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Flashcards in The Use of Data Deck (97)
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1
Q

Why is data gathered?

A

So that we can communicate risk to patients

2
Q

What does data about illness allow us to determine?

A

Treatment plans

3
Q

What are guidelines such as SIGN based on?

A

Data, known as the “hierarchy of evidence”

4
Q

What does general practice act as?

A

The interface between the public and secondary care (hospital)

5
Q

What percentage of general practice consultations are referred onto hospital investigation or care?

A

3%

6
Q

Most illnesses are unreported, what is this known as?

A

Iceberg of illness

7
Q

What is a disease?

A

Disorder of structure or function

8
Q

What is an illness?

A

Disease or period of sickness affecting the body or mind

9
Q

What are some factors affecting the uptake of care?

A
  • Concept of lay referral
    • “Granny knows best”
  • Sources of info
    • Peers, family, internet
  • Medical factors
    • New symptoms, visible symptoms, increasing severity, duration etc
  • Non-medical factors
    • Crises, peer pressure, “wife sent me”, patient beliefs, expectations, social class, economic, psychological, environment, cultural, ethnic, age, gender, media etc
10
Q

What are some medical factors that impact the uptake of care?

A
  • New symptoms, visible symptoms, increasing severity, duration etc
11
Q

What are some non-medical factors affecting the uptake of care?

A
  • Crises, peer pressure, “wife sent me”, patient beliefs, expectations, social class, economic, psychological, environment, cultural, ethnic, age, gender, media etc
12
Q

What are the different categories of illnesses?

A

Acute, chronic or self-limiting

13
Q

Do more males or females see their GP?

A

More females see their GPs than males, until over 65s

14
Q

What are some possible issues from the patients POV about accepting they have an illness?

A
  • Believes themselves to be healthy
  • Is physically fit
  • Proud to not be using tablets
  • If treatment is proposed, how would he feel better
15
Q

What is epidemiology?

A

The branch of medicine which deals with incidence, distribution and possible control of disease and other factors relating to health

16
Q

What are the 3 main aims of epidemiology?

A
  • Description
    • To describe the amount and distribution of disease in human populations
  • Explanation
    • To elucidate the natural history and identify aetiological factors for disease usually by combining epidemiological data with data from other disciplines such as biochemistry, occupational health and genetics
  • Disease control
    • To provide the basis on which preventative measures, public health practices and therapeutic strategies can be developed, implemented, monitored and evaluated for the purposes of disease control
17
Q

What does description mean in terms of epidemiology?

A
  • To describe the amount and distribution of disease in human populations
18
Q

What does explanation mean in terms of epidemiology?

A
  • To elucidate the natural history and identify aetiological factors for disease usually by combining epidemiological data with data from other disciplines such as biochemistry, occupational health and genetics
19
Q

What does disease control mean in terms of epidemiology?

A
  • To provide the basis on which preventative measures, public health practices and therapeutic strategies can be developed, implemented, monitored and evaluated for the purposes of disease control
20
Q

Epidemiology compares groups (study populations) in order to detect differences pointing to what?

A
  • Aetiological clues
  • Scope for prevention
  • Identification of high risk or priority groups in society
21
Q

What are examples of things that can define a study population?

A

Age

Sex

Location

22
Q

What is a fundamental difference between clinical medicine and epidemiology?

A

Clinical medicine deals with individual patient

Epidemiology deals with populations

23
Q

What is done to be clear about which populations we are talking about when we carry out studies?

A

We talk about ratios:

  • Number of events/population at risk
    • Such as deaths from IHD in men aged 55-63 in Grampian in 1990/all men aged 55-64 in Grampian in 1990
  • Ratios are usually converted into rates by expressing them in terms of a specified time period (per year) and a notional ‘at risk’ population of 10n (eg % per 1000 or per 100000)
24
Q

What is incidence?

A

Number of new cases of a disease in a population specified period of time

25
Q

What does incidence and prevalence tell us about?

A

Incidence tells us something about the trends in causation and the aetiology of disease

Prevalence tells us something about the amount of disease in a population

26
Q

What is prevalence?

A

Number of people in a population with a specific disease at a single point in time or in a defined period of time

27
Q

What is relative risk?

A

Measure of the strength of an association between a suspected risk factor and the disease under study

28
Q

What does RR stand for?

A

Relative risk

29
Q

What formula describes relative risk?

A
30
Q

What is absolute risk?

