Radiation Safety Measures and Metrics That Matter! Robert Emery, DrPH, CHP, CIH, CSP, RBP, 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
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Radiation Safety Measures and Metrics That Matter! Robert Emery, DrPH, CHP, CIH, CSP, RBP, CHMM, CPP, ARM Vice President for Safety, Health, Environment.
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Radiation Safety Measures and Metrics
That Matter!
Robert Emery, DrPH, CHP, CIH, CSP, RBP, CHMM, CPP, ARMVice President for Safety, Health, Environment & Risk Management
The University of Texas Health Science Center at HoustonAssociate Professor of Occupational Health
The University of Texas School of Public Health
Objectives
• Part 1:– Identify and classify the different types of measures
accrued by radiation safety programs– Differentiate between program measures and metrics– Discuss how these measures may be used
• Part 2:– Examine the science and art of effective data displays– Identify the basic characteristics of effective data
displays– Review actual before and after “make overs” of actual
programmatic data displays
Why Training on Measures?
• An interesting dilemma:
– Radiation safety programs thrive on data
– Virtually every important radiation safety decision is based on data to some extent
– Formal training in the area of compelling data presentations is somewhat rare for radiation safety professionals
– The ability to compellingly display data is the key to desired decision making
Why Training on Data Presentation (cont.)?
• The radiation safety profession is 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 management who do not understand what their radiation safety programs do.
Radiation Safety Program Measures
• Step 1. Actual field measurements• Radiation exposure levels, rates• Radiation dose levels, rates• Amounts of radioactivity• Other aspects – distance, mass, area
• Step 2. Programmatic measures• Indicators of workload
• Number of principle investigators• Number of authorized labs• Lab inspections
• Indicators of program outcomes• Regulatory inspection outcomes?• Actual doses received? In excess of ALARA limits?
• Note – what is the applicability of this information to the annual Radiation Protection Program review?
Radiation Safety Program Measures
• Step 3: Programmatic metrics
• Comparing data to major organizational drivers, such as
• Institutional extramural research expenditures?• Patient revenues?• Institutional square footage?
• Example of the power of metrics: What does the license/registration cost versus what is it worth?
Radiation Safety Program Measures
• Step 4: Actually presenting or communicating the data to others
• Some key questions:
• To whom might we be presenting your data to?
• Will these different stakeholders understand or comprehend what you’re trying to say?
• How long do you typically have to tell your story?
How Do We Achieve Data Display Excellence?
• The goal is to present 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
• Tufte, ER, The Visual Display of Quantitative Information, Cheshire, CT, 2001
• Tufte, ER, Envisioning Information, Cheshire, CT, 1990
• Tufte, ER, Visual Explanations, Cheshire, CT, 1997
Sample Recommendations
• Don’t blindly rely on the automatic graphic formatting provided by Excel or Powerpoint!
• Strive to make large data sets coherent
• Encourage the eye to compare different data
• Representations of numbers should be directly proportional to their numerical quantities
• Use clear, detailed, and thorough labeling
Sample 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 Tufte Remark
• 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?”
Three UTHSCH “Make Over” Examples
• Data we accumulated and displayed on:– Nuisance Fire Alarms– Workers compensation experience modifiers– 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
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Contractor Smoke/Fire
Spontaneous Maintenance
Results of the Great UTHSC-H Nuisance Fire Alarm Challenge
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Results of the Great UTHSC-H Nuisance Fire Alarm Challenge
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Contractor Smoke/Fire Spontaneous Maintenance
Results of the Great UTHSC-H Nuisance Fire Alarm Challenge
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Contractor Smoke/Fire Spontaneous Maintenance
Results of the Great UTHSC-H Nuisance Fire Alarm Challenge
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Sept Oct Nov Dec Jan Feb Mar Apr May Jun Jul Aug
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Contractor Smoke/Fire
Spontaneous Maintenance
Results of the Great UTHSC-H Nuisance Fire Alarm Challenge
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Sept Oct Nov Dec Jan Feb Mar Apr May Jun Jul Aug
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Contractor Smoke/Fire
Spontaneous Maintenance
Results of the Great UTHSC-H Nuisance Fire Alarm Challenge
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Sept Oct Nov Dec Jan Feb Mar Apr May Jun Jul Aug
