Transcript Building a Bridge over Troubled QALYs: Developing

Third Plenary Session
ISPOR 14th Annual International Meeting
Effectiveness in CEA: QALYS
Life expectancy multiplied by
health-related quality of life:
Quality-adjusted life years
Calculating QALYS:
If,
HRQL= 0.7
And,
A treatment gives 10 extra years of
life (@ 0.7 per year)
Then….
People receiving the treatment gain
an average of 7 QALYs each
A QALY is a QALY is a QALY
Saves
Lives
Improves
HRQL
#People HRQL
LE
100
x 0.8 x 50
=
=
QALYs
4000
10,000
=
4000
x
0.1
x
4
The cost-effectiveness of one thing
compared to another…
Cost treatment 1 – Cost treatment 2
Effectiveness treatment 1 – Effectiveness treatment 2
= COST per QALY
For example…
Cost
Life Expectancy HRQL
Group A
$80,000
2 Years
Group B
$ 8,000
1 Year
X
X
.6
.8
QALYS
=
=
Cost-effectiveness:
$80,000 - $8,000 = $72,000 = $180,000/QALY
1.2 – 0.8
0.4
1.2
0.8

The QALY is a widely used measure of
health gain.

Long-standing criticism of the theoretical
basis, and practical application of,
QALYs.

Plenary session, 10th Annual International
Meeting (Kahneman), May 2005.

Issues panel, 11th Annual International
Meeting (Fryback, Kahneman, McGuire),
May 2006.

Two-day invitational consensus
development workshop, November 2007.



Funding from AHRQ and NCI.
25 participants.
Discussion of:
- the basics of QALYs;
- the main challenges surrounding QALYs;
- retaining and enhancing QALYs;
- the use of QALYs in decision-making;
- towards a consensus on the QALY
Milton C. Weinstein PhD
Harvard School of Public Health, Boston MA, USA
George Torrance PhD
McMaster University, Hamilton, ON, Canada
Alistair McGuire PhD
London School of Economics, London, UK
Method for valuing health effectiveness
in cost-effectiveness analysis for
resource allocation decisions
 Values health based on time spent in
health states
 Endorsed by US Panel and NICE for
reference case


Represent individual patient preferences

Reflect equity, fairness, or political goals
Grounded in decision science (based on
expected utility theory)
 Individuals move through health states
over time.
 Each health state has a “value”
 Health = value-weighted time (QALYs)


Perfect health = 1.0, dead = 0.0

Interval scale properties
 e.g., 0.2  0.4 = 0.6  0.8

States worse than dead have
negative value
Value = preference (desirability)
 Valued by whom?

 individuals experiencing a health state or
illness
 individual who may or may not experience
that health state in the future
 individuals considering the health of a
community

(Values are for health states, not for changes in
health states)
What is being valued?
 Whom do we ask?
 What do we ask?
 How are health outcomes defined?




What is being valued?
Whom do we ask?
How are health outcomes defined?
Conventional QALYs allow for different
answers to these questions
 The answer depends on the question
being asked

Societal resource allocation: priority
setting across proposed programs or
interventions
 Societal (programmatic) audit:
evaluation of ongoing
activities/programs
 Personal clinical decisions or
decisions about insurance coverage


Personal clinical/insurance choice
 desirability of health outcomes to the
individual
 ex ante perspective

Societal/program audit
 current health of affected population
members, as valued by themselves
 ex post perspective (i.e. patient
preferences/experience utility)

Societal resource allocation
 individual health (aggregated) or
community health
 ex ante or ex post

Personal clinical/insurance
 the individual, +/- informed by
patients/disabled people

Societal/program audit
 members of the affected population

Societal/individual health
(aggregated)
or

Societal/community health
 representative sample of population
○ including patients/disabled people
○ informed by patients/disabled people







HUI-2
HUI-3
SF-6D
QWB
EQ-5D
15D
AQOL
 patient  health state
 community survey  value score
 US Panel and NICE reference case method
 different instruments give different results
 value scores may be population-specific

Health states
 valuation independent of duration or
sequence

Health states
 conventional QALY approach
 valuation independent of duration or sequence

Health paths (profiles)
 theoretically superior
 practical problem: large number of paths

Health changes
 can incorporate equity or fairness
 practical problem: large number of changes
 order of changes matters

QALYs should be discounted at the
same rate as costs (US Panel, NICE)
Erik Nord PhD
Norwegian Institute of Public Health, Oslo, Norway
Norman Daniels PhD
Department of Population and International Health, Harvard School
of Public Health, Boston, MA, USA
Mark Kamlet PhD
Heinz School of Public Policy and Management, Carnegie Mellon
University, Pittsburgh, PA,USA
The Conventional QALY

Defined as expressing the personal
utility of health outcomes as judged ex
ante, “on average,” by the general
public, from behind a veil of ignorance,
about future health, based on self
interest.
Issues:

(i) Substantial, empirical inter-method
variation in ex ante assessment
 SG yields higher values than TTO and greater
in turn than rating scale
 Which one is “right”?

