Global Burden of Diseases, Injuries, and Risk Factors: An opportunity to strengthen health evidence in Indonesia

Professor Simon HayInstitute for Health Metrics and Evaluation, University of Washingtonsihay@uw.edu

“Knowledge is Power”

You can’t save lives if you don’t know what people are dying from

By measuring the health of everybody,

everywhere, the Global Burden of Disease

attempt to provides this knowledge

Some history

~100 causes, 8 regions

~300 causes, 188 countries, from 1990 to

2010, with annual updates (GBD 2013 and GBD 2015

published)

What is it, exactly?

A systematic, scientific effort to quantify the comparative magnitude of health loss from all major diseases, injuries, and risk factors for all ages, sexes, and geographies, and over time

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How many people die? (overall mortality)What do people die from? (causes of death)What makes people sick? (non-fatal health outcomes)What are the risks for health loss? (risk factors)

Eight scientific principles underlie the GBD methodology

Principle No. 1Consider all evidence

Principle No. 2Compare like with like

Principle No. 3Correct for errors

Principle No. 4Leave no blanks

Principle No. 5Communicate the strength of the evidence

Principle No. 6Ensure internal consistency

Principle No. 7Iterative approach to estimation

Principle No. 8Pick the best model based on performance

Unifying these components requires a framework

A global effort

~2,000 collaborators from 125+ countries and one territory

The Collaborative network:GBD Collaborators

Core Analytic Team

GBD Management Team

GBD Scientific Council

Independent Advisory Committee

The Collaborative network:GBD Collaborators are organized by country, roles:

Assess the face validity of country results.Identify missing datasets or inadequate or

incorrect interpretation of available data.Interpret findings and facilitate country policy

translation.Where feasible, undertake sub-national

assessments.

The Collaborative network:GBD Collaborators

Core Analytic Team

GBD Management Team

GBD Scientific Council

Independent Advisory Committee

The Collaborative network:GBD Collaborators

Core Analytic TeamResearch teams

DemographicsCauses of deathNon-fatal health outcomesSystematic reviewsCovariatesRisk FactorsCentral computationCancerInjuries

The Collaborative network:GBD Collaborators

Core Analytic Team

GBD Management Team

GBD Scientific Council

Independent Advisory Committee

The Collaborative network:GBD Collaborators (née “Experts”)

Core Analytic Team

GBD Management Team

Led by PI Chris Murray, with faculty leads and project managers

Facilitates the estimation process, ensures the study meets critical deadlines, and approves final GBD results

The Collaborative network:GBD Collaborators

Core Analytic Team

GBD Management Team

GBD Scientific Council

Independent Advisory Committee

The Collaborative network:GBD Collaborators

Core Analytic Team

GBD Management Team

GBD Scientific Council

Internal & external, chair Chris Murray

30 members (10 internal, 20 external)

Oversees GBD. Makes scientific decisions about GBD processes and methods

The Collaborative network:GBD Collaborators

Core Analytic Team

GBD Management Team

GBD Scientific Council

Independent Advisory Committee

The Collaborative network:GBD Collaborators

Core Analytic Team

GBD Management Team

GBD Scientific Council

Independent Advisory Committee

External advisory body (13), led by Dr. Peter PiotReports annually to IHME board

Advises & makes recommendations on new data collection & analysisCollaboration opportunities & dialogue

IHME Board of Directors• Chaired by Julio Frenk, IHME’s

Board of Directors is the most senior strategic governing body of IHME and composed of leading figures of public health from around the world

• IHME is grateful for the participation of Dr. Nafsiah Mboias a member of its Board of Directors

What were the results?

Key Results from the GBD 2015 for Indonesia

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Life expectancy in Indonesia increasing for males and females

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Change in Life expectancy 1990 (solid vertical line) to 2015 (dashed vertical line)

Change in Life expectancy 1990 (solid vertical line) to 2015 (dashed vertical line)

Rapid progress in reducing Under 5 mortality for males and females

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Reduction in Under 5 mortality driven by large decreases in death rate from Diarrhea/LRI/Common infections (light red) and neonatal (red)

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Indonesia ranked 5th

compared to countries in the region, for Under 5 mortality

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For all ages, large increase in death rate from CVD

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Leading causes of deaths, 2005 to 2015

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Leading causes of premature mortality, 2005-2015

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Leading causes of disability, 2005-2015

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Leading causes of total health loss (DALYs) and % change 2005-2015

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Leading risks for total health loss (DALYs) and % change 2005-2015

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What is next?

Partnering to generating complete burden of disease subnationally in Indonesia

Partnering to improve health evidence: subnational Global Burden of Disease collaborations

Overview

1) Demand and use for sub-national burden of disease2) GBD model for sub-nationals3) Determining subnational locations4) Data sources to inform sub-national BoD5) Data quality review/model interpretation and refinement6) Making sense of the findings

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Demand for subnational GBD estimates

• GBD 2010 generated considerable interest in benchmarking – using GBD estimates to examine how outcomes compare to peers.

