Health Economics in a Nutshell:
A Blood Banking perspective
Evan M Bloch, MD, MS
Associate Clinical Investigator, BSRI
Assistant Adjunct Professor, UCSF
Conferencia Regional Seguridad Sanguinea en America Latina
Lima, Peru
30th March 2014
Today’s Presentation
Health economics in 15minutes…
•Similar to life in 35 seconds
•Caveats: neither comprehensive nor complete
•I’m no expert
• The principles of health economics
– What and why?
– Decision analysis
– Basic terminology: Quality Adjusted Life Years and Health state utilities
– How one evaluates “cost-effectiveness”?
– Benefits and limitations
• Health economics in the context of blood banking
–Successes and setbacks
–Example: Babesia microti
2
Introduction to health economics:
What and why?
What is health economics?
•Systematic identification, enumeration and valuation of costs
and benefits (or consequences) of health care interventions or
programs: ‘value for money’
•Welfare economics: Allocation of scarce resources in a way
that maximizes benefit to society (social welfare theory)
Why is it important?
• Scarcity
– insufficient resources for all activities or interventions
• Choice
– decisions between competing initiatives
– by choosing to use resources in one way we forego using
the same resources in other ways
3
Economics Do Matter
Inflation Adjusted Red Cell Service Fees
ABC Newsletter 2008
4
Determinants of health priorities
Where does Health economics fit in?
Robinson, Health Policy, 1999;49:13-26
5
How?
Decision Analysis and Health Economics
Decisions have to be made…
Are there ways to optimize the outcome?
Decision analysis is a systematic, quantitative, and
explicit approach for assessing the relative value of
different decision options
• assesses the probability and value of multiple outcomes
• enables incorporation of data from multiple sources, makes assumptions
explicit, and quantifies the decision parameters
• Highlights data strengths and deficiencies
6
Health Economics
Types of analyses…what do they mean?
Can we afford it?
• Budget Impact Analysis (BIA)
Is it Worth Doing?
• Cost-effectiveness: results expressed as a cost per natural
unit e.g. infection prevented or lives saved
• Cost-utility analysis: cost per QALY
• Cost-benefit analysis: costs and benefits expressed as
monetary values
7
Basic Terminology
QALY: Quality-Adjusted Life Year
• is a measure of disease burdenGain in QALYs
• The QALY is based on the number of years of life that would be
added by the intervention
– both quality and quantity of life lived
• QALY= year of life x health state utility
Health state utility
• Each year in perfect health is assigned the value of 1.0 down to a
value of 0.0 for being dead
– the extra years that are not lived in full health (e.g. Blindness,
amputation) incur a utility of between 0 and 1
– Based on perception of outcomes
DALY: The Disability-Adjusted Life Year
• alternative measure of overall disease burdenDALYs averted
• expressed as the number of years lost due to ill-health, disability or
early death
Terminology continued…
CER: Cost-effectiveness Ratio
CER is the ratio of the costs to benefits of an intervention e.g. treatment,
testing etc.
ICER: Incremental Cost-effectiveness Ratio
ICER is the ratio of the change in costs to incremental benefits of a
therapeutic intervention or treatment
If there is nothing currently in place e.g. comparing the addition of new
testing with no testing…CER and ICER will be the same
The analysis: getting started
The Decision Tree
Probability
Probability
Outcomes
Outcomes
Cost
Option #1
Cost
Option #2
The Decision Tree
Donor
deferral
and loss
Disposal
of
blood
Disease
progression
/clinical
sequelae
Prevalence
Donors≠
General
population
Transmissibility
Infection
averted
Infection
Complication
s
±death
Treatment
Performance
characteristics
Testing
Test
Cost
No Test
Cost
Loss of
income
No testing
The Decision Tree
Blood
culture
Treatment

febrile
reaction
s
Cost
Leukoreduction
Febrile
transfusion
reactions
No cost of
Intervention
Investigation
Probability
of febrile
reactions
Health
impact in
utilities
No leukoreduction
Additional considerations
Pitfalls and the complexity of analysis
Considerations
• Life-expectancy in transfusion recipients
• Risk varies by component
Methodology
• Health states are dynamic
• Inflation
• Discounting: adjusting future costs and outcomes to present day
value (money worth more today than it is in the future)
How much is cost-effective?
Based on societal willingness to pay…
• Historically, $50-100,000 per QALY gained (or DALY averted)
• Per WHO, 3 x Gross Domestic Product (GDP) per capita
–US (~$150,000 per QALY)
• Human component as to why one implements an intervention
–Ethics of resource allocation to certain populations, diseases etc.
