Module 6: Evidence Based Approaches To Monitoring And Supporting The Health Of Indivuals And Populations Flashcards
Passive surveillance
Relies on the health provider remembering to send through health information to the relevant health authority
Passive surveillance pros and cons
- Low cost, data linkage, wide area
- Under reporting
Active surveillance
Is when a health authority actively seeks relevant health information
Active surveillance pros and cons
- May provide more complete health data resulting in more accurate and immediate description of what’s happening
- Almost impossible to do at a national level and can be expensive and intensive
Sentinel surveillance
Refers to health authorities monitoring the health of individuals at specific sites within a population to provide an indication of the wider population
Unlinked anonymous
People who agree to be tested may have a lower prevalence so can be good to make testing anonymous to get a better view of the general population health
Event based surveillance
Less organised
Reports, media, rumours
Indicator based surveillance
Disease specific
Passive
What are the three levels of prevention? Clarify between the levels
Primary - to reduce incidence rates
Secondary - to improve outcomes in people who have already been diagnosed
Tertiary - to reduce the impact of consequences of a disease
Population vs Individual prevention strategies
Population prevention strategies aim to reduce the risk of disease for an entire population, so therefore affect a larger group of people meaning that it has the largest absolute decrease
Individual prevention strategies identity individuals at high risk and prevention strategies are applied only to them
Importance of evidence based practice
Evidence based practice is important to ensure the best available care is provided to patients
List 3 characteristics of the disease you want want to consider when deciding whether to implement a mass screening programme
The seriousness of the disease
The prevalence of the disease
The length of lead time
Positive predicted value (PPV) and negative predicted value (NPV) calculation
True positives/all positives x 100
True negatives/all negatives x 100
If the negative predicted value (NPV) was 95.5%, what does this tell us
That 95.5% of those who tested negative were actually negative, so therefore 4.5% of those who testes negative were a false negative and were actually positive
What is the main reason that researchers conduct meta analysis rather than rely on the results from a single study?
To increase the precision of the estimate
