WST PhD presentation for PenTAG 17may11

Will Stahl-Timmins

17th May 2011

Information Graphics in

Health Technology Assessment

Information Graphics

maximumvalue

minimumvalue

upperquartile

median

lowerquartile

PhD research intro

A journey

My PhD (so far)

Opportunities

Scientific

Evidence

Medical

Practice

Health Policy

HTA

EBM

Virtual presentations of information, which use graphical elements (eg position, colour, size, etc) to present scientific evidence, informing health policy-making in terms of recommendations for

the adoption of specific health interventions.

Information Graphics in


How should information graphics be designed, produced and used in health technology

assessment?

Research Question

NICE interviews

TAR review

Design & critique

SOC test

COGS test

Methodsstudy

Methodsstudy

NICE interviews

Design & critique

SOC test

COGS test

TAR review

TAR review

• 50 of 98 NICE TAR reports reviewed

• dated Oct 2003 - Nov 2007

• content analysis

• graphics categorised

• 965 graphics used


• graphics in every report but one



• 0.20 graphics per page




• 0.58 tables per page




• 0.58 tables per page

1.0

0.8

0.6

0.4

0.2

0GRAPHICS

PER PAGETABLESPER PAGE

TIME

SER

IES

102

CEAC

124

THRE

SHOL

D AN

ALYS

IS

37

OTHE

R

38

STAT

E TR

ANSI

TION

78

DECI

SON

TREE

41

OTHE

R

5

BAR

CHAR

T

88

SCAT

TER

PLOT

55

OTHE

R

44

FORE

ST P

LOT

331

OTHE

R

22

OTHER

AREA/POSITION

FLOW

LINE

124

301

187

353

AREA/POSITION

LINE

FLOW

OTHER

TIME SERIES

CEAC

THRESHOLD

OTHER

STATE TRANSITION

DECISION TREE

OTHER

BAR CHART

SCATTER PLOT

OTHER

FOREST PLOT

OTHER

INTRO/BACKG.

SYSTEM.REVIEWMETHODS

SYSTEM.REVIEWRESULTS

MODELREVIEWS

MODELMETHODS

MODELRESULTS

CONC. APPEN-DICES

10

10

3

3

3

5

6

6

1

1

1

5

8

5

8

8

31

1 1

1 11

11

1

14

4

2

20

25

2

2

2 2 2

2

2

2

10

30

8

10

16

4

4

41

1

9

2

2

2

1

1

2

14

7

5040302010

ALL CALCULATIONS FOR CIRCLE SIZES ARE AREA-BASED. SO,

A CIRCLE REPRESENTING 50 REPORTS HAS A DIAMETER OF 10mm,

AND AN AREA OF 7.9mm2. A CIRCLE REPRESENTING 25 REPORTS

HAS AN AREA OF 3.9mm2 AND A DIAMETER OF 7.1mm.

USED IN NICE-COMMISSIONED TECHNOLOGY ASSESSMENT REPORTS, 2003-2007

CIRCLES REPRESENT THE NUMBER OF REPORTS THAT USED A TYPE OF GRAPHIC AT LEAST ONCE, BY REPORT SECTION

TAR review

Design & critique

SOC test

COGS test

Methodsstudy

NICE interviews

NICE technical advisorstelephone interviews - needs assessment

• 5 interviews

• ~30 minutes

• gist transcribed

• framework analysis

• Looking for instances of:- complexity (Remus, 1984; 1987)

- summary/overview needed (Tufte 2001)

- comparison needed (Spence 2007)

- time limited (Resnikoff, 1989)

- selective focussing needed (Thomas, 2005)






“It’s difficult - because it depends on the individual appraisal”

Some things were thought to lead to complex data included:

- Multiple outcome measures

- Many subgroups

- Sequential treatments

- Mixed treatment comparisons

- Many variables in SA

- Many disease states in model






“In terms of [presenting a large] quantity of information, then the problem is usually with the clinical effectiveness, and summarising that.”

Data must be split over several pages, or slides.

Also sensitivity analysis of models mentioned.





- selective focussing needed (Thomas, 2005)The most commonly mentioned type of data that needed to be compared to another was the ICER, the overall measure of the cost-effectiveness of an intervention.

