Data Flashcards
what is the purpose of a GP?
● Interface between public and secondary care
● Not a filter for hospital medicine: patients move back and forth and there is communication
What are the factors of care uptake (going to get care)?
Lay referral: going from family → community → traditional/cultural healing → medical system
Sources of info: peers, family, and media
Medical factors: new symptoms, increasing severity, duration
Non-medical factors: crisis/psychological state, peer pressure (spouse/friends), ICE, class/culture/age/gender/economic position
Issues
○ Patient believe self to be healthy: physically fit, doesn’t want to use tablets
○ Doctor: perform additional investigation, educate self of concerns
epidemiology has 3 main aims, what are they?
description
explanation
disease control
EPIDEMIOLOGY: Define description
describe amount and distribution of disease in human population
EPIDEMIOLOGY: Define explanation
elucidate natural history and aetiology of disease by combining data from epidemiology with data from biochem/occupational health/genetics
EPIDEMIOLOGY: Define diseases control
provide bases for preventative measures/public health practices/therapeutic strategy for disease control
what are the sources of data
○ Mortality
○ Health and household surveys
○ NHS expenditure
○ Drug misuse
○ Hospital data:
- Reproductive, cancer, accidentwhat are the basic concepts which are relevant to epidemiology and how does this impact on how useful the findings of the study may be
It compares groups (study populations) in order to detect differences pointing to find:
aetiological clues
scope of prevention
identify high risk groups
Populations can be defined by age/sex/location or be same group over time
Compare how an event appears in one group with another
What are the fundamentals of data. and rates
● Clinical medicine deals with individual patient
● Epidemiology deals with population(specify groups)
● Ratios with:
Numerators = events, Denominator = population at risk
○ Within specific time
○ % or per 10^n
○
define relative risk
Relative risk: strength of association between risk factor and disease
■ Incidence in exposed group/incidence in unexposed group
what is health literacy
knowledge/skills/understanding/confidence of healthcare information by people, to use healthcare system, and be an active partner in their own care
● Scottish gov’t: Making it Easy - A Health Literacy Action Plan for Scotland
what info is needed for gps
● Scoring systems: CHA2DS2-VASc, bleeding risk tool
SIGN guidelines:
○ Goals
- Help healthcare professional/patients understand medical evidence
- Reduce variations in practice
- Improve care by focusing on patient important outcomes
○ Based on systematic review of literature
○ Rating evidence
define the various study types
● Descriptive study: describe amount and distribution of disease in a given population
○ No definitive conclusions, does clue risk factors and aetiology
○ Cheap, quick, overview
● Analytical study:
○ Cross sectional(disease frequency/survey): observations in a point in time
○ Case Control: comparison of 2 groups (cases/controls)
● Cohort: baseline data on a group, then followed until disease developed in sufficient numbers to allow analysis
● Trials: Test ideas about aetiology or evaluate interventions
○ “Randomised controlled trial”: varying intervention on patients and analysis of results
what is descriptive study
describe amount and distribution of disease in a given population
○ No definitive conclusions, does clue risk factors and aetiology
○ Cheap, quick, overview
what is analytical study
Cross sectional(disease frequency/survey): observations in a point in time ○ Case Control: comparison of 2 groups (cases/controls)
define cohort study :
baseline data on a group, then followed until disease developed in sufficient numbers to allow analysis
define trials
Test ideas about aetiology or evaluate interventions
○ “Randomised controlled trial”: varying intervention on patients and analysis of results
what factors should you consider when interpreting results
● Standardisation: adjust for effects of confounding variables
● Standardised Mortality Ratio: standardised death rate converted to ratio, e.g. standard is 100, 120 means 20% more death than expected
● Quality of Data: ensure data is trustworthy
● Case definition: decide if an individual has the condition of interest or not; varying definition from study maker to interpreter
● Coding and classification: relevant to case definition in data analysis
● Ascertainment: completeness of data. One group looking harder than another
what is bias:
name and describe the different types
● Any trend in collection, analysis, interpretation, publication, or review that leads to conclusions different from the truth
● Selection bias: sample is not representative of whole study population
● Information bias: Systematic errors in measuring exposure/disease e.g. researcher knowing “case”vs“control”, and working harder on “case”
● Follow up bias: one group of subjects is followed up more assiduously
● Systematic error: measurement bias where measurements tend to fall on one side of the truth e.g. machine calibrated incorrectly, poorly written survey
what are cofounding factors?
associated independently with both the disease and with the exposure under investigation and so distorts the relationship between the exposure and disease.
may be the true causal factor, and not the exposure that is under consideration.
Age, sex and social class are common confounders. There are several ways to deal with confounding, depending on the particular study design
how can we deal with cofounding factors
- 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.
what is the criteria of causality
● Difficult to prove so criteria are layed out(only Temporality has to be followed):
○ ○ Temporality: exposure comes before disease [only absolute criterion]
○ Strength of association: relative risk ratio
○ Consistency: repeated observation of association in differing populations
○ Specificity: single exposure leads to single disease
○ Biological gradient: dose response relationship i.e. exposure UP = risk UP
○ Biological plausibility: association agrees with biology of disease
○ Coherence: association does not conflict with biology of disease
○ Analogy: another relationship exists that can be used as a model for current
○ Experiment: suitably controlled experiment to prove association as causal(uncommon in human populations)
What is audit: criteria and standards
○ Reason ○ Criteria that are being measured ○ Standards ○ Preparation and planning ○ Results from collection 1 ○ Change implemented ○ Results from collection 2 ○ Reflection
