Use of stats for IP Flashcards

1
Q

Rate formula

A

X/Y *K

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2
Q

Measure of the frequency of death in a defined population during a specified time (usually a year)

A

Mortality rate

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3
Q

Measures the proportion of the population dying each year from all causes

A

crude mortality rate

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4
Q

Measures mortality from a specified cause for a population

A

cause-specific mortality rate

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5
Q

crude rate k

A

1000

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6
Q

cause specific rate k

A

100,000

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7
Q

Summary measure that compares HAI rates over time among one or more groups of patients to that of a standard population

A

Standardized Infection Ration (SIR)

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8
Q

Who calculates SIR?

A

NHSN

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9
Q

True or false: each SIR is procedure specific and based on specific patient risk factors

A

True

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10
Q

What does the standardized infection ration (SIR) measure?

A

How a single hc facility’s infection rates differ from a national standard

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11
Q

calculation for SIR

A

Observed # of infections/ expected # of infections

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12
Q

how to interpret an SIR

A

SIR =1: the facility’s rates are the same as expected by the NHSN benchmark

SIR >1: Facility’s rates are higher than the NHSN benchmark

SIR <1: Facility’s rates are better than the NHSN benchmark

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13
Q

Measure of the strength of association used in prospective and experimental studies

A

relative risk

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14
Q

equation for relative risk

A

Probability of developing disease if the risk factor is present / probability of developing disease if risk factor is not present

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15
Q

what does relative risk estimate?

A

how much more likely disease is to occur in exposed groups compared to unexposed ones

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16
Q

what studies are relative risk (risk ratio) used for?

17
Q

What question does relative risk answer?

A

what is the risk of developing disease if exposed to the risk factor?

18
Q

Interpreting the risk ratio

A

RR=1: there is no significant association
RR>1: there is a positive association
RR<1: there is a negative association (protective)

19
Q

Measure of association- the probability of having a particular risk factor if a condition or disease if condition is present

A

Odds Ratio

20
Q

Calculation for odds ratio

A

Probability of having risk factor if disease present/ probability of having risk factor if disease is not present

21
Q

Types of studies for odds ratios

A

Case control
cross-sectional studies

22
Q

Is OR appropriate for chronic diseases?

A

No, because it looks at prevalence not incidence

23
Q

What question does the odds ratio ask?

A

If the disease is present, what is the likelihood of having been exposed to the risk factor?

24
Q

Used to calculate the direction and magnitude of a relationship between two variables

A

Correlation

25
What is the value calculated for correlation?
r
26
range for correlation
-1 to 1
27
positive correlation
as one variable increases, so does the other
28
Negative correlation
as one variable increases, the other decreases
29
Strength of association- r=1 or r=-1
strong association
30
Strength of association: r=0
Weak or no correlation
31
Can a normal distribution be assumed for day to day surveillance and data collection?
No because sample sizes usually small
32
This type of testing estimates the likelihood that a result did not occur by chance
Hypothesis testing
33
Rejecting the Ho when it is true
Type 1 error
34
what is the probability of a type 1 error?
p-value
35
Null hypothesis is false and you accept it
Type II error
36
The probability of getting unusual results
P-value
37
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