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Teaching Pack

Valuing Individual Health Outcomes

An educational production of

All materials produced by the Center for Health Decision Science are free and publicly accessible for educational use

These companion slides accompany the videos included in the teaching pack on Valuing Individual Health Outcomes, in which students learn how to assign quantitative values to health outcomes at the individual level, including: expected utility theory, the axioms of this theory, distinguishing between preference-based measures of value and health-related quality of life outcomes, measuring utility using the standard gamble, the time trade-off, and the visual analog scale, and understanding the limitations of these measures.

This teaching pack was developed by Sue J. Goldie and Eve Wittenberg at the Center for Health Decision Science at the Harvard T.H. Chan School of Public Health. The multimedia components were developed as part of a series of pilots while constructing an online course for graduate students in public health.

Citation: Companion Slides. Teaching Pack: Valuing Individual Health Outcomes. Center for Health Decision Science, Harvard T.H. Chan School of Public Health 2017. https://repository.chds.hsph.harvard.edu/repository/2847/.

Valuing Individual Health Outcomes

https://repository.chds.hsph.harvard.edu/repository/2847/

Upon completion of this teaching pack students should be able to:

1. Define utility.

2. Distinguish between preferences and measures of health status.

3. Define expected utility theory and describe its axioms.

4. Describe how to perform a standard gamble and how to calculate standard gamble utilities.

5. Demonstrate an understanding of the limitations of the standard gamble and the advantages and disadvantages of alternative utility measures.

Valuing Individual Health Outcomes: Objectives

Companion Slides. Teaching Pack: Valuing Individual Health Outcomes. Center for Health Decision Science, Harvard T.H. Chan School of Public Health 2017http://repository.chds.hsph.harvard.edu

http://repository.chds.hsph.harvard.edu/

• Video 1.1 Including intermediary outcomes (~12 min)

• Video 1.2 Using the standard gamble (SG) (~17 min)

• Video 1.3 Alternatives to the SG (~10 min)

• Video 2.1 Putting utilities into a tree (~4 min)

• Video 2.2 Utilities for different people (~5 min)

• Video 2.3 Different methods, different utilities (~7 min)

Video Outline


https://vimeo.com/241045385






http://repository.chds.hsph.harvard.edu/repository/collection/5/

Video 1.1

Including intermediary outcomes:An example when facing a tough decision

after a motor vehicle accidentwith

Eve Wittenberg

Imagine a decision with three options for repair of a leg injury following a motor vehicle accident

Three options:

1. Experimental surgical repair

2. Surgical amputation

3. Do nothing



The goal is to allow for outcomes that are intermediate to survival (=1) and death (=0)



“An economic theory that describes how people make decisions when faced with an uncertain set of outcomes”

Expected Utility Theory



1. Completeness

2. Transitivity

3. Independence

4. Continuity

Axioms of Expected Utility Theory



1. Completeness: if 2 options exist, A&B, either A>B, B>A, or A=B

2. Transitivity

3. Independence

4. Continuity




1. Completeness: if 2 options exist, A & B, either A>B, B>A, or A=B

2. Transitivity: If 3 options exist, A, B, & C, if A>B and B>C then A>C

3. Independence

4. Continuity






3. Independence: If more than 3 options exist, A, B, C, and others, if A>C then another alternative such as E, F, or G does not change A>C preference

4. Continuity






3. Independence: If more than 3 options exist, A, B, C, and others, if A>C then another alternative such as E, F, or G does not change A>C preference.

4. Continuity: if A>B>C, then there exists a lottery between A & C such that a person is indifferent between B for certain and an A/C lottery




Continuity axiom



Video 1.2

Using the standard gamble (SG)with

Eve Wittenberg

• 0 = being dead

• 1 = perfect health, best imaginable health

Utility scale



How to value states between dead and perfect health: “intermediate states”?

“Standard gamble”

Certain outcome = intermediate state(a) Survive, prosthetic leg”(b) Survive, not able to walk and in pain

Gamble, or “lottery” is between dead (=0) and perfect health– fully functional leg (=1.0)



Standard gamble for “survive, prosthetic leg”: “Flo”

FLO

Is indifferent between certain state of prosthetic leg and gamble where probability of fully functional leg = 0.7 and dead =1.0-0.7=0.3

EV of gamble = 0.7

So utility of prosthetic leg = EV of gamble = 0.7



Standard gamble for “survive, not able to walk and in pain”: “Flo”

FLO

Is indifferent between certain state of survive, not being able to walk and in pain and gamble where probability of fully functional leg = 0.4 and dead =1.0-0.4=0.6

EV of gamble = 0.4

So utility of not being able to walk and in pain = EV of gamble = 0.4



Putting utilities back into decision tree



Averaging out and folding back tree

EV of experimental surgical repair branch = 0.8EV of surgical amputation branch = 0.686Value of no surgery branch = 0.4

So optimal choice for Flo is experimental surgical repair.



Video 1.3

Alternatives to the SGwith

Eve Wittenberg

Time trade-off (TTO): 10 years in intermediate health state = ? years in perfect health



TTO for prosthetic leg

6 years in perfect health = 10 years with prosthetic leg

TTO “utility” for prosthetic leg = 0.6



Visual Analog Scale (VAS)

NOT a utility

0-100 scale

“Where on line would you place your health?”



Video 2.1

Putting utilities into a treewith

Eve Wittenberg

Standard gamble can replace an intermediate state at end of tree branch

The break-even “gamble” or “lottery”—at the point of indifference with the intermediate health state--can replace that intermediate state returning the tree to one in which all outcomes are in terms of survival or death, 1 or 0.



Video 2.2

Utilities for different peoplewith

Eve Wittenberg

Different individuals may have different utility for the same health state

Utilities are subjective preferences, so may differ across individuals.

Flo places greater value on ambulation because she is a professional athlete. As a result, her utility for states with compromised mobility is LOWER than Maya’s (a writer by profession). Maya is also a mother of two, which may influence her willingness to trade any risk of death for improved health (as is the premise of the SG).



Video 2.3

Different methods, different utilitieswith

Eve Wittenberg

1. Standard gamble• Involves a trade-off• Interval scale• Incorporates uncertainty

2. Time trade-off• Involves a trade-off• Interval scale• No uncertainty

3. Visual analog scale• No trade-off• Ordinal, not interval scale• No uncertainty

Characteristics of methods



Created by the Center for Health Decision ScienceHarvard T.H. Chan School of Public Health

All materials produced by the Center for Health Decision Science are free and publicly accessible for educational use

chds.hsph.harvard.edu

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