VfM Tools:

Optimizing Value for Money

in Health SpendingWhat Ministries of Finance should know

Michael Borowitz, Chief Economist Global Fund

Sarah Barber, Head of WHO office, South Africa

Tomas Roubal, Health economist, WHO office, former health economist Czech Ministry of Health

Karen Hofmans, Wits, head of Priceless project, part of NICE-Gates network in South Africa.

2

VfM Tools

• National Health Accounts

• All health spending, not just public spending

• Out of pocket spending as key indicator

• Spending by different categories

• Allows comparative analysis

• Disease Accounts

• Measuring productivity—National Income and Product Accounts

Provider Payment

• Linking inputs with outputs and outcomes

• Results Based Financing

• New methods of hospital payment

• New methods of primary care payment: risk adjusted capitation, P4P/fee schedule

• Reforming Public Financial Management

• Priority Setting and Health Technology Assessment

• NICE and Gates support for HTA in Africa

• HTA for new technologies/value-based pricing

• Priority Setting

3

Overview of Health Financing in Africa

• What is normative spending levels for health?

• Total versus public versus oops

• Minimum package of public spending based on income WDR1993

• Global spending estimates for basic package

Growth trajectory for public spending

• Sin Taxes/Sarah Barber

• Health insurance Sarah Barber

One Health Tool module for Health planning

• Fiscal module—being revised

• Other needed tools from finance?

Stewardship (oversight)

Financing (collecting,

pooling and purchasing)

FUNCTIONS THE SYSTEM PERFORMS GOALS / OUTCOMES OF THE

SYSTEM

Health(level and equity)

Financial protection

and fair distribution

of burden of funding

Responsiveness

(to people’s non-

medical expectations)

Creating resources

(investment and training)

Service delivery

(personal and

population-based)

Goals of health systems, as per WHO’s

World Health Report 2000

Adapted from P. Travis

Cost sharing/user fees(provider payment)

Health care

Ind

ivid

uals

Collection of funds

Provision of services

Purchasing of services

Pooling of funds

Allocation mechanisms

Allocation mechanisms

(provider payment)

Allocation mechanisms

Coverage

Coverage

Choice?

Choice?

Contributions

Go

ve

rnan

ce, re

gu

lati

on

,

info

rmati

on

Policy choices in health financing

(lots of them!)

Diagnostic tree as a tool

Low public

spend on

health

Inequitable

distribution of

public

spending

Inefficiency

Possible

causes

Entitlements

unclear

High

OOPS in

poor

districts

Problem

(symptom)

UHC

dimension

Inequity in

service

use

High risk of

impoverish-

ment

Why?

Revenue

collection

Content

area

Population

engage-

ment

Benefit

design

Fiscal/macro

context

Public admin

structure

Pooling

Purchasing

Inadequate

equalization

Historical budget

incentives

Poor knowledge

of rights and

entitlements

Complex user fee

structure

Exemptions not

enforced

Less taxation in

poor regions

Low tax base

Low priority

But policy choices are constrained

• Fiscal context is especially relevant to health financing policy

– Taxation capacity, income, growth, labor market structure, etc.

– Limits what can be implemented (reform choices) and what can be achieved (extent of goal attainment)

• Other key contextual factors

– structure of public administration, strength of key interest groups, culture of public governance, etc.

Fiscal Space for Health

Availability of budgetary room for increasing

government spending for health without

jeopardizing macroeconomic and fiscal

stability.

Now we are also talking about prioritizing within

the budget

African health systems are

spending below Abuja target

-Is this a reasonable target?

-what is reasonable target?

-important task for this group!

Overall spending is critical

Not just government spending

Chatham House working group on

health financing

Minimum level of spending

Costing the basic package

Costing system building blocks

$40 per day

Benefits package for public

spending

Comparison of:

•Costed plans (planned expenditures)

with

•Financial space

available for

health (multiple

scenarios)

OneHealth Tool Financial Space

OOP varies from

4% to 76% of

THE in 2012

Influenced by a

number of factors

including HF

policy

Wide variation in OOP

Source: WHO estimates for 2012, countries with population > 600,000

• Catastrophic expenditure – OOPS that have a severe economic impact on

families

– Measured as OOPS exceeding a defined threshold of a household's non-subsistence spending (i.e. excluding spending for basic needs, such as food)

