Transcript Slide 1

Global Health Decisions:
a web tool for HIV decision-making
Mohsen Malekinejad MD DrPH 1
Elliot Marseille DrPH, MPP 2
James G. Kahn MD, MPH1 (PI)
1 - Philip R Lee Institute for Health Policy Studies
University of California San Francisco, San Francisco, CA
2 - Health Strategies International, Oakland, CA
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Overview
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First section (~20 min)
• Background
• Methods
• GHD website conceptual model
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Q&A (10 min)
Second section (~15 min)
• GHD live website tour
• Case study: Ghana
• Next steps
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Background: Policy-making in HIV
global settings – Challenges
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Efficacy (risk reduction in ideal setting) essential
but insufficient alone
Evidence on intervention effectiveness often
scarce - reliance on research from less-relevant
settings
Complexity and inconsistency of data reported in
scientific journals is daunting
Policy-makers often lack advanced
epidemiological or cost-effectiveness training
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GHD – Goal
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To Provide health policymakers around
the globe with an evidence-based and
easy-to-use web application that
translates scientific data into the likely
costs and health benefits of prevention
and treatment portfolios.
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GHD: Specific Aims
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Assess evidence of effectiveness (vs. Efficacy) of
HIV prevention and treatment: How well does the
intervention evidence base reflect real-world
practice?
Translate the effect of specified interventions
implemented at large scale into reduced
population-level disease burden measured in
DALYs
Calculate the cost-effectiveness of sets of
interventions, incorporating effectiveness, burden
reduction, and cost
Make findings easily accessible to decisionmakers and other technical and non-technical end
users thorough a web-based resource
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Methods – Overview
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Studies search & screening: systematic review of
selected HIV prevention and treatment interventions
Data Extraction: relevant HIV outcome and cost data
Data analysis: translate outcome data into a
standard metric of RRR and conduct meta-analysis
Assess internal validity: rate scientific quality of
evidence
Assess external validity: rate relevance of evidence
to a specific target setting
Epi model: develop parsimonious model to evaluate
intervention effects
Cost-effectiveness model: calculate incremental costeffectiveness ratio
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Methods – Search & Screening
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Search: conduct searches of systematic reviews in major
biomedical and public health databases
• Interventions: HIV testing and counseling, needle and syringe
exchange program, opioid substitution treatment, sex worker
programs, prevention of mother to child transition, antiretroviral
treatment.
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Screening: dual independent screening based on pre-defined
inclusion and exclusion criteria in three levels:
1. Systematic reviews: stepwise (Title & Abstract, Full text)
2. hand search references of SRs to extract individual studies
3. Individual studies: stepwise (Title, Abstract, Full text)
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Expert consultation. contact topic experts for studies or
documents potentially missed by search process.
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Methods – IOPT Extraction
extract all relevant data points at the level of
Intervention, Outcome, Population Trio (IOPT)
 different than conventional systematic reviews with narrow
scope
 Why IOPT? Studies report >1 useful data point share
some overall aspects of the study (e.g., settings,
investigators, etc.), but vary in respect to other aspects:
1. Intervention: subjects may receive different
intervention due to variations in dose, frequency,
and content of interventions.