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MaintenanceSpontaneousSmoke/FireContractor
Results of the Great UTHSC-H Nuisance Fire Alarm Challenge (FY04)
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Sept Oct Nov Dec Jan Feb Mar Apr May Jun Jul Aug
Nu
mb
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of A
larm
s
Caused by UTHSCH Facilities work
Caused by detector malfunction or dust accumulation
Caused by actual smoke or fire
Caused by outside contractor work
Fiscal Year 04
Results of the Great UTHSC-H Nuisance Fire Alarm Challenge
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Contractor Smoke/Fire
Spontaneous Maintenance
Employee Worker’s Comp Experience Modifier
compared to other UT health components, FY 98-FY 04
0
0.2
0.4
0.6
0.8
1
98 99 2000 2001 2002 2003 2004
UT-Tyler UTMB UT-SA MDA UT-H UT-SW
Rate of "1" industry average, representing $1 premium per $100
Worker’s Compensation Insurance Premium Adjustment for UTS Health Components Fiscal Years 2002 to 2007
(discount premium rating as compared to a baseline of 1, three year rolling average adjusts rates for subsequent year)
0.00
0.10
0.20
0.30
0.40
0.50
0.60
0.70
0.80
0.90
1.00
2002 2003 2004 2005 2006 2007 2008
UT Health Center Tyler (0.45)
UT Medical Branch Galveston (0.35)
UT HSC San Antonio (0.25)
UT Southwestern Dallas (0.20)UT HSC Houston (0.16)UT MD Anderson Cancer Center (0.11)
3 year period upon which premium is calculated
Medical School Building Hallway Occlusion (2004)
0 100 200 300 400
Basement (under construction) - Pete Martinez
Ground - Pete Mart inez
1 - J ason LeBlanc
2 - Matthew Keck
3 - Gamalial Torres
4 - Leon Brown
5 - Dita Geary
6 - Selome Ayele
7 - J ulie Broussard
Penthouse - J ason Bible
T otal Oc c l uded Feet
Feb-04
Apr -04
May-04
J un-04
J ul -04
Aug-04
Sep-04
Oct-04
Dec-04
J an-05
Feb-05
MSB Corridor Blockage in Cumulative Occluded Linear Feet, by Month and Floor
(building floor indicated at origin of each line)
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200
400
600
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1000
1200
1400
1600
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2000
Feb Apr May Jun Jul Aug Sep Oct Dec Jan Feb
Cum
ulat
ive
Occ
lude
d lin
ear
feet
20042005
7th
6th
5th
4th
3rd
2nd
1st
G
Three Radiation-specific Examples
• Three examples:
• 1. Communicating to room occupants their possible radiation exposures
• 2. Communicating to the radiation safety committee and upper management the capacity of our broad scope license
• 3. Communicating to upper management general radiation safety trends
Example 1: Area Radiation Levels
Upset administrative workers being placed in new workplace cube farm near source storage area
Area monitoring dutifully performed, but mere data printout provided
Future occupants still concerned
Figure 1. Recorded radiation doses in mrem/yr on inside walls of vault room as compared to regulatory limits, as recorded by area dosimeters in place for calendar year 2004
0
1,000
2,000
3,000
4,000
5,000
6,000
North wall East wall South wall West wall
Location of monitoring device on inside of vault wall
Average Cost of Workers Compensation Claims, by Cause, for Period FY01 - FY06
Average cost from total of 3 events
Average cost from total of 3 events
Average cost from total of 4 events
Average cost from total of 4 events
Average cost from total of 10
events
Average cost from total of 4
events
2006 Dental Injuries by Type
0
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Septe
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Total
Month
Nu
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xpo
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Puncture cutlaceration
Needlestick
Reported Sharps Injuries by Type for Academic Year 2006 (total n = 22)
0
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JUL AUG SEP OCT NOV DEC JAN FEB MAR APR MAY JUN
Month of academic year 2006
Nu
mb
er
of r
ep
ort
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eve
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Number caused by non-needle sharps
Number caused by hollow-bore needles
Start of Academic Year
Building Related Programs
-100
0
100
200
300
400
500
1986 1996 1998 2003
Years
Perc
en
t G
row
th
Fire Ext. Systems
Fire Extinguishers
Fire Related Incidents
Asbestos Projects
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
Building Fire Systems to be Serviced
050
100150200250
1986
1988
1990
1992
1994
1996
1998
2000
2002
2004
Years
Num
ber
Required Portable Fire Extinguishers
0
1,000
2,000
3,000
4,000
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1988
1990
1992
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2000
2002
2004
Years
Num
ber
Fire Related incidents
0
500
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1500
1986
1988
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2004
Years
Num
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Asbestos Projects
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Years
Num
ber