– For international comparisons, WHO uses a threshold of 40%, but other thresholds can be used

• Impoverishing expenditure– Extent to which OOPS pushes households below the

poverty line

– Can show the impact of OOPS on both the poverty “headcount” (number or percent of households Impoverished) and “depth” (magnitude of the impoverishing impact)

Two related measures of impact of out-

of-pocket spending (OOPS)

Xu et al. 2010

Financial protection

0.00%

2.00%

4.00%

6.00%

8.00%

10.00%

12.00%

Sou

th A

fric

a

Gha

na

Cro

atia

Ma

law

i

Cape

Verd

e

Djib

ou

ti

Th

aila

nd

Jo

rdan

Phili

ppin

es

Mo

rocco

Me

xic

o

Rw

an

da

Za

mb

ia

Yem

en

Sen

ega

l

Arg

en

tin

a

Tu

nis

ia

Sri L

an

ka

Ken

ya

Burk

ina

Fa

so

Ukra

ine

Leb

ano

n

Ban

gla

de

sh

Ugan

da

Nepa

l

Cam

bod

ia

Ind

one

sia

Egyp

t

Ind

ia

Kyrg

yzsta

n

Re

pu

blic

of M

old

ova

Chin

a

Colo

mb

ia

Geo

rgia

Côte

d'Iv

oir

e

Bra

zil

Vie

t N

am

% of hshds w/ catastrophic expenditure % of hshds w/ impoverishing expenditure

Globally each year:

150 million people face catastrophic expenditure

100 million people face Impoverishing expenditures

Source: compiled based on data from Xu et al. 2010

Medicines: underuse of

generics, higher than

necessary prices

Services: medical errors, sub-

optimal quality of care

Medicines: inappropriate or

ineffective use

Services: inappropriate

hospital size (low use of

infrastructure)

Medicines: use of sub-

standard and counterfeit

medicines

Services: inappropriate

hospital admissions and length

of stay

Services and products:

oversupply and overuse of

equipment, investigations,

procedures

Health workers: inappropriate

or costly staff mix, unmotivated

workers

Interventions: inefficient mix

or inappropriate level of

strategies

Leakages: waste, corruption,

fraud

Ten leading sources of inefficiency

Source: World Health Report (2010), Chapter 4

• Value for money = Cost-Effectiveness– Effectiveness: does it work

– At what cost? Intervention costing studies

– Cost/effectivness:• Gates Reference case

• CE thresholds

• Uses of Cost-effectivness– Generally introduced for new products

– Can be used to set benefit package for UHC

– Can be used for value based pricing

– Can be used for P4P indictators in provider payment

– Can be used for more generalised priority setting

Health Technology Assessment

Uncertainty of clinical effectiveness

Source: BMJ 2007

• Independent agency looking at VfM

-National Institute of Health and Clinical Excellence

(NICE)

-HITAP in Thailand

-Gates Funded International Decision

Support Initiative (IDSi)

support available if interested!

Institutional framework for HTA

The Gates Reference Case on Economic Evaluation:

The Gates-RC (Reference Case) sets out a standardised methodology based oncommon principles of good practice for the planning, conduct and reporting ofeconomic evaluations for informing priority setting in health.

The Bill and Melinda Gates Foundation commissioned the development of theGates-RC to be used in economic evaluations that receive BMGF funding, but theGates-RC has many further potential uses including:• empowering policy makers in low and middle-income countries to make their own

investment decisions based on relevant and high quality economic analyses;• driving methodological research; and• challenging the way donors and development partners think about the evidence

required to inform investments in health.• Using the reference case for Global Fund decisions on new technologies

This information session has been designed specifically Geneva-based colleagueswho were unable to attend the recent Gates-RC launch events in London. Thesession will introduce elements of the Gates-Reference Case and facilitate discussionabout the relevance of the Gates-Reference Case to individual organisations.

Sustainable UHC means actively setting priorities

by following a robust process that makes best use

of scientific evidence and people’s own values

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UHC

Financial protection Better health Social redistribution

Technical tools

•Different tools and evidence for priority-setting at different levels (e.g. operations research, clinical guidelines, HTA)•Redistribution objectives (e.g. targeting diseases that disproportionally burden the poor)

Process tools

• Active and explicit process

• Localised, inclusive decision-making, and independent from vested interests

• Downstream, implementation issues

Chalkidou et al. (2013) Lancet, Smith (2013) Health Econ.

