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Public Health Flashcards

1
Q

Study design where the frequency of disease and frequency of risk related factors are assessed in the present.

A

Cross sectional study - “What is happening”

Disease prevalence but does not assess causality

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2
Q

Study design that compares a group of people with disease to a group of people without disease. Looks to see if odds of prior exposure or risk factor differs by disease state

A

Case-control study - “what happened”

ODDs ratio

ex) people with COPD had higher odds of a smoking history than those without COPD

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3
Q

Study design that compares a group with a given exposure or risk factor to a group without such exposure. Looks to see if exposure or risk factor is associated with later development of disease.

A

Cohort study - “Who will develop the disease” or “who developed the disease”

Can be prospective or retrospective

Relative risk

ex) smokers have a higher risk of developing COPD than nonsmokers

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4
Q

Clinical trial phases: phase I

A

think “SWIM”

Phase I -“is it SAFE”. Small number of healthy volunteers or pt with dz of interest. Assess safety,toxicity, pharmkinetics, pharmdynamics

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5
Q

clinical trial : phase II

A

think “SWIM”

Phase II- “Does it WORK”. Moderate numbers of patients with disease of interest. Assess treatment efficacy, optimal dosing, and adverse effects

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6
Q

Clinical trial: phase III

A

think “SWIM”

Phase III- “IMPROVEMENT?” . Large number of pt with placebo and then with treatment. Compares new treatment to current standard of care

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7
Q

Clinical trial: Phase IV

A

think “SWIM”

Phase IV: “Can it stay in MARKET”. This is after being approved. Detects rare or long term effects

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8
Q

Sensitivity

A

True positive rate. Probability that when a dz is present then the rest is positive. SCREENING test

If negative then rules OUT a disease. Higher sensitivity has a lower false negative rate.

TP/(TP + FN) = 1- FN rate

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9
Q

Specificity

A

True negative rate. Probability that when the disease is absent the test is negative. CONFIRMATION test

When positive it rules IN a disease. Higher specificity means lower false positive rate

=TN/(TN+FP) = 1-FP rate

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10
Q

positive predictive value

A

probability that a person who has a positive test result actually has the disease

PPV= TP/(TP + FP)

varies directly with pretest probability. High pretest probability results in a high PPV

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11
Q

negative predictive value

A

probability that a negative rest actually does not have the disease

NPV=TN/(TN+FN)

varies indirectly with pretest probability. high pretest probability results in low NPV

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12
Q

Likelihood ratio

A

Likelihood that a given result would be expected in a patient with the target disorder compared to the likelihood that the same result would be expected in a patient without the target disorder

LR+ >10 and or LR- 0.1 indicates a useful diagnostic test

LR+=sensitivity/(1-specificity)=TP rate/FP rate
LR-=1-sensitivity/specificity= FN rate/TN rate

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13
Q

Odds ratio

A

Odds of a certain exposure given an event vs the odds of exposure in the absence of that event. Used in case control studies

OR=ad/bc

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14
Q

Relative risk (RR)

A

the # times risk of cancer in the exposed vs the unexposed. Used in cohort studies

RR=risk in exposure/risk in unexposed
RR=((a/a+b)/(c/c+d))

RR=1 there is not association between exposure and disease
RR>1 there is an association that causes increase in dz
RR<1 there is an association that causes decrease in dz

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15
Q

Attributable risk (AR)

A

The difference in risk between exposed and unexposed groups

Risk in exposed - risk in unexposed

AR=(a/a+b)-(c/c+d)

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16
Q

Relative risk reduction (RRR)

A

The proportion in risk reduction attributed to the intervention as compared to a control

RRR=1-RR

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17
Q

Absolute risk reduction (ARR)

A

The difference in risk (not the proportion) attributable to the intervention as compared to a control

ARR=((c/c+d) - (a/a+b))

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18
Q

Number needed to treat (NNT)

A

Number needed to treat for 1 patient to benefit

low number is better

NNT=1/ARR

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19
Q

Number needed to harm (NNH)

A

number needed to be exposed for 1 patient to be harmed

high number is better

NNH=1/AR

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20
Q

Incidence

A

new cases/#at risk

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21
Q

prevelaence

A

existing cases/total#of people in a population

increase prevalence causes increase in PPV and decreases in NPV

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22
Q

Precision

A

reliability

The consistency and reproduciblity of a test. The absence of random variation in a test

