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Ash's Certification Study > CIC to review: Stats and Epi > Flashcards

CIC to review: Stats and Epi Flashcards

1
Q

Chart used to compare values across multiple groups

A

Bar

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2
Q

Types of data used for bar graph

A

1 Q
1 C

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3
Q

Chart used to examine distribution of quantitative variable by splitting it into multiple groups

A

Histogram

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4
Q

Data types for histogram

A

2Q (one displayed as groups)

Bars represent mutually exclusive groups

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5
Q

Chart used to show changes over time

A

Line chart

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6
Q

Types of data for line chart

A

1Q, 1C

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7
Q

Charts used to show how each category contributes to the whole

A

Pareto
Pie

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8
Q

Types of data for pareto chart

A

1 Q, 1 C

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9
Q

Types of data for a pie chart

A

1Q, q C

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10
Q

Chart used to look for correlation between variables

A

Scatterplot

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11
Q

Data types of scatterplot

A

2Q

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12
Q

Attributable proportion

A

RR-1 / RR

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13
Q

Measure of extent to which the distributions of possible results under the research hypothesis and null hypothesis do not overlap

A

Effect size

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14
Q

subset of sample statistics used to estimate a point characteristic of the population (eg it’s central tendency) rather than it’s dispersion (range, variance, etc)

A

Point estimate

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15
Q

way of assessing how much independent information is available from you data to estimate the parameter or determine the shape of the distribution

A

degrees of freedom

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16
Q

Using false positive- what happens if p <= alpha?

A

the risk of a false positive is acceptable, we reject the null hypothesis and conclude a statistically significant difference exists

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17
Q

Type 1 error

A

alpha- false positive

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18
Q

Type 2 error

A

beta- false negative

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19
Q

parametric tests used to determine whether two or more groups differ from each other based on the variability of values within each group versus the variability of values bewtween the groups

A

ANOVA

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20
Q

A nonparametric test used to evaluate how close the observed counts are for a single variable to those expected if the data fit a specific distribution

A

Chi square goodness of fit test

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21
Q

A nonparametric test used to determine how different the observed counts are from those expected if there is now association between the tested variables

A

Chi square test of association (AKA pearson’s chi square or chi-square test for independence)

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22
Q

Tests measuring the strength and direction of the relationship between two quantitative variables

A

Correlation

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23
Q

Parametric correlation

A

Pearson’s correlation

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24
Q

Nonparametric correlation

A

Spearmans

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25
Q

Models used to determine whether the linear relationship between 2+ variables is statistically signficiant, to assess the strength and direction of that relationship, and to predict values of the dependent variable for given values of the independent variables

A

Linear regression

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26
Q

Models used to predict probability of a particular outcome based on the values of one or more independent variables. The outcome possibilities must be dichotomous (ie survived/ died; infection/ no infection)

A

Logistic regression

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27
Q

nonparametric alternative to independent samples t-test, used to determine whether two groups differ based on ordinal ranks

A

Mann-Whitney U-Test AKA Mann-whitney wilcoxin test

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28
Q

Nonparametric test used to determine whether two related groups differ based on responses to a dichotomous variable. It is often applicable to pretest/ posttest studies with matched pairs

A

McNemar test

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29
Q

Parametric test used to determine whether the average values of two groups (or one group and a test value) are different. Versions of the test differ depending on how many groups are being examined and whether or not they are independent of each other

A

t-test

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30
Q

non-parametric alternative to the paired-samples t-test, used to compare the median value of a group to that of another group

A

Wilcoxon signed-rank test

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31
Q

What report shows facilities with need for improvement?

A

TAP- targeted assessment prevention

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32
Q

What is the CAD?

A

Cumulative attributable difference- # of infections to prevent to meet goals

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33
Q

Elements of effective surveillance program

A
  • Select methodology
  • assess and define pops to be studied
  • choose events to monitor
  • Determine time pd for observation
  • ID surveillance criteria (case definitions)
  • ID elements to be collected
  • Determine methods for data collection and mangement
  • Design interpretive surveillance report
  • ID recipients of surveillance report
  • Develop written surveillance plan
  • surveillance program evalulation
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34
Q

What should be considered when selecting an event for surveillance?

A
  • type of hc setting
  • pop being studied
  • Procedures performed/ services provided
  • acuity of care
  • risk assessment
  • regulatory requirements
  • Available resources
  • PH needs
  • performance improvement initiatives
  • organization objectives

Note- usually high risk/ high volume events

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35
Q

Considerations when writing surveillance report

A
  • Define event, population, setting, time period
  • case definition criteria
  • numbers
  • methods
  • purpose
  • interpretation
  • action/ recommendations
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36
Q

Examples of process events

A

Compliance with IP protocols
- Isolation
- Safe injection
- HH
- env cleaning

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37
Q

Methods to compare surveillance rates

A

z-test
SIR

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38
Q

Surveillance summary measure used to track performance across groups over time

A

Standardized infection ratio

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39
Q

Measure used to target prevention by identifying which locations have highest burden of excess infections

A

CAD- cumulative attributable difference

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40
Q

Risk adjusted measure used to track device utiliztation

A

SUR- standardized utilization ratio

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41
Q

Summary measure comparing antimicrobial use within and across facilities to guide stewardship effforts

A

SAAR- standardized antimicrobial administration ratio

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42
Q

Surveillance that uses real time data for early response

A

Syndromic surveillance

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43
Q

Surveillance that collects data from sample reporting sites

A

Sentinel surveillance

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44
Q

Ability to detect specified difference?

