lejweleputswa: DC18


GP West Rand: DC48

Sedibeng: DC42

Johannesburg: JHB

Tshwane: TSH

Ekurhuleni: EKU

KZN Zululand: DC26

Umzinyathi: DC24

Sisonke: DC43

Umkhanyakude: DC27

Ugu: DC21

Uthungulu: DC28

Uthukela: DC23

eThekwini: ETH

iLembe: DC29

uMgungundlovu: DC22

Amajuba: DC25

LP Vhembe: DC34

Gr Sekhukhune: DC47

Capricorn: DC35

Waterberg: DC36

Mopani: DC33

MP Ehlanzeni: DC32

Nkangala: DC31

G Sibande: DC30

NC JT Gaetsewe: DC45

Siyanda: DC8

Frances Baard: DC9

Namakwa: DC6

Pixley ka Seme: DC7


NM Molema: DC38

RS Mompati: DC39

Bojanala: DC37

WC Cape Town: CPT

Overberg: DC3

Eden: DC4

Central Karoo: DC5

Cape Winelands: DC2

West Coast: DC1

0.8

0.8

0.8

0.9

0.7

0.6

1.1

1.1

SA

: 1.3

2.5

0.7

1.3

1.3

1.2

1.5

0.8

1.9

1.0

1.2

1.5

1.5

1.8

7.9

1.7

1.4

1.2

1.2

1.1

1.1

1.1

1.5

1.3

1.7

1.7

1.6

1.9

1.9

1.3

0.5

0.9

0.7

1.3

1.6

1.5

0.8

0.7

1.0

0.9

1.3

1.2

1.2

1.1

1.1

2SD 2SD1SD 1SD

Ratio Ambulatory to Inpatient days (District Hospitals) by district, grouped by province, showing standard deviations from average, 2012/13Prov

ECFSGPKZNLPMPNCNWWC

Units: NumberSource: DHIS

53


Figure 15: Ratio ambulatory to inpatient days (district hospitals) by district, grouped by province, showing standard deviations from the average, 2012/13

Annual trends: Ratio Ambulatory to Inpatient days (District Hospitals)

Num

ber

0

2

4

6

8EC FS

● ●●

GP

0

2

4

6

8KZN

●●

●

LP MP

0

2

4

6

8

2010

/11

2011

/12

2012

/13

NC

2010

/11

2011

/12

2012

/13

NW20

10/1

1

2011

/12

2012

/13

●● ●

WC





●

●

●

54


Figure 16: Annual trends: Ratio ambulatory to inpatient days (district hospitals)

55


3.5 OPD new client not referred rate

This indicator is new and refers to the proportion of new outpatient clients who enter a hospital without a referral letter. OPD new client not referred rate is a percentage of the new OPD cases that are not referred (numerator) divided by all new OPD cases (denominator). OPD follow-up and emergency clients are excluded from the denominator. OPD new client not referred rate monitors utilisation trends of clients’ by-passing PHC facilities. There is no target set for this indicator.

In 2012/13 the average OPD new client not referred rate was 64.1% (Figure 17). The highest was Frances Baard (NC) with 94.9% and the lowest was Dr K Kaunda (NW) with 6.1%. There are no distinct provincial patterns. However the Gauteng districts do not exceed 63.1% and the Limpopo districts in contrast do not drop below 61.2%. There are no values for the WC for OPD new client not referred rate.

There are substantial intra- and inter-provincial variations. High OPD new client not referred rate values could imply overburdened primary health care facilities or inadequately performing ones resulting in poor referral systems. Long queues and lack of faith in nursing staff could also motivate clients to attend hospital OPDs without consulting a primary health care facility first.

Four of the NHI districts have OPD new client not referred rate values greater than the average. This is important particularly because this indicator will highlight the effect of PHC re-engineering on OPD utilisation. If PHC improves, then this value should ideally decrease. This value will be closely monitored over the next few years and should provide key evidence as to how the re-engineering process is evolving.

OPD new client not referred rate (District Hospitals) by district, 2012/13

Percentage [Source: DHIS]

Frances Baard: DC9Waterberg: DC36

Mopani: DC33Pixley ka Seme: DC7

iLembe: DC29Gr Sekhukhune: DC47

C Hani: DC13Joe Gqabi: DC14Ehlanzeni: DC32Amathole: DC12

Fezile Dabi: DC20G Sibande: DC30Umzinyathi: DC24

Bojanala: DC37Cacadu: DC10Vhembe: DC34

Buffalo City: BUFWest Rand: DC48

A Nzo: DC44Ekurhuleni: EKUCapricorn: DC35Mangaung: MANUthungulu: DC28

Sisonke: DC43T Mofutsanyane: DC19

Zululand: DC26Namakwa: DC6

Lejweleputswa: DC18Siyanda: DC8

eThekwini: ETHUmkhanyakude: DC27

JT Gaetsewe: DC45Uthukela: DC23

OR Tambo: DC15Nkangala: DC31

Tshwane: TSHAmajuba: DC25

NM Molema: DC38Sedibeng: DC42

uMgungundlovu: DC22Xhariep: DC16

N Mandela Bay: NMAUgu: DC21

RS Mompati: DC39Dr K Kaunda: DC40

20 40 60 80 100

63.4

72.4

74.6

78.0

76.0

48.1

62.4

22.3

25.8

55.8

58.5

74.5

60.7

38.6

63.1

62.2

47.3

21.0

26.1

49.3

73.9

46.3

57.0

51.4

59.4

81.7

59.1

51.8

82.9

70.8

61.2

92.8

81.2

74.2

48.0

75.1

49.6

56.9

82.3

51.9

94.9

72.5

45.5

6.6

6.1


56


Figure 17: OPD new client not referred rate (district hospitals) by district, 2012/13

