Where are the data on health spending and HIV?

Understanding and using the evidence

Anna Vassall (PhD)HIV Modelling and Economics Group

London School of Hygiene and Tropical Medicine

Introduction

•Why estimate expenditures?•What do we know?

– Different efforts/ sources available– Some patterns

•Key issues – the way forward – Methods– Analysis/ Use

Definitions•What are we trying to measure?

•Expenditures not commitments/ budgets

•Disbursements vs. expenditures vs. ‘getting there in the end’

Why estimate expenditures?

To assess whether countries and donors adhere to their policy commitments and are meeting the resource requirements for services for populations impacted by HIV/AIDS

Why estimate expenditures?•Broader perspective – country level

• Tracking costs/ cost control• Showing ‘value for money’• Sector/ institution wide – enables the

planning revenues/ financial impact• Evaluation (cost-effectiveness, but also

resource allocation)• Comprehensive planning and priority setting

Why estimate expenditures?

•Some examples – global analysis– Patterns of flows for different epidemic and

country settings (Izazola-Licea et al 2009)– Examining what outcomes can be achieved

within current expenditure projections (Barnighausen et al IAEN 2010)

– Assessing fungability; examining net increases in HIV/AIDS expenditures, compared to DAH funds. (Lu et al 2010)

Levels of data?Advocacy- Aggregate estimates of expenditures, but also an

assessment of allocations by different groups/ countries

Research - Detailed expenditure data possibly on specific

interventions - Large datasets for cross-country analysesNational policy- Breakdowns by region, different interventions, time

series

Levels of data?

Not ‘one size fits all’ but look for standardisation and complementarity

Eg. micro-cost estimates used for national estimates and then validating global results

global methods can feed into country planning processes

Sources

NASA/UNAIDS – Detailed country based estimates using a

combination of sources– Annual monitoring report – 170 countries

report, supplemented by other data sources, by financing sources and categories

– (details to be presented later)

SourcesUNFPA resource flows (NIDI)

Survey of donors/ case studies/ projections 2008-2010

OECD DAC/CRS Annual reporting from OECD countries, some development banks and multi-laterals, includes coding for HIV/AIDS at the aggregate and project level

OECD ‘Plus’ - eg IHME/ PLAIDFilling gaps, other donors, errors, unreported data

Where are we?NASA

• Large subset of countries (50 countries) enabling cross country analysis

• Some examples of links with NHA (Kenya)OECD-DAC/ Plus

• Time series data emerging (comparable across sectors),

• Likely to under-estimate HIV/AIDS expenditures/ budget support.

• Private sector/NGO DAH expenditure tracking weakCountry level

• Positive case studies of NASA/ NHA exercises influencing policy,

• Patchwork availability of information, and linkage with government processes

The context: DAH funding

• Overall DAH growing rapidly– 1990 – US$ 5.59 billion– 2007 – US$ 21.79 billion

• Increases in both volumes and % for HIV/AIDS related DAH expenditures, until 2008– $US 0.2 billion 1990/ $US 0.7 billion 2000/$ US 4.9 billion

2007– Health systems support stagnated– MNH maintained %, (increasing amounts)– Tuberculosis and malaria increasing (although later than

HIV/AIDS)(Ravishankar, N et al, Lancet 2009. Lu et al, Lancet 2010)

All figures in 2007 US$

Other observations

• Some shift towards poorer countries and burden of disease (SSA 9.7%- 22.7%)

• Health sector suffers from large numbers of donors with specific projects.– High admin costs– Duplication

• High levels of fungability in the health sector, (at the aggregate level)

Some issues:Methodology - Estimation

Data quality• Substantial investment in primary data collection• Donor reporting

NGO sector expenditures

Bringing disease/ health area focused efforts and broader efforts.

General/ sector budget supportI

Example - PEPFAR Expenditure Reporting

Routine partner reporting of expenditures can provide critical data for PEPFAR field team planning and management– Provides fresh data on expenditures to capture

dynamic aspects of program– Provides estimation of USG costs-per-output across

program areas– Partner expenditures are mapped to outputs, by

program area– Allows PEPFAR teams to identify efficient and

effective programs and redirect outliers• Will ultimately support national level efforts to

improve programming and efficiency

Sample Output from PEPFAR Expenditure Analysis: Sample Output from PEPFAR Expenditure Analysis: Mean USG Cost Per Client Mean USG Cost Per Client Receiving Receiving Pre-ART Care

30%

38%

32%

$71.82Category Mean Range

Central Support 21.59 2.67-93.35

Operating 27.38 12.56-253.11

Investment 22.85 6.85-136.69

Total 71.82 31.91-483.15

Category ALL Partners

Range

Central Support 30 % 8 %-44 %

Operating 38 % 32 %-66 %

Investment 32 % 15 %-52 %

SAMPLE Cost Per Client by Cost Category (USD)

Distribution of Costs by Category

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IssuesUse - analysis/ research

•Costs that achieve ‘value for money’•Understanding the links between resource allocation and outcomes in HIV programmes•Additionality and complementarity•Sustainability/ financial impact

– Amounts/modalities/processes

Use at the country level

•Country level– Linking to national planning processes– Timely nature– Role of ‘brokers’ at the country level– Not a ‘one off’ effort– Incremental effort on country capacity– Layered efforts (full use of NHA flexibility)– Co-ordinated approach (not sellers of different products)– HIV/AIDS and NHA ‘ piggy –backing’ – Projections limited (MTEFs)

Example: GAVI use of funds to support NHA in Sudan

•GAVI funded the first NHA– A new expanded health economics unit– Indirectly supports training– No previous information on private sector in

Sudan or even public expenditures•But perhaps does not meet immediate need, and is it sustainable?

Conclusions/ Way Forward•HIV/ AIDS programmes will be increasingly asked to show ‘value for money’ •Co-ordination of efforts (standardise not blueprint approach)•Continuing support for OECD-DAC / internal donor reporting systems•Long-term approach (in the same way as building HMIS or other systems)

London School of Hygiene and Tropical Medicine Anna. Vassall@lshtm.ac.uk