2. Outcomes: different time-interval, or type (e.g.,
morbidity, mortality, behavioral)
3. Population: sub-analysis of findings by severity of
underlying diseases (e.g., HIV serostatus)
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Methods – Data Analysis
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Studies report data in various type (RR, OR, pre-post
prevalence)
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transformed all data type to standardized outcome
metric of “relative risk reduction” - RRR
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RRR: the proportionate reduction in risk of negative
health outcomes associated with the intervention – e.g.:
RRR = control event rate (CER) – experimental event rate
(EER) control event rate (CER)
RRR = 1- RR
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RRR facilitates comparison across studies and
intervention types with varying levels of baseline risk
Meta-analysis: random effect model using inverse of
variance to calculate summary effect measure and 95%
CI
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GHD Internal Validity (GIV)
Scoring System
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Objective: To assess and translates
methodological aspects underlying data points into
a simple, transparent, and intuitively meaningful
ordinal score (1 – 6)
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Modified version and hybrid product of two
existing tools EPHPP and Cochrane GRADE
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GIV score generated at IOPT level in three steps:
1. Assign an initial score based on study design (1–5)
2. Rate the potential risks of bias to adjust initial
score
3. Assign an overall GIV score (0 – 6)
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GIV - Domains
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Study design (used to assign the initial score)
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Comparability of study arms
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Performance of intervention provider
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Performance of outcome assessor
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Performance of participants
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Accuracy of measurement tools
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Withdrawal and differential drop-out
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Intervention contamination
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Conflict of interest
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GIV - Advantages
Four important features representing
improvement over earlier efforts:
1. More precise capture of differences in study
design and risk of bias
2. Assessment of the risk of bias at the level of
an intervention-outcome pair
3. Relatively easy to implement by research
staff
4. Sophisticated algorithm to automate
calculation of internal validity score
Methods – GHD External
Validity (GEV)
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Objective: Allow user to consider external
validity in assessing body of effectiveness
evidence.
Definition: Set of indicators that describe
how likely it is that the results found in a
study will be replicated in a target setting.
Methods – GEV
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Indicators. Reflect geography, population,
implementation details, ability to scale and legal and
cultural context.
Indicator weights. Assigned weights to reflect relative
importance of each indicator.
• Delphi two rounds
• Principle component analysis (PCA)
• Meta-regression
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Scoring. GEV instrument generates a score for each IOPT
and for intervention as a whole.
Methods – Epidemiologic Model
Parsimonious models that relate epidemiology, RRR and
coverage, to change in disease burden for each
intervention; integrated with other intervention models.
Inputs
 Epidemiologic data – population by risk group, prevalence
and incidence.
 Estimates of RRR for different outcomes.
Outputs
 Estimate key health outcomes, e.g., averted infections,
deaths, morbidity, DALYs.
Calibrated parsimonious models for each intervention against
full, validated models.
Methods – Cost
GHD developed a methodology for rating published costing
studies, and used that data in a costing tool that generates
costs in US $ today, adjusted from other years, other
currencies, and across geographic locations.
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Costs of components (e.g., personnel, goods and
services) were identified and adjusted using a hierarchy
of sources.
GHD generated costs of interventions
• By units (per person served)
• By duration (per person year of service)
• By method of intervention delivery
Methods – Cost-Effectiveness
Determining CE involves:
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Summing cost across time and interventions;
Calculating averted disease burden;
Comparing across intervention sets (e.g. current vs
proposed); and
Calculating Incremental Cost-Effectiveness Ratio
(ICER).
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GHD – Web Conceptual Model
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Q&A
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Detour – GHD LIVE
www.globalhealthdecisions.org
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What’s Next for GHD?
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To complete data extraction and analysis (RRR,
GIV, GEV) for 3-4 more interventions
NIDA proposal – focusing on integration of
HIV,HCV, TB, and drug abuse services for
injection drug users
NIMH proposal – expand data extraction for more
HIV interventions and other disease areas
Field test GHD with policy-makers in Africa to
assess usability and uptake
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GHD Team
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Investigators:
James G. Khan MD, MPH (PI)
Mohsen Malekinejad MD, DrPH
Elliot A. Marseille DrPH MPP
Jonathan Showstack PhD MPH
Ali Mirzazadeh MD PhD
Senior researchers:
Sabina S. Alistar PhD MS
Stephane Verguet MS PhD MPP
Research support:
Devon McCabe MA
Alex J. Goodell
Pam DeCarlo BA
Erin Barker MLIS
Justina Wu MPH
Jeff Loi MS
Leon Traister BS
Grant Storey
Lena Libatique
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Thank You
GlobalHealthDecisions.org