Health Economics in a Nutshell:

About This Presentation
Title:

Health Economics in a Nutshell:

Description:

Health Economics in a Nutshell: A Blood Banking perspective Evan M Bloch, MD, MS Associate Clinical Investigator, BSRI Assistant Adjunct Professor, UCSF – PowerPoint PPT presentation

Number of Views:9
Avg rating:3.0/5.0
Slides: 22
Provided by: Evan163

less

Transcript and Presenter's Notes

Title: Health Economics in a Nutshell:


1
  • 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
2
  • Todays Presentation
  • Health economics in 15minutes
  • Similar to life in 35 seconds
  • Caveats neither comprehensive nor complete
  • Im 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

3
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

4
Economics Do Matter Inflation Adjusted Red Cell
Service FeesABC Newsletter 2008
5
Determinants of health prioritiesWhere does
Health economics fit in?Robinson, Health Policy,
19994913-26
6
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

7
  • Health Economics
  • Types of analyseswhat 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

8
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

9
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
testingCER and ICER will be the same
10
The analysis getting startedThe Decision Tree
Probability
Probability
Outcomes
Outcomes
Cost Option 1
Cost Option 2
11
The Decision Tree
Disease progression/clinical sequelae
Prevalence Donors? General population
Donor deferral and loss
Disposal of blood
Transmissibility
Complications death
Infection averted
Infection
Treatment
Performance characteristics
Test Cost
No Test Cost
Loss of income
Testing
No testing
12
The Decision Tree
Blood culture
Investigation
Treatment
Febrile transfusion reactions
? febrile reactions
Probability of febrile reactions
Health impact in utilities
Cost
No cost of Intervention
Leukoreduction
No leukoreduction
13
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)

14
  • 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

15
Cost Utility and Blood TransfusionsCost Utility
League Table of Blood Safety Interventions (USA
Setting)
Intervention (Comparator) Cost per QALY (US) Year of Publication Year of Publication
HCV Ab (no screen) Cost saving 1997 1997
HIV Ab (no screen) 3,600 1988 1988
WNV NAT (no screen) 520,000 897,000 2005 2005
T cruzi Ab (no screen) 757,000 1,360,000 2010 2010
PRT platelet concentrates (current screens) 458,000 1,816,000 2003 2003
PRT platelets and plasma (current screens) 1,423,000 2010 2010
Minipool HIV/HCV/HBV NAT (serology) 1,500,000 2004 2004
Individual Donation HIV/HCV/HBV NAT (serology) 7,300,000 2004 2004
Bacterial culture of platelets Not available Not available Not available
Syphilis and HTLVI/II Not available Not available
Babesia microti See Example See Example
16
Successes and Setbacks (USA) Responding to
emerging infectious diseases
  • West Nile Virus Epidemic (2002)
  • Risk per unit transfused during epidemic
    2-5/10,000
  • Within 1 year (2003) NAT testing initiated
  • Since NAT, transfusion transmission rare
  • 2003 to 2010 gt3,000 WNV NAT-reactive units

The cost utility analysis requires contemporary
local or regional data
  • Trypansoma Cruzi Chagas disease
  • Antibody screening for T. cruzi began in Jan 2007
  • Rate of true positives is 130,000 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

17
Quantifying the uncertaintyIts 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

18
Transfusion Transmitted BabesiosisA 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 DONT tend to transfuse the healthy
19
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)
Twenty state 6,685,000 (1,610,000 - 20,720,000) 11,720,000 (3,560,000 - 69,980,000)
Fifty state 8,921,000 (2,610,000 - 29,420,000) 20,276,000 (-246,330,000 - 276,430,000)
ELISA PCR  
Four state 5,219,000 (870,000 - 16,500,000) 5,219,000 (870,000 - 16,500,000)
Seven state 6,582,000 (1,250,000 - 17,340,000) 11,436,000 (-39,930,000 - 60,540,000)
Twenty state 14,228,000 (3,520,000 - 36,560,000) 25,374,000 (8,790,000 - 93,720,000)
Fifty state 19,177,000 (5,500,000 - 55,870,000) 44,315,000 (39,800,000 - 533,000,000)
The model highlights uncertainty surrounding
estimates of transmissibility, disease
progression, and epidemiology
20
  • 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

21
Conclusions
  • Decision analysis/health economics valuable tool
  • Quantifies value of a given intervention
  • Informs rational resource allocation
  • Cost analyses are only one source of data that
    will drive decision-making
  • Not intended to be the single deciding factor
  • Dynamic changing over time
  • Its not all about the money
  • Highlights gaps in knowledge
  • Quantifies the uncertainty and the potential
    impact
Write a Comment
User Comments (0)