“Needs&based)budgetallocaons) –models)for)“ rurality”?Districtbudgetper)capita(average/...

“Needs-‐based budget alloca0ons – models for “rurality”?

Richard Cooke Rural-‐Proofing Policy and Budge0ng

Programme Workshop 04/11/2013

Economic ac0vity

Popula0on

Surface area

Percentages

45%

23%

15%

9%

7%

0.8%

2%

24%

71%

0.1%

2%

6%

4%

88%

Arid, Protected & Mountainous

Areas

High Density Periphery Low Density Periphery

Low Density Core

High Density Core

2% 11.2 million people

Classify South Africa’s territory in terms of accessibility & density of economic ac0vity/ popula0on (CSIR/STATS SA)

0.4 million people

Acknowledgement: CSIR/STATS SA

7% 10%

7% 5% 6%

9% 6% 9%

6% 3%

32%

KZN POPULATION (TOTAL) BY DISTRICT 2008/9

6% 14%

4% 4% 5%

5% 5% 9% 4% 3%

41%

DH BUDGET ALLOCATIONS BY DISTRICT ( AV. 2008-‐11)

District budget per capita (average/3yrs)

0

200

400

600

800

1000

1200

1400

1600

AVERAGE DISTR BUDGET/CAP (3yr mean)

Budget, Spend & Pop density

0

20

40

60

80

100

120

140

160

180

200

0 20 40 60 80 100 120 140 160 180

Average pe

r cap

ita bud

get/10

Average per capita spend/10

General RelaRonship between budget, spending and populaRon density at district level

UMgungundlovu

Ugu

Ilembe

Ethekwini

% Increase in budget in deprived areas

0

10

20

30

40

50

60

%INCREASE IN BUDGET (3 YRS)

Depriva0on Index 1.  Children below the age of 5 2.  Female-‐ headed households 3.  Household heads have no

schooling 4.  Unemployed 5.  Living in tradi0onal dwelling /

shack / tent 6.  no piped water on site 7.  a pit / bucket toilet or no form

of toilet 8.  have no access to electricity or

solar power

•  eThekwini is in the second-‐least deprived quin0le of South African districts (quin0le no 4).

•  Mgungundlovu and Amajuba are in the quin0le no 3

•  Uthungulu and Ilembe are in quin0le no 2.

•  The most-‐deprived quin0le of districts in South Africa (quin0le no 1) contains all of Uthukela, Ugu, Sisonke, Zululand, Umkhanyakude, and Umzinyathi districts.

Equity alloca0on at District Hospitals

Bethesda Hospital, KZN Northdale, Pietermaritzburg, KZN

Danger alert in NHI plans!!! “At the hospital level, accredited and contracted facili0es will be reimbursed using global budgets in the ini0al phases of implementa0on with a gradual migra0on towards diagnosis-‐related groups (DRGs) with a strong emphasis on performance management”

Source: NHI Green Paper

Diagnosis-‐related groups

Diagnosis -‐related group (DRG) systems are paRent-‐classificaRon systems that have four main characteris0cs: (1) rou$nely collected data on pa$ent discharge are used to classify pa$ents into (2) a manageable number of groups that are (3) clinically meaningful and (4) economically homogeneous.

DIAGNOSIS –RELATED GROUPS (DRGs) COSTED...

1 = All the Pneumonias

2 = All the Hip Replacements

3, 4, 5 = etc “CASE-‐MIX COMPLEXITY FACTOR (EACH “PRICED”).... Severity?

Treatment difficulty?

Prognosis?

Resource intensity?

AMOUNT OF BUDGET ALLOCATED !!!!!

Bumped up/Dropped down by a...


PERFORMANCE FACTOR (Care pathways)...

GROUP PATIENTS WITH THE SAME DIAGNOSES (EACH HAS UNIT ‘PRICE)

DRG APPROACH: INCENTIVES

HOSPITAL STRATEGY

HOSPITAL ACTION RURAL IMPLICATION

Reduce costs per paRent Raise income per paRent

Reduce length of stay

• Op0mize internal care pathways • Transfer to other providers increase • Inappropriate early discharges

Referral pathways more difficult to resource Access and outreach more difficult

Reduce intensity of provided services Change prac0ce paqerns

•  Avoid delivering unnecessary services • Subs0tute high-‐cost services with low-‐cost alterna0ves •  Bias :higher-‐revenue diagnoses

Specialisa0on is favoured, therefore reducing access

Select pa0ents Facility selects for its compe00ve advantage

Difficult to develop compe00ve advantage / economies of scale in rural

Diagnosis-‐related groups

INCENTIVE HOSPITAL STRATEGY

HOSPITAL ACTION

RURAL IMPLICATION

Increase number of pa0ents

Change admission rules

•  reduce wai0ng list • split care episodes into mul0ple admissions • admit pa0ents for unnecessary services (‘supplier-‐induced demand’)

Implies demand is close to need! Access and con0nuity of care more difficult

DIAGNOSIS –RELATED GROUPS (DRGs) COSTED...