(ii) Empirical unwillingness to trade-off
lifetime
 Means that less is invested in preventing the
outcome “confined to a wheel chair”
 Use of “experience” utility disfavors
prevention, use of ex-ante utility doesn’t
capture adaptation/foregone opportunities
iii. Concerns for fairness

No consideration for pretreatment health
state
○ At odds with ethical theory/public opinion that
suggests that in setting priorities societies
often emphasize how bad off individuals
would be without intervention
○ i.e. concern for “severity”
iii.Concerns for fairness

Conventional QALY model implies that the
value of an intervention is proportional to the
beneficiary’s capacity to benefit
 At odds with theory/public opinion that it should not
be held again people that they have conditions for
which there are no complete cures or whose
remaining lifetime is shorter

Similarly, life years gained for those at full
health valued more than life years gained for
those at less than full health
 Conflicts with equal right to protection of life by all
iv. Subtraction doesn’t “add up”

Standard QALYs measure differences in
health states, not gains in health
 Ex ante preference elicitation on health states and
subsequent subtraction of health state values from
one another
 Decreases data requirements, i.e. the number of
possible changes is much highter than the number
of possible states

Nonetheless, this is a proxy approach, yet to
be validated in the health economics literature
Incorporating concerns
for fairness

Count as “1” all gained life years if good
enough to be desired by affected persons
 Leads to inconsistencies with individual preferences


Place less weight on the duration of health
benefits in comparisons of programs for
patients with different life expectancies
Add explicit equity weights
 Overload the model?


Different “priority classes” for QALYS with
different ratio cut-offs
Treat “prevention” differently than “treatment”
Joseph Lipscomb PhD
Department of Health Policy and Management, Rollins School of
Public Health, Emory University, Atlanta, GA, USA
Dennis Fryback PhD
University of York, York, UK
Marthe Gold MD, MPH
University of Wisconsin, Madison, WI, USA
Dennis Revicki PhD
City University of New York Medical School, New York, NY, USA




For analyses requiring a summary measure of health
that integrates quantity of life and quality of life, QALY
is arguably the gold standard.
But should it truly be the coin of the realm?
Substantive concerns have been raised
Our conclusion (in preview): These conceptual and
methods issues signal opportunities for making
important incremental improvements in the QALY –
rather than abandoning the construct.

Conceptualization and construction of health states
- Which domains?
- Which health levels within each domain?

Psychometric approaches for eliciting preferences

Statistical strategies for deriving overall value weights
for QALYconv
For example……



Highly simple model structure: QALYconv linearly additive
function of time in health states, with an exponential
discounting factor to reflect time preference
Distributional and other ethical issues not formally
integrated into model
Some suggest that the value component of QALY should
be “experience-based” (from real-time perspective)
rather than “ex ante”

In fact, QALYconv plays important role in regulatory and
purchasing decisions in many industrialized nations
 But push back with NICE
 Non-QALY approaches being taken in France/Germany

Much less in U.S:





Not (yet) by FDA
Not (yet) by Center for Medicare & Medicaid Service
Not (yet) by most private payers
Recent studies suggest that resistance to CEA may be less than
suggested particularly given serious cost issues within public
programs and employers
Should we abandon the QALY?



QALYconv has proved to be serviceable vehicle for
quantifying joint mortality-morbidity impacts at
individual and population level
To abandon QALYconv now is to sever link to
hundreds of published studies & multiple ongoing
investigations – including many capitalizing on data
now collected in national surveys, clinical trials,
observational studies…..
A more productive pathway: pursue program of
research that takes QALYconv as starting point for
“continuous QALY improvement” over time


Prominent “health measurement systems” (e.g.,
HUI2/3, EQ-5D, QWB, and also SF-36) are the major
engines behind preference-based assessments,
including CEAs and population surveillance
Multiple applications now in national surveys of health
(e.g.,MEPS, U.S.-Canada Joint Survey, Medicare HOS)

But, basic issues about what exactly to measure
remain active topics for investigation
 All major systems view health as multidimensional concept, but
domains vary across systems
 Even for similar domains (e.g., Mobility/Ambulation) item content
differs across systems