One interviewee noticed that it was frequently necessary in committee meetings to “flip backwards and forwards” between slides when questions were asked about the certainty of evidence.






When asked if time was limited (in any part of the appraisal process), interviewees responded:

“Time is always limited”

or

“Yes, is the short answer!”

All five interviewees stated that time was always limited for decision-makers to familiarise themselves with the necessary information before an appraisal committee.






Most interviewees seemed very uncomfortable about the idea.

“it’s really not fair, on- it’s not right to give some of them extra detail.”

NICE interviews

TAR review

SOC test

COGS test

Methodsstudy

Design & critique

10 information graphics

The Friday Information Graphic

Peninsula Technology Assessment Group

www.pms.ac.uk/pentag

Noy Scott HouseBarrack Road

Exeter EX2 5DW

Information Graphics in Health Technology Assessment

www.pms.ac.uk/infographics

Will [email protected]+44 (0) 1392 406 967 1

16th Oct 2009

Link diagrams for showingconnections between search

strategies in multiple systematic reviews

1. Small multiple techniques including Sankey diagrams for overview of studies in a systematic review

2. Two-way sensitivity analysis matrix / bubble chart

3. Parallel coordinates for probabilistic sensitivity analysis

4. Technology assessment report graphical overview

5. Sankey Markov overview

6. ‘Whirlpool’ display for enhancing tornado diagram in deterministic sensitivity analysis

7. Survival synthesis bubble chart

8. Distribution-based forest plot

9. Search strategy link diagram

10. Individual patient display for discrete event simulation

Evaluation?

NICE interviews

TAR review

Design & critique

SOC test

COGS test

Methodsstudy

graphical presentationnumerical presentation

online decision task study

gradually increasing decision complexity (subgroups)

measurements: decision accuracy, time & preference

measurements test (experiment)

sample: generalinternet-usingpublic - respondent-driven sample

http://www.pms.ac.uk/infographics/















seed 1

seed 2

seed 3

25+ participants...






single group males and females low, medium, high riskmales and females

increasing complexity

measurements test (findings)


Study Duration: 36 days (15th June - 21st July 2009)



244 entries were recorded during this time.




48 excluded as possible duplicates, leaving 196 for the analysis




48 excluded as possible duplicates, leaving 196 for the analysis

99 participants received the graphical presentation first. 97 received the numerical one first.

did notcomplete

task 1 (N=19)

did not completetask 2 (N=7)


did not completedetails collection

(N=6)



did not give preference (N=2)

did notcompletetask 1 (N=22)



did not completedetails collection(N=2)




did not give preference (N=5)

Detailscollection

Task 1

Task 2

Task 3

Task 4

Task 5

Task 6

Preferencecollection

38 people gave apreference for thenumerical display

43 people gave apreference for thegraphical display

25 people liked the displays

equally

Numerical first (N=97) Graphical first (N=99)

Randomised to receive:

Y1 Y2 Y3 Y4 Y5 Y6

Average Deaths (mean)Numerical - Graphical group

Graphical - Numerical group

Min. Possible Deaths 50745015

Max. Possible Deaths 7224 7224

4748

7224

5920

7787

5466

7787

5114

7787

N=78N=77

N=71N=70

N=69N=67

N=65N=54

N=63N=54

N=61N=52

mean (g-n group)

95% confidence

mean (n-g group)

95% confidence

Y1 Y2 Y3 Y4 Y5 Y6

Average Times (mean)Numerical - Graphical

Graphical - Numerical

N=78N=77

N=71N=70

N=69N=67

N=65N=54

N=63N=54

N=61N=52

0 seconds

200 seconds

mean (n-g group)

95% confidence

mean (g-n group)

95% confidence

NumericalPreference

Undecided GraphicalPreference

0secs

gra

ph.

tas

k

num

. tas

k

gra

ph.

tas

k

num

. tas

k

gra

ph.

tas

k

num

. tas

k

20mins

rs = .484

p < 0.05

Y1 Y2 Y3 Y4 Y5 Y6



N=78N=77

N=71N=70

N=69N=67

N=65N=54

N=63N=54

N=61N=52

0 seconds

200 seconds

mean (n-g group)

95% confidence

mean (g-n group)

95% confidence


Y1 Y2 Y3 Y4 Y5 Y6



N=78N=77

N=71N=70

N=69N=67

N=65N=54

N=63N=54

N=61N=52

0 seconds

200 seconds

mean (n-g group)

95% confidence

mean (g-n group)

95% confidence


“in this case, i think the graphical plus the numerical makes for more confustion. one or the other is sufficient”

“[the graphical presentation]seemed more confusing - too manty differnt elements to look at - visual noise”

“I found the screen cluttered.”