A

Absolute risk is the probability of an event happening, number of events that occurred in a group divided by the number of people in that group, this is also known as actual risk

31
Q

What is absolute risk also known as?

A

Actual risk

32
Q

What are examples of sources of epidemiological data?

A
  • Mortality data
  • Hospital and clinical activity statistics
  • Reproductive health statistics
  • Infectious disease statistics
  • Cancer statistics
33
Q

What is health literacy about?

A

Is about people having the knowledge, skills, understanding and confidence to use health information, to be active partners in their care and to navigate health and social care systems

34
Q

What are SIGN guidelines based on?

A

Based on systematic review of the scientific literature and aimed at aiding the translation of new knowledge into action

35
Q

What are SIGN guidelines intended to do?

A
  • Help health and social care professionals and patients understand medical evidence and use it to make decision about healthcare
  • Reduce unwarranted variations in practice and make sure patients get the best care available, no matter where they live
  • Improve healthcare across Scotland by focusing on patient important outcomes
36
Q

What are different classes of study types?

A

Descriptive studies

Analytical studies

Cohort studies

Trials

37
Q

What are descriptive studies useful for?

A
  • Identifying emerging public health problems through monitoring and surveillance of disease patterns
  • Signalling the presence of effects worthy of further investigation
  • Assessing the effectiveness of measures of prevention and control (such as screening programmes)
  • Assessing needs for health services and service planning
  • Generating hypotheses about disease aetiology
38
Q

What do descriptive studies attempt to do?

A
  • Attempt to describe the amount and distribution of a disease in a given population
39
Q

What does descriptive studies not provide?

A
  • Does not provide definitive conclusions about disease causation but gives clues to possible risk factors (exposures) linked to candidate aetiology
40
Q

What are advantages of descriptive studies?

A
  • Usually cheap, quick and give a valuable initial overview of a problem
41
Q

What are different kinds of analytical studies?

A
  • Cross sectional study
    • Looks at disease frequency, survey, prevalence study)
    • Observations are made at a single point in time
    • Conclusions are drawn about the relationship between diseases (or other health-related characteristics) and other variables of interest in a defined population
    • Strength is delivers results quickly, usually impossible to infer causation though
  • Case control study
    • Two groups of people are compared
      • Group of individuals who have the disease of interest (cases)
      • Group of individuals who do not have the disease (controls)
    • Results are expressed as odds ratios or relative risk
    • Confidence intervals or ‘p values’ are presented as a guide as to whether the results could be a chance finding
42
Q

What do cross sectional studies look at?

A
  • Looks at disease frequency, survey, prevalence study
43
Q

In cross sectional study are observations made at a single point of time or longitudinal?

A

Single point of time

44
Q

Cross sectional studies draw conclusions about what?

A
  • Conclusions are drawn about the relationship between diseases (or other health-related characteristics) and other variables of interest in a defined population
45
Q

What are advantages of cross sectional studies?

A
  • Strength is delivers results quickly, usually impossible to infer causation though
46
Q

What are case control studies?

A
  • Two groups of people are compared
    • Group of individuals who have the disease of interest (cases)
    • Group of individuals who do not have the disease (controls)
47
Q

What are the results of case control studies expressed as?

A
  • Results are expressed as odds ratios or relative risk
  • Confidence intervals or ‘p values’ are presented as a guide as to whether the results could be a chance finding
48
Q

What do confidence intervals or ‘p values’ indicate?

A

Whether the results could be a chance finding

49
Q

What happens in cohort studies?

A
  • Baseline data on exposure are collected from a group of people who do not have the disease under study
  • Followed through time until a sufficient number have developed the disease to allow analysis
  • Allows calculation of cumulative incidence, allowing for differences in follow up time
  • Results are expressed as relative risks
50
Q

What do cohort studies allow for the calculation of?

A
  • Allows calculation of cumulative incidence, allowing for differences in follow up time
51
Q

What are the results of cohort studies expressed as?

A
  • Results are expressed as relative risks
52
Q

What are trials?

A
  • Experiments used to test ideas about aetiology or to evaluate interventions
53
Q

What is the definitive method of assessing any new treatment in medicine?

A

Randomised conrol trial

54
Q

What happens in a randomised control trial?