A

Power

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45
Q

What impacts the power in a statistical study?

A
  • sample size
  • Significance level (alpha)
  • true value of parameter being tested (higher effect size, higher power)
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46
Q

Hill’s criteria

A

Strength of association
Specificity
Temporality
Biological gradient
plausibility
coherence
experiment
analogy

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47
Q

Incidence of disease is higher in those exposed (example lung cancer common in smokers)

A

Strength of association

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48
Q

Association observed in numerous studies

A

Consistency

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49
Q

1 factor, 1 disease

A

Specificity

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50
Q

Exposure to hypothesized causal factor precedes disease onset

A

Temporality

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51
Q

Dos/ response relationship (longer 1 smokes, more likely to develop lung cancer)

A

Biological gradient

52
Q

Association should be in accordance with other facts known about the natural history of the disease

A

Coherence

53
Q

Association in question biologically plausible in light of current knowledge

A

Plausability

54
Q

Analogous studies available, experiments completed that show association

A

Experiement

55
Q

Similar association shown to be causal

A

Analogy

56
Q

Frequency polygpn

A

X axis- values of the variable (ie age of residents at a nursing home)
y-axis- # of observations connected with straight lines

57
Q

What test is used if chi square would be used but at least 1 cell <5 or sample size <20

A

Fisher exact test

58
Q

Artificial/ Spurious association

A

May be caused by
- errors in study design
- bias
- errors in analysis
- failure to control for confounding factors

59
Q

Indirect/ noncausal association

A

Confounding variable

60
Q

Causal association

A

1 factor raises the probability of disease

61
Q

Examples of primary prevention

A

Wellness and prevention programs
Immunizations

62
Q

Example secondary prevention

A

Early dx

63
Q

Tertiary prevention

A

Improve quality of life

64
Q

Recovered, but still carry the organism

A

Convalescent carriers

65
Q

What type of graph is an epi curve and example of?

A

Histogram

66
Q

3 D’s of epidemiology

A

Distribution
Determinants
Deterrents

67
Q

At what point in disease do primary, secondary, and tertiary prevention happen?

A
  1. primary- before disease
  2. Secondary- pre-clinical, asymptomatic disease
  3. Tertiary- clinical disease
68
Q

Who should receive communications about outbreaks

A
  • clinicians working in affected area, get input from them regularly
  • patients (consult with admin, ethics, and risk management)
  • Update admin, risk management, pt safety, and PR regularly
  • findings- broader scientific community
69
Q

What does an epi-curve answer

A

Source of infection?
Length of incubation
Case #s increasing/ decreasing

70
Q

Epi-curve where all cases have the same origin

A

common source

71
Q

Epi-curve for person to person spread

A

Propogated

72
Q

What is the importance of surveillance in outbreaks?

A

Early ID
effective control
prevention of secondary cases
resource allocation

73
Q

Resistance mechanisms never or very rarely ID’d in U.S., pan-resistant organisms with the potential for wide spread in a region

A

Tier 1

74
Q

Mechanisms and organisms not regularly found in regiond

A

Tier 2

75
Q

Mechanisms and organisms regularly found in a region, but not endemic

A

Tier 3

76
Q

what are measure that should always be taken for Tier 1 and 2 organisms

A
  • review patient’s hc exposures prior to and after the positive culture
  • Screening hc roommates
  • Prospective lab surveillance
  • Retrospectice lab surveillance
  • prompt notification of hcp and patient and implementation of appropriate TBP
  • Clear communication of patient status with transferring facilities
  • ICAR
77
Q

Steps to OB investigation

A
  1. confirm presence of OB
  2. ID inv team
  3. Verify dx
  4. Establish preliminary case def
  5. alert admin and stakeholders
  6. Detailed lit review
  7. Method- case finding
  8. line list and epi curve
  9. observe/ review pt care activities
    10.. environmental sampling? (driven by line list)
  10. implement controls
78
Q

Follow up steps to an outbreak investigation

A
  • refine the case definition
  • case finding and surveillance
  • review regulatory controls
  • maintain surveillance
  • analytical study?
79
Q

Describe the different types of data

A
  1. Categorical
    - Nominal
    - ordinal
  2. Quantitative
    - discrete
    - continuous
80
Q

Proportion

A

Numerator is a subset of the denominator

81
Q

What can rates be used for?

