Public Health Flashcards

(130 cards)

1
Q

3 domains of public health

A

PIS

Health protection (control infectious diseases / environmental hazards)

Health improvement (social interventions aimed at preventing disease / promoting health / reducing inequality)

Health services (organisation and delivery of safe, high quality services)

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2
Q

Inverse care law

A

The availability of medical or social care tends to vary inversely with the need of the population served

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3
Q

Determinants of health

A

PROGRESS:

Place of residence
Race/ethnicity
Occupation
Gender
Religion
Education
Socio-economic status
Social capital/resources

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4
Q

Horizontal vs vertical equity

A

Horizontal = equal treatment for equal need e.g. two identical twins with same level of asthma get same treatment

Vertical = unequal treatment for unequal need e.g. one person with life threatening asthma vs one person with mild asthma get different treatment, or the UK tax system

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5
Q

Health needs assessment definition

A

A systemic approach for reviewing health issues which leads to agreed priorities and resource allocation to improve health and decrease inequalities (takes into account need, demand, supply)

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6
Q

Epidemiological health needs assessment definition

A

Disease incidence & prevalence
Morbidity & mortality
Life expectancy
Services available (location, cost, utilisation, effectiveness)

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7
Q

Limitations of a epidemiological health needs assessment

A

Data availability may be poor
May be inadequate evidence base / quality of evidence
Reinforces a biomedical model of care / doesn’t consider felt need

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8
Q

Comparative health needs assessment definiton

A

Compares services received by one population to another
Spatial (e.g. different towns) or social (e.g. age, social class)
Evaluates variation in performance/costs of services

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9
Q

Comparative health needs assessment limitations

A

Data available may vary in quality
May be hard to find comparable population
Comparison may not be perfect

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10
Q

Corporate health needs assessment definition

A

Takes into account views of any groups that may have an interest e.g. patients, health professionals, media, politicians

Example of data collection = focus groups

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11
Q

Corporate health needs assessment limitations

A

May be hard to distinguish need from demand
Groups have vested interest - leads to bias
Dominant individuals may have undue influence

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12
Q

Types of need in health needs assessment (4) / Bradshaw taxonomy of social need

A

FENC

Felt need
Expressed need
Normative need
Comparative need

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13
Q

‘Felt need’ definition

A

Individual perceptions of deviations from normal health

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14
Q

‘Expressed need’ definition

A

Seeking help to overcome variation in normal health

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15
Q

‘Normative need’ definition

A

Professional expert defines intervention for expressed need e.g. vaccination

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16
Q

‘Comparative need’ definition

A

Comparison between severity, range of interventions and cost

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17
Q

Maslow’s hierarchy of needs

A

Physiological
Safety
Love/belonging
Esteem
Self-actualisation

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18
Q

Egalitarian resource allocation + pro/con

A

Provide all care that is necessary and required to everyone

+ equal for everyone
- economically restricted

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19
Q

Maximising resource allocation + pros/cons

A

Based solely on consequence

+ resources allocated to those likely to receive most benefit
- those with ‘less need’ will receive nothing

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20
Q

Libertarian resource allocation + pros/cons

A

Each individual responsible for own health

+ onus on patient, therefore may be more engaged
- not all diseases are self-inflicted

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21
Q

Maxwell’s 6 dimensions of quality

A

3 A’s, 3 E’s

Appropriateness / Effectiveness
Acceptability / Efficiency
Accessibility / Equity

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22
Q

Donabedian’s 3 step approach to quality

A

Structure
Process
Outcome

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23
Q

Examples of ‘structure’ in Donabedian’s 3 step approach to quality

A

Buildings e.g. wards
Facilities e.g. beds
Staff e.g. ratios to patients
Equipment e.g. new investment
Technology e.g. electronic notes

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24
Q

Examples of ‘process’ in Donabedian’s 3 step approach to quality

A

Guidelines + Protocols + Pathways of care = followed
Number of patients treated
User satisfaction surveys
Waiting times
Frequency of follow-up

