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Presentation top tips LSA Trainees Prize Feedback from LSA Trainees Prize events Dr P Mullen (LSA Committee) v. Nov2012.

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Presentation on theme: "Presentation top tips LSA Trainees Prize Feedback from LSA Trainees Prize events Dr P Mullen (LSA Committee) v. Nov2012."— Presentation transcript:

1 Presentation top tips LSA Trainees Prize Feedback from LSA Trainees Prize events Dr P Mullen (LSA Committee) v. Nov2012

2 Background In 2011, for the first time the audience voted the winner and runner up at the annual LSA Trainees Prize event. Free text feedback from the audience formed part of the process This presentation is (mostly) based on feedback from the 2011 & 2012 Trainees Prize events, and may inform trainees generally about pointers towards a quality presentation

3 LMI founded in what year? LMI current building opened?

4 Historical trivia LMI 1739 LMI building 1837

5 Lecture theatre Last refurbished? Seating capacity?

6 Lecture theatre Last refurbished 1998 Seating capacity (~120 max) When was LSA founded?

7

8

9 LSA & Trainees Prize

10 Jackson Rees Medal

11 LSA Trainees Prize Most recent winner/runner-up? Past winners? What sort of projects? Prize £ ?

12 2012 Dr Clint Chevannes (1st Prize) Dr Christine Bell (President LSA) 2011 L to R: Dr Will Lo (2 nd Prize) Dr Christine Bell (President LSA) Dr Adie Morrison (1st Prize) L to R: Prof. J Hunter (President LSA), Dr C Mollitt (2 nd ), Dr C Hammell (1 st ), Prof R Jones (Judge) L to R: Dr A McDonald (1 st ), Prof. Jennie Hunter (President LSA), Dr H Neary (2 nd )

13

14 Previous LSA winning projects Fast ROTEM evaluation in major obstetric hemorrhage (2012) Intra-thecal magnesium meta-analysis (2011) Spinal vs iv diamorphine for spinal surgery Intra-thecal diamorphine for THR Survey of patient satisfaction with GA Evaluation of new airway device for Loscopy

15 2011 Entries submitted

16 = Presentation top tips!

17 Free-text comments (= top tips for presentations) from LSA Prize 2010 (prelims), 2011 & 2012 (Prize meetings) (plus some example slides)

18 Introduction/Methods/Results Interpretation/Skills Feedback/Tips – Introduction

19 INTRODUCTION (background/clinical importance/aims/objectives) No background slides Too long introduction. Very relevant to current practice and well presented What is the incidence of e.g. pre-op hypothermia and post –op hypothermia? How big are these problems? Literature overview slide would have been better at the start in Introduction section rather than later on Excellent overview & background, lacking only in references

20 INTRODUCTION (background/clinical importance/aims/objectives) Good clinical relevance and good to see critical care network guidelines developed as a result. Excellent background knowledge No relationship (relevance) to (my) practice Too many assumptions that assembled audience familiar with subject (e.g.CPX testing) (many retired members of LSA probably not) We didnt need an explanation of how to do a meta-analysis but would have liked to see more results, e.g. how long the block was delayed etc.

21 Feedback/Tips – METHODS Introduction/Methods/Results Interpretation/Skills

22 METHODS (Quality of the design, effort required by the individual e.g. in data collection) Need to tell us how much of the work he/she did Effort required in data collection by the individual was low because it was a survey Data quality likely to be very subjective Ethically very very shaky – should have sought ethics committee advice at least. Very serious concerns over ethics. I disagree about the No need for ethical approval Ethical approval? Was consent sought? Was any (informal) advice sought from ethics committee members even?

23 METHODS (Quality of the design, effort required by the individual e.g. in data collection) I have not got a clear idea what the study aims were Survey, not audit A lot of work, ?usefulness Small sample size, appears large amount of effort How valid is Parklands formula? – reference? - the audit standard hinged around this validity. How valid is the rule of thumb regarding mortality prediction (in burns patients)? Supporting references? Data quality poor How was weight estimated? – potentially large errors Too much data, in search of a missing link

24 METHODS (Quality of the design, effort required by the individual e.g. in data collection) Large study although unclear how much done by presenter How much analysis did presenter do himself? Why no data on elective/urgent surgery? Surely surgical experience is of relevance? Did those with a previous LSCS need more blood transfusion than primips? Project (a meta-analysis) results hinged mainly on data pick-up from e-search – what steps were taken to check validity - that some papers were not missed (3 key words were used for searching – was any attempt made to use different but similar key words, e.g. patient instead of human?)

25 METHODS (Quality of the design, effort required by the individual e.g. in data collection) Choice of statistic analyses not correct Good explanation of stats I didnt understand propensity scoring (despite long explanation; did I really need to understand it?) If you use a statistical method that a substantial part of your audience is likely to be unfamiliar with then explain briefly (1 minute rather than 3-4 minutes of a 10 minute presentation); e.g. propensity scoring Use of integers for LOS data not explained, otherwise excellent.

