Transcript Slide 1

‘Presentation top tips LSA
Trainees Prize’
Feedback from LSA Trainees Prize events
Dr P Mullen (LSA Committee)
v. Nov2012
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
LMI founded in what year?
LMI current building opened?
Historical
trivia
LMI 1739
LMI building
1837
Lecture theatre
• Last refurbished?
• Seating capacity?
Lecture theatre
• Last refurbished 1998
• Seating capacity (~120 max)
When was LSA
founded?
LSA & Trainees Prize
Jackson Rees Medal
LSA Trainees Prize
• Most recent winner/runner-up?
• Past winners?
• What sort of projects?
• Prize £ ?
Dr Clint Chevannes (1st Prize)
Dr Christine Bell (President LSA)
2012
2011
L to R:
Dr Will Lo (2nd Prize)
Dr Christine Bell (President LSA)
Dr Adie Morrison (1st Prize)
2010
2009
L to R: Dr A McDonald (1st), Prof. Jennie
Hunter (President LSA), Dr H Neary (2nd)
L to R: Prof. J Hunter (President LSA), Dr C Mollitt
(2nd), Dr C Hammell (1st), Prof R Jones (Judge)
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 L’oscopy
2011 Entries submitted
= Presentation
‘top tips’!
Free-text comments
(= ‘top tips’ for presentations)
from LSA Prize 2010 (prelims),
2011 & 2012 (Prize meetings)
(plus some example slides)
Feedback/Tips – ‘Introduction’
Introduction/Methods/Results
Interpretation/Skills
•
•
•
•
•
•
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
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 didn’t 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.
Feedback/Tips – ‘METHODS’
Introduction/Methods/Results
Interpretation/Skills
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?
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
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’?)
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 didn’t 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.
Feedback/Tips – ‘RESULTS’
Introduction/Methods/Results
Interpretation/Skills
(Often very useful to have a flow chart, outlining how arrived at population)
Meditech
n=199
+


Extras from
booking forms
n=100
Total cases found
N = 299
No booking date/time (104),

Operation cancelled (4)
n = 191
No operation date/time (30),
Booking date/time error likely
(3)

n = 158
This example = audit of time between booking of case for urgent/emergency surgery
and actual arrival into anaesthetic room, 1 month period)
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’ doesn’t cut
it!);
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, don’t 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)
D
Fair bit of data here, but essentially one main difference between the
D
?
Good pie
diagram or not?
How would you
improve it?
Too many categories, difficult
to compare
Comparison now easy. Note that if countries were listed on
the X-axis then problems reading, except for circus acts!
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)
?
?
In a 3D Pie diagram the 3-6pm slice is often falsely
perceived as larger than actually is.
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 didn’t 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
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)
• Don’t bother mentioning non significant trends (time)
• (If there are ‘outliers’ then offer an explanation)
Step 2 Hrs
Time from booking to start of anaesthetic/intervention
100
90
80
n = 107/158
70
60
50
40
30
20
10
0
Can you spot any problems or errors
here? What would be a simple
summary statement?
Mean
14.4 hrs
Step 2 Hrs
Time from booking to start of anaesthetic/intervention
100
90
80
(Mean
14.4 hrs)
n = 107/158
70
60
The wrong
‘average’ to
use here!
50
40
30
20
10
0
Skewed data. In this e.g. the *
symbol = outliers, i.e. beyond
Q3 + 1.5(IQR); the mean is not
resistant to outliers whilst the
median is.

Median 6.2 (IQR 2.8 – 20.4) hours
‘Most interventions began within 24 hours’
Comparative boxplots are often an excellent way of
getting summary data across quickly and effectively,
comparing 2 or more groups.
e.g.
Time from booking to start of anaesthetic/intervention
70
60
(*p = 0.0006)
Hours
50
40
30
20
10
0
1
GenSurg
2
Ortho
3
Plastics
Speciality
* Mann-Whitney, 2 sided, alpha = 0.05
RESULTS
Data quality (validation), data analysis, effort,
correct stats
• Colour scheme for slides could be better
• Not sure of the matching/confounding factors
• (Limitations)
What do you think of this graph? Good and bad points = ?
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
hat it is a ‘screenshot’, obtainable from the ‘prt sc’ of your laptop, which has been then pasted).
Feedback/Tips – ‘Interpretation’
Introduction/Methods/Results
Interpretation/Skills
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.
In theatre ….
Step 5: Surgical Time
6
5
Hours
4
3
2
1
0
Median:
IQR:
Range:
0.7 hours
0.5 - 1.3
[0.1 - 5.5]
In theatre ….
Step 5: Surgical Time
6
5
Hours
4
3
2
1
0
Median:
IQR:
Range:
0.7 hours
0.5 - 1.3
[0.1 - 5.5]
Majority of surgical
interventions were
completed quickly in theatre
INTERPRETATION
(Conclusions, Recommendations, action plan)
• Interesting subject but didn’t 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
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
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)
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
Feedback/Tips – ‘SKILLS’
Introduction/Methods/Results
Interpretation/Skills
Know your venue
Know your venue/audience
Features
•
•
•
•
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•
•
•
•
Moderate size
Unfamiliar
Formal
Colours iffy
Font size >/=20
PA system
No roving mike
Many retired
Much experience
of research
• Features of this venue?
• Features of this venue?
Features
•
•
•
•
•
•
•
Small/cozy
Intimate
Familiar
Smaller font ok
Hot/sleepy
Interactive
Just after
Wednesday
Chester cake club!
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’
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.
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!
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!
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
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!]
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
• Didn’t deal with questions very well; unconvincing
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; didn’t do so well with question of why (Mg) not
licensed; good knowledge of all papers
LSA Prize Feedback
Main points/Summary
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
The gold standard?
What needs changing on this, if anything?
?
Comments/questions to [email protected]
This presentation will be made available to the members of the
Mersey Post FRCA group, and will be also available on the LSA
site www.lsoa.org.uk
Next LSA trainees prize event = Friday 22nd February 2013