*Cornerstone of epidemiology: Observational studies and routine data Flashcards Preview

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Flashcards in *Cornerstone of epidemiology: Observational studies and routine data Deck (10):
1

Hierarchy of study design (highest to lowest)

1. Systematic review and meta-analysis (highest, but can still be inadequate)
2. Randomised controlled trial
3. Cohort studies
4. Case-control studies
5. Ecological studies
6. Descriptive/cross-sectional studies
7. Case report/series (lowest - but can still be valuable)

Descriptive studies in epidemiology examine the distribution of disease across various factors including population or sub-groups, geographical location and time period

2

Cross-sectional survey examples

Examples:
- 2001 Census
- Health survey for England
- NHS Inpatient survey on patient experience

3

Routine data

Data routinely collected and recorded in an ongoing systematic way
Often for administrative or statutory purposes and without any specific research question in mind at the time of collection

4

Types of routine data

- Health outcome data: e.g. deaths, hospital admissions and primary care consultations or prescriptions, levels of well-being from national surveys
- Exposures and health determinant data: e.g. smoking, air pollution, crime statistics
- Disease prevention data: e.g. screening and immunisation uptake
- Demographic data: e.g. census population counts
- Geogrpahical data: e.g. health authority boundaries, location of GP practices
- Births
- Deaths
- Cancer registrations
- Notifications of infectious diseases
- Terminations of pregnancy
- Congenital anomalies
- Hospital admissions
- Community systems
- GP consultation data
- Prescriptions
- Road traffic accidents

5

Standardized Mortality Ratios (SMR)

Key confounders such as age vary between populations.

Confounders: variables that influence both the independent and dependent variables, making a false relationship

Population death rates may be compared taking into account (or adjusting) for the effect of age.
One way to do this is using the SMR.
SMR is a rate ratio adjusted for age.
It is the ratio between the number of observed deaths (or cases of disease) in a particular population to the number that would be expected if the population had the same mortality and morbidity experience as a standard population, corrected for differences in age structure.

SMR=(Number of observed deaths)/(Number of expected deaths if experienced the same age specific rates as standard population)

It is common for SMRs to be adjusted for age and also for sex.

6

Standardized Mortality Ratios (SMR)

Key confounders such as age vary between populations.

Confounders: variables that influence both the independent and dependent variables, making a false relationship

Population death rates may be compared taking into account (or adjusting) for the effect of age.
One way to do this is using the SMR.
SMR is a rate ratio adjusted for age.
It is the ratio between the number of observed deaths (or cases of disease) in a particular population to the number that would be expected if the population had the same mortality and morbidity experience as a standard population, corrected for differences in age structure.

SMR=(Number of observed deaths)/(Number of expected deaths if experienced the same age specific rates as standard population)

It is common for SMRs to be adjusted for age and also for sex.

7

LO1: To recall the major sources of routine data on health and illness in the UK

Routine data:
Data routinely collected and recorded in an ongoing systematic way
Often for administrative or statutory purposes and without any specific research question in mind at the time of collection

Sources:
- Health outcome data: e.g. deaths, hospital admissions and primary care consultations or prescriptions, levels of well-being from national surveys
- Exposures and health determinant data: e.g. smoking, air pollution, crime statistics
- Disease prevention data: e.g. screening and immunisation uptake
- Demographic data: e.g. census population counts
- Geogrpahical data: e.g. health authority boundaries, location of GP practices
- Births
- Deaths
- Cancer registrations
- Notifications of infectious diseases
- Terminations of pregnancy
- Congenital anomalies
- Hospital admissions
- Community systems
- GP consultation data
- Prescriptions
- Road traffic accidents

8

LO3: To define standardised mortality ratios and demonstrate with examples their use in comparing health in populations

Key confounders such as age vary between populations.

Confounders: variables that influence both the independent and dependent variables, making a false relationship

Population death rates may be compared taking into account (or adjusting) for the effect of age.
One way to do this is using the SMR.
SMR is a rate ratio adjusted for age.
It is the ratio between the number of observed deaths (or cases of disease) in a particular population to the number that would be expected if the population had the same mortality and morbidity experience as a standard population, corrected for differences in age structure.

SMR=(Number of observed deaths)/(Number of expected deaths if experienced the same age specific rates as standard population)

It is common for SMRs to be adjusted for age and also for sex.

9

LO4: To explain standardised mortality ratios (SMRs) and how they can be used in comparing health in populations

Key confounders such as age vary between populations.

Confounders: variables that influence both the independent and dependent variables, making a false relationship

Population death rates may be compared taking into account (or adjusting) for the effect of age.
One way to do this is using the SMR.
SMR is a rate ratio adjusted for age.
It is the ratio between the number of observed deaths (or cases of disease) in a particular population to the number that would be expected if the population had the same mortality and morbidity experience as a standard population, corrected for differences in age structure.

SMR=(Number of observed deaths)/(Number of expected deaths if experienced the same age specific rates as standard population)

It is common for SMRs to be adjusted for age and also for sex.

10

LO2: To critique routine health data by identifying their strengths and weaknesses

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