26 Feedback/Tips – RESULTS Introduction/Methods/Results Interpretation/Skills

27 Total cases found N = 299 n = 191 n = 158 Meditech n=199 Extras from booking forms n=100 No booking date/time (104), Operation cancelled (4) No operation date/time (30), Booking date/time error likely (3) + (Often very useful to have a flow chart, outlining how arrived at population) This example = audit of time between booking of case for urgent/emergency surgery and actual arrival into anaesthetic room, 1 month period)

28 RESULTS (Data quality – e.g. validation – and data analysis; + effort, correct stats) Presentation of numerical data Use appropriate number of decimal places e.g. 2.1 days not 2.12 days, Hb 12.1 not 10.92; be consistent with number of decimal places within data domains (e.g. avoid LOS Control Group = 2.1 days, Treatment Group = 2.15 days) Avoid expressing continuous data as discrete data (e.g. 2 days) unless obvious difference between the results (2 days versus 13 days) Indicate which average was used (mean, median, mode, are all averages) Indicate which statistical tests were used (I used Excel doesnt cut it!);

29 RESULTS (Data quality – e.g. validation – and data analysis; + effort, correct stats) Presentation of tabular data If using busy tables then colour fill the rows that you wish to draw attention to (using a side arrow partly does this but it can be difficult to follow the row of data across in the table that is quite busy); Avoid moving rapidly thro busy tables, without using the above device; Comparing data from 2 groups, dont just use mean of each group and the difference between the means - include spread of data (IQR, SD) as well as central location (median, mean)

30 Fair bit of data here, but essentially one main difference between the 2 results columns – can you spot it? D

31 D

32 ? Good pie diagram or not? How would you improve it?

33 Too many categories, difficult to compare

34 Comparison now easy. Note that if countries were listed on the X-axis then problems reading, except for circus acts!

35 RESULTS Data quality (validation), data analysis, effort, correct stats Presentation of graphical data Quite busy graphs Results too condensed Exploded pi-diagram: avoid white segmnt on white b/ground Use the pointer to draw attention to key point(s) Busy not easy intelligible graphs Percentages on Y axis may be better than absolute numbers Too many groups for a pie chart (try horizonthal bar chart)

36 ? ?

37 In a 3D Pie diagram the 3-6pm slice is often falsely perceived as larger than actually is.

38 RESULTS Data quality (validation), data analysis, effort, correct stats Presentation of graphical data No graphs regarding range/spread presented (e.g. IQR, SD) Was mean the correct average to use? Some box and whisker plots would have been nice Displaying some of the results in a table would have been better. The vertical bar charts didnt quite work – using horizontal bar chart would have made it easier to read the text. Avoid using 28.00% on X-axis Pie charts not clear (light blue vs grey!) - very difficult to interpret/separate out groups Best to avoid blue against blue bar chart comparisons (use a different contrasting colour) Avoid graphs with same coloured lines

39 RESULTS Data quality (validation), data analysis, effort, correct stats Lean on statistics (e.g. mean used a lot, no indication of spread of data so this may have been the wrong average to use) Dont bother mentioning non significant trends (time) (If there are outliers then offer an explanation)

40 Mean 14.4 hrs n = 107/158 Can you spot any problems or errors here? What would be a simple summary statement?

41 Median 6.2 (IQR 2.8 – 20.4) hours (Mean 14.4 hrs) Most interventions began within 24 hours n = 107/158 The wrong average to use here! Skewed data. In this e.g. the * symbol = outliers, i.e. beyond Q (IQR); the mean is not resistant to outliers whilst the median is.

42 Comparative boxplots are often an excellent way of getting summary data across quickly and effectively, comparing 2 or more groups.

43 GenSurg Ortho Plastics (*p = ) * Mann-Whitney, 2 sided, alpha = 0.05 e.g.

44 RESULTS Data quality (validation), data analysis, effort, correct stats Colour scheme for slides could be better Not sure of the matching/confounding factors (Limitations)

45 What do you think of this graph? Good and bad points = ?

46 Fantastic graph! Text a little small perhaps, but colours, trends, absolute numbers, etc have all been combined into 1 results slide. This is clearly a slide to dwell on in a presentation. (Note: in this instance part of the reason for the small text is that it is a screenshot, obtainable from the prt sc of your laptop, which has been then pasted).

47 Feedback/Tips – Interpretation Introduction/Methods/Results Interpretation/Skills

48 In theatre …. Median:0.7 hours IQR: Range:[ ] A scatterplot, showing raw data points can be a useful graph. But what is a simple summary/interpretation of this data? Summaries should not repeat data %s etc. Lead on to conclusions.

