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FRM > Final Exam > Flashcards

Final Exam Flashcards

1
Q

Steps of evidence-based practice

A

Formulate question, search for evidence, critical appraisal, apply to patient, evaluate performance

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2
Q

where is research applied in the steps of evidence-based practice

A

critical appraisal, apply to patient

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3
Q

Simplified steps of evidence-based practice

A

Formulate, search, appraise, decide, reflect

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4
Q

In own words, definition of evidence-based practice

A

Appropriately integrating the best available evidence (obtained through systematic and thorough literature review), patient preference, and clinical expertise to make decisions about patient care.

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5
Q

the 5 A’s of evidence-based practice

A

Ask, acquire, appraise, apply, assess/adjust

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6
Q

what are the types of EBP questions?

A

Diagnosis, treatment, prognosis, epidemiology

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7
Q

MeSH stands for

A

medical subject headings

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8
Q

steps for case control study

A

Identify group with the disease (cases), identify healthy people who resemble the cases (controls), examine histories of cases and controls to identify possible causes, determine proportion of cases to controls who have the exposure

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9
Q

how many controls should there be per case in a case control study

A

1-4

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10
Q

what should be used to study a rare disease?

A

case control study

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11
Q

what size population do case control studies require

A

relatively small

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12
Q

what are case control studies best used for

A

identify possible causes of a rare disease

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13
Q

which study type uses odds ratio

A

case control study

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14
Q

what is the odds ratio

A

the likelihood that an effect will occur with an exposure over the likelihood that it will occur without an exposure

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15
Q

odds ratio >1 means

A

increased occurrence of an event (correlation)

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16
Q

odds ratio <1 means

A

decreased occurrence of an event (protective exposure)

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17
Q

what is a cause

A

A condition that precedes an event such that if the condition were different, the event would not have occurred

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18
Q

Bradford Hill’s elements of sufficient cause

A

Biological plausibility, temporal relationship, strength of association, experimental evidence, dose-response relationship, replication/consistency

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19
Q

types of cohort studies

A

retrospective, prospective

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20
Q

equipoise

A

the point at which a rational and informed person has no preference between two courses of action

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21
Q

first RCT

A

streptomycin for TB infection in UK 1949

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22
Q

types of data

A

nominal, ordinal, interval, ratio

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23
Q

nominal data

A

puts things into named categories without hierarchy

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24
Q

ordinal data

A

puts thing into named categories with hierarchy but no assumption of equal intervals

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25
Q

examples of nominal data

A

eye color, gender, marital status

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26
Q

examples of ordinal data

A

improved/same/worse

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27
Q

interval data

A

ordered but with the same distance between sets and an arbitrary zero

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28
Q

examples of interval data

A

Farenheit/Celsius, IQ

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29
Q

ratio data

A

ordered with same distance between sets and a meaningful zero

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30
Q

examples of ratio data

A

Kelvin, weight, height, length

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31
Q

Factors in evaluating health data

A

Timeliness of data, how representative is the data of the defined population, completeness of data, data collection issues, agenda of collecting organization, accessibility of data

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32
Q

Incidence and prevalence are measures of

A

disease frequency

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33
Q

Prevalence

A

amount of disease in a population at a given time

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34
Q

Prevalence is expressed in

A

percentage or proportion

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35
Q

point prevalence vs period prevalence

A

point prevalence is one point in time, period prevalence is over a defined amount of time

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36
Q

formula for prevalence

A

people with disease/people in population

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37
Q

Incidence

A

the rate of new disease development over a given period of time

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38
Q

what is implicit in most definitions of incidence

A

the population was initially free of disease

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39
Q

cumulative incidence aka

A

incidence proportion

40
Q

cumulate incidence formula

A

number of new diseases over time/population without disease at baseline X 100

41
Q

what is cumulative incidence used for

A

to monitor a specific population over time

42
Q

cumulative incidence is like (EMS)

A

continuous infusion

43
Q

formula for incidence rate

A

number of new diseases over time/person-time at risk X 100

44
Q

what is a problem with calculating incidence rate?

A

difficult to calculate person-time at risk for a large population…they use census data and report in cases/100,000, but it’s not exact

45
Q

what is the only formula with time in the denominator

A

incidence rate

46
Q

incidence rate is like (EMS)

A

drip rate for bolus

47
Q

what types of studies determine prevalence

A

cross-sectional survey, descriptive

48
Q

what types of studies determine incidence?

