Transcript Slide 1

The Effective Display of
Health & Safety Data to
Achieve Desired Decision
Making
Robert Emery, DrPH, CHP, CIH, CBSP, CSP, CHMM, CPP, ARM
Vice President for Safety, Health, Environment & Risk Management
The University of Texas Health Science Center at Houston
Associate Professor of Occupational Health
The University of Texas School of Public Health
Why Training on Data
Presentation ?
• An interesting dilemma:
– Almost all programs thrive on data
– Virtually every important decision is based on data to
some extent
– Formal training in the area of compelling data
presentations is rare for many professionals
– The ability to compellingly display data is the key to
desired decision making
Why Training on Data
Presentation (cont.)?
• The safety profession is particularly awash in
bad examples of data presentations!
• We’ve all endured them at some point in our
careers!
• Commentary: This may be the reason for
repeated encounters with stakeholders do
not understand what safety does.
Achieving Safety & Security
Data Display Excellence
• The presentation of complex ideas and
concepts in ways that are
– Clear
– Precise
– Efficient
• How do we go about achieving this?
Go to The Experts On Information
Display
•
Tukey, JW, Exploratory Data Analysis, Reading, MA 1977
•
Tukey, PA, Tukey, JW Summarization: smoothing; supplemented views,
in Vic Barnett ed. Interpreting Multivariate Data, Chichester, England,
1982
•
Tufte, ER, The Visual Display of Quantitative Information, Cheshire, CT,
2001
•
Tufte, ER, Envisioning Information, Cheshire, CT, 1990
•
Williams, R The Non-Designers Book: Design and Typographic Principles
for the Visual Novice. Berkley, CA, 1994
•
Tufte, ER, Visual Explanations, Cheshire, CT, 1997
Recommendations
• Don’t blindly rely on the automatic graphic
formatting provided by Excel or Powerpoint!
• Encourage the eye to compare different data
• Representations of numbers should be directly
proportional to their numerical quantities
• Use clear, detailed, and thorough labeling
Recommendations (cont.)
• Display the variation of data, not a
variation of design
• Maximize the data to ink ratio – put most
of the ink to work telling about the data!
• When possible, use horizontal graphics:
50% wider than tall is usually best
Compelling Remark by Tufte
• “Visual reasoning occurs more effectively
when relevant information is shown
adjacent in the space within our eye-span”
• “This is especially true for statistical data
where the fundamental analytical act is to
make comparisons”
• The key point: “compared to what?”
Four UTHSCH “Make Over”
Examples
• Data we accumulated and displayed on:
–
–
–
–
Nuisance Fire Alarms
Workers compensation experience modifiers
First reports of injury
Corridor clearance
• But first, 2 quick notes:
– The forum to be used:
• The “big screen” versus the “small screen”?
• In what setting are most important decisions made?
– Like fashion, there are likely no right answers – individual tastes
apply, but some universal rules will become apparent
Results of the Great UTHSC-H Nuisance
Fire Alarm Challenge
8
Number of Alarms
7
6
5
4
3
2
1
0
Spontaneous
Maintenance
Aug
Smoke/Fire
Jul
Jun
May
Apr
Mar
Feb
Jan
Dec
Nov
Oct
Sept
Contractor
Results of the Great UTHSC-H Nuisance
Fire Alarm Challenge
10
Number of Alarms
9
8
7
6
5
4
3
2
1
0
Aug
Jul
Spontaneous
Jun
May
Apr
Smoke/Fire
Mar
Feb
Jan
Dec
Nov
Oct
Sept
Contractor
Maintenance
Results of the Great UTHSC-H Nuisance
Fire Alarm Challenge
10
Number of Alarms
9
8
7
6
5
4
3
2
1
0
Aug
Jul
Spontaneous
Jun
May
Apr
Smoke/Fire
Mar
Feb
Jan
Dec
Nov
Oct
Sept
Contractor
Maintenance
Results of the Great UTHSC-H Nuisance
Fire Alarm Challenge
10
Number of Alarms
9
8
7
6
5
4
3
2
1
0
Aug
Jul
Spontaneous