NICE interviews

TAR review

Design & critique

SOC test

Methodsstudy

COGS test

COGS (Clinical effectiveness Overview Graphical Summary

Task-based cognitive interviewing

Speak-aloud protocol

9 expert users (HTA systematic reviewers)

Randomised, sequencial comparison to report

Quantitative results (time and accuracy)

Qualitative results (actions and words of participants - framework analysis)

COGS test

TASK

1reportgivenfirst

graphicgivenfirst

TASK

2TASK

3TASK

4

TASK

5TASK

6TASK

7TASK

8TASK

1TASK

2TASK

3TASK

4

TASK

5TASK

6TASK

7TASK

8TASK

9TASK

10TASK

11TASK

12

Randomised, crossover design

12 tasks

1 4 5 8 9 2 3 6 7

24.1%

6.9%9.3%

17.9%

12.0%13.5% 12.3%

16.4% 17.0%

COGS display report section

Task 4: Can you tell me about selection bias in the Peters et al. (2007) trial please?

Task 8: Of the unilateral cochlear implants vs non-technological support trials, which reported at least one significant outcome measure, and which measures were these?

1 4 5 8 9 2 3 6 7

15.0%

18.2%

13.3%15.1%

32.4%

5.4% 6.3%7.9%

5.1%

COGS displayreport section

!"#$%&'()*

+&,-.*,/0.*12&!"#$%#&$&'(#&')*#&+,-.

345

675

645

75

45

/00$0#1'0)2#34"#56

two-sample t(69) = 4.4

p < 0.001

task accuracy

COGS: 74.3%

report: 46.4%

c2 (1, N = 63) = 5.12, p = 0.024

Those given COGS first took a mean of 99.5% of their COGS task time with the report.

Those given the report first took a mean of 268.5% of their COGS task time with the report.

two-sample t(7) = 4.0, p = 0.005

Those given COGS first took a mean of 99.5% of their COGS task time with the report.

Those given the report first took a mean of 268.5% of their COGS task time with the report.

two-sample t(7) = 4.0, p = 0.005

Interview 8:

“I would say I got much more of an overview, just from looking at that graphical summary”

Interview 3:

(pointing to graphic)

“This really helps to have all of those elements brought together, so you can get a more holistic view of where is it from and how big is it, what’s the study design.”

Interview 1:

“I speculate that I would have had a much, much less detailed idea of the quality of the evidence if I’d been confronted with that [the report] first.”

familiar-isation 1

display 1display 1

task 1

task 2

task 3

task 4

generalreliability 1

familiar-isation 2

display 2

task 5

task 6

task 7

task 8


familiar-isation 3

display 3

task 9

task 10

task 11

task 12

probe

useful for this review?

general questions

useful for other reviews?

validate tasks

interactive version

usingCOGS

using report

keystated preference for COGSstated preference for reportdid not state preference during task

familiar-isation 1

display 1display 1

task 1

task 2

task 3

task 4


familiar-isation 2

display 2

task 5

task 6

task 7

task 8


familiar-isation 3

display 3

task 9

task 10

task 11

task 12

probe


general questions


validate tasks

interactive version

usingCOGS

using report


Interview 7:

“I do think [the overall quality of the evidence is] easier to see with this, actually. It’s a good way of presenting it.”