–Childhood leukemia vs. myelodysplastic syndrome
–Breast cancer vs. prostate cancer
• What constitutes “cost-effective” differs based on perspective
–Blood center vs. hospital vs. patient vs. society
• Effects on blood banking decision making has been limited
–Implicit threshold of $1 million per QALY in the United States
14
Cost Utility and Blood Transfusions
Cost Utility League Table of Blood Safety Interventions
(USA Setting)
Intervention (Comparator)
Cost per QALY
($US)
Year of
Publication
HCV Ab (no screen)
Cost saving
1997
HIV Ab (no screen)
3,600
1988
WNV NAT (no screen)
520,000 – 897,000
2005
T cruzi Ab (no screen)
757,000 – 1,360,000
2010
PRT platelet concentrates (current screens) 458,000 – 1,816,000
2003
PRT platelets and plasma (current screens)
1,423,000
2010
Minipool HIV/HCV/HBV NAT (serology)
1,500,000
2004
Individual Donation HIV/HCV/HBV NAT
(serology)
7,300,000
2004
Bacterial culture of platelets
Not available
Syphilis and HTLVI/II
Not available
Babesia microti
See Example
Successes and Setbacks (USA)
Responding to emerging infectious
diseases
West Nile Virus Epidemic (2002)
– Risk per unit transfused during epidemic 25/10,000
– Within 1 year (2003) NAT testing initiated
– Since NAT, transfusion transmission rare
analysisunits
requires
– 2003 toThe
2010:cost
>3,000utility
WNV NAT-reactive
contemporary local or regional data
• Trypansoma Cruzi – Chagas disease
• Antibody screening for T. cruzi began in Jan 2007
• Rate of true positives is 1:30,000 units nationwide
• Analysis post implementation of universal testing:
– transfusion transmission very low
– Shift to one time donor testing for T. cruzi
– High cost and low enthusiasm for new tests
Quantifying the uncertainty
It’s not all about cost
• 1-way sensitivity analysis
– Evaluating the impact of a single variable on the CER e.g. prevalence
– Provides a high and low estimate of the CER
• Tornado diagram
– Series of 1-way sensitivity
analyses, shown graphically
• Monte Carlo method
– Computer simulation to assess
collective uncertainty across all
parameters
Transfusion Transmitted Babesiosis
A Contemporary Example of cost-utility analysis
• Babesiosis = tick-borne Intra-erythrocytic protozoan infection
• Majority of cases caused by B.microti
– widely endemic North Eastern and Upper Midwestern US
• Increase in naturally acquired and transfusion-transmitted babesiosis
• Over 162 transfusion associated cases since 1979 with 12 fatalities
– Any RBC containing product
• Clinical
– Mild febrile illness: immunocompetent
– Severe disease: at extremes of age, asplenic and
immunocompromised
– hemolytic anemia, renal-, cardiorespiratory failure and death
We DON’T tend to transfuse the healthy
Cost-effectiveness ratios (cost per QALY):
screening vs no screening, stratified by test modality and
extent of geographic inclusion
Costs, consequences, and cost-effectiveness of strategies for Babesia microti blood donor screening
strategies the US blood supply (unpublished)
Alex J Goodell, Evan M Bloch, Peter J Krause and Brian Custer
Cost effectiveness ratio:
intervention compared to no
screening
Incremental cost effectiveness
ratio (ICER):
intervention compared to the
preceding intervention
ELISA only
Four state
$2,615,000 ($290,000 - $10,540,000)
$2,615,000 ($290,000 - $10,540,000)
Seven state
$3,231,000 ($550,000 - $11,450,000)
$5,424,000 ($-20,730,000 - $29,360,000)
$6,685,000 ($1,610,000 - $20,720,000)
$11,720,000 ($3,560,000 - $69,980,000)
$20,276,000 ($-246,330,000 $276,430,000)
Twenty state
Fifty state
$8,921,000 ($2,610,000 - $29,420,000)
The model
highlights uncertainty surrounding
ELISA +estimates
PCR
of transmissibility, disease progression, and
epidemiology
Four state
$5,219,000 ($870,000
- $16,500,000)
$5,219,000 ($870,000 - $16,500,000)
Seven state
Twenty state
$6,582,000 ($1,250,000 - $17,340,000)
$14,228,000 ($3,520,000 $36,560,000)
$19,177,000 ($5,500,000 -
$11,436,000 ($-39,930,000 - $60,540,000)
$25,374,000 ($8,790,000 - $93,720,000)
Emotional decision making and blood safety
• Zero defect policy
– The legacy of HIV and blood transfusion
• The lemming effect
– Industry standards and the obligation to conform
– Competitive environment
• Perception
– Client hospitals and commercial ramifications of Transfusion
transmitted infection
– Public: increased awareness
• Fear
– Wasted resources: lessons learned from T.cruzi
– Implementation of testing with incomplete data
and no exit strategy
20
Conclusions
•
•
Decision analysis/health economics valuable tool
–
–
Cost analyses are only one source of data that will drive
decision-making
–
–
•
Quantifies value of a given intervention
Informs rational resource allocation
Not intended to be the single deciding factor
Dynamic: changing over time
It’s not all about the money
–
–
Highlights gaps in knowledge
Quantifies the uncertainty and the potential impact