Jun
May
Apr
Smoke/Fire
Mar
Feb
Jan
Dec
Nov
Oct
Sept
Contractor
Maintenance
Results of the Great UTHSC-H Nuisance
Fire Alarm Challenge
10
9
Number of Alarms
8
7
6
5
4
3
2
1
0
Sept
Oct
Nov
Dec
Jan
Contractor
Smoke/Fire
Spontaneous
Maintenance
Feb
Mar
Apr
May
Jun
Jul
Aug
Results of the Great UTHSC-H Nuisance
Fire Alarm Challenge
10
9
Number of Alarms
8
7
6
5
4
3
2
1
0
Sept
Oct
Nov
Dec
Jan
Contractor
Smoke/Fire
Spontaneous
Maintenance
Feb
Mar
Apr
May
Jun
Jul
Aug
Results of the Great UTHSC-H Nuisance
Fire Alarm Challenge
10
Maintenance
Spontaneous
Smoke/Fire
Contractor
9
Number of Alarms
8
7
6
5
4
3
2
1
0
Sept
Oct
Nov
Dec
Jan
Feb
Mar
Apr
May
Jun
Jul
Aug
Results of the Great
UTHSC-H Nuisance Fire Alarm Challenge (FY04)
10
9
Number of Alarms
8
Caused by UTHSCH Facilities work
Caused by detector malfunction or dust accumulation
Caused by actual smoke or fire
Caused by outside contractor work
7
6
5
4
3
2
1
0
Sept
Oct
Nov
Dec
Jan
Feb
Mar
Fiscal Year 04
Apr
May
Jun
Jul
Aug
Results of the Great UTHSC-H Nuisance
Fire Alarm Challenge
8
Number of Alarms
7
6
5
4
3
2
1
0
Spontaneous
Maintenance
Aug
Smoke/Fire
Jul
Jun
May
Apr
Mar
Feb
Jan
Dec
Nov
Oct
Sept
Contractor
Employee Worker’s Comp Experience
Modifier
compared to other UT health components, FY 98-FY 04
1
Rate of "1" industry average, representing $1 premium per $100
0.8
0.6
0.4
0.2
0
98
99
UT-Tyler
2000
UTMB
2001
2002
2003
2004
UT-SA
MDA
UT-H
UT-SW
WCI Premium Adjustment for UTS Health Components
(discount premium rating as compared to a baseline of 1)
1
0.9
0.8
0.7
0.6
0.5
UT Health Center Tyler (0.40)
UT Medical Branch Galveston (0.38)
0.4
0.3
UT HSC San Antonio (0.27)
UT Southwestern Dallas (0.24)
0.2
UT HSC Houston (0.17)
UT MD Anderson Cancer Center (0.14)
0.1
0
1998
1999
2000
2001
2002
2003
Fiscal year
2004
2005
2006
2007
2008
Losses – Personnel
Reported Injuries by Population
800
690
694
715
675
623
608
511
600
400
200
0
98
99
Employee
00
01
02
Resident
03
04
Student
Number of First Reports of Injury, by Population Type
800
700
600
Total (n = 513)
500
400
300
Employees (n = 284)
200
Residents (n = 140)
100
Students (n = 89)
0
FY98
FY99
FY00
FY01
FY02
FY03
FY04
FY05
FY06
FY07
MSB Corridor Blockage in Cumulative Occluded Linear Feet,
by Month and Floor
(building floor indicated at origin of each line)
2000
7th
1800
Cumulative Occluded linear feet
1600
6th
1400
1200
5th
1000
800
4th
600
3rd
400
2nd
1st
200
0
G
Mar
Apr
May
Jun
Jul
2004
Aug
Sep
Oct
Nov
Dec
Jan
Feb
2005
Mar
Important Caveats
• Although the techniques displayed here are
powerful, there are some downsides to this
approach
– Time involved to create assemble data and create nonstandard graphs may not mesh with work demands
– Relentless tinkering and artistic judgment
• Suggested sources for regular observations to
develop an intuitive feel for the process
– Suggested consistent source of good examples:
• Wall Street Journal
– Suggested consistent source of not-so-good examples:
• USA Today “char-toons”
Summary
• The ability to display data compellingly is the key to
desired decision making
• Always anticipate “compared to what?”
• Maximize the data-to-ink ratio – e.g. eliminate the
unnecessary
• Think about what it is you’re trying to say
• Show to others unfamiliar with the topic without speaking
– does this tell the story we’re trying to tell?
Your Questions at This Point?
Now Let’s Look at
Some Other Examples
COLLABORATIVE LABORATORY INSPECTION PROGRAM (CLIP)
•During October 2005, 80 Principle Investigators for a total of 316 laboratory
rooms were inspected
•A total of 30 CLIP inspections were performed
PI Inspections:
Total PI’s
#Without Lab
Violations
# With Lab
Violations
%Without Lab
Violations
%With Lab
Violations
May 2005
94
53
41
56.38
43.62
June 2005
