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FOPC Year 2 and 3 > The Use of Data > Flashcards

The Use of Data Flashcards

1
Q

Define disease

A

Disease – symptoms, signs – diagnosis.

Bio-medical perspective

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2
Q

Define illness

A

Illness – ideas, concerns, expectations – experience.

Patients perspective

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3
Q

Factors affecting uptake of care?

A
  • Concept of Lay Referral = “Granny knows best”
  • Sources of info = Peers, family, TV, internet etc
  • Medical factors - New symptoms, increasing severity, duration etc
  • Non-medical factors = Crisis, peer pressure (“Wife sent me”), economic, psychological, environmental, culture, age, gender etc
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4
Q

Type of illness?

A
  • Acute
  • Chronic
  • Self-limiting
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5
Q

What issues can there be in delivery of care due to the patients point of view?

A

> Believes himself to be healthy.

> Is physically fit.

> Proud not to be using tablets.

> Both he and his wife associate all illnesses to do with the Heart with Ischaemic Heart Disease.

> If treatment is proposed, how would he feel better?

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6
Q

What issues can there be in delivery of care due to the GPs point of view?

A

> You wish to perform a couple more tests – E.g. a Holter Monitor and an Echocardiogram – why might you do these tests?

> Assuming they return as confirming AF, you are worried about the consequences for Mr Blackwood’s long term health.

> Why might that be – what are you concerned about, and what sources of information might you have used to educate yourself about that?

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7
Q

What are the three main aims of epidemiology?

A

Description

Explanation

Disease control

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8
Q

What are the three main aims of epidemiology - Description?

A

Description:

To describe the amount and distribution of disease in human populations.

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9
Q

What are the three main aims of epidemiology - Explanation?

A

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.

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10
Q

What are the three main aims of epidemiology - Disease control?

A

Disease control:
To provide the basis on which preventive measures, public health practices and therapeutic strategies can be developed,
implemented, monitored and evaluated for the purposes of disease control.

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11
Q

What does Epidemiology provide?

A

It compares groups (study populations) in order to detect differences pointing to:
> Aetiological clues (what causes the problem)

> The scope for prevention

> The identification of high risk or priority groups in society.

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12
Q

Clinical medicine deals with what?

A

Individual patients

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13
Q

Epidemiology deals with what?

A

Populations

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14
Q

How is the rate determined in epidemiology?

A

Using ratios:

Events / Population at risk

The numerator is the top line, the number of events (in this example deaths).

The denominator is the bottom line, the population at risk.

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15
Q

What is incidence?

A

Incidence - is the number of new cases of a disease in a population in a specified period of time

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

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16
Q

What is prevalence?

A

Prevalence - is the number of people in a population with a specific disease at a single point in time or in a defined period of time

Prevalence tells us something about the amount of disease in a population. It is useful in assessing the workload for the health service but is less useful in studying the causes of disease

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17
Q

What is relative risk?

A

This is the measure of the strength of an association between a suspected risk factor and the disease under study.

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18
Q

How is relative risk calculated?

A 
Relative risk (RR) = 	(Incidence of disease in exposed group) /
(Incidence of disease in unexposed group)

Slide 28 for examples

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19
Q

Sources of Epidemiological Date?

A

Include, but not restricted to

Mortality data
Hospital activity statistics
Reproductive health statistics
Cancer statistics
Accident statistics
General practice morbidity
Health and household surveys
Social security statistics
Drug misuse databases
Expenditure data from NHS
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20
Q

Health literacy ?

A

Health literacy 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.

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21
Q

CHA(2)DS-VASc?

A

Used to determine risk involved in Non-rheumatic AF

C = CHF history
H = Hypertension history 
A = Age (65-74 = 1 point, >75 = 2 points)
D = Diabetes history 
S = Stroke/TIA/Thromboembolism

V = Vascular disease history

Score of:
1 = Low risk, consider anti platelet or anticoagulation
>2 = Moderate risk, should be on anticoagulation

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22
Q

HAS-BLED score?

A

Measure risk of major bleed when using warfarin

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23
Q

NOAC’s?

A

Measure reduced risk and expense saved using warfarin

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24
Q

How is information gathered for SIGN guidelines?

A

1) Gather lived experience
2) Identify question
3) Search for evidence
4) Look at the evidence
5) Make judgements and recommendations
6) Ask people for feedback
7) Publish
8) Let everybody know about the guidelines

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25
Q

How is evidence rated by SIGN guidelines?

A

Alphabetically with A being the best, the following are used in this judgement:

> Methodology checklist 1: systematic reviews and meta-analyses
Checklist
Notes

> Methodology checklist 2: randomised controlled trials
Checklist
Notes

> Methodology checklist 3: cohort studies
Checklist
Notes

> Methodology checklist 4: case-control studies
Checklist
Notes

> Methodology checklist 5: diagnostic studies
Checklist

> Methodology checklist 6: economic studies
Checklist
Notes

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26
Q

Types of studies - Descriptive studies?

