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PP5 Lectures (Bal) > Application of Evidence-Based Medicine > Flashcards

Application of Evidence-Based Medicine Flashcards

1
Q

What is EBM?

A

Evidence based practice (EBP) is the integration of clinical expertise, patient values, and the best evidence into the decision making process for patient care.

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2
Q

What is filtered information?

A

Provide an appraisal of the quality of the studies and make recommendations for practice

  • summarise and analysis of evidence based on primary resources
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3
Q

What is unfiltered information?

A

Primary sources

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4
Q

What is the proposed new evidence-based medicine pyramid?

A

use systematic reviews/meta analysis as a lens for the things below it

  • consume and apply evidence from research into practice
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5
Q

What are the FIVE steps of intergrating EBM to practise?

A
  1. Form an answerable question
  2. Find the best evidence
  3. Critically evaluate the evidence
  4. Individualise response, based on professional expertise and patient concern
  5. Evaluate your own performance

In simpler terms, ask + acquire + appraise + apply + act

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6
Q

Why does EBM matter to pharmacists?

A

Competency Standards for Pharmacists in Australia 2016

  • Standard 5.3: Research, synthesise and integrate evidence into practice
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7
Q

Whats wrong with only using journals with a high impact factor?

A

Impact Factor rankings may be misleading

  • Impact factor indicates the average number of citations that each published article has received in the last year (for a given journal) (average is calculated based on the preceding 2 years)

Impact factor is a measure of INFLUENCE, not quality!

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8
Q

We are (currently) poorly equipped to tell good from bad research, how so?

A

detection rates:

  • Poor Randomisation methods (by name or day)
  • Not intention-to-treat analysis
  • Poor response rate -
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9
Q

for critical evaluation, how to interpret study results?

A

What are the RESULTS? „

Are the results VALID? „

Are results RELIABLE?

Are the results USEFUL?

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10
Q

What are the type of results?

A

Dichotomous variables

  • Yes/ no
  • Alive/ dead
  • Pain/ no pain

Continuous variables

  • Age
  • Hair length

Terminology

  • Control group
  • Treatment or Intervention group

Descriptive:

  • Describe the population studied –> age range, gender
  • Cannot be generalized to any larger group

Inferential:

  • Make predictions or inferences about a population from observations and analyses of a sample
  • Sample must be representative of the larger population that it represents
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11
Q

How to know if results valid?

A

Were participants treated the same at the:

  • start
  • during and
  • end of the study
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12
Q

What are some considerations when doing EBM research?

A
  • Randomisation
  • Concealment and blinding
  • Intention to treat analysis
  • Baseline risk
  • Confounding
  • Looking at population subsets
  • Type of outcomes
  • Lost to follow-up
  • Placebo effects
  • Other factors
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13
Q

How to see if results reliable?

A

Confidence intervals

  • Measure of reliability
  • Range of possible results, within which the true result should be
  • Narrower the range, the better reliability

95% CI levels = 95% sure that true result lies within the ground

> difference in means that has 95% CI includes 0 = no difference between groups

> includes value of 1 in the range = no difference between groups

Standard deviation

  • Measures how much individual scores of a given group vary from the average (mean) score of the whole group
  • Measures the spread of the individual results around the average of all the results
  • High standard deviation: data widely spread i.e. less reliable
  • Low standard deviation: data clustered close to the mean i.e. more reliable
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14
Q

How to see if the results are useful?

A

Consider clinical importance & size of benefit

clinical importance

consider the outcome measured

  • disease-orientated outcome (DOO)
  • patient-orientated outcome (POO)

size of benefit

  • absolute risk reduction (ARR)
  • relative risk (RR) and hazard ratio (HR)
  • relative risk reduction (RRR)
  • number needed to treat (NNT)
  • number needed to harm (NNH)
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15
Q

What large benefits are we looking for?