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25
Examples of 'outcome' in Donabedian's 3 step approach to quality
Recovery Morbidity rates Mortality rates Trends in preventable disease Reduction in incidence in a population
26
Health behaviour aim
Behaviour aimed at preventing disease e.g. going for a run
27
Illness behaviour aim
Behaviour aimed at seeking remedy e.g. going to GP for a symptom
28
Sick role behaviour aim
Behaviour aimed at getting well e.g. taking antibitiotics
29
6 models of behaviour change
Theory of planned behaviours Nudge theory Health belief model Motivational interviewing Transtheoretical model Financial incentives
30
Theory of planned behaviours model
*intention is the greatest predictor of health behaviours* 1. Attitudes 2. Subjective norms 3. Perceived behaviour control
31
Advantages of theory of planned behaviours model
Can be applied to wide variety of health behaviours Useful for predicting intention Takes into account importance of social pressures
32
Disadvantages of theory of planned behaviours model
No temporal element, direction or causality Doesn't consider the complexity of human emotions Assumes attitudes can be measured
33
Health belief model key 5 factors
Perceived susceptibility Perceived severity Health motivation Perceived benefits Perceived barriers
34
Other variables that could influence the health belief model
Demographic variables including age, gender and SE status Psychological characteristics including personality, peer pressure
35
Advantages of the health belief model
Can be applied to wide variety of health behaviours Cues to action are unique component Longest standing model
36
Disadvantages of the health belief model
Other factors may influence the outcome Doesn't consider emotions Doesn't differentiate between first time and repeated behaviours
37
4 questions to consider when assessing medical negligence
Was there duty of care? Was there a breach in that duty? Was the patient harmed? Was the harm due to the breach in care?
38
Twin pillars of medical negligence
Bolam rule (would a reasonable doctor do the same?) Bolitho rule (would that be reasonable?)
39
Error definition
'never events' A serious largely preventable patient safety incident that should not occur if available, preventative measures have been implemented
40
Types of error (7)
Lack of skill Over attachment (conducting tests to confirm what we expect to see) Failure to consider the alternative Mistriage Ignorance Inheriting thinking Bravado
41
Variables of 'self' in the 3 bucket model of error
Level of knowledge Level of skill Level of expertise Current capacity to do task
42
Variables of 'context' in the 3 bucket model of error
Equipment + devices Physical environment Workspace Team + support Organisation + managment
43
Variables of 'task' in the 3 bucket model of error
Errors Task complexity Novel task Process
44
4 screening tests in UK
E.g: Newborn (heel prick) Breast cancer (mammography) Cervical cancer (smear) Bowel cancer (stool in the post)
45
Screening criteria: disease factors
Important Pre-clinical phase Natural history known Early treatment better than late / effective treatment available
46
Screening criteria: test
Fit for purpose (sensitive, specific, cost-calculated) Acceptable to the population Facilities available Simple, safe, precise and validated
47
Screening criteria: outcomes
Ongoing feasibility Treatment available Cost-benefit analysis
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True positive
Test +ve Dx +ve
49
False +ve
Test +ve Dx -ve
50
False -ve
Test -ve Dx +ve
51
True -ve
Test -ve Dx -ve
52
Cross-sectional study definition
Snapshot data of those with and without disease to find associations at a single point in time
53
Cross-sectional study positives (2)
Quick and cheap Few ethical issues Large sample size
54
Cross-sectional study negatives (2)
Risk of recall bias and non-response Cannot measure incidence Risk of reverse causality
55
Case-control study definition
**Retrospective observational** study which looks at a certain exposure and compares similar participants with and without the disease
56
Case-control study advantages
Good for **rare** diseases e.g. cancer **Quicker** than cohort or intervention as **the outcome has already happened**
57
Case-control study negatives
Can only show association (not causation) Unreliable due to **recall bias**
58
Cohort study description
**Longitudinal prospective** study which takes a population of people recording their exposures and conditions they develop
59
Cohort study advantages
Can follow-up a group with a rare exposure e.g. natural disaster Less risk of selection and recall bias Good for common outcomes
60
Cohort study negatives
Takes a long time Large amount lost to follow up (people dropping out) Large sample size needed Expensive