A

Descriptive studies attempt to describe the amount and distribution of a disease in a given population, for the purposes of gaining insight into the aetiology of the condition or for planning health services to meet the clinical need.

Studies may look at the disease alone or may also examine one or more factors (exposures) thought to be linked to the aetiology.

This kind of study does not provide definitive conclusions about disease causation, but may give clues to possible risk factors and candidate aetiologies.

27
Q

What are the key things descriptive studies are used for?

A

Descriptive studies follow the time, place, person framework. Descriptive epidemiological studies are useful in:
> 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 (eg, screening programmes).
> Assessing needs for health services and service planning.
> Generating hypotheses about disease aetiology.

28
Q

What are the advantages of descriptive studies?

A

Such studies are usually cheap, quick and give a valuable initial overview of a problem.

29
Q

What are the disadvantages of descriptive studies?

A

They do not provide evidence about the causes of disease.

They do not test hypotheses.

30
Q

Types of Studies - Analytic Studies - Cross-sectional?

A

Cross-Sectional (disease frequency, survey, prevalence study)

> In cross-sectional studies, 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.

31
Q

Advantage of analytic studies - Cross-sectional?

A

A strength of this method is its ability to provide results quickly

32
Q

Disadvantage of analytic studies - Cross-sectional?

A

It is usually impossible to infer causation.

33
Q

Types of Studies - Analytic Studies - Case control studies?

A

In case control studies, two groups of people are compared:

1) A group of individuals who have the disease of interest are identified (cases)
2) A group of individuals who do not have the disease (controls).

The odds ratio or relative risk are then determined usually presented as P values.

34
Q

Types of Studies - Analytic Studies - Cohort studies?

A

In cohort studies, baseline data on exposure are collected from a group of people who do not have the disease under study. The group is then followed through time until a sufficient number have developed the disease to allow analysis.

The original group is separated into subgroups according to original exposure status and these subgroups are compared to determine the incidence of disease according to exposure. Cohort studies allow the calculation of cumulative incidence, allowing for differences in follow up time.

The results are expressed as relative risk, with confidence intervals or p values.

35
Q

Types of Studies - Trials?

A

Trials are experiments used to test ideas about aetiology or to evaluate interventions. The “randomised controlled trial” is the definitive method of assessing any new treatment in medicine.

1) Two groups at risk of developing a disease are assembled, a study (intervention) group and a control group.
2) An alteration is made to the intervention group (eg, a suspected causative factor is removed or neutralised), whilst no alteration is made to the control group.
3) Data on subsequent outcomes (eg, disease incidence) are collected in the same way from both groups, and the relative risk is calculated.

The aim is to determine whether modification of the factor (removing, reducing or increasing exposure) alters the incidence of the disease.

36
Q

Factors to consider in interpreting results?

A

1) Standardisation
2) Standardised Mortality Ratio
3) Quality of Data
4) Case Definition
5) Coding and Classification
6) Ascertainment

37
Q

Factors to consider in interpreting results - Standardisation?

A

A set of techniques used to remove (or adjust for) the effects of differences in age or other confounding variables, when comparing two or more populations.

38
Q

Factors to consider in interpreting results - Standardised mortality ratio (SMR)?

A

It is simply a standardised death rate converted into a ratio for easy comparison.

The figure for a standard reference population (eg, Scotland) is taken to be 100 and the standardised death rates for the comparison (study) populations (eg, Grampian) are expressed as a proportion of 100. A figure below one hundred means fewer than expected deaths, and above 100 means more.

39
Q

Factors to consider in interpreting results - Quality of Data?

A

In working with data about health and disease, we must be careful to ensure that the data are trustworthy.

40
Q

Factors to consider in interpreting results - Case definition?

A

The purpose of case definition is to decide whether an individual has the condition of interest or not. It is important in because not all doctors or investigators mean the same thing when they use medical terms.

Differences in incidence of disease over time or in different populations may be artefact, due to differences in case definition, rather than differences in true incidence.

41
Q

Factors to consider in interpreting results - Coding and classification?

A

This is related to the issue of case definition. When data are being collected routinely (eg, death certificates), it is normal to convert disease information to a set of codes, to assist in data storage and analysis. Rules are drawn up to dictate how clinical information is converted to a code. If these rules change, it sometimes appears that a disease has become more common, or less common, when in fact it has just been coded under a new heading.

42
Q

Factors to consider in interpreting results - Ascertainment?

A

Is the data complete - are any subjects missing?

43
Q

What is bias?

A

Bias is any trend in the collection, analysis, interpretation, publication or review of data that can lead to conclusions that are systematically different from the truth. There are very many types of bias which can creep into epidemiological studies.

44
Q

What are the four types of bias?

A

1) Selection Bias
2) Information Bias
3) Follow up Bias
4) Systematic Error

45
Q

Describe the types of bias - Selection bias? Give an example.