Interview 2:

“again, I’m going to use the graphical summary because it’s far more useful [for this task], I think.”

familiar-isation 1

display 1display 1

task 1

task 2

task 3

task 4


familiar-isation 2

display 2

task 5

task 6

task 7

task 8


familiar-isation 3

display 3

task 9

task 10

task 11

task 12

probe


general questions


validate tasks

interactive version

usingCOGS

using report


familiar-isation 1

display 1display 1

task 1

task 2

task 3

task 4


familiar-isation 2

display 2

task 5

task 6

task 7

task 8


familiar-isation 3

display 3

task 9

task 10

task 11

task 12

probe


general questions


validate tasks

interactive version

usingCOGS

using report


Preferred elements (N):

The outcomes display (2)

The quality grid (2)

Follow-up display (1)

Being able to compare characteristics, quality and outcomes together (1)

Being able to compare characteristics between studies (1)

The study design symbols (3)

Age display (1)

COGS test - conclusions

Search time reduced - however, there was less information available overall in COGS.

Gives overview

Failed to present study designs successfully - revisions to key needed

Different intervention areas will need different data

pre/post design (same cohort is measured before

and a er intervention).

retrospective non-randomised cohort study design

survey design

cross-sectional /non-randomised

cohort design

pre-interventionN = 29

post-interventionN = 20

pre-interventionN = 7

post-interventionN = 2

N = 49

Intervention N = 29

Control N = 20

Intervention N = 29

Control N = 20 Control N = 2

Intervention N = 7

N = 49 N = 9

Intervention N = 29

Control N = 20

Intervention N = 7

Control N = 2

randomised design

Height of arrow is proportional to N (number of people tested)

Design/size arrows

larger study smaller study

Control N = 2

Intervention N = 7

N = 9

Intervention N = 29

Control N = 20

cross-sectionaldesign (no follow-up)

Intervention N = 29

Control N = 205 year follow-up

Intervention N = 29

Control N = 2012 year follow-up

0 yrslength of follow-up

5 10 10

0yr 5 10 15

N = 43

Intervention N = 21

Control N = 22

CAP

CDT

CID

CNC

CPT

CUN

YES

PFM

WT

GAS

PG

SL

outcome measures follow-up

55 75 95

ADAS

-cog

MM

SE SIB

othe

rAD

CS-A

DL

DAD PDS

othe

rNPI

othe

rCI

BIC

GD

SCD

RAD

CS-C

GIC

QoLauthor ageslocation

design, size & follow-up

studyquality

cog

0yr 1 2

no. ofcentres

0 10 20 30

baselineMMSE sex

outcome measures usedfunc be glo

55 75 95

ADAS

-cog

MM

SESIB

othe

rAD

CS-A

DL

DAD

PDS

othe

rNPI

othe

rCI

BIC

GD

SCD

RAD

CS-C

GIC

QoL

0yr 1 2 0 10 20 30 cog func be glo

N = 161

Donepezil 1mg N = 42 M FRandCharBlindAnaly

N = 473

M F

M F

RandCharBlindAnaly

M F

M F

RandCharBlindAnaly

Rogers et al.

1998 (B)

Rogers &

1996? Donepezil 3mg N = 40

Donepezil 5mg N = 39Placebo N = 40

Donepezil 5mg N = 154

Placebo N = 162

N = 468


Placebo N = 153

M FM FM F

Rogers et al.

1998 (A)Donepezil 10mg N = 157

M F

Donepezil 10mg N = 158M F

M F

M F

RandCharBlindAnaly

M FM F

RandCharBlindAnaly

M F

M F

RandCharBlindAnaly

M F

M F

RandCharBlindAnaly

N = 818


Placebo N = 274

N = 60

Donepezil 5mg (D)

Placebo (p)

N = 268


Placebo N = 129

N = 431


Placebo N = 217

Burns et al.

1999

Greenberg et al.

2000

Homma et al.

2000

Mohs et al.

2001

Donepezil 10mg N = 273M F

group 1 (p-D-p-p) N=30group 2 (p-p-D-p) N=30

1mg3mg5mg

5mg

10mg

5mg10mg

5mg10mg

NICE interviews

TAR review

Design & critique

COGS test

Methodsstudy

SOC test

State Occupancy Charts (SOCs)

temozolomide vs placebofor the treatment of newly

diagnosed high-grade glioma

1 — State Occupancy Chart

2 — State Occupancy & Absolute Quality of Life

3 — State Occupancy & Absolute Costs Per Person

4 — Incremental State Occupancy

5 — Incremental QALYs

6 — Incremental Costs

State Occupancy Charttreatment arm

state occupancy

– surgery (week 1)– post-op recovery (weeks 2- 6)– radiotherapy (weeks 7-12)– stable disease (week 13+)– progressive disease– death

placebo armstate occupancy

!is graphic shows the number of simulated people in the six di"erent states of the model, over the 260 one-week cycles of the model.