A
  • No single epidemiological study is persuasive by itself unless the lower limit of its 95% confidence level falls above a threefold (200%) increased risk
  • As a general rule of thumb, we are looking for a relative risk of 3 or more (>200% increased risk) [before accepting a paper for publication
  • My basic rule is if the relative risk isn’t at least 3 or 4 [200 – 300% increased risk], forget it.
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16
Q

How to know if results are useful

A

P value

  • Probability that a difference will be observed between 2 interventions, when there is actually no difference between them
  • measured on scale 0 to 1 (0 = impossible and 1 = certain to happen)

Convention: p<0.05 regarded as statistically significant

Statistical significance ≠ Clinical significance

> Small differences between groups within a study may approach statistical significance, particularly if the population sizes are large

> but, the difference may not be clinically meaningful

17
Q

How can i apply the results to my patients care?

A

Were the study patients similar to my patient? „

Were all clinically important outcomes considered? „

Are likely treatment benefits worth the potential harm and costs?

18
Q

How to know if study patients similar to my patient?

A
  • Inclusion/ exclusion criteria

> limitations

  • Treatments are not uniformly effective in every patient
  • Trials estimate average treatment effects
19
Q

What if my patient does not fit the study inclusion/exclusion criteria?

A

> look at the criteria your patient did not satisfy

> would that affect the outcome or applicability of the results to your patient

Consider

  • Studies in specific genders, ethnic or socio-economic groups
  • Age groups
  • Disease severity
  • Co-morbidities
20
Q

what questions to ask self if it is a good study?

A
  • What if I do nothing? „
  • What other options are there? „
  • Compare the benefits and harms of all options „
  • Do I have enough information to decide? (… any other studies)
21
Q

What is absolute risk (AR)?

A

Chance an outcome will happen

> simplest measure of association

> AR of XXX = 6% risk of suffering an MI with XXX

> AR placebo = 8% risk of suffering an MI with placebo

22
Q

What is absolute risk reduction (ARR)?

A

Difference in proportion of participants who had outcome in control compared with treatment group

> XXX reduces the absolute risk of an MI by 2%

23
Q

What is relative risk?

A

Relative likelihood

> RR is less than 1.0, we can say that XXX has made the risk of an MI less likely (3/4) compared with placebo

24
Q

What is hazard ratio (HR)?

A

CI for this not including 1 = difference = statistically significant

HR = 1 –> probability of events in two groups is the same

HR > 1 or <1 = relative probability of an event is greater in one of the two groups

  • Similar to relative risk
  • Probability of an event in 2 groups over time
  • Useful when risk changes over time
  • Weighted for number of participants at different time points

e.g HR of 1.31 = 31% increased risk for people take ACEI.

25
Q

What is relative risk reduction (RRR)?

A

Estimates the proportion of baseline risk that is removed by the therapy

> treatment with XXX decreases the risk of MI by 25%

26
Q

What is Odds ratio (OR)?

A
  • Odds that an outcome will occur with a particular exposure, compared with the odds of the outcome occuring in the abscence of that exposure

OR = 1 –> exposure does not affect odds of outcome -

OR > 1. Exposure associated with higher odds of outcome

OR < 1 Exposure associated with lower odds of outcome

i.e. odds of an MI in patients receiving XXX was approx 3/4 of that seen in patients receiving placebo

27
Q

what is the line of unity in OR, RR and RRR?

> watch this again in lecture

A

OR, RR = 1

RRR= 0

no difference in outcome between intervention and contol groups

28
Q

what is number needed to treat (NNT)?

A

Number of patients that needs to be treated with intervention to produce one positive outcome

> NNT are usually rounded up

> 1/0.02 = 50, 50 patients need to be treated with XXX to prevent one MI

29
Q

Number needed to harm (NNH)

A

Number of patients that we would need to treat with intervention to produce one negative outcome

> NNH are usually rounded down = AE of medicines = worse case scenaio

> calculate aboslute risk increase (ARI) then do 1/ARI = e.g. 1/0.04 = 25 .25 patients would need to be treated with XXX for 1 person to suffer a psychotic event.

PP5 Lectures (Bal) (19 decks)

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