49 In theatre …. Median:0.7 hours IQR: Range:[ ] Majority of surgical interventions were completed quickly in theatre

50 INTERPRETATION (Conclusions, Recommendations, action plan) Interesting subject but didnt seem to come to any conclusions Slides (as presenter actually alluded to) were cluttered and unclear with no conclusions or recommendations. No definite conclusion to study Good presentation and plenty of material and information, but need to tell us: how much LA used in each technique, need to highlight difference between statistical significance vs clinical importance; these results could provide basis for number needed to treat to aid statistical significance in future prospective study More diagrams and focusing on the main messages in results would have been better

51 INTERPRETATION (Conclusions, Recommendations, action plan) Good subject …good material, I think one of the main messages he did not bring forward was to stress the fact that "Rehearsal" of the Guideline is essential for future adherence to it Less introduction, more results and conclusion please Avoid 1 patient ruined my data comments If the study data showed a reduced LOS in the study group then it is not reasonable to say that this was due to earlier mobilisation (unless the mobilisation variable was also assessed and correlated accordingly with the LOS data). It may have been due to earlier mobilisation, but we have no data on this would be more accurate When making summary comments, make sure your they accurately reflect the project results; if based on previous publication, then reference this

52 INTERPRETATION (Conclusions, Recommendations, action plan) Interesting topic but struggled to find relevance to my practice Did not adequately explain relevance to most anaesthetists Some of the recommendations were not directly as a result of the audit Many recommendations at end – not clear on what these were based, many seemed not based on the data presented; a slide re limitations of the audit would have been useful Composite end points have their limitations so draw attention to these (i.e. show insight)

53 INTERPRETATION (Conclusions, Recommendations, action plan) More diagrams and focusing on the main messages in results would have been better Unclear conclusions with too much information

54 Feedback/Tips – SKILLS Introduction/Methods/Results Interpretation/Skills

55 Know your venue

56 Features Know your venue/audience Moderate size Unfamiliar Formal Colours iffy Font size >/=20 PA system No roving mike Many retired Much experience of research

57 Features of this venue?

58 Features Features of this venue? Small/cozy Intimate Familiar Smaller font ok Hot/sleepy Interactive Just after Wednesday Chester cake club!

59 SKILLS (quality of the presentation oral/visual, handling of Q/A from audience) Pre-event advice from a previous adjudicator: (General) Speak up, steady pace not too slow or too fast, acquaint yourself to all tools you are going to use on the night, use pointers, look at audience and your slides, if using busy slides apologise about but only point out the salient information in the slide, if co-authored paper try to point to the audience how much work you have done yourself

60 SKILLS (quality of the presentation oral/visual, handling of Q/A from audience) Voice Good presentation but was hurried, … Too quiet Project your voice Good subject, plenty of material but very slow, low voice, slides are too busy Good punchy presentation. Good manner of speech, not rushed.

61 SKILLS (quality of the presentation oral/visual, handling of Q/A from audience) Slides Slides a bit too busy in places and needs to look at audience more than the screen. Avoid looking back at the screen too much, but rather address the audience Clear delineation of Method, Result, Discussion not done Nice tables and stats; a little quick through the slides (too many of these) Nice LWH logo slides!

62 SKILLS (quality of the presentation oral/visual, handling of Q/A from audience) Props Great speaker. Good use of audiovisual props Having a video running at the same time (on a different screen) is very distracting and not a good idea Need to point to slides for areas of interest Use the pointer!

63 SKILLS (quality of the presentation oral/visual, handling of Q/A from audience) Great presentation, clear not rushed. Covered aims, methods results and conclusions. Confident presentation Handled quite well, good time keeping but seemed a bit rushed. Liked the extra slides at the end to cover (potential) questions Too fast

64 SKILLS (quality of the presentation oral/visual, handling of Q/A from audience) Poor time keeping - STICK TO TIME! The content of the slide on view should reflect/coincide with the content of what the speaker is saying Too many slides; too many crowded busy slides; pushed to stay within time limit Heading of slides is difficult to read - improved by better choice of colour scheme [not faint blue text against white background!]

65 SKILLS (quality of the presentation oral/visual, handling of Q/A from audience) Q&A Sufficient time to any individual slide – if going to run over then exclude some slides for oral presentation and keep them in reserve slides for Q&A use Avoid talking over the person asking the question. Allow him/her to finish the Q. Good knowledge of subject ; answered questions well Some answers plainly incorrect Excellent handling of audience questions. Clear concise PowerPoint slides Didnt deal with questions very well; unconvincing

66 SKILLS (quality of the presentation oral/visual, handling of Q/A from audience) Q&A Nicely presented. Not a lot of data. Did not cope that well with questions Slides too fast. Muddled answers to some questions. Not prepared for the questions being asked. Needs to be a little more anticipating of issues likely to be raised Clear introduction of meta-analysis and explanation of results; didnt do so well with question of why (Mg) not licensed; good knowledge of all papers

67 LSA Prize Feedback Main points/Summary

68 Summary Clinical relevance Know your subject Know your venue and props Know the score-sheet/system Concise and clear slides/presentation Q/A tricks & tips

69 The gold standard?

70 What needs changing on this, if anything?

71 ? This presentation will be made available to the members of the Mersey Post FRCA group, and will be also available on the LSA site Next LSA trainees prize event = Friday 22 nd February 2013 Comments/questions to


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