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Hss4303b

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Hss4303b intro to epidemiology April 8, 2010 epidemiology and health policy Example of Expected utility Disease = cardiac valve failure Intervention (decision ... – PowerPoint PPT presentation

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Title: Hss4303b


1
Hss4303b intro to epidemiology
  • April 8, 2010 epidemiology and health policy

2
Exam Review
  • April 22, 2pm-330pm, SCS E218
  • April 26, 2pm-330pm, SCS E218

3
Poster Sht
  • For those printing their posters with the
    Geography dept or Merriam Print, the deadline is
    TODAY in order to assure pick-up by Saturday

4
Important Poster Sht
  • The agenda and list of presenters is now posted
    on the website
  • Your presentation time is also listed
  • If you are scheduled to present in the afternoon,
    you are still encouraged (dare I say, required?)
    to register in the morning
  • If you are not there to present to the judges
    when they come around, you will receive zero

5
What is this?
6
OTTAWA - Health Canada is advising Canadians
about important safety information for CRESTOR
(rosuvastatin). A recent US study has found that
Asian patients may be at greater risk of
developing muscle-related adverse events with
this drug. CRESTOR is a cholesterol-lowering
drug in the "statin" family. "Statins" are a
specific type of cholesterol-lowering
medication. In Canada, and internationally,
CRESTOR has been associated with reports of a
serious condition called rhabdomyolysis.
Rhabdomyolysis results in muscle breakdown and
the release of muscle cell contents into the
bloodstream. Symptoms of rhabdomyolysis include
muscle pain, weakness, tenderness, fever, dark
urine, nausea, and vomiting. In severe cases,
rhabdomyolysis can lead to kidney failure and be
life-threatening. For some patients, there may
be pre-existing conditions or other personal
factors that could cause a greater risk of
developing muscle-related problems, including
rhabdomyolysis, if they are using "statin"
medications.
7
RISK
The techniques of epidemiology are used to
collect data and create information to quantify
risk in order to allow more informed policy.
8
What is health policy?
9
Dark blue slides are from Dr Spasoff, supercourse
10
Light blue slides by Dr Akram, supercourse
11
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12
Policy is like sausage it may taste good, but
its best that you dont know what went into it
13
Epidemiology contributes at each step
14
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15
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17
What if questions
  • What if questions like What would be the
    effect on the overall health of the population if
    we reduced smoking by 20?
  • Sort of like program evaluation

18
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20
Clinical Decision Making
  • In a clinical medical environment, sometimes we
    need to use evidence to quantify our
    decision-making process
  • Eg, to choose one therapy over another

21
Decision Tree
Also called chance node
Also called choice node
22
Data for Decision Tree
  • Epidemiology
  • Probabilities of outcomes
  • Meta-analyses
  • Systematic reviews
  • Analytical studies
  • Pilot studies

23
Motivating Case
Example Slides by Dr James Kahn, UCSF, 2010
Decision Analysis
  • Ms. Brooks is a 50 year old woman with an
    incidental cerebral aneurysm. She presented with
    new vertigo 3 weeks ago and her primary MD
    ordered a head MRI. Her vertigo has subsequently
    resolved and has been attributed to
    labyrinthitis.
  • Her MRI suggested a left posterior communicating
    artery aneurysm, and a catheter angiogram
    confirmed a 6 mm berry aneurysm.

24
Case Presentation (contd)
  • Past medical history is remarkable only for 35
    pack-years of cigarette smoking.
  • Exam is normal.
  • Ms. Brooks I dont want to die before my time.
  • Question is Do we recommend surgical clipping of
    the aneurysm or no treatment?

25
Overview of DA Steps
  • 1. Formulate an explicit question
  • 2. Make a decision tree. (squares decision
    nodes, circles chance nodes)
  • a) Alternative actions branches of the
    decision node.
  • b) Possible outcomes of each branches of
    chance nodes.
  • 3. Estimate probabilities of outcomes at each
    chance node.
  • 4. Estimate utilities numerical preference for
    outcomes.
  • 5. Compute the expected utility of each possible
    action
  • 6. Perform sensitivity analysis

26
1. FORMULATE AN EXPLICIT QUESTION
- Formulate explicit, answerable question. - May
require modification as analysis progresses. -
The simpler the question, without losing
important detail, the easier and better the
decision analysis.
In the aneurysm example, our interest is in
determining whats best for Ms. Brooks so we'll
take her perspective. We will begin with the
following question Which treatment strategy,
surgical clipping or no treatment, is better for
Ms. Brooks considering her primary concern about
living a normal life span?
27
2. MAKE A DECISION TREE
Creating a decision tree structuring the
problem Provide a reasonably complete depiction
of the problem. Best is one decision node (on
the left, at the beginning of the tree).
Branches of each chance node -- exhaustive and
mutually exclusive. Proceed incrementally.
Begin simple.
28
Simple Tree
29
More complicated tree
30
Crazy complicated
31
3. Fill in the Probabilities
  • Use info from the literature
  • Case fatality rates
  • Population mortality rates
  • etc

32
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33
Expected Utility
  • The average or expected outcome if one follows a
    given branch of the tree
  • Sum of desirable outcomes within a given branch

34
Example of Expected utility
  • Disease cardiac valve failure
  • Intervention (decision) surgery vs no surgery
  • If surgery, possible outcomes are complications
    vs no complications
  • Further possible outcomes are death or survival
  • If no surgery, the only possible outcomes are
    death or survival

35
Example of Expected utility
  • Lets follow surgery node
  • 90 chance of no complications
  • 90 survive
  • 10 chance of complications
  • 50 survive
  • What is expected utility at the surgery node?

36
Example of Expected utility
  • Lets follow surgery node
  • 90 chance of no complications
  • 90 survive
  • 10 chance of complications
  • 50 survive

EU (P of no complications)(survival) (P of
complications)(survival) 0.90 x 0.90
0.10 x 0.50 0.81 0.05
0.86
37
COMPUTE THE EXPECTED UTILITY OF EACH BRANCH
  • Called "folding back" the tree.
  • Expected utility of action each possible
    outcome weighted by its probability.
  • Simple arithmetic calculations

38
Back to Ms Brooks
(Using a fairly complex system that I wont
expect you to duplicate)
39
5. Compute expected utility of each branch
.55
0
.55
0
40
5. Compute expected utility of each branch
.9825
.9921
.55
1.0
.55
.977
0
41
Ms. Brooks
We recommend NO surgery.
  • Thanks But I meant I wanted to live the most
    years possible. Dying at age 80 isnt as bad as
    dying tomorrow

42
Improve the Analysis
  • Add layers of complexity to produce a more
    realistic analysis.

43
Eg Add Another Outcome
Three outcomes Determine utility as a portion of
expected life span -Normal survival 1.0 -Early
death 0.5 -Immediate death 0
44
Summary of Formal Decision Analysis
  • Explicit question.
  • Decision tree.
  • Probabilities of each outcome.
  • Utilities for each outcome.
  • Expected utility of each course of action.
  • Sensitivity analysis.
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