Variations in domain structure allows selection of
particular QALYconv deemed best for application at
hand – but does not promote comparability across
studies. Solutions?
 Work toward “consensus domain structure” as one aspect of
community-based deliberative processes to identify and codify
citizen perspectives on health measurement, or else
 Cross-walk QALY scores between measurement systems

To appraise, and improve, item content (within a
domain), apply well-defined psychometric methods
 Mixed qualitative-quantitative approaches to improve content
and construct validity e.g. HUI2/3 and SF36v1/v2
 Promising development: application of item response theory
(irt) methods, e.g., Pickard et al. to study 3-Level vs. 5-Level
EQ-5D
Across the major health measurement systems, derivation
of the value component of QALYconv (the “Q part”) varies
in important ways:
 Method for eliciting preferences
- Standard gamble vs. time-tradeoff vs. visual analog scale
- Assumed duration of health state (1 day, 1 year, 10 years)

Deriving aggregate QALY score for a multidimensional
health state
- Multi-attribute utility modeling (HUI2/3)
- Econometric modeling (EQ-5D, QWB, SF-6D)

States worse than death
- EQ-5D and HUI2/3 allow for them
- QWB, SF-6D, HALex do not

Cross-walk scores across measurement
systems
 Predicting one set of QALY scores from another via
regression modeling (e.g., an EQ-5D to SF-6D mapping)
 Hierarchical irt modeling (a la Fryback et al) to map (for
example) from EQ-5D to irt-derived latent variable continuum
to SF-6D
or…….
 Initiate consensus process leading to
“Reference Case” QALY, establishing baseline
expectations about health state definition and
valuation
Additional issues raised about QALYconv
 No health state duration or sequencing
effects incorporated
 Investigate preferences over multi-state health profiles,
with states drawn from current measurement systems
(e.g., from the EQ-5D)

Value component of QALYconv based
(typically) on community-derived health state
preferences
 Instead, draw community preferences from those who’ve
experienced the states of health (Nord proposes SAVE)
 Instead, of using ex ante community preferences, use
experience-based valuations (Dolan and Kahneman)
 (The challenge is how to operationalize for efficient
application to health program evaluation)
Fairness matters – but it is not a matter that can be settled
by QALYconv
In response….

Equity Weighting: Factor fairness directly into the
preference weighting process (e.g., approaches advanced
by Nord, by Wagstaff, and by Johannesson)

Constrained Optimization Modeling: Maximizing QALY
improvement, subject to meeting equity conditions (e.g.,
as illustrated by Stinnett and Paltiel and by Chen and Bush)

Community-Based Deliberative Processes where the
implications of cost-effectiveness decisions based on
QALYconv can be examined for fidelity to public values
(e.g. Citizen’s Councils)
Must one decide between “building a bridge over
troubled QALYs” and “sailing off into the lesscharted waters” of non-QALY approaches?
False Choice!
Instead, cross that bridge and boldly set sail to new
lands,
(BUT treat the conventional QALY as the point of
departure for the development of new models in
order to capitalize on what has been learned
across many years. This will also allow us to
maintain continuity/comparability in tracking of
trends in population health and in CEAs.)
Paul Kind
University of York, York, UK
Jennifer Elston Lafata PhD
Center for Health Services Research, Henry Ford Health System,
Detroit, MI, USA
Karl Matuszewski MS, PharmD
Elsevier/Gold Standard, Tampa, FL, USA
Dennis Raisch BSPharm, MS, PhD
University of New Mexico, Albuquerque, MN, USA
 Who
are they?
 Faceless bureaucrats?
 Company management?
 Health plan CEOs?
 Mysterious, nameless committees?
 Doctors & hospitals?
 Patients?
 All of the above?

Matrix of potential users/uses of QALYs
 Patients, provider(s), employer/ins, govt.
 Observing health status, comparing to
reference norm, changes over time
 Aggregation levels (individual, groups, pop.)
Lack of consensus on HrQoL by
instrument developers, economists
 There is hope, there is no better
alternative

Pick a measure/methodology
 Incorporate into studies
 Report results
 Educate all constituencies

One health-based input to
decisions (of many)
2. Can be used at various levels in
health system
3. Reference method is required
1.
Michael Drummond DPhil
University of York, York, UK
Diana Brixner BSPharm, PhD
University of Utah, Salt Lake City, UT, USA
Marthe Gold, MD, MPH
City University of New York Medical School, New York, NY USA
Paul Kind
University of York, York, UK
Alistair McGuire PhD
London School of Economics, London, UK
Erik Nord PhD
Norwegian Institute of Public Health, Oslo, Norway
Context for consensus
Many “perspectives”
 Desire to move economic analyses
along in a manner that overcomes
outsider scepticism
 Therefore:

 Best agreement on high level principles
 Areas of departure described in the agenda
for further research
1. QALYs are but one input to
health care decision-making

There are always additional factors that society and
decision-makers must take into account, i.e.
 Equity, social justice
 Budget

These factors need to be incorporated within
healthcare decision making in a manner that allows:
 Transparency
 Legitimacy
2. QALYs can be used in different ways
at multi-levels of health care
Traditionally QALYs have been used for resource
allocation between groups in the population
 QALYs can serve additional purposes in systems
where there is no universal budget

 The context may be narrower when the
government is not the funder of health care e.g.,
○ different treatments for the same condition
○ focusing on health outcomes rather than $s.
3. Health is a determinant
of well-being
The QALY is a measure and valuation of
health, but intersectoral decision-making may
benefit from the broader context of the concept
of “well-being”
 (In the interim the QALY remains highly
serviceable for population-based health care
decision making)

4. Both ex-ante preferences
and experience should count
Health state valuations should reflect both
the experience of people who have familiarity
with them, as well as ex-ante preferences
that reflect forgone capabilities and
opportunities
 But, how do we take account of differences
between patients and the “inexperienced”
 Can differences be melded into a common
language to serve broader resource
allocation decisions?

5. Distributive issues must be
addressed satisfactorily
Cost/QALY is a measure of efficiency,
not of fairness
 Failure to attend to this distinction will
sink the credibility of economic
analyses
 (Distributive issues can be addressed
within the QALY measure itself, or
within the accompanying decisionmaking process)

6. Different methods for
valuing QALYs yield different
results
7. The QALY approach to
summing health gains over
time is simplistic
The Panel on Cost-Effectiveness in
Health and Medicine, 1996

Recommendations for Reference Case
analyses stopped short of endorsing a single
approach. Agreement:
 Generic HRQL
 0-1 scale preference based
 include domains important to the problem under
consideration;
 include effects of morbidity on productivity and
leisure

PCEHM research recommendations
 Support research that assesses the performance of
different measurement strategies in relationship to
others
 Compare valuation strategies
 Develop a catalogue of weights
8. The time has come for all good health
economists to rally behind a
Reference Case QALY

As an outcome measure for decision making,
the QALY continues to fall short of its potential
 CEAs remain non-comparable across diseases and
interventions
 Academic debate rolls on and distracts from progress
in moving economic analyses into mainstream
decision making

A process should be put in place to define a
reference case for QALY measurement
Reference Case QALY II: Ways
Forward
Acclaim a measure (without excluding
others)
 Use cross-walks that allow
interpretability between studies using
different measures
 Set up a consensus group to determine
criteria for a preferred approach

 An extant measure?
 Cross walks?
 New measure?
Michael Drummond DPhil
Professor of Health Economics
Centre for Health Economics
University of York
York, UK

Publication of the consensus workshop
proceedings in Value in Health (vol. 12,
suppl. 1, 2009) available free at:
http://www.ispor.org/meetings/Invitational/
WorkshopPhila1107.asp

Accompanying editorials, raising additional
challenges

Official pushback on QALYs, most notably
in Germany.

NICE’s supplementary guidance on ‘end of
life’ therapy.

Research agenda from the workshop.

Some additional thoughts.
The relevance of non-health objectives
to health-care decision-making.
 Case studies on the use of QALYs at
different levels in the health-care
system.
 Case studies on the use of QALYs in
decentralized, privately funded healthcare systems.

The impact of health on broader well-being.
 The role of an expanded QALY,
incorporating dimensions other than
health.
 The relationship between the valuations of
those experiencing, or having experience
of, health states and the valuations of the
general public.





Methods for briefing members of the public
on the experiences of those in particular
health states.
Comparisons between the main methods for
valuing health in respect of their
incorporation of distributional concerns.
Weighting schemes reflecting distributional
concerns.
Qualitative research into the community’s
views about distributional concerns.
Evaluation of health gains versus the
evaluation of health states.
 Research into the assumption of linearity of
preferences over time and the ways of
obtaining valuations of pathways or
profiles.
 Development of a reference case, or series
of reference cases, for estimating QALYs.

Any decision-making procedure for allocating
healthcare resources needs to weigh benefits
and costs, plus their distribution.
 All approaches are value-laden, whether the
values are made explicit or not.
 The main issue for health economics and
outcomes research is the extent to which
quantification and aggregation contributes to
the decision-making process.
