Hss4303b – intro to epidemiology April 8, 2010 – epidemiology and health policy

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  • Hss4303b intro to epidemiologyApril 8, 2010 epidemiology and health policy

  • Exam ReviewApril 22, 2pm-3:30pm, SCS E218

    April 26, 2pm-3:30pm, SCS E218

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

  • Important Poster Sh*tThe agenda and list of presenters is now posted on the websiteYour presentation time is also listedIf you are scheduled to present in the afternoon, you are still encouraged (dare I say, required?) to register in the morningIf you are not there to present to the judges when they come around, you will receive zero

  • What is this?

  • 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.

  • RISKThe techniques of epidemiology are used to collect data and create information to quantify risk in order to allow more informed policy.

  • What is health policy?

  • Dark blue slides are from Dr Spasoff, supercourse

  • Light blue slides by Dr Akram, supercourse

  • Policy is like sausage: it may taste good, but its best that you dont know what went into it

  • Epidemiology contributes at each step

  • What if questionsWhat 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

  • Clinical Decision MakingIn a clinical medical environment, sometimes we need to use evidence to quantify our decision-making processEg, to choose one therapy over another

  • Decision TreeAlso called chance nodeAlso called choice node

  • Data for Decision TreeEpidemiologyProbabilities of outcomesMeta-analysesSystematic reviewsAnalytical studiesPilot studies

  • Motivating Case: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.Example Slides by Dr James Kahn, UCSF, 2010 Decision Analysis

    without HAART

  • 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?

  • Overview of DA Steps1. Formulate an explicit question2. 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 action6. Perform sensitivity analysis

  • 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?

  • 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.

  • Simple Tree

  • More complicated tree

  • Crazy complicated

  • 3. Fill in the ProbabilitiesUse info from the literatureCase fatality ratesPopulation mortality ratesetc

  • Expected UtilityThe average or expected outcome if one follows a given branch of the treeSum of desirable outcomes within a given branch

  • Example of Expected utilityDisease = cardiac valve failureIntervention (decision) = surgery vs no surgeryIf surgery, possible outcomes are: complications vs no complicationsFurther possible outcomes are death or survivalIf no surgery, the only possible outcomes are death or survival

  • Example of Expected utilityLets follow surgery node:90% chance of no complications90% survive10% chance of complications50% survive

    What is expected utility at the surgery node?

  • Example of Expected utilityLets follow surgery node:90% chance of no complications90% survive10% chance of complications50% 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

  • 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

  • Back to Ms Brooks(Using a fairly complex system that I wont expect you to duplicate)

  • 5. Compute expected utility of each branch=0=0=.55=.55

  • 5. Compute expected utility of each branch=1.0=.55=.55=.9825=0=.9921=.977

  • Ms. Brooks

    Thanks But I meant I wanted to live the most years possible. Dying at age 80 isnt as bad as dying tomorrowWe recommend NO surgery.

  • Improve the AnalysisAdd layers of complexity to produce a more realistic analysis.

  • Eg: Add Another OutcomeThree outcomesDetermine utility as a portion of expected life span-Normal survival 1.0-Early death 0.5-Immediate death 0

  • Summary of Formal Decision AnalysisExplicit question.Decision tree.Probabilities of each outcome.Utilities for each outcome.Expected utility of each course of action.Sensitivity analysis.