Priority-setting

A growing network of partners

sharing the same principlesWe are committed to partnerships with academic,

public sector and international development

groups from across the world, and supporting

regional hubs for priority-setting.

Health Technology Assessment in South Africa

CABRI Johannesburg

2014

Karen HofmanUniversity of Witwatersrand School of Public Health

South African govt is spending a lot of money on health…

0

20

40

60

80

100

120

Housing Water supply School nutrition Welfare services Health services

Bill

ion

s o

f R

and

2009/10

2010/11

2011/12

22

South African govt is spending a lot of money on health…

0

20

40

60

80

100

120

Housing Water supply School nutrition Welfare services Health services

Bill

ion

s o

f R

and

2009/10

2010/11

2011/12

24

… but SA is not getting good value

for money

0

50

100

150

200

250

300

350

Public exp/cap US$ PPP LE at birth Under 5 mortality

Mexico

Brazil

South Africa

Russia

Thailand

25

A best buy is a measure of life years gained or magnitude of disease (DALY) prevented per

ZAR spent

Cost-effectiveness analysis: Compares costs and health outcomes of 2 or more interventions

Disability adjusted life year (DALY)

• Quantifies death PLUS disability in populations

• Allows morbidity and mortality to be expressed in a single measure

• Lower cost per health outcome is better

“Best Buys” in Sub-Saharan Africa

Health Intervention

Cost (in US$)

Per DALY

Averted*

Childhood Immunization $1-5

Prevention of traffic crashes $2-12

Malaria prevention $2-24

Surgical services and emergency care $7-215

Management of childhood illness $9-218

Cardiovascular diseases $9-273

HIV/AIDS prevention $6-377

Maternal and neonatal care $82-409

Adapted from: Laxminarayan, R. and Ashford, L. “Using Evidence About ‘Best Buys’ to Advance Global

Health.” Disease Control Priorities Project. August 2008.

By 2015, 15 interventions could save an additional 10,000 maternal and child lives in SA

Newborn and child interventions Maternal interventions

Intervention Lives saved

% lives

saved

Intervention Lives saved

% lives saved

1 Antenatal corticosteroids for preterm labour

1542 12% Labour and delivery

management*

615 49%

2 Labour and delivery management*

1315 10% Early detection and treatment

of HIV (pregnant women)

350 28%

3 PMTCT 1195 9% TB management in pregnant

women

158 13%

4 ORS - oral rehydration solution 1153 9% Clean birth practices 47 4%

5 Hand washing with soap 898 7% Inter-facility transport 20 2%

6 Case management of severe neonatal infection

885 7%

7 Water connection in the home 591 5%

8 ART for children 503 4%

9 Pneumococcal Vaccine 490 4%

10 Therapeutic feeding - for severe wasting

462 4%

11 Treatment of injuries 435 4%

Lives saved as % of total 9469 75% Lives saved as % of total 1190 94%

*Labour and delivery management counts towards saving both mothers and babies

PRICELESS SA

Priority

Cost Effective

Lessons for

Systems

Strengthening

South Africa

SYSTEMATIC DECISION-MAKING for HEALTH BASED ON EVIDENCE

32

Priority setting for HIV/AIDS, TB, Malaria, MCH, health

systems

• Many different models for optimising spending for HIV/AIDS

• New World Bank Optimyze includes best solution for money of allocative efficiency

• New models for TB

• Working on malaria

• MCH model with LIST—SA PRICELESS project

• One Health should has overall system tools

• Global Fund can support tool use in your country through Special Initiative

• Modelling combined with country support process

33

Sudan: Optimal allocation of 2013 funding levels to minimize

HIV incidence by 2020 (PMTCT fixed at 2013 spending level)

3

3

Re-prioritizing expenditure reduces cumulative HIV incidence by approx.

16,500 infections or 32% by 2020, while maintaining a small PMTCT program.

This optimal allocation also reduces cumulative deaths by about 6,700.

34

Bangladesh: used resource allocation tools to ground

discussion on what interventions to prioritize

0

20

40

60

80

100

120

140

160

180

0 50 000 100 000 150 000 200 000 250 000 300 000 350 000 400 000

QA

LY

s G

ain

s (

Th

ou

sa

nd

s)

IRS Hotspo 2 Diagnostic 4 LLN 60% - 1 IRS 25% po 3

…however, analysis showed that while targeted

IRS, improve diagnostic (from 80% to 100%)

and LLINs (coverage increase from 60% to 80%

were very effective, general IRS was incredibly

expensive and did not yield as much impact.