Growth in Occupational Safety Responsibilities 1986 to 2003
Building Fire Systems to be Serviced
050
100150200250
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1990
1992
1994
1996
1998
2000
2002
2004
Years
Num
ber
Required Portable Fire Extinguishers
0
1,000
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4,000
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1988
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1996
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2004
Years
Num
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Fire Related incidents
0
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1500
1986
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2000
2002
2004
Years
Num
ber
Asbestos Projects
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Years
Num
ber
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20,000
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140,000
160,000
180,000
200,000
1999 2000 2001 2002 2003 2004 2005
Wastes Generated from Laboratory OperationsWaste Generated from Administrative DepartmentsWaste Generated from Renovation ProjectsTotal Waste Generatation
Figure 1: Laboratory Waste verses Total Waste Generated
0
20,000
40,000
60,000
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100,000
120,000
140,000
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200,000
1999 2000 2001 2002 2003 2004 2005 2006 2007 2008
Fiscal Year
We
igh
t in
Po
un
ds
Amount from administrative departments
Amount from renovation projects
Total hazardous waste generation in pounds
Amount from laboratory operations
Figure 1: Hazardous Waste Generation in Pounds by Type of Institutional Activity
$0
$50,000
$100,000
$150,000
$200,000
$250,000
$300,000
FY00/01 FY01/02 FY02/03 FY03/04 FY04/05 FY05/06
Cost of Wastes Generated from Laboratory OperationsCost of Waste Generated from Administrative DepartmentsCost of Waste Generated from Renovation ProjectsTotal Cost of Waste Generatated by the University of Delaware
Figure 1: Laboratory Waste verses Total Waste Generated
$0
$50,000
$100,000
$150,000
$200,000
$250,000
$300,000
2001 2002 2003 2004 2005 2006 2007 2008
Fiscal Year
Do
llars
Figure 2: Annual Hazardous Waste Disposal Cost by Type of Institutional Activity
Total cost
Cost of waste from lab operations
Cost of waste from administrative departments
Cost of waste from renovation projects
2005 Workers' Compensation by Injury Type
0
5
10
15
20
25
30
Month
Nu
mb
er o
f C
ases
Burn/Scald
Caught In
Cut, Puncture, Scrape
Fall, Slip, Trip
MVA
Strain
Strike Against
Struck By
Rub/Abraded
Misc.
2005 Total Number of Monthly Workers Compensation Claims inclusive of the three most frequent identifiable classes of injuries
0
10
20
30
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Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
Year
Num
ber o
f eve
nts
Total
FallStrainCut, Puncture
0
5
10
15
20
25
Car
eer
FTE
Fiscal Year
EH&S Staffing Trends
EHS StaffBudget Augments
Budget Cuts
UCR EH&S Staff, Extramural Research Funding and Grant Awards
418
457
498484
559
529 523
583
622 619610
710
735
800816
$23$26
$28
$33$36
$40 $39$43
$45 $45
$51
$58
1518.5 19 19 20 19 19 18.5 17
1518
2022 20.5
17
$65
$143
$166
$87$82
$106
$123
0
100
200
300
400
500
600
700
800
900
19
90
19
91
19
92
19
93
19
94
19
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19
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19
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19
98
19
99
20
00
20
01
20
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07
20
08
Fiscal Year
Nu
mb
er o
f G
ran
t A
war
ds
0
20
40
60
80
100
120
140
160
180
EH
S S
taff; Extram
ural A
ward
s-Millio
n $
Number of Awards
Grants in Millions $
EHS Career Staff
Campus Sq. Footage & EHS Staffing
72,964
55,200
29,700
20,000
30,000
40,000
50,000
60,000
70,000
1990 2005 2010
Fiscal YearG
SF
in T
en
s o
f Th
ou
sa
nd
s
10.00
20.00
30.00
40.00
50.00
60.00
EH
S F
TE
EHS Staffing & Student Growth
8,006
15,666
20,140
-
5,000
10,000
15,000
20,000
1990 2005 2010
Fiscal Year
10
15
20
25
30
35
40
45
50
55
60
All Students
EHS Staff
UCR Campus Growth Indicators Compared to EH&S Staffing
Campus Gross Square Footage
0
20,000,000
40,000,000
60,000,000
80,000,000
1990 1995 2000 2005 2010
Years
Sq
ua
re F
oo
tag
e
Student Population
0
5,000
10,000
15,000
20,000
25,000
1990 1995 2000 2005 2010
Years
Nu
mb
ers
of S
tud
en
ts
Extramural Research Funding
0
20,000,000
40,000,000
60,000,000
80,000,000
100,000,000
1990 1995 2000 2005 2010
Years
Do
llars
EH&S Staffing
0
5
10
15
20
25
1990 1995 2000 2005 2010
Years
Nu
mb
er
of S
taff
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
0
50
100
150
200
250
300
350
400
0 15 30 45 60 75
Time in minutes
ppm
Qua
nter
nary
Am
mon
ium
Chl
orid
e
Cotton Towel Solutions
0
50
100
150
200
250
300
350
400
0 15 30 45 60 75
Time in minutes
ppm
Qua
nter
nary
Am
mon
ium
Chl
orid
e
EPA Limit EPA Limit
*Towels removed and rinsed at each interval
Offshore Benzene
Time Sample Taken (Hours) 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
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)