• Next step in the policy dialogue is to consider how different regions within a country compare on key outcomes on change overtime.

• Local, timely and valid information useful for local decision-making.• Uses include setting overall strategy for public health, input to resource allocation

across units, identification of good and poor performers, tailoring human resource allocation to needs, national R&D priority setting, input to estimating future health expenditures, …..

In response to GBD findings, the UK government issued a call to action, started putting new health policies into place, created a burden of disease unit, and began to study disease burden subnationally.

“Despite real progress in cutting deaths, we remain a poor relative to our global cousins on many measures of health, something I want to change. For too long we have been lagging behind and I want the reformed health system to…turn this shocking underperformance around.”

UK and Public Health England collaboration

• Subnational analysis in GBD 2013o 9 regions of England oWithin each region, 5 quintiles of

deprivation defined geographicallyoScotlandoWales oNorthern Ireland

• Published in the Lancet September 2015

• PHE used results to set PHE strategy

Public Health England collaboration overview

• Core group was formed with leads from IHME and PHE in 2012• Initial findings benchmarking the UK against the rest of Europe were

presented to PHE in late 2012• Other collaborators were invited• PHE shared data with IHME• PHE researchers visited IHME to train, collaborate, and drive the all -

cause mortality work

Public Health England collaboration overview

• All estimation part of the GBD routine machinery• PHE established a Burden of Disease unit within the government• PHE has taken the lead on generating funding for the collaboration• England results were published September 2015• Next generation: burden at 150 upper tier local authorities

China collaboration overview

• China Centers for Disease Control, China Maternal and Child Surveillance System, and China Cancer Registration System collaborating with IHME

• Produced GBD 2013 burden of disease analysis at the province level

• Produced county level estimates of MDG4 with China MCSS

• Published province burden in October 2015

China collaboration overview• Policy dialogue with 200 participants hosted by China

Medical Board, Peking Union Medical College, China CDC, and IHME in Beijing in April 2013

• Chinese researchers visited IHME and IHME researchers visited China for training and technical knowledge sharing

• China provided detailed data• IHME provided baseline GBD research• Chinese researchers did their own analysis on top of

IHME work • Collaboration has produced multiple papers, some

published and some in production• National Commissioner for the National Commission for

Health and Family Planning sent a memo to the Politburo (governing body for China) proposing the use of HALE in the planning for the Healthy China 2030 initiative.

Overview

1) Demand for sub-national burden of disease2) GBD model for sub-nationals3) Level of disaggregation4) Data sources to support sub-national BoD5) Data quality review6) Model interpretation and refinement7) Making sense of the findings

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GBD model for sub-national assessments

1) Blend of the advantages of highly standardized GBD approach to mis-certification of causes of death and case definitions for disease and injuries and advantages of local leadership in the analysis.

2) Data identification, quality review, model interpretation and refinement, and report drafting led by national teams.

3) Central computation undertaken by the GBD – advantages of borrowing strength in Bayesian estimation components (CODEm, DisMod-MR 2.1), maintains comparability across time and geographies (garbage code redistribution, cross-walks).

Sub-national estimates -- Status

1) GBD 2013 included subnational assessments for the UK, Mexico and China

2) GBD 2015 includes UK, Mexico, China, Brazil, United States, South Africa, Kenya, Saudi Arabia, India, Japan

3) GBD 2016 will include Indonesia and England (upper tier authorities)4) Decision-making process: Selection of future subnationals will be

based on several criteria1) availability of data for the four building blocks2) national team willing to do most of the work, 3) if needed availability of supplementary funding, 4) global strategic importance for the GBD

Overview

1) Demand for sub-national burden of disease2) GBD model for sub-nationals3) Level of disaggregation4) Data sources to support sub-national BoD5) Data quality review6) Model interpretation and refinement7) Making sense of the findings

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Choice of subnational disaggregation

• To date, GBD sub-national assessment has been at mostly first administrative level.

• For China child mortality estimation at the county level.

• For the US because of the availability of data, we have developed a full set of age-sex-cause mortality and YLL estimates by county. But not yet full burden.

• For India, because of data availability, analysis is for state urban and rural separately.

• Future, second administrative level may be undertaken for full burden.

Overview

1) Demand for sub-national burden of disease2) GBD model for sub-nationals3) Level of disaggregation4) Data sources to support sub-national BoD5) Data quality review6) Model interpretation and refinement7) Making sense of the findings

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Data review

1) First step and part of the assessment of how hard it is to undertake a GBD subnational assessment is the data inventory.

2) Way to think about data is in terms of the platforms that collect data, and the content of what is collected by each platform.

3) Often data exists, but the biggest challenge is negotiating access to data across different parts of government, and different research groups within a country.

