Critical Appriaisal Skills Basic 1 | May 4th 2011
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NHS Education Scotland Produced in collaboration with the Association of Scottish Medicines Information Pharmacists Group
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Critical Appriaisal Skills Basic 1 | May 4th 2011
- 8. Expert opinion/ clinical experience from respected sources Case series then Case reports Cross sectional surveys Case control studies Cohort studies RCTs Systematic reviews Meta-analyses Hierarchy of evidence
- 29. Estimation Statistics Help assess “usefulness of the trial” by determining clinical importance and magnitude of the benefit by using data to estimate a range of probable values for the population.
- 30. Example study 96 1128 Control Group (Received Placebo) 845 2073 Intervention Group (Received Drug X) Pain free within 2 hours Total Number of patients in each group Group
Editor's Notes
- Today we are going to concentrate on appraising the RCT.
- Research starts with 1 of 2 hypothesis to be tested
- Say before starting on slide contents: Having explained what ‘p’ is in isolation, we should consider its application to research papers. When making a statement that a difference has been found between the experimental group and the control group in a study, the ‘p’ value that follows is …… Say after finished with slide contents: So if the statement appears Drug A lowers BP more than Drug B, it means “ we think Drug A lowers BP more than Drug B but there is still a 1 in 20 chance we are wrong.
- The smaller the effect we are trying to measure the more subjects/observations we need in the sample The we set the level of significance, the larger the sample we need to detect an event of a given size
- Type 1 & Type 2 errors – probability of occurrence decreases as sample size increases Type 2 Error sometimes used by unscrupulous drug companies when marketing ‘me too’ drugs and making comparison to the market leader- using a smaller number of patients in each group is unlikely to show a ‘statistically’ difference between the two medications.
- When a study is carried out in a particular population, for practicality purposes only a sample from this population can be chosen. Different types of sampling techniques used (e.g. random, quota, stratified, etc) to try to ensure that the sample selected is representative of the population being studied. However, do not know if the sample represents the population. If poor sampling then variation may arise. Hence, means of estimating the representativeness of the population is required
- It is neither standard nor does it represent error! To understand its correct usage lets imagine: Take a sample of people from a large population -> measure particular parameter and take the mean. Then replace the sample and repeat the process. After measuring many you would have a collection of the means, which when plotted would produce a normal distribution. The mean of these means would then be the ‘true population mean’ and the standard deviation of these means is the famous ‘Standard Error of the Means’
- Relating percentages to clinical practice is difficult NNT is easier to understand and apply. Example = Therefore, 14 patients must be treated with drug X to prevent one death at five years.