A

Occurs when the study sample is not truly representative of the whole study population about which conclusions are to be drawn.

For example, in a randomised controlled trial of a new drug, subjects should be allocated to the intervention (study) group and control group using a random method. If certain types of people (eg, older, more ill) were deliberately allocated to one of these groups then the results of the trial would reflect these differences, not just the effect of the drug.

46
Q

Describe the types of bias - information bias? Give an example.

A

Arises from systematic errors in measuring exposure or disease.

For example, in a case control study, a researcher who was aware of whether the patient being interviewed was a ‘case’ or a ‘control’ might encourage cases more than controls to think hard about past exposures to the factors of interest. Any differences in exposure would then reflect the enthusiasm of the researcher as well as any true difference in exposure between the two groups.

47
Q

Describe the types of bias - follow up bias? Give an example.

A

Arises when one group of subjects is followed up more assiduously than another to measure disease incidence or other relevant outcome.

For example, in cohort studies, subjects sometimes move address or fail to reply to questionnaires sent out by the researchers. If greater attempts are made to trace these missing subjects from the group with greater initial exposure to a factor of interest than from the group with less exposure, the resulting relative risk would be based on a (relative) underestimate of the incidence in the less exposed group compared with the more exposed group.

48
Q

Describe the types of bias - systematic error bias? Give an example.

A

A form of measurement bias where there is a tendency for measurements to always fall on one side of the true value.

It may be because the instrument (eg, a blood pressure machine) is calibrated wrongly, or because of the way a person uses an instrument.

This problem may occur with interviews, questionnaires etc, as well as with medical instruments.

49
Q

What are cofounding factors and why are they important to consider?

A

A confounding factor is 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.

In some cases the confounding factor may be the true causal factor, and not the exposure that is under consideration.

50
Q

What are examples of cofounding factors?

A

Age, sex and social class are common confounders

51
Q

How can you deal with cofounding factors?

A

> In trials, the process of randomisation (in effect the play of chance leads to similar proportions of subjects with particular
confounding in the intervention and control groups).

> Restriction of eligibility criteria to only certain kinds of study subjects .

> Subjects in different groups can be matched for likely confounding factors.

> Results can be stratified according to confounding factors.

> Results can be adjusted (using multivariate analysis techniques) to take account of suspected confounding factors.

52
Q

Criteria for Causality?

A

1) Strength of association
2) Consistency
3) Specificity
4) Temporality
5) Biological gradient
6) Biological plausibility
7) Coherence
8) Analogy
9) Experiment

53
Q

Criteria for Causality - Strength of association?

A

Strength of association - As measured by relative risk or odds ratio.

54
Q

Criteria for Causality - Consistency?

A

Consistency - Repeated observation of an association in different populations under different circumstances.

55
Q

Criteria for Causality - Specificity?

A

Specificity - A single exposure leading to a single disease.

56
Q

Criteria for Causality - Temporality?

A

Temporality - The exposure comes before the disease.

57
Q

Criteria for Causality - Biological gradient?

A

Biological gradient - Dose-response relationship. As the exposure increases so does the risk of disease.

58
Q

Criteria for Causality - Biological plausibility?

A

Biological plausibility - The association agrees with what is known about the biology of the disease.

59
Q

Criteria for Causality - coherence?

A

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

60
Q

Criteria for Causality - Analogy?

A

Analogy- Another exposure-disease relationship exists which can act as a model for the one under investigation.

For example, it is known that certain drugs can cross the placenta and cause birth defects, it might be possible for viruses to do the same.

61
Q

Criteria for Causality - Experiment?

A

Experiment - A suitably controlled experiment to prove the association as causal - very uncommon in human populations.

62
Q

Audit criteria and standards?

A

Need to set criteria and standards to measure. A clinical audit evaluates how well current best practice is being carried out; audits ask “are we doing the right thing and are we doing it the best way?”

> Could define own:

  • Time consuming
  • Needs more research

> Could utilise others if available:
- Guidelines based on systematic review of evidence

63
Q

Overview of the audit cycle?

A

Step 1: Define the standard
> Determine the criteria for the current best practice.
> Common standards include: NICE guidance, Royal College Guidance, national service frameworks, local policies etc.

Step 2: Collect the data
> Identify what data needs to be collected, how, and who is going to collect it.
> Decide whether the data will be collected prospectively or retrospectively and what sample size is needed.

Step 3: Compare current practice with standard
> Analyse the data collected (actual performance within the department) with the set standard.
> Evaluate how well the standards were met and if not, identify reasons for this.

Step 4: Implement a change to improve service
> Present the results to the relevant multidisciplinary teams in your organisation.
> Develop, agree and implement an action plan to bring actual practice closer to the standard.

Step 5: Close the audit cycle loop
(repeat steps 1-4)
> After time for the intervention to take effect, collect new data and determine the impact.
> Then comparing again with the standard and establish if there was an improvement in practice.

FOPC Year 2 and 3 (9 decks)

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