Public Health Sciences Flashcards
Cross sectional study
Frequency of disease and risk factors both assessed in the present
Measured by disease prevalence
Case control study
Group of people with a disease compared to a group without disease, look at ODDS of prior exposure or risk factor makes a difference
Measured by OR
Cohort study
Looks at a group with a given exposure/risk and a group without and assesses risk factor association with disease development later on
Measured by RR
Can be prospective (who will develop) or retrospective (who developed)
Phase I drug trials
Assesses safety, toxicity, pharmacokinetics/dynamics in small # of healthy volunteers
Phase II drug trials
Assesses if it works – treatment efficacy, optimal dosing, adverse effects in small # pts with disease
Phase III drug trials
Compares tx to standard of care or placebo to see if its an improvement in a large number of randomly assigned patients with disease
Phase IV drug trials
Postmarketing surveillance – if rare/long-term adverse effects may be withdrawn from market
Sensitivity
TP/(TP+FN) or 1-FN
Def: when disease present, how many test positive
Highly sensitive rules OUT disease (i.e. low false negative) – best for screening
Specificity
TN/(FP+TN) or 1-FP
Def: when disease not present, how many test negative
Highly specific rules IN disease (i.e. low false positive) – best for confirmation after screening
PPV
TP/(TP+FP)
Def: Proportion of positives that are true positives
Person with a positive test actually has disease
Varies with pretest probability (higher pretest prob –> higher PPV)
NPV
TN/(TN+FN)
Def: Proportion of negatives that are true negatives
Person with a negative actually doesn’t have disease
Varies w/ pretest probability (higher pretest prob –> lower NPV)
LR+
Sense/(1-spec) = TP/FP
>10 useful diagnostic test
LR-
(1-sens)/spec = TN/FN
<0.1 useful diagnostic test
(- –> negative sign on top!)
Odds ratio
OR=(a/b)/(c/d) or ad/bc
Used in case control studies to depict odd of event given an exposure vs odds of it happening w/o exposure
Relative risk
=[a/(a+b)]/[c/(c+d)]
Used in cohort studies to determine risk of developing disease in exposure group divided by risk in unexposed group
-For rare disease (i.e. low prevalence) – approximates RR
-If 1 –> no relationship between exposure/disease
-If >1 –> positive association between disease and exposure
-If <1 –> negative association between disease and exposure
Attributable risk
Difference in risk between exposed and unexposed groups – proportion of disease attributable to exposure
AR=[a/(a+b)]-[c/(c+d)]
Relative risk reduction
Proportion of risk reduction attributable to an intervention vs control
RRR=1-RR
Absolute risk reduction
Difference in risk (not proportion) attributable to intervention vs control
ARR = [c/(c+d)]-[a/(a+b)]
ABCD on table!
disease
+ -
risk factor + a b
- c d
NNT
Number needed to be treated for 1 pt to benefit (lower is better)
=1/ARR
NNH
Number needed to be exposed to risk factor for 1 patient to be harmed (higher number is better)
=1/AR
Precision
aka reliability Reproducibility – increased=lower SD, higher statistical power
Accuracy
aka validity Trueness of test measurements – absence of systematic error/bias in a test
Selection bias
Non random sampling or treatment allocation so that population in study is not representative (usually a sampling bias
Berkson bias
Study pop from hospital – less healthy than general pop
Healthy worker effect
Study populatio in healthier than general pop
Non-response bias
Participating subjects differ from those who do not respond
To reduce selection bias…
Randomization, ensure choice of right comparison/reference group
Recall bias
Awareness of disorder alters recall (esp in retrospective studies) – recall exposure upon hearing about similar cases
To reduce recall bias…
Less time from exposure to followup
Measurement bias
Information gathered in a distorted manner
Hawthorne effect
A measurement bias – participants change behavior in response to be observed
To reduce measurement bias…
Use objective, establish testing methods for data collection, utilize a placebo group
Procedure bias
Subjects in diff groups not treat the same
To reduce procedure bias
Use blinding and placebos
Observer-expectancy bias
Researchers belief in efficacy of a treatment changes it’s outcome (Pygmalion effect, self-fulfilling prophecy)
To reduce observer expectancy bias…
Blind and use placebos
Confounding bias
Factor is related to exposure and outcome but not causal – can distort/confuse effect of exposure on outcome
To reduce confounding bias…
Multiple/repeated studies, crossover studies (patients are their own control), matching (patients similar in both groups), restriction, randomisation
Lead-time bias
Early detection is not the same as longer survival