During the #rst week of treat-ment, all of the people in the model were assumed to undergo surgery, which is represented with a seperate state in the model.

From weeks 2-6, patients can either be in a post-operation recovery (treatment-free) state, or move to death in any of these #ve weeks.

In weeks 7-12, patients will undergo radiotherapy, have progressive disease or be dead.

From week 13 onwards, the model becomes a fairly typical three-state model, with patients either in a stable state, having progressive disease, or dead.

10% 25% 50% 75% 100% 0% 25% 50% 75% 100%

week 13+ stable/progressive/death

weeks 2-6 post-op recoveryweeks 7-12 radiotherapy

week 1 surgery

week26

week13

week 7week 2week 1

week39

week52

week65

week78

week91

week104

week117

week130

week143

week156

week169

week182

week195

week208

week221

week234

week247

week260

week26

week39

week52

week65

week78

week91

week104

week117

week130

week143

week156

week169

week182

week195

week208

week221

week234

week247

week260

0% 25% 50% 75% 100% 0% 25% 50% 75% 100%



week 1 surgery

week26

week39

week52

week65

week78

week91

week104

week117

week130

week143

week156

week169

week182

week195

week208

week221

week234

week247

week260

week26

week13

week 7week 2week 1

week39

week52

week65

week78

week91

week104

week117

week130

week143

week156

week169

week182

week195

week208

week221

week234

week247

week260

utility of 1 (per person)

utility of 0

utility of 0.5

!is information graphic shows the absolute quality of life experienced by the simulated patients in the model. !e shades of grey provide a scale from black (a utility of 1 per person) to white (a utility of 0 per person).

!ese shades of grey are presented in bars whose length correspond to the number of people in that state in the model during that week, as in graphic 1 — State Occupancy.

!e slowly lightening e"ect in the progressive state is caused by the gradual decomposition of utility values in this state in the model. !e simulated patients experience less quality of life the longer they spend in this state. !e values presented here are the average (mean) of the utility scores experienced by the cohort in that week of the model.

State Occupancy & Absolute Quality of Life

treatment armplacebo arm

2

0% 25% 50% 75% 100% 0% 25% 50% 75% 100%



week 1 surgery

week26

week39

week52

week65

week78

week91

week104

week117

week130

week143

week156

week169

week182

week195

week208

week221

week234

week247

week260

week26

week13

week 7week 2week 1

week39

week52

week65

week78

week91

week104

week117

week130

week143

week156

week169

week182

week195

week208

week221

week234

week247

week260

£3000 per person

£0 per person

£1500 per person

!is information graphic shows the absolute costs incurred per person in the model, on a scale from black (£3000 per person) to white (£0 per person).

!ese shades of grey are presented in bars whose length correspond to the number of people incurring that cost in that state in the model, as in graphic 1 — State Occupancy.

!e small dark bars appearing between the progressive and death states represent the one-o" costs assigned to death in the model. !e length of these bars is again proportional to the number of people dying during that week of the model.

Similar dark boxes appear between the stable and progressive states to indicate the higher costs assigned to a patient’s #rst week in the progressive state.

Costs for surgery in week 1 are o" the scale at £5953 per person, but this cost is identical in both arms of the model.

State Occupancy & Absolute Costs Per Person

treatment armplacebo arm

3



week 1 surgery

week26

week13

week 7week 2week 1

week39

week52

week65

week78

week91

week104

week117

week130

week143

week156

week169

week182

week195

week208

week221

week234

week247

week260

week26

week39

week52

week65

week78

week91

week104

week117

week130

week143

week156

week169

week182

week195

week208

week221

week234

week247

week260

Incremental State Occupancy

progressive death

5% shi!

stable

"e di#erence in state occupancy between the two arms of the model are shown here.

A bar extending to the le! shows that there were more people in that state during that week in the placebo arm than in the temozolomide arm. Extending to the right indicates more people in the temozolo-mide arm.

"e length of the bars, indicat-ing the incremental di#erence between the state occupancy of the two arms, are proprtional to graphic 1: State Occupancy. A 10% shi! is indicated by a thin vertical white line.