61
RCT description
Similar participants randomly controlled to intervention or control groups to study the effect of the intervention GOLD STANDARD
62
RCT study positives
Can infer **causality** **Less risk of bias**/confounders
63
RCT study negatives
Time consuming and expensive Ethical issues can interfere
64
Bradford Hill criteria for causality (4)
Specificity (relationship specific to outcome of interest) Strength of association Dose response relationship Temporality
65
Confounding factor definiton
Risk factor independently associated with the exposure and the outcome
66
Bias definition
A systematic error that results in a deviation from the true effect of an exposure of an outcome
67
Types of bias (SIP)
Selection Information Publication
68
4 types of information bias
Measurement bias (different equipment used to measure the outcome in the different groups) Observer bias (not double blind) Recall bias (past events incorrectly remembered) Reporting bias (responder doesn't tell the truth)
69
Sensitivity equation
it is able to pick it (true positives) up but it might not pick it all up (false negatives left behind)
70
Specificity equation
True negatives / True negatives + False positives
71
2 ethical frameworks that can be used to assess an ethical dilemma
Seedhouses's ethical grid Four quadrants approach
72
Four quadrants approach to an ethical dilemma
Medical indications (beneficence and non-mal) Contextual features (justice) Patient preferences (autonomy) Quality of life (beneficence and non-mal) *Analogy: GP appointment - PC/PMH (medical indications), social history (contextual features), ICE (patient preferences), Management (QOL)*
73
Seedhouse's ethical grid 4 layers
Core rational Deontological layer (beneficence and non-mal) Consequential layer (increase of good) External considerations
74
Who can provide consent for a child who lacks capacity
Consent from one parent is sufficient to administer treatment as long as it is in the best interest of the child
75
Public health definition
The science and art of preventing disease, prolonging life and improving health through organised efforts of society
76
3 perspectives of a health needs assessment
1. Epidemiological 2. Comparative 3. Corporate
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3 systems of resource allocation
1. Egalitarian 2. Maximising 3. Libertarian
78
Primary prevention
**P**reventing disease from occurring in the first place e.g. vaccine
79
Secondary prevention
Early identification/**S**creening e.g. cancer screening
80
Tertiary prevention
Limit consequences/**T**reatment e.g. stroke rehab
81
**Population** approach to prevention
Shift the risk factor distribution curve e.g. dietary salt reduction through legislation to reduce blood pressure
82
**High risk** approach to prevention
Identify high risk individuals and treat them e.g. screening for BP and treating with anti-hypertensives
83
Prevention paradox
Benefit to the population often offers little impact to each participating individual e.g. most people don’t ever need a seatbelt but wearing a seatbelt saves thousands of lives
84
Pros of screening
Reproductive choice Informed decision Reassurance More effective treatment
85
Cons of screening
Exposure of well individuals to distressing or harmful diagnostic tests e.g. colonoscopies Detection and treatment of sub-clinical disease that would never have caused any problems Over treatment Difficult decisions Anxiety or false reassurance
86
UK screening programmes (11)
3 in pregnancy (sickle cell and thalassaemia, infectious disease (HIV, Hep B and syphilis), and Down’s, Edward’s and Patau’s) 3 in newborn baby (NIPE, hearing, heel prick) 5 in young people and adults - BBC (bowel 60-74, breast 50-70, cervical 25-64), Diabetic eye screening (from age 12), Abdominal aortic aneurysm (over 65 men)
87
Wilson and Jungner Criteria for a screening test
1. The condition: knowledge of the disease (important, understood, recognisable stages) 2. The screening programme (ongoing, cost balance) 3. The test (suitable test, accepted by public) 4. The treatment (accepted treatment, enough facilities, agreed policies on who to treat)
88
Sensitivity definition
The ability of a test to correctly identify patients with a disease
89
Specificity definition
The ability of a test to correctly identify people without the disease
90
Positive predictive value definition
Out of the total positive screening test **results**, who was actually positive?
91
Negative predictive value definition
Out of the total negative screening test **results**, who was actually negative?
92
Analysing screening test (2 types of bias)
Length time bias Lead time bias
93
Top of the hierarchy of evidence
Systematic reviews & meta analysis
94
Bottom of the hierarchy of evidence
Editorial reviews
