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This 2 page Class Notes was uploaded by Tara on Monday October 3, 2016. The Class Notes belongs to HSC 4711 at Florida State University taught by Mark Kasper in Fall 2016. Since its upload, it has received 6 views.
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Date Created: 10/03/16
▯ 9/19/2016 ▯ Medical Model: Symptom/ Sign Assessment Biological Testing Diagnosing Treatment ▯ ▯ The bigger issue is “over-diagnosis” Medical Model of disease Harms and costs of over-treatment Driver is “over-diagnoses” Sub-Clinical disease- high sensitivity Ever lower risks Health system litigation (for under but not over-diagnosis) ▯ ▯ Genomics- Genomics is the study of all the genes in a person, as well as the interactions of those genes with each other and a person’s environment. All people are 99.9% identical in makeup, but difference in the remaining 0.1% hold important clues about health and disease Limitations: o Symptomatic Testing o High risk testing o Probability not certainty o Doesn’t suggest “severity” of disease o Interpretation and treatment issues o Lab error Potentials: o Identification of responders vs. non-responders o Targeted Treatment (to specific gene) o Specific treatment (Such as dosage or frequency) o Better outcomes o Avoid unnecessary procedures Harms: o Detection > Treatment (ethical issues?) o Anxiety, depression, suicide o Survivors Guilt (I don’t but my sibling does) o Parents Guilt (passed to my child) o Discrimination (Insurance & employment) ▯ ▯ Relative Risks: he most common statistics used to quantify the risk of mortal or morbid outcomes associated with different patient groups and therapeutic interventions ▯ ▯ Absolute Risk: One population Risk of developing a disease over a time-period “The lifetime risk of a women developing invasive breast cancer is __%” ▯ ▯ Numbers needed to treat: Average number of people needed to treat (screen) in order to have one additional (favorable) event occur A small value means a lot of favorable events in very little time ▯ ▯ Number needed to harm: In the vaccine group, 1.9% developed a fever. Only 0.8% of the controls developed a fever. Absolute difference= 1.9-0.8 = 1.1% “For ever 90 people who get the vaccine, you will see one additional fever on average” ▯ ▯
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