1 = All the Pneumonias

2 = All the Hip Replacements

3, 4, 5 = etc

COMPLEXITY FACTOR.... Severity? Treatment difficulty?

Prognosis?

Resource intensity?

AMOUNT OF BUDGET ALLOCATED !!!!!

UNMET NEED

COVERAGE

NEED/ ACCESS / COVERAGE FACTORS (ACROSS ALL RELEVANT BUDGET ITEMS)... !!



Bumped up by a....

PERFORMANCE FACTOR....

ACCESS

DH Need +Access + Coverage

PHC

PHC

PHC

PHC

DH

Level of DeprivaRon

Burden of Disease

No of health points

RH

Distance to Regional Hospital

Av. Distance to clinics

Cost of PaRent Day Equivalent

Need & Access

Coverage

RESOURCES

Can we develop a tool to capacitate decisions around needs-‐based budge0ng?

District Hospital /35

Budget/

cap Budget Deprv. Index

No. of Health points

Average distance to clinic

Distance to RH

Cost of paRent day equiv.

Rankings out of 35 DH hospitals in KZN...

Source: KZN BAS/STP, courtesy of A. Mansvelder

DH Budget/Capita

Budget

Greytown Highest 17th highest

DeprivaRon Index (sub-‐district)

No of health points

Average distance to clinics

Distance to RH

Cost of paRent day equivalent

PMR

11th best 5th lowest

15th lowest

17th highest

“Middle range” (16th)

20



DH Budget/Capita

Budget

Hlabisa 8th lowest

6th highest


No of health points


Distance to RH


PMR/1000 live births

11th highest 2nd most

Longest! 18th highest

10th highest

23



DH Budget/Capita

Budget

Northdale 3rd lowest

Highest


No of health points


Distance to RH


PMR

3rd best Most! 16th highest

34th highest

Highest! 34



DH Budget/Capita

Budget

BenedicRne 4th highest

2nd highest


No of health points


Distance to RH



Most deprived

14th highest

23rd highest

8th highest

5th highest 35



DH Budget/Capita

Budget

Manguzi 2nd highest

11th highest


No of health points


Distance to RH



9th worst 29th highest

2nd lowest

Longest! “Middle range” (11th)

23

Interna0onal precedent... •  Transport vouchers in China, Taiwan, Korea, Nicaragua and Mexico •  “Cri0cal Access Hospitals” in the US (further than 35 miles away

from another hospital, or 15 miles in the case of mountainous terrain)

•  An independent body advises the Australian government on a fair /efficient price for hospital services, including considera0on of the health care needs of rural Australians

•  The state of Victoria (Aus) accounts for “small rural facili0es” when alloca0ng funds

•  In Tanzania, budget alloca0on considers popula0on size, poverty levels and a proxy for burden of disease, AND “the mileage covered for service supervision and distribu0on of supplies (10% weigh0ng)”

Sources: Available on www.rhap.org.za

Can’t just throw good money auer bad

OPTIMAL FINANCIAL MANAGEMENT

PLUS INDICATORS OF:

CONTINUITY OF CARE AND OUTREACH

COMMUNITY NEED

EFFICIENCY EQUITY EFFECTIVENESS SUSTAINABILITY

MEETING TARGETS COST/BENEFIT

STAFFING NORMS

CAPACITY / QUALITY OF CARE

ADVERSE EVENTS/ PATIENT COMPLAINTS

“PERFORMANCE” UNDER NHI

Equality vs Equity: Can we document the evidence on the ground?

EQUAL HEALTH OUTCOMES FOR ALL

Urban Community Rural Community

Crypto outcomes (as current policies and prac0ce)

Burden of disease

Fewer resources

Fixing failures

Fragile family

R E S O U R C E S

Depriva0on

RURAL-‐PROOFING REQUIRED!

Head-‐start!

“Needs&based)budgetallocaons) –models)for)“ rurality”?Districtbudgetper)capita(average/...

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