One plan considered was to do IRS for 25% of households at risk...

Cost 2014-2025 ($000s)

Low $/ High QALY gains High $ /QALY gained

Analysis of Malaria Programming (QALY gained (K) / $ 000s)

Provided quantifiable evidence to demonstrate how expensive it can be to eliminate malaria

and what could have been the missed opportunities to save lives by investing the money in

other health programs

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Application Status of the main resource allocation tools

Disease

Specific

Health

Sector

Tool Description Application Status

HIV:

AIM/Goals For intervention prioritization of general and concentrated

epidemics

Calibrated for 32 countries,

including 15 HI

AEM For intervention prioritization of concentrated epidemics Applied to 14 countries,

including 9 HI

OPTimyze For intervention optimization of different epidemics Applied to 21 countries,

including 9 HI

TB: TIME For intervention prioritization, models TB/HIV interaction New, applied to Sudan and

Bangladesh

Malaria:

JANUS Platform to link to various malaria epi models, support

intervention prioritization

Being applied to Mozambique

OpenMalaria Sophisticated dynamic malaria impact model support

intervention prioritization

Applied to Bangladesh,

Mozambique, Ethiopia and

Madagascar

SMI Simple model, quick to be calibrated Applied to Sudan and

Bangladesh

OneHealth Designed to be a one-stop shop Used in 27 countries,

including 9 HI

STAR Decision-making conferencing tool, provide visual

presentation of VfM, incorporating non CEA factors

Applied in UK, Italy, Sudan

and Bangladesh

WHO-

Choice

Provide normative guidance on whether an intervention is

cost-effective given certain threshold

Likely to be ready by the end

of the year for countries to use

36

OneHealth Tool: Launched May 2012

3

6

37

OneHealth: Model cost and impact with a health system approach

3

7

National

Hospital

Health Centre

Outreach

Community M

ala

ria

TB

HIV

Repro

ductiv

e H

ealth

WA

SH

Imm

un

iza

tion

Child

Health

Nutritio

n

NC

D

Oth

ers

InfrastructureHuman

Resources

Supply

Chain

Health

Information Governance

Health

Financing

Strengthening Health Systems

Financial Affordability

Lives saved,

healthier

populations

Increasing coverage

of effective

interventions

38

Pre-existing Tools Incorporated into OneHealth Tool

3

8

Tool Specific areas incorporated

MBB Bottleneck analysis, Fiscal space analysis;

Budget mapping

WHO (stop TB) TB planning

WHO (iHTP) Detailed intervention planning for

RMNCH (staff time minutes; drugs

commodities)

LiST (Lives Saves Tool) Impact for child and maternal health

Resource Needs Model Costs for HIV/AIDS interventions

AIM, GOALS Impact for HIV/AIDS interventions

WHO ( Child Health Cost

Estimation tool)

Intervention costing for child health;

Overall Framework for Programme

Activity Costing

FamPlan Impact for Family Planning interventions

UNFPA RH costing tool Costing reproductive health interventions

39

OneHealth Applications

Sector wide national planning and costing:Angola PNDS

Benin (3 year plan)

Botswana EPHS

Burkina Faso triennial health plan 2011-2013

Cap Vert national health plan

DRC national health plan

Kenya national health plan

Liberia (National Health and Social Welfare Plan of Liberia (2011-2021)

Mozambique national health plan 2013-2017

Senegal national investment plan

Sudan National Health Sector Strategy Plan 2012-2016

South Africa: Gauteng and KZN provinces

Lesotho –July 2013

Malawi national health plan

Specific programme focusEthiopia (reproductive health focus)

Lesotho (MNH)

Morocco (Plan d’action d’accélération de la mortalité maternelle et infantile pour la période 2012-2016)

Nigeria strategic malaria plan 2014-2020.

Nigeria HIV/AIDS response

Paraguay (National Comprehensive Condom Program )

Papua New Guinea (National plan for Child, Maternal and Newborn health)

Rwanda - National HIV/AIDS Strategic Plan

Sri Lanka (National and sub-national MCH and Nutrition plan)

Tajikistan (initial MNH focus)

Turkmenistan (National Safe Motherhood program 2013-2017)

Zambia (March 2013) – malaria and child health

Viet Nam RMNCH plan

Mongolia

• Move from inputs to outputs to outcomes

• Most African health systems use budget-based approach based on inputs.