A

-Track trends over time
- assess impact of interventions
- ID emerging patterns
- make strategy adjustments

82
Q

Relative risk

A

incidence of outcome in exposed group/ incidence of outcome in unexposed group

83
Q

Type of studies that you can use relative risk for

A

Cohort

84
Q

Attributable proportion

A

RR-1/RR

85
Q

Odds ratio

A

Odds of exposure in group with outcome/ odds of exposure in group without the outcome

86
Q

Range of values where the population parameter is likely to be

A

Confidence interval

87
Q

What test must be used for discrete/ categorical data?

A

Chi square test

88
Q

Comparing means in 3+ groups

A

ANOVA

89
Q

Comparing means between 2 groups

A

t-tests

90
Q

Reasons a hospital may not be able to use SIR

A

procedure uncommon or hospital small

91
Q

Method of inquiry that seeks to develop a new theory from group up based on findings

A

Inductive approach

92
Q

Testing existing theory from top down

A

Deductive approach

93
Q

Qualitative methods that includes complex account of an individual’s experience in context of their social or cultural env

A

Narrative

94
Q

Qualitative method that strives to remove individuality and discover essence of phenomenon

A

Phenomenology

95
Q

Qualitative method used to generate new theories, explanations, or concepts about a process or series of actions

A

Grounded theory

96
Q

Qualitative method in which the goal is to understand lives of individuals meaning of human behavior, linked to culture experiences

A

Ehtnography

97
Q

Goal of qualitative studies

A
  • lead to generation of hypotheses
98
Q

Ability of another researcher to follow decision trail of investigator (documentation of methods, interview script, etc)

A

Reliability

99
Q

Using multiple sources to answer the same question

A

Triangulation

100
Q

Making investigation conclusions useful to others

A

Transferability

101
Q

Sampling methods that selects the most relevant individual for the questions based on the study aim

A

Purposive sampling

102
Q

How long do you continue qualitative study?

A

Sample until questions answered/ no new information gained

103
Q

What are resources required for qualitative studies?

A
  • time
  • connection to the right people
  • transcription service, audio/ video recorder/ ect.
104
Q

Who determines what information can be shared with participants about the qualitative study?

A

IRB

105
Q

How to analyze qualitative data

A

1) manage and organize data
2) familiarize yourself with data
3) Interpret key themes in context of the question
4) develop manuscript or diagram/ matrix

106
Q

Strengths of qualitative studies

A
  • participants view represented
  • development of theory or hypothesis
  • discover new insights/ phenomena
107
Q

Limitations of qualitative studies

A
  • limited generalizability
  • time consuming
  • investigator bias
  • unlikely to be published
108
Q

Type of study: description of SSI among among patients, accentuating the fear, frustration, and insecurity of patients with this experience

A

Phenomenology

109
Q

Type of study: exploration of the process of patient prep for colon surgery to enhance the effectiveness of preoperative prevention practices

A

Grounded theory

110
Q

Type of study: study of hospital specific cultural influences on hand hygiene and PPE use

A

Ethnography

111
Q

Example of descriptive studies

A

Case report/ case series

112
Q

Questions that are answered in meta-analysis

A

What is known?
What still needs to be addressed?

113
Q

Ability of a test to detect a specified difference (or the probability of rejecting the null hypothesis when it’s false)

A

Power

114
Q

What impacts power?

A
  • sample size
  • significance level
  • the true value of the parameter being tested
115
Q

The greater the difference between the true value of a parameter and the value specified in the null hypothesis the _______ the power of the test

A

Greater

116
Q

Core elements of asp

A

Leadership
Commitment
Accountability
Drug expertise
Action
Tracking
Reporting
Education

117
Q

Core component of antibiotic stewardship program that involves dedicating necessary human, financial and information technology resources

A

Leadership commitment

118
Q

Core elements of asp that involves appointing a single leader responsible for program outcomes. Experience with successful programs show that a physician leader is effective

A

Accountability

119
Q

Core element of ASP that involves appointing a single pharmacist leader responsible for working to improve antibiotic use

A

Drug expertise

120
Q

Core elements of ASP that involves implementing at least one recommended action such as systematic evaluation of ongoing treatment need after a set period of initial treatment ( antibiotic time out after 48 hours)

A

Action

121
Q

ASP core element that involves monitoring antibiotic prescribing and resistance patterns

A

Tracking

122
Q

ASP core element that involves regular reporting information on antibiotic use and resistance to doctors, nurses and relevant staff

A

Reporting

123
Q

ASP Court element that involves educating clinicians about resistance and optimal prescribing

A

Education

124
Q

How long does UV radiation take to clean a room?

A

15 to 20 minutes

125
Q

Precautions for adenovirus

A

Contact and standard

126
Q

Precautions or para influenza

A

Contact and standard

127
Q

Precautions for enterovirus

A

Contact for diapered and incontinent and standard

Ash's Certification Study (22 decks)

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