4) Best strategy is to try and engage everyone with relevant data as part of the subnational effort. Broad ownership of the results will also enhance uptake of the results.

Some key data collection platforms

1) Censuses (critical for pop denominator)2) Vital statistics – births, deaths with a death certificate (even if

incomplete). Sample registration also very useful3) Household surveys with or without biomarkers– DHS, MICS,

LSMS, GATS, national surveys, etc4) Patient – provider interaction data: Health facility administrative

records – hospital discharges, clinic visits5) Police records (useful for injuries and homicides)

Some key data collection platforms

6) Disease registries – population-based cancer registries, ESRD registries, others…

7) Health insurance claims data – new source that can if insurance is widespread be useful for some chronic conditions with long duration

8) Where national VR does not exist: Sample registration data or Demographic surveillance site data can be useful source

9) Reportable morbidity notification data – usually under counts but can help in geographic distribution

Identifying data sources – different in every country

• Published literature – need to search local language publications as well as international literature (most of the latter should already be in the GBD databases)

• Ministry of Statistics – many surveys run by statistical agencies of government• Ministry of Health – infectious disease notifications, registries, local surveys

(NTDs), administrative data,

Identifying data sources – different in every country

• Census Bureau – census data can be very useful for local assessment but has only a limited number of items

• Registrar-General – vital statistics, even incomplete, can be very helpful with appropriate corrections

• Surveillance sites – in countries without VR surveillance sites can be useful but generalizability is the key challenge

• International funded surveys – DHS, MICS, LSMS, others…

Overview

1) Demand for sub-national burden of disease2) GBD model for sub-nationals3) Level of disaggregation4) Data sources to support sub-national BoD5) Data quality review – model interpretation refinement6) Making sense of the findings

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Data quality assessment

1) Most labor intensive part of the subnational GBD work is assessing the quality of all the available data sources.

2) Local knowledge is critical to interpretation of findings: central challenge is distinguishing data error from special epidemiological circumstances in a subnational unit.

3) Including local expertise on diseases and risks can be an important contribution to this work.

Mexico collaboration overview

• Mexican collaborators worked closely with IHME on data selection, preparation, and analysisoProduced some of their own covariatesoVery involved in all-cause mortalityoWorked to sort out sources from subnational and

national• IHME went to Mexico to train researchers • Mexican researchers spent time at IHME• Based at INSP, the collaboration includes academia

and government

Data review and validation

Sharing of preliminary

results

Data review by local experts

Feedback on results

Integration of feedback

Reassessment of results

Creation of figures and

tablesManuscriptpreparation

Data prep Estimation of preliminary

results

Model refinement

• GBD cycle allows for several points to improve models. • For each of the components, first round models can be inspected,

outliers detected, covariates changed, change in model hyper-parameters to improve the model fit and plausibility.

Overview

1) Demand for sub-national burden of disease2) GBD model for sub-nationals3) Level of disaggregation4) Data sources to support sub-national BoD5) Data quality review6) Model interpretation and refinement7) Making sense of and disseminating the findings

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Making sense of and disseminating the findings

• Local knowledge and engagement with stakeholders across government and provinces will be critical to making sense of findings

• Dissemination efforts can include writing scientific publications, developing policy briefs and reports, and presenting to various audiences

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ProductsPeer-reviewed publicationsCountry profiles & reportsOnline visualization tools

Scientific impact? On GBD publications alone since 2012:

5,600+ citations

Five of the top 10 most cited papers in The Lancet since 2012

Policy Impact? IndonesiaThe Indonesian Directorate of Health Promotion and Community Development, MoH, used GBD data on mortality from malaria to inform it’s malaria elimination strategy

Policy Impact? RwandaGBD 2010: air pollution #1 risk factor for health loss

Health minister institutes program for distribution of 1 million clean cooking stoves

Wins $100,000 Roux Prize for turning evidence into impact

Policy Impact? EthiopiaNational burden of disease group forms among collaborators, submits national level papers

IHME post-graduate fellow, Dr. Awoke Temesgen, presents at conference in Ethiopia, invited to meet Ethiopian Public Health Institute (EPHI) Deputy Director

Deputy Director convenes meeting with Minister of Health, Dr. Kesete Admasu

Minister wants a burden of disease unit within MOH

Dr. Murray, Dr. Temesgen and Minister Kesete meet, agree to establish disease burden unit and do subnational burden

Policy Impact? USA“This research makes clear that poor nutrition is the single-greatest cause of preventable diseases and ailments in this country –the single-greatest cause. Simply what we put into our bodies – seems obvious, but we still resist that truth.”

-Michelle Obama

Public discourse? Obesity paper media release leads to 1200+ stories worldwide, including Lebanon, Pakistan, Chile, Australia

Public discourse?Breadth and depth of coverage

What’s next?

More collaboration = more local results = influencing local level policy as well as national policy