4

10% shi!

15% shi!

20% shi!



week 1 surgery

week26

week39

week52

week65

week78

week91

week104

week117

week130

week143

week156

week169

week182

week195

week208

week221

week234

week247

week260

week26

week13

week 7week 2week 1

week39

week52

week65

week78

week91

week104

week117

week130

week143

week156

week169

week182

week195

week208

week221

week234

week247

week260

!is graphic shows the di"erences between the two arms of the model in terms of the quality adjusted life years (QALYs) that would be experienced by a simulated cohort of 1000 people.

A bar extending to the le# shows that, during that week, more QALYs were experienced by the people in the placebo arm than the temololomide arm. A bar extending to the right represents more QALYs experienced in the temozolo-mide arm.

!in vertical white lines show the number of QALYs that would be experienced in a cohort of 1000 simulated patients. A bar that reaches one line represents one QALY.

!e death state is not shown, as no QALYs are experienced in that state, as it was assigned a utility of 0.

!e “total” column on the far right shows a sum of the values from the other two states.

Incremental QALYs

totalstable progressive

5

1

2

3

incremental QALYs



week 1 surgery

week26

week39

week52

week65

week78

week91

week104

week117

week130

week143

week156

week169

week182

week195

week208

week221

week234

week247

week260

week26

week13

week 7week 2week 1

week39

week52

week65

week78

week91

week104

week117

week130

week143

week156

week169

week182

week195

week208

week221

week234

week247

week260

!is graphic shows the di"erences in costs between the two arms of the model, again with a cohort of 1000 simulated patients.

As before, a bar extending to the le# shows higher costs in the placebo arm, and a bar extending to the right shows higher costs in the temozolomide arm.

!e thin vertical white lines show cost thresholds in increments of £100,000

!e “total” column on the far right shows a sum of the values from all three states of the model.

Incremental Costs

totalstable progressive death

6

£100,000£200,000£300,000£400,000£500,000£600,000

incremental costs

Task-based cognitive interviewing

Probing protocol (Interviewer-led)

6 expert users (HTA modellers)

Stand-alone evaluation (no comparator)

Tasks used to assess understanding

Qualitative results (participants asked for opinions - framework analysis)

SOC test

Task 1

Q: How many people have progressive disease in week 52 of the temozolomide arm of the model?

A: 32.7%

Task 1

Task 2Q: Where do the costs tend to come from in each arm of the model?

Task 2

Task 6Q: Where does the greatest difference between the costs of the two arms lie?

Task 6

SOC test - conclusions

Participants largely understood meaning of displays

Main function is to give overview, adding a temporal display to existing methods

Considered useful by participants

Could be used to display SA?

Applicability to other models - with many more states?

0% 25% 50% 75% 100%

week 1 surgeryweek

26

week39

week52

week65

week78

week91

week104

week117

week130

week143

week156

week169

week182

week195

week208

week221

week234

week247

week260

£3000 per person

£0 per person

£1500 per person

radiotherapy

chemotherapy drugs

hospital outpatient

hospital inpatient

placebo arm

£5.9m

£1.6m

£6.7m

£3.1m

weeks 7-12 radiotherapy

weeks 2+ progressive disease

weeks 2+ death



week 1 surgery

week26

week39

week52

week65

week78

week91

week104

week117

week130

week143

week156

week169

week182

week195

week208

week221

week234

week247

week260

week26

week13

week 7week 2week 1

week39

week52

week65

week78

week91

week104

week117

week130

week143

week156

week169

week182

week195

week208

week221

week234

week247

week260

!is graphic shows how adopting temozolomide treatment would a"ect quality of life and costs incurred over time.

!e grey bars show the change in costs and QALYs each week, and the solid black lines show the cumulative e"ects of adopting the treatment.

It should be noted that the weekly values are presented on a di"erent scale to the cumulative values. !is is necessary for the two to be compared overlaid in this manner.

Total Incremental Costs and QALYs 7incremental

total

total QALY gain:223.1ICER = £36,171 per QALY

total cost:£8.1m

QALYsincremental

totalcosts

incremental costs / QALYs

cumulativeincremental

costs / QALYs

Overall Conclusions

NICE interviews

TAR review

Design & critique

SOC test

COGS test

Methodsstudy

How should information graphics be designed, produced and used in health technology

assessment?