78
40
38
51.28
48.72
July 2005
84
54
30
64.29
35.71
August 2005
74
54
20
72.97
27.03
September 2005
69
39
30
56.52
43.48
October 2005
80
50
30
62.50
37.50
Comprehensive Laboratory Inspection Program
(CLIP) Activities and Outcomes, 2005
Month in
Year 2005
Number of Principle
Investigators Inspected
Inspections
Without Violations
Inspections
With Violations
May
94
53 (56 %)
41 (44%)
June
78
40 (51%)
38 (49%)
July
84
54 (64%)
30 (36%)
August
74
54 (73%)
20 (27%)
September
69
39 (56%)
30 (44%)
October
80
50 (62%)
30 (38%)
2005 Collaborative Laboratory Inspection Program (CLIP)
Inspection Activities and Compliance Findings
No. of Principal Invesitgator Inspections
100
90
80
70
60
Number without violations
50
40
30
Number with violations
20
10
0
May
Jun
Jul
Aug
Sep
Oct
Months within Calendar Year 2005
Nov
Dec
2005 Collaborative Laboratory Inspection Program (CLIP)
Inspection Activities and Compliance Findings
No. of Principal Invesitgator Inspections
100
90
80
70
60
Number without violations
50
40
30
Number with violations
20
10
0
May
Jun
Jul
Aug
Sep
Oct
Months within Calendar Year 2005
Nov
Dec
Figure 3. Receipt of Radioactive Material
Number of Receipts
6000
5000
4000
Non-Medical
Medical
Total
3000
2000
1000
0
FY00
FY01
FY02
FY03
FY04
Fig. 3. Receipts of Radioactive Materials
6,000
Number of receipts
5,000
4,000
Number of non-medical use
radioactive material receipts
3,000
2,000
Number of medical use
radioactive material receipts
1,000
0
FY 00
FY 01
FY 02
FY 03
Fiscal Year
FY 04
FY 05
FY 06
Fig. 3. Receipts of Radioactive Materials
6,000
Number of receipts
5,000
4,000
Number of non-medical use
radioactive material receipts
3,000
2,000
Number of medical use
radioactive material receipts
1,000
0
FY 00
FY 01
FY 02
FY 03
Fiscal Year
FY 04
FY 05
FY 06
OSHA LAB STANDARD &
EPA COMPLIANCE
350
325
300
275
250
225
200
175
150
125
100
75
50
25
0
2004
labs audited
2005
Total # of labs
# in compliance
Results of University EH&S Lab
Inspection Program, 2003 to 2005
Number of labs existing
but not inspected
350
300
Number of labs inspected
and one or more violation
detected
Number of Labs
250
200
Number of labs inspected
and no violations detected
150
100
Note: 33 labs added to campus
in 2005, increasing total from
269 to 302.
50
0
2003
2004
2005
Calendar Year
2006
2007
$45,000.00
$40,000.00
$35,000.00
$30,000.00
$25,000.00
$20,000.00
$15,000.00
$10,000.00
$5,000.00
$0.00
Avg/Claim
ve
ru
se
n.
.
/o
ve
re
xt
en
si
Il l
on
ne
/..
ss
.
–
du
e
to
re
pe
at
e.
..
ob
je
ct
–
O
an
dl
in
g
in
cl
ud
in
g.
..
Li
fti
ng
/h
ob
je
ct
(
St
ri k
in
g
an
d/
or
fa
ll
fa
ll
–
–
ou
ts
...
in
si
d.
..
#
Sl
ip
/tr
ip
an
d/
or
Sl
ip
/tr
ip
Cost of Claim
Average Cost of Workers Compensation Claims By Cause
Period FY01 - FY06
Type of Claim
Average Cost of Workers Compensation Claims, by Cause, for Period FY01 - FY06
$45,000
$40,000
Slips, trips, falls – inside
$35,000
Cumulative trauma
$30,000
Overextension, twisting
$25,000
Slips, trips, falls – outside
$20,000
Lifting/handling
$15,000
Uncontrolled object
$10,000
$5,000
$0
Average
cost from
total of 3
events
Average
cost from
total of 10
events
Average
cost from
total of 4
events
Average
cost from
total of 3
events
Average
cost from
total of 4
events
Average
cost from
total of 4
events
2005 Workers' Compensation
by Injury Type
30
Burn/Scald
Caught In
Cut, Puncture, Scrape
20
Fall, Slip, Trip
MVA
15
Strain
Strike Against
10
Struck By
Rub/Abraded
5
Misc.
Month
De
c
No
v
Au
g
Se
pt
O
ct
Ju
ly
Ap
ril
M
ay
Ju
ne
ar
ch
M
Fe
b
0
Ja
n
Number of Cases
25
2005 Total Number of Monthly Workers Compensation Claims
inclusive of the three most frequent identifiable classes of injuries
80
Number of events
70
60
50
Total
40
30
20
Fall
Strain
Cut, Puncture
10
0
Jan
Feb