OPD new client not referred rate (District Hospitals) by NHI district, 2012/13

Percentage

Pixley ka Seme: DC7

G Sibande: DC30

Umzinyathi: DC24

Vhembe: DC34


OR Tambo: DC15

Tshwane: TSH

Amajuba: DC25

uMgungundlovu: DC22

Dr K Kaunda: DC40

20 40 60 80 100

48.1

58.5

47.3

26.1

73.9

46.3

70.8

74.2

82.3

6.1

SA averageProvincesECFSGPKZNLPMPNCNWWC

DC6

DC7

DC8

DC10

DC5

DC36

DC39

DC1

DC16

DC13

DC19DC18

DC30

DC4

DC2

DC38

DC32

DC45

DC14

DC34

DC12

DC35

DC20

DC33

DC37

DC31

DC3

DC9

DC26

DC40

DC27

DC47

DC15

DC23

DC44

DC43

DC22

DC24

DC28

TSH

MAN

DC25

TSH

DC42

DC48 EKUJHB

Gauteng

LegendProvince

District

OPDNNREF_DH_20126 - 26

27 - 52

53 - 63

64 - 78

79 - 95

57


Figure 18: OPD new client not referred rate (district hospitals) by NHI district, 2012/13

Map 5: OPD new client not referred rate (district hospitals) by district, 2012/13

0 10 20 30 40 50 60 70 80 90 100Indicator Value


OR Tambo: DC15

A Nzo: DC44

Buffalo City: BUF

Cacadu: DC10

Amathole: DC12

Joe Gqabi: DC14

C Hani: DC13

FS Xhariep: DC16

Lejweleputswa: DC18


Mangaung: MAN

Fezile Dabi: DC20

GP Sedibeng: DC42

Tshwane: TSH

Ekurhuleni: EKU

West Rand: DC48

KZN Ugu: DC21

uMgungundlovu: DC22

Amajuba: DC25

Uthukela: DC23

Umkhanyakude: DC27

eThekwini: ETH

Zululand: DC26

Sisonke: DC43

Uthungulu: DC28

Umzinyathi: DC24

iLembe: DC29

LP Capricorn: DC35

Vhembe: DC34

Gr Sekhukhune: DC47

Mopani: DC33

Waterberg: DC36

MP Nkangala: DC31

G Sibande: DC30

Ehlanzeni: DC32

NC JT Gaetsewe: DC45

Siyanda: DC8

Namakwa: DC6

Pixley ka Seme: DC7

Frances Baard: DC9


RS Mompati: DC39

NM Molema: DC38

Bojanala: DC37

22.3

74.6

76.0

78.0

62.4

63.4

72.4

48.1

.

7

SA

: 64.

1

58.5

74.5

25.8

55.8

60.7

47.3

38.6

62.2

63.1

51.8

73.9

46.3

49.3

81.7

21.0

57.0

51.4

59.4

26.1

59.1

70.8

82.9

92.8

61.2

81.2

48.0

74.2

75.111

51.9

56.9

94.9

82.3

49.6

45.5

72.5

6.6

6.1

2SD 2SD1SD 1SD

OPD new client not referred rate (District Hospitals) by district, grouped by province, showing standard deviations from average, 2012/13Prov

ECFSGPKZNLPMPNCNW

Units: PercentageSource: DHIS

58


Figure 19: OPD new client not referred rate (district hospitals) by district, grouped by province, showing standard deviations from the average, 2012/13

Annual trends: OPD new client not referred rate (District Hospitals)

Perc

enta

ge

20

40

60

80

100EC FS

●●

●

GP

20

40

60

80

100KZN LP

●

●●

MP

20

40

60

80

100

2010

/11

2011

/12

2012

/13

NC

2010

/11

2011

/12

2012

/13

NW

EC A NzoEC AmatholeEC Buffalo CityEC C HaniEC CacaduEC Joe GqabiEC N Mandela BayEC OR TamboFS Fezile DabiFS LejweleputswaFS MangaungFS T Mofutsanyane

FS XhariepGP EkurhuleniGP SedibengGP TshwaneGP West RandKZN AmajubaKZN eThekwiniKZN iLembeKZN SisonkeKZN UguKZN uMgungundlovuKZN Umkhanyakude

KZN UmzinyathiKZN UthukelaKZN UthunguluKZN ZululandLP CapricornLP Gr SekhukhuneLP MopaniLP VhembeLP WaterbergMP EhlanzeniMP G SibandeMP Nkangala

NC Frances BaardNC JT GaetseweNC NamakwaNC Pixley ka SemeNC SiyandaNW BojanalaNW Dr K KaundaNW NM MolemaNW RS Mompati

●

●

59


Figure 20: Annual trends: OPD new client not referred rate (district hospitals)

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