Increase precision causes decrease in standard deviation

increase in precision causes increase in statistical power

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23
Q

Accuracy

A

validity

systemic error decreased accuracy in a test

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24
Q

Berkson bias

A

study population selected from hospital is less healthy than general population

type of selection bias

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25
Non response bias
participating subjects differ from non respondents in meaningful ways type of selection bias
26
Hawthorne effect
participants change behavior upon awareness of being observed measurement bias use placebo group to avoid
27
Procedure bias
avoid with blinding and use of placebo
28
Observer expectancy bias
avoid with blinding and use of placebo
29
Lead time bias
early detection is confused with increased survival avoid by measuring back end survival (Adjust survival according to the severity of disease at the time of diagnosis)
30
Length time bias
Screening test detects diseases with long latency period while those with shorter latency period become symptomatic earlier i.e. a slowly progressive cancer is more likely detected by a screening test than a rapidly progressive cancer prevent via a randomized controlled trial
31
Standard error
an estimate of how much variability exists in a theoretical set of sample means around the true population mean SD/sq root(sample size)
32
variance formula
SD^2
33
Bimodal distribution
suggests two different populations
34
Positive skew
mean>median>mode long tail on right
35
Negative skew
mean
36
Normal distribution
mean=median=mode
37
Null hypothesis (H0)
Hypothesis of no difference or relationship
38
Alternative (H1)
Hypothesis of some difference or relationship
39
null hypothesis rejected in favor or alt hypothesis means
there is an effect or difference when one exists
40
Type 1 error
false positive arror stating that there is an effect when there isnt α is the probability of making a type I error Alpha=An innocent man
41
Type II error
False negative error stating there isnt an effect when there is β is the probability of making a type II error and is related to statistical power (1- β) Beta=blindy let the guilty go
42
Confidence interval
range of values within which the true mean of the population is expected to fall, with a specified probability CI for sample mean = mean +/- Z(SE) 95% CI , α=.05, Z=1.96 if CI for a mean difference bteween 2 variables includes 0=null not rejected if CI for odds ratio or relative risk includes 1 then null not rejected if the CI between 2 groups do not overlap then there is a statistically significant difference if the CI between 2 groups overlap then there is no significant difference
43
t test
checks difference between means of 2 groups ex) mean bp between men and women
44
ANOVA
checks difference between means of 3 or more gorups comparing the mean bp between 3 different ethnic groups
45
Chi sq
checks the difference between 2 or more percentages or proportions of categorical outcomes (not mean values) ex) comparing the percentage of members of 3 different ethnic groups who have essential hypertension
46
Pearson correlation coefficient
r is between -1 and +1. the closer the absolute value of r is to 1 the stronger the linear correlation between the 2 variables r^2=coefficient of determination. This is the amount of variance in one variable that can be explained by variance in another variable
47
core principle of ethics : justice
treat persons fairly and quitably all principles are autonomy, beneficence, non maleficence, justice
48
car seats
2 yrs old for rear facing 4 yrs old for with harness booster seat till 8 children <12 should not ride in front
49
primary dz prevention
prevent dz before it occurs hpv vaccine
50
secondary dx prevention
screen early for and manage existing but asymptomatic dz pap smear
51
tertiary dz prevention
treatment to reduce complications from dz that is ongoing or has long term effects
52
quaternary dz prevention
identifying patients at risk of unnecessary treatment, preventing from the harm of new interventions
53
Exclusive Provider Organization
restricted to limited panel except in emergences no referrel needed for specialist
54
Health maintenance organization (HMO)
restricted to limited panel except in emergencies, denies for any service that does not meet establish evidence based quidelines, requires referel from primary care provider
55
Point of service
Patient can see providers outside the network, higher copays and deductibles for out of network services, requires referral form primary care provider
56
Preferred provider organization
patient can see providers outside network, higher copays and deductibles for all services, no referral required
57
bundled payment
healthcare org receives a set amount per service regardless of how much the patient uses the healthcare system
58
capitation
physician received a set amount per patient assigned to them per period of time, regardless of how much he patient uses the healthcare system used by some hmo
59
discounted fee for service
patient pays for each individual service at a discounted rate predetermined by providers and payers
60
fee for service
patient pays for each individual service
61
global payment
patient pays for all expenses associated with a single incident of care with single payment elective surgeries
62
Medicare
elderly
63
medical
destitute and poor A-hospital B-outpatient C-Both D-drugs
64
hospice care
medicare, medical, and most private insurance companies pay for hospice care if <6months to live principle of double effect- prioritize positive effects over negative effects of drugs
65
readmission
considered when <30 days from discharge
66
Human factors design
forcing functions (those that prevent undesirable actions) are the most effective standardization and simplification are beneficial deficient designs hinder workflow and lead to staff workarounds that bypass safety features
67
PDSA cycle
P-Plan, define problem and situation D-Do, test new process S-study, measure and analyze data A- Act, integrate new process into regular workflow
68
Quality measures
Structural - physical equipment, resources, facilities (number of diabetes educators) Process- performance of system as planned (percentage of diabetic patients whose HbA1c was measures int he past 6 months) Outcome- Impact on patients (average HbA1C of patients with diabetes) Balancing-impact of other systems/outcomes (incidence of hypoglycemia among patients who tried an intervention to lower HbA1C)
69
Swiss cheese model
focuses on systems and conditions rather than an individuals error patient harm can occur despite multiple safeguards when "the holes int he cheese line up" potential failures in defense strategies
70
Active error
occurs at level of frontline operator immediate impact
71
Latent error
occurs in processes indirect from operator but impacts patient care (different types of IV pumps used within the same hospital)
72
Root cause analysis
retrospective approach. applied after failure event to prevent recurrence
73
Failure mode and effects analysis
forward looking approach. Applied before process implementation to prevent failure occurrences uses inductive reasoning to identify all the ways a process might fail and prioritizes them by their probability of occurrence and impact on

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