• Almost all OECD countries have abandoned this approach and use more output based approaches to provider payment

• Key challenge now is linking output and outcome

Provider Payment: key future challenge

in African health systems

What are the options?

Payment Method Definition

Line-item budget Providers receive a fixed amount to cover specific

input expenses (e.g., personnel, drugs, utilities,).

Global budget Providers receive a fixed amount of funds for a

certain period to cover aggregate expenditures.

Budget is flexible and not tied to line items.

Per diem Hospitals are paid a fixed amount per day that an

admitted patient is treated in the hospital.

Case-based / DRG Hospitals are paid a fixed amount per

admission depending on patient and clinical

characteristics.

Fee-for-service Providers are paid for each individual service

provided. Fees are fixed in advance for each

service or group of services.

Diagnosis-related groups (DRGs) a specific case-mix based payment system, formula based

• A DRG case is characterized by a homogenous resource consumption pattern and at the same time is clinically meaningful – i.e. cases within the same DRG are economically and

medically similar

• Two core components and characteristics of a DRG-based payment system:– Exhaustive patient case classification system (i.e.

the system of diagnosis related grouping)

– Cost weights or prices given to DRGs in relation to the intensity of resources used

The base rate usually is a

monetary value and is the same

for all DRGs.

Grouping algorithm of the

respective DRG-system (set

of coding standards and rules

for assigning diagnoses and

procedures to cases)

The cost weight is usually a

relative measure which reflects

the relative use of resources of

a specific DRG compared to

other DRGs.

Cost weights setting and

adaptation:

There is need for

adaptation to get the

"right" relative costs for

a country context. Cost

weights are in principle

independent from

budgetary concerns.

Setting relatively higher

cost-weights allows to

over-compensate highly

cost-effective services.

This is the actual

reimbursement for the clinical

case. It is a monetary value

attached to the specific DRG.

Adjustment factors are a tool to

adjust the DRG-based payment

rate. Reasons can be additional

funding for teaching hospitals,

regional differences and many

others.

Expenditure ceiling:

While costing

considerations should

be taken into account

for setting the base rate,

this will also be largely

influenced by overall

available funds and

allows to build in an

expenditure ceiling.

The base rate can cover

all costs or specific

costs.

Clinical case:

- Patient‘s personal characteristics (age, co-morbidities etc.)

- diagnoses

- procedures

Specific DRG is

assigned to the

clinical case

Adjustment factors:

This allows for further

adjustment. Reasons

for adjustment factors

are manifold but often

compromise the

system as cost-

weights should

already reflect

differences in

resource intensity.

Design aspects

/ policy levers

Explanation

DRG variant:

The DRG variant (case

classification)

determines the number

of groups and how

disaggregated the

grouping turns out. If

the number of case

groups is too small,

providers have

incentives to focus on

easy cases per group.

Base rateAdjustment

factorXCost weight X=

DRG-based payment

rate for a case group

Formula

Mathauer/Wittenbecher (2013)

More and more low- and middle-income

countries implement or explore DRGs

Countries with established

DRG systems

1. Croatia

2. Estonia

3. Hungary

4. Indonesia

5. Kyrgyzstan

6. Lithuania

7. Macedonia

8. Mexico

9. Mongolia

10. Poland

11. Romania

12. Thailand

Countries exploring or piloting DRG payment

systems

1. Argentina

2. Bulgaria

3. Chile

4. Colombia

5. Costa Rica

6. Islamic Republic of Iran

7. Latvia

8. Malaysia

9. Montenegro

10. Moldova

11. Serbia

12. South Africa

13. Tunisia

14. Turkey

15. Uruguay

16. Viet Nam

In blue: meanwhile high-income countries Situation as of mid 2013

Mathauer/Wittenbecher (2013)

Results Based Financing/ Pay for

performance

• Rwanda model

– Autonomisation of

health facilities/bank

accounts

– Fee-for-service with

quality components

– External verification

• Wide roll-out

• Other RBF models

– Inter-provincial

budgetting/ Plan Nacer

in Argentina

• Mixed provider

payment in Estonia

• Donor-based RBF

• Verifiable contracts

with NGOs