Public Health Formulas Flashcards

1
Q

Sensitivity

A

1 - FN rate

Ruling out disease (screening)

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2
Q

False Negative Rate

A

FN / FN + TP

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3
Q

Specificity

A

1 - FP rate

Ruling in disease

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4
Q

Incidence

A
# new cases / # of people at risk         
(per unit of time)   

EXCLUDE PATIENTS THAT ARE ALREADY DIAGNOSED

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5
Q

Negative likelihood ratio

A

(1 - sensitivity) / specificity

(FNrate) / (TNrate)

probability of negative result in patient with disorder / probability of negative result in patient without disorder

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6
Q

Positive likelihood ratio

A

Sensitivity / (1 - specificity)

(TP rate) / (FP rate)

probability of positive result in patient with disorder / probability of positive result in patient without disorder

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7
Q

Prevalence

A

of existing cases / total # of people in a population

(at a point in time)

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8
Q

Prevalence / 1 - prevalence

steady state population

A

incidence rate X average duration of disease

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9
Q

Relative Risk

A

[a/(a+b)] / [c/c+d)]

incidenceof disease in exposed group / incidenceof disease in unexposedgroup)

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10
Q

Relative Risk Reduction

A

1 - RR

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11
Q

Odds Ratio

A

(a/c) / (b/d)

a x d) / (b x c

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12
Q

Exposure Attributable Risk

A

(incidence ratein exposedgroup) -(incidence ratein unexposedgroup)

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

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13
Q

Population Attributable Risk

A

(incidence ratein the entire studypopulation) -(incidence ratein the unexposedgroup)

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

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14
Q

Attributable Risk %

A

[(RR-1) / RR] X 100

(Attributable Risk / Incidence of disease in the exposed group) X 100

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15
Q

Attributable Risk Reduction (ARR)

A

(absoluteriskin the unexposedgroup) -(absolute riskin the exposedgroup)

c/(c + d) – a/(a + b)

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16
Q

Number Needed to Treat (NNT)

A

1 / ARR

17
Q

Number Needed to Screen (NNS)

A

1 / ARR

18
Q

Number Needed to Harm (NNH)

A

1 / AR

19
Q

Hazard Ratio

A

Incidenceof outcome in exposed group / incidenceof outcome in unexposedgroup

[a / (a + b)] / [c / (c + d)]

20
Q

Absolute Risk Reduction is also known as _______.

A

Risk difference

21
Q

Case fatality rate is also known as _______.

A

Lethality

22
Q

Case Fatality Rate

A

(# deaths from a specific condition / # cases with the same specific condition) X 100

23
Q

Attack rate is also known as _______.

A

Cumulative incidence

24
Q

Attack Rate

A

People who become ill / Total people exposed

DO NOT SUBTRACT DEATHS FROM DENOMINATOR

25
Q

Mortality rate is also known as _______.

A

Crude death rate

26
Q

Mortality Rate (crude death rate)

A

of deaths / total population size

27
Q

Cause Specific Mortality Rate

A

of deaths of particular disease / total population size

28
Q

Standardized Mortality Ratio

A

Observed # of deaths / Expected # of deaths

29
Q

Maternal Mortality Rate

A

(# of maternal deaths / # of live births) X 100,000

30
Q

Perinatal Mortality Rate

A

[(# of stillbirths + # of infant deaths during first week after birth) / total number of births] X 1,000

31
Q

Crude Birth Rate

A

of live births / total population size

32
Q

Fetal Mortality Rate

A

[(# of infant deaths during the first 24hours after birth) / (total number of live births)] X 1,000

33
Q

Reliability Coefficient

A

Variance of the true value (population variance) / Variance of the measured value (sample variance)

Reliability coefficient =1 →thevarianceof the samplemeanis equal to thevarianceof the truemeasure →the study/test is highly reliable

34
Q

Standard Deviation (σ)

A

√variance

35
Q

Variance

A

SDˆ2

36
Q

Standard Error of the Mean

A

Standard deviation / √(sample size)

37
Q

Standard normal value(Z-score,Z-value, standard normalized score)

A

(value -populationmean) / standard deviation

Z-scorefor a 90%confidence interval= 1.64
Z-scorefor a 95%confidence interval= 1.96
Z-scorefor a 97.5%confidence interval= 2.24
Z-scorefor a 99%confidence interval= 2.58

38
Q

Confidence Interval for Sample Mean

A

Mean +/- Z(standard error of the mean)

Mean+/- Z (standard deviation / √samplesize)

Confidence interval (CI) = 1 – α.

39
Q

Coefficient of Determination

A

rˆ2

Amount of variance in one variable that can be explained by variance in another variable