To reduce lead-time bias…
Measure “back end” survivial (adjust survival according to severity of disease at time of diagnosis)
Variance
=SD^2
Standard error
Estimate of how much variability exists in a theoretical set of sample means around the true population mean
=SD/[sqr of n]
Positive skew
Mean>med>mode (tail to right)
Negative skew
Mode>med>mean (tail to left)
Type I error (alpha)
Stating there is a difference when none exists (accusing an innocent man) – incorrectly reject Ho (false pos)
alpha – probability of making a type I error – p is judged against alpha level of significance
Type II error (beta)
Stating that there is not a difference when there is one (blindly let the guilty go), incorrectly accept Ho (false neg)
beta – probability of making a type II error – related to statistical power
Power
=1-beta Increased power (lower beta): -bigger sample -larger expected effect size - increased precision of measurment
Confidence interval
Range of values within which the true mean is expected to fall w/ a specified probability
For population = mean +Z(SE)
95%, Z=1.96
99% Z=2.58
If a CI includes 0 – dont reject Ho
If CI for 2 groups overlap, no significant diff
If they dont – significant dif
T test
Means of 2 groups
ANOVA
Means between 3+ groups
Chi square
Difference in 2+ percentages/proportions of categorical outcomes
Coefficient of determination
=r^2 – amount of variance in on variable that can be explained by variance in another variable
In informed consent
Disclosure, understanding, capacity, voluntariness
No parental conset needed for minors for
Sex (contraception, STIs, pregnancy)
Drugs (substance abuse)
Rock/roll (emergency/trauma)
Surrogate decision maker order
Spouse–>adult children–>parents–>siblings–>other relatives
Moro reflex disappears
3mo
Rooting reflex disappears
4mos
Palmar reflex disappears
6mos
Babinski reflex disappears
12mos
Lifts head up prone
1 mo
Rolls/sits
6 mos
Crawls
8mos
stands
10mos
Walks
12-18mos
Passes toys hand to hand
6 mos
Pincer grasp
10 mos
Points to objects
12 mos
Social smile
2 mos
Stranger anxiety
6mos
Separation anxiety
9 mos
Orients to voice
4mos
Orients to name/gestures
9mos
Object permanence
9mos
Mama/dada
10mos
Takes first steps
12 mos
Climbs stairs
18mos
Cubes stacked
age(yr)*3
Feeds self with fork/spoon
20mos
Kicks ball
24 mos
Parallel play
24-36 mos
Rapprochment (moves away from and returns to mother)
24mos
Core gender identity formed
36 mos
How many words by age 2?
200
How many words in a sentence at age 2?
2 words
Tricycle ride
3yr
Copies line/circle/stick figure
4yr
Hops on one foot
4yr
Uses buttons/zippers/grooming
5yr
Comfortably spends part of day away from mother
3yr
Cooperative play/imaginary friends
4yr
How many words by age 3?
1000 (3 zeros)
Uses complete sentences/prepositions
4yr
Can tell detailed story
4yr
Rear facing car seat until
2 yrs
Car seat in general until
4 yrs
Booster seat until
8yrs or proper fit of seat belt
Age when you can ride w/ front facing airbag
12 yrs
HMO
Only in network
Must get referral
PPO
Can go out of network
No need for referral
Point of service
Can go out of network
Must get referral
Exclusive provider org
Only in network
No need for referral
Primary prevention
Prevent before it happens
Secondary prevention
Screen and manage existing asymptomatic disease
Tertiary prevention
Reduce complications from a disease that is ongoing/has long term effects
Quaternary prevention
Identify patients at risk of unnecessary tx, protect from harm of new interventions
Capitation
Physicians receive a set amount per patient assigned to them per period of time, regardless of system usage
Discounted fee for servie
Patient pays for each individual service at predetermined/discounted rate
Global payment
Patient pays for all expenses re: a single incident of care w/ single payment
Medicare available to
Those over 65, less than that with some disabilities or ESRD
Medicare part A
Hospital insurance, home hospice
Medicare part B
Doctor’s fees, diagnostic tests, basic medical bills
Medicare part C
A+B from approved private companies
Medicare part D
prescription drugs
Most common causes of death less than a year
- congenital malform
- preterm birth
- maternal preg complication
Most common causes of death 1-14yr
- Unintentional injury
- Cancer
- Congenital malform
Most common causes of death 15-34yr
- Unintentional injury
- Suicide
- Homicide
Most common causes of death 35-44
- Unintentional injury
- Cancer
- Heart disease
Most common causes of death 45-64
- Cancer
- Heart disease
- Unintentional injury
Most common causes of death 65+
- Heart disease
- Cancer
- Chronic resp disease
Outcome measure
Impact on patients
Process measure
Performance of system as planned
Balancing measure
Impact on other systems/outcomes