Mar
Apr
May
Jun
Jul
Year
Aug
Sep
Oct
Nov
Dec
Building Related Programs
500
400
Percent Growth
300
Fire Ext. Systems
Fire Extinguishers
Fire Related Incidents
Asbestos Projects
200
100
0
1986
1996
1998
2003
-100
Years
Fire Extinguisher
Systems
Fire Extinguishers
Fire Related
Incidents
Asbestos
Projects
1986
0
0
0
0
1996
203
19
91
55
1998
208
25
15
68
2003
437
46
-18
191
Growth in Occupational Safety Responsibilities 1986 to 2003
Required Portable Fire Extinguishers
250
4,000
200
3,000
Number
Number
Building Fire Systems to be Serviced
150
100
50
0
2,000
1,000
0
1986 1988 1990 1992 1994 1996 1998 2000 2002 2004
1986 1988 1990 1992 1994 1996 1998 2000 2002 2004
Years
Years
Asbestos Projects
Fire Related incidents
1500
60
Number
40
20
0
1000
500
Years
20
04
20
02
20
00
19
98
19
96
19
94
19
92
19
90
Years
19
88
0
1986 1988 1990 1992 1994 1996 1998 2000 2002 2004
19
86
Number
80
UCR EH&S Staff,
Extramural Research Funding and Grant Awards
900
180
$166
816
800
800
160
Number of Awards
$143
735
Grants in Millions $
710
EHS Career Staff
140
610
583
600
120
559
529
$106
523
498
484
500
100
457
$82
$87
418
400
80
$65
$58
300
60
$51
$43
$40
200
$33
$23
$45
$39
$36
40
$28
$26
18.5
100
$45
19
19
20
19
19
18.5
15
17
18
20
22
Campus Sq. Footage & EHS Staffing
60.00
70,000
60,000
50,000
GSF in Tens of Thousands
72,964
50.00
40.00
55,200
30.00
40,000
30,000
29,700
20.00
20.5
17
15
20
20,000
10.00
1990
2005
2010
Fiscal Year
2008
2007
2006
2005
2004
2003
2002
2001
2000
1999
1998
1997
1996
1995
1994
1993
1992
0
1991
0
Fiscal Year
EH&S Staffing Trends
60
25
20,000
EHS Staffing & Student Growth
55
20,140
20
50
15,000
All Students
45
15,666
EHS Staff
40
35
10,000
30
Career FTE
15
10
25
8,006
5
5,000
20
15
2005
Fiscal Year
2010
EHS Staff
Budget Augments
Budget Cuts
Fiscal Year
20
04
20
02
20
00
19
98
19
96
19
94
10
1990
19
92
0
-
19
90
1990
Number of Grant Awards
619
$123
EHS Staff; Extramural Awards-Million $
622
EHS FTE
700
UCR Campus Growth Indicators
Compared to EH&S Staffing
Campus Gross Square Footage
Student Population
Numbers of Students
Square Footage
80,000,000
60,000,000
40,000,000
20,000,000
0
1990
1995
2000
2005
25,000
20,000
15,000
10,000
5,000
0
2010
1990
1995
Years
2005
2010
Years
Extramural Research Funding
EH&S Staffing
25
Number of Staff
100,000,000
80,000,000
Dollars
2000
60,000,000
40,000,000
20,000,000
0
20
15
10
5
0
1990
1995
2000
Years
2005
2010
1990
1995
2000
Years
2005
2010
Journal of Environmental
Health, September 2006,
page 49
Quat-Safe and Cotton
Food Service Towel Quanternary Ammonium Chloride Solution
Concentration Compared Over Time*
Quat-Safe Solutions
Cotton Towel Solutions
400
350
300
250
FDA Std
200
150
100
50
0
ppm Quanternary Ammonium Chloride
ppm Quanternary Ammonium Chloride
400
350
300
250
FDA Std
200
150
100
50
0
0
15
30
60
45
75
0
Time in minutes
*Towels removed and rinsed at each interval
15
30
45
Time in minutes
60
75
Offshore Benzene
Time Sample Taken (Hours)
Example of oil spill
worker benzene
exposure monitoring
data posted on OSHA
website by BP
industrial hygiene
program prior to the
availability of any
independent OSHA
sampling results
(June 2010)
Sampling Result in ppm
0
0
2
0.25
4
0.3
6
0.4
8
0.1
10
0.002
12
0.3
14
0.2
16
0
18
0.25
20
0.3
22
0.4
24
0.1
26
0.002
28
0.3
30
0.2
32
0
34
0.25
36
0.3
38
0.4
40
0.1
42
0.002
44
0.3
46
0.2
48
0
50
0.25
Gulf Worker Benzene Exposure
1.2
1.1
OSHA Permissible Exposure
Limit 1 ppm (maximum exposure
1.0
allowed over 8 hour timeframe)
Sam pling Result (ppm )
0.9
0.8
0.7
0.6
OSHA Action level 0.5 ppm
0.5
(harmful level requiring
protection for workers )

0.4
0.3

0.2





0






0.1
0.0



10






20

30


40

50
60
70
80
Tim e Sam ple Taken (hours post leak event)
Cristina Alvarez Graphic Assignment