A

cohort, RCTs

49
Q

another way to think of prevalence

A

incidence times duration

50
Q

when should a highly sensitive test be used?

A

A case where a false negative would be really bad: Infectious disease, serious can’t miss diagnoses…also at the beginning of a diagnosis process to narrow the possibilities

51
Q

when should a highly specific test be used?

A

to confirm or rule in a suspected diagnosis, or when a false positive could harm the patient

52
Q

predictive value of test aka

A

post-test probability

53
Q

goal in ordering diagnostic tests re: post-test probability

A

to make the post-test probability significantly higher or lower than the pre-test probability

54
Q

predictive values are influenced by

A

prevalence

55
Q

positive predictive value formula

A

(true positives)/(total tested positive) x 100

56
Q

negative predictive value formula

A

(true negatives)/(total tested negative) x 100

57
Q

sensitivity formula

A

true positives/total with disease x 100

58
Q

specificity formula

A

true negatives/total without disease x 100

59
Q

what is positive predictive value

A

the probability that a person with a positive test result has the disease

60
Q

what is negative predictive value

A

the probability that a person with a negative result does not have the disease

61
Q

what affect on positive predictive value does a low prevalence have

A

it makes the ppv low and specificity has a higher impact on PPV

62
Q

what affect on npv does prevalence have

A

not very much

63
Q

PPV is highest for ___ diseases

A

common

64
Q

ways to measure post-test probability

A

predictive values, likelihood ratios, diagnostic criteria

65
Q

what is a likelihood ratio

A

the likelihood of a given test result in a person with the disease compared with the likelihood of the same result in a person without the disease

66
Q

likelihood ratio formula

A

sick people with given test result/well people with given test result

67
Q

how to calculate positive likelihood ratio

A

sick people who tested positive/well people who tested positive

68
Q

how to calculate negative likelihood ratio

A

sick people who tested negative/well people who tested negative

69
Q

how to calculate positive likelihood ratio in sensitivity

A

sensitivity/(1-specificity)

70
Q

how to calculate negative likelihood ratio in specificity

A

(1-sensitivity)/specificity

71
Q

what likelihood ratio value is helpful in ruling in a disease because it largely increases post-test probability

A

> 10

72
Q

what likelihood ratio value is helpful in ruling out a disease because it largely decreases post-test probability

A

<0.1

73
Q

benefits of using likelihood ratio

A

not dependent on prevalence, can be used for non-dichotomous tests, less exaggeration of benefits of test compared with sensitivity and specificity

74
Q

what is key to establishing pre-test probability

A

good history and physical

75
Q

at what pre-test probability are tests most useful

A

around 50%

76
Q

in sequential testing, the post test probability becomes

A

the pretest probaility of the next test

77
Q

what is the null hypothesis

A

the initial assumption that the results in the study are no different than the results that would have occurred by chance alone

78
Q

what does it mean when the null hypothesis is rejected

A

the observed differences between the groups are not due to chance

79
Q

what does it mean when the null hypothesis is not rejected

A

there is no way to tell whether the differences are from chance or not

80
Q

what does the p value measure

A

the likelihood that the result is due to chance alone (the probability that the null hypothesis is true)

81
Q

what is the range for p values

A

0-1

82
Q

the smaller the p value

A

the less likely the result was due to chance

83
Q

if p value is <0.05

A

the results are statistically significant, the null hypothesis is rejected, and the results are likely not due to chance

84
Q

if p value is >0.05

A

the results are statistically significant, the null hypothesis is not rejected, and it is unknown whether the results are due to chance

85
Q

what do confidence intervals measure

A

precision

86
Q

what do overlapping confidence intervals mean

A

that no likely difference would occur when treatments are administered to larger population

87
Q

what does it mean if CI crosses 0

A

no statistically significant difference between groups being compared

88
Q

what does a wide CI mean

A

results were imprecise, uncertain quality of data

89
Q

what does it mean if CI does not cross 0

A

statistically significant difference between groups being compared

90
Q

what is number needed to treat

A

measurement of the impact of a therapy

91
Q

what is the ideal number needed to treat

A

1

92
Q

what causes nnt to become larger

A

cointerventions that alter outcome

93
Q

what nnt is considered acceptable for a symptomatic condition

A

usually 5 or under

94
Q

what is number needed to harm

A

measure of harm caused by intervention when compared to control group

95
Q

the larger the number needed to harm

A

the lower the likelihood of adverse effects

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