Research Question

Design

Research Area ECEHHRESEARCH OUTPUTS

Design

Production

1. Using standard visualisation tools in spreadsheet software (current situation – suitable for HTA professionals)

2. Developing new specialist software for use by HTA professionals (such as currently used for Forest plots)

3. Designing graphics on an individual basis (ie. in collaboration with trained information design professionals)

UseLikely that a combination of all three production methods will continue

Depends on:

- complexity of information to be presented

- available resources

- available skills

- which (or whether) specialist software tools are developed

Production

1. Using standard visualisation tools in spreadsheet software (current situation – suitable for HTA professionals)

Suitable for simpler reports:

- small number of trials in review

- few subgroups, sequencial treatments or other complicating factors

- simple treatment pathway for model

Production

2. Developing new specialist software for use by HTA professionals (such as currently used for Forest plots)

COGS software would be suitable for giving overview of more complex systematic reviews

SOC suitable for models in which time is a key consideration

Likely to be other graphics - these would further testing and evaluation

Production

3. Designing graphics on an individual basis (ie. in collaboration with trained information design professionals)

Suitable for the most complex reviews and models, where:

- different media become useable /dominant

- particular information needs highlighting (area of world, timing of trials, etc)

0 5 10 15 20

1ST

2 ST

AVG

N AB BKB

auth date ages design/size qualityfollow-up0yr 5 10 15

1ST

2ST

AVG

NAB BK

B

0 5 10 15 20 0yr 5 10 15

Pr Se As At Po Ot

Pr Se As At Po Ot

Pr Se As At Po Ot

Pr Se As At Po Ot

Pr Se As At Po Ot

Pr Se As At Po Ot

Pr Se As At Po Ot

Pr Se As At Po Ot

Har

rison

et

al.

2005

Niko

lopo

ulos

et

al.

2004

Man

rique

et

al.

2004

Stall

er

et al

.

2002

MED

-EL

2001

Niko

lopo

ulos

et

al.

1999

Illg e

t al.

1999

Kessl

er

et al

.

1997

N = 82

N = 82

N = 182

N = 78

N = 82

N = 126

N = 167

N = 49

20052004200320022001200019991998199719961995199419931992

Harrison et al.Nikolopolous et al.

Manrique et al.Staller et al.

MED-ELNikolopolous et al.

Illg et al.Kessler et al.

Future research

Developed graphics

- Use and monitoring

Evaluation of new graphics

- Other graphics designed for PhD

- Different designers’ work

- Different media?

Different audiences

- Public

- Medical professionals

Current work

E u r o p e a n C e n t r e f o r E n v i r o n m e n t a n d H u m a n H e a l t h

ENERGY

UK CARBON EMISSIONS

2009IN 2009, THE UK’S DEPARTMENT

FOR ENERGY AND CLIMATE CHANGE

CALCULATED THAT WE EMMITTED

564 TONNES OF CO2 - CARBON

DIOXIDE. HERE’S HOW THAT

BREAKS DOWN INTO DIFFERENT

SECTORS.

TRANSPORT

BUSINESS

RESIDENTIAL

AGRICULTURE

WASTE

INDUSTRIAL

PUBLIC SECTOR

195t

123t

86t79t

50t

18t

10t

8t

STRATOSPHERE10—50 km

UPPER TROPOSPHERE1—10 km

LOWER TROPOSPHERE0—1 km

ATMOSPHERIC COLUMN ATMOSPHERIC SERVICES

COLUMN BASE:1 km2

WIND TURBINES80—130 m

POWER STATIONS80—350 m

AIRCRAFTCRUISING6—12 km

WEATHERBALLOONS0—40 km

SOUNDINGROCKETS50—1500 km

SATELLITESLOW EARTH ORBIT160—2000 km

SERVICES AT ALL THREE ALTITUDES

PLASMA AND METEORS

DISPERSION OF AIR POLLUTION

PROPERTIES

UPPER AND LOWER TROPOSPHERE

WST PhD presentation for PenTAG 17may11

Documents

Transcript of WST PhD presentation for PenTAG 17may11