95
Odds equation
Probability event occurs / probability event does not occur
96
Causes of association
Bias Confounding factors Chance Reverse causality True association
97
Epidemiology
Branch of medicine that deals with incidence, distribution and possible control of diseases
98
Incidence
Number of new cases over a certain time period
99
Prevalence
number at set point in time
100
Person-time definition
Measure of the actual ‘time at risk’ that all patients contributed to a study
101
Risk definition
The probability that an event will occur
102
Relative risk
Percentage of outcomes in one group/percentage of outcomes in another group e.g. 1/3 women getting breast cancer vs 1/833 men RR = 0.33/0.001 = 330 (women are 330 x more likely to get breast cancer than men)
103
Number needed to treat definition
The number you need to treat to **prevent one bad outcome** from happening
104
Factors that influence perceptions of risk (4)
Lack of **personal experience** with problem Belief that it is **preventable by personal action** Belief that if it has **not happened by now, its not likely to** Belief that the problem is **infrequent**
105
Transition points (6)
Leaving school Entering the workforce Becoming a parent Becoming unemployed Retirement Bereavement
106
Transtheoretical model **stages of change**
107
Principles of treating drug use
Reduce harm to user, friends and family Improve health Stabilise life Reduce crime
108
Level of alcohol dependency factors (3)
Withdrawal symptoms Tolerance Narrowing of repertoire
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Barriers to refugee health
Reluctance of GPs to register them Illiteracy Communication Lack of permanent site Mistrust of professionals
110
Malnutrition 2 groups
Under nutrition Overweight, obesity Triple = coexistence of undernutrition (stunting and wasting), micronutrient deficiencies (often termed hidden hunger), and overnutrition (overweight and obesity)
111
4 dimensions of food insecurity
Availability (affordability) of food Access - economic Utilisation Stability
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Need definition
The ability to benefit from an intervention
113
Need supply demand Venn diagram
114
Benefits of comparative health needs assessment
Quick Inexpensive
115
Evaluation of health needs assessment (2 +, 2 -)
+ improved patient care + better use of resources - data access - conflicts of interest
116
Health equity audit
Helps services reduce health inequalities by using evidence to inform service planning and investment decisions
117
Health impact assessment
Systematically assesses the potential health impacts of programmes and policies to improve decision making and help to predict future positive and negative health impacts of other projects
118
Quaternary prevention
Prevent complications from over medicalising or over treatment of a condition
119
Primordial prevention
Prevents **risk** from developing
120
Public health interventions at population vs individual vs community level examples
Population: clean air act to reduce air pollution e.g. smoking ban Individual: childhood immunisation schedule Community: creating community spaces e.g. playgrounds
121
Prevalence of no disease
Everyone who does not have the disease out of the whole population tested i.e. are we testing for a disease that is actually rare? Is it worth testing for?
122
Length time bias example
Less aggressive cancers are diagnosed more on screening tests because a patient will survive longer to participate in screening
123
Lead time bias
A patient can appear to have survived longer from a disease because their disease was identified earlier
124
Absolute risk
**Risk of developing a disease over a time period** e.g. 1 in 3 women will develop breast cancer during their lifetime
125
Reverse causation
People believe X causes Y, but actually Y causes X
126
Odds ratio
How strongly an event is associated with exposure, commonly reported for case control studies **Odds** of event in **exposed group** **/** **odds** of event in **non-exposed group**
127
Advantage of the epidemiological approach health needs assessment
Uses existing data e.g. from GPs Provides data on disease incidence, mortality etc. Can calculate services by trends over time
128
Selection bias
Systematic error in selection of study participants 1. Non-response 2. Loss to follow up 3. Differences in intervention group to control
129
Corporate health needs advantages
Based on the **felt** and **expressed** needs of the population in question Recognises the detailed knowledge of those working with the population e.g. teachers, social workers
130
Comparative health needs assessment advantages
Quick and cheap if data is available Indicates whether health or services provision is better or worse than comparable areas