A
  • Two groups at risk of developing a disease are assembled, a study (intervention) group and a control group
  • Alteration made to intervention group (such as suspected causation factor neutralised) whilst no alteration is made to the control group
  • Data on subsequent outcomes (such as disease incidence) are collected in the same way for both groups, and the relative risk is calculated
  • Aim is to determine whether modification of the factor (removing, reducing or increasing exposure) alters the incidence of disease
  • In trial for new treatment, the design is the same, the intervention group receives new therapy and the control group receives current therapy or a placebo and the treatment outcomes are compared between the two groups
55
Q

What is the aim of randomised control trials?

A
  • Aim is to determine whether modification of the factor (removing, reducing or increasing exposure) alters the incidence of disease
56
Q

What are factors to consider when interpreting results?

A
  • Standardisation
    • Techniques used to adjust for the effects of differences in age or other confounding variables when comparing two or more populations
    • Before standardisation it is known as crude rates
  • Standardised mortality ratio
    • Special kind of standardisation, simply a standardised death rate converted into a ratio for easy comparison
    • Figure for a standard reference population is 100
    • So an SMR (standardised mortality ratio) below 100 is fewer than expected deaths, and above 100 is more than expected
    • For example, SMR of 120 means that 20% more deaths occurred than expected in the study population
  • Quality of data
    • Ensure data is trustworthy
  • Case definition
    • Decide whether an individual has the condition of interest or not
    • Important because not all doctors or investigators mean the same thing when they use medical terms
  • Coding and classification
    • When data is being collected it is normally converted to a set of codes to assist in data storage and analyses
  • Ascertainment
    • Is the data complete or are any subjects missing
57
Q

What is standardisation?

A
  • Techniques used to adjust for the effects of differences in age or other confounding variables when comparing two or more populations
58
Q

What are rates known as before standardisation?

A

Crude rates

59
Q

What is standardised mortality ratio?

A
  • Special kind of standardisation, simply a standardised death rate converted into a ratio for easy comparison
  • Figure for a standard reference population is 100
60
Q

What does SMR stand for?

A

Standardised mortality ratio

61
Q

What does a SMR below 100 indicate?

A

Fewer then expected deaths

62
Q

What does a SMR above 100 indicate?

A

More than expected deaths

63
Q

What does a SMR of 120 mean?

A

20% more deaths occured than expected in the study population

64
Q

What is meant by quality of data?

A
  • Ensure data is trustworthy
65
Q

What is meant by case definition?

A
  • Decide whether an individual has the condition of interest or not
  • Important because not all doctors or investigators mean the same thing when they use medical terms
66
Q

What is meant by coding and classification?

A
  • When data is being collected it is normally converted to a set of codes to assist in data storage and analyses
67
Q

What is meant by ascertainment?

A
  • Is the data complete or are any subjects missing
68
Q

What is bias?

A

Any trend in the collection, analysis, interpretation, publication or review of data that can lead to conclusions that are systemically different from the truth

69
Q

What are different kinds of bias?

A
  • Selection bias
    • Study sample is not truly representative of the whole study population about which conclusions are to be drawn
  • Information bias
    • Systemic errors in measuring exposure or disease
    • Such as encouraging cases more than controls to think hard about past exposures to the factor of interest
  • Follow up bias
    • One group of subjects is followed up more assiduously than another to measure disease incidence or another relevant outcome
    • Such as subjects move address or fail to reply to questionnaires sent out, then greater attempts made to trace missing subjects from one group and not another
  • Systemic error
    • Form of measurement bias where there is a tendency for measurements to always fall on one side of the true value
    • May be because of the instrument being calibrated wrong, or because the person is using it wrong
    • Can occur with interviews and questionnaires as well as medical instruments
  • Publication bias
    • Where positive results have greater chance of being published than negative results
70
Q

What is selection bias?

A
  • Study sample is not truly representative of the whole study population about which conclusions are to be drawn
71
Q

What is information bias?

A
  • Systemic errors in measuring exposure or disease
  • Such as encouraging cases more than controls to think hard about past exposures to the factor of interest
72
Q

What is follow up bias?

A
  • One group of subjects is followed up more assiduously than another to measure disease incidence or another relevant outcome
  • Such as subjects move address or fail to reply to questionnaires sent out, then greater attempts made to trace missing subjects from one group and not another
73
Q

What is systemic error?

A
  • Form of measurement bias where there is a tendency for measurements to always fall on one side of the true value
  • May be because of the instrument being calibrated wrong, or because the person is using it wrong
  • Can occur with interviews and questionnaires as well as medical instruments
74
Q

What can systemic bias occur due to?

A
  • May be because of the instrument being calibrated wrong, or because the person is using it wrong
75
Q

What is publication bias?

A
  • Where positive results have greater chance of being published than negative results
76
Q

What are confounding factors?

A

One which is associated independently with both the disease and with the exposure under investigation and so distorts the relationship between the exposure and disease

77
Q

What are examples of common confounding factors?

A

Age

Sex

Social class

78
Q

What are different ways of dealing with confounding factors?

A
  • In trials, the process of randomisation
  • Restrictions of eligibility criteria to only certain kinds of study subjects
  • Subjects in different groups being matched for likely confounding factors
  • Results stratified according to confounding factors
  • Results adjusted (using multivariable analyses techniques) to take into account the suspected confounding factors
79
Q

Is it easy to prove causation between exposure and disease?

A

Difficult to prove causation between exposure and disease

Often the best that can be achieved is to demonstrate a weight of evidence in favour of a causal relationship

80
Q

What has been devised to help investigators assess the available evidence for causality?

A

Criteria for causality

81
Q

What are examples of criteria for causality?

A
  • Strength of association
    • Measured by relative risk or odds ratio
  • Consistency
    • Repeated observation of an association in different populations under different circumstances
  • Specificity
    • Single exposure leading to a single disease
  • Temporality
    • The exposure comes before the disease
  • Biological gradient
    • Dose-response relationship, as the exposure increases so does the risk of the disease
  • Biological plausibility
    • The association agrees with what is known about the biology of the disease
  • Conference
    • The association does not conflict with what is known about the biology of the disease
  • Analogy
    • Another exposure-disease relationship exists that can act as a model for the one under investigation
    • Such as it is known that certain drugs can cross the placenta and cause birth defects, so it might be possible for viruses to do the same
  • Experiment
    • A suitably controlled experiment to prove the association as causal
82
Q

In terms of criteria for causality, what is meant by strength of association?

A
  • Measured by relative risk or odds ratio
83
Q

In terms of criteria for causality, what is meant by consistency?

A

Repeated observation of an association in different populations under different circumstances

84
Q

In terms of criteria for causality, what is meant by specificity?

A

Single exposure leading to a single disease

85
Q

In terms of criteria for causality, what is meant by temporality?

A

The exposure comes before the disease

86
Q

In terms of criteria for causality, what is meant by biological gradient?

A

Dose-response relationship, as the exposure increases so does the risk of the disease

87
Q

In terms of criteria for causality, what is meant by biological plausibility?

A

The association agrees with what is known about the biology of the disease

88
Q

In terms of criteria for causality, what is meant by conference?

A

The association does not conflict with what is known about the biology of the disease

89
Q

In terms of criteria for causality, what is meant by analogy?

A
  • Another exposure-disease relationship exists that can act as a model for the one under investigation
  • Such as it is known that certain drugs can cross the placenta and cause birth defects, so it might be psosibe for viruses to do the same
90
Q

In terms of criteria for causality, what is meant by experiment?

A

A suitably controlled experiment to prove the association as causal

91
Q

Does failure to furfil all of the criteria of causation rull our the causation?

A

Not necessarily

92
Q

What is an audit?

A

Systematic approach for peer review of medical care in order to identify opportunitie for improvement and provide a mechanism for realising them

93
Q

What must be done before doing an audit?

A

Before doing an audit need to set criteria and standards to measure:

  • Could define your own
    • Time consuming
    • Needs more research
  • Could utilise others if available
    • Guidelines based on systemic review of evidence
94
Q

What are disadvantages of defining your own criteria and standards to measure for an audit?

A
  • Time consuming
  • Needs more research
95
Q

What is an example of an audit?

A
  • An example is checking that all patients were prescribed the correct drugs as according to SIGN guidelines
96
Q

What should be done after doing an audit?

A

After doing the audit should do some intervention before repeating the audit (such as with the example of prescribing drugs correctly):

  • Find the ones who prescribed inappropriately and tell them not to do it again
  • Present audit results to the practice
  • Circulate current guideline summary to GPs
97
Q

Audits have limitations, what are examples of limitations from the following:

an example is checking that all patients were prescribed the correct drugs as according to SIGN guidelines

A
  • Sample is of those prescribed the antiviral drug only
  • Misses patients who should have received the drug but never