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Radiation Safety Measures and Metrics
That Matter!
Robert Emery, DrPH, CHP, CIH, CSP, RBP, CHMM, CPP, ARMAssistant Vice 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?
Examples
• Four examples of safety data displays (3 radiation-related, the fourth more generic)
• 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
• 4. Multiple examples of attempts to communicate effects of routine surveillance program
Example 1: Area Radiation Levels
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
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North wall East wall South wall West wallLocation of monitoring device on inside of vault wall
Ann
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in m
illire
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Background radiation dose level 360 mrem/yr
Occupational dose limit 5,000 mrem/yr, beyond 360 mrem/yr background dose level
General public limit 100 mrem/yr beyond background dose level of 360 mrem/yr
Example 2: Broad Scope License Capacity
Fig. 1 Summary of UTHSCH Broad Scope Radioactive Material License Possession Limits, Collective Sublicensee Possession Limits and Actual On-hand Collective Inventory(a)
0123456789
1011121314151617181920
H-3 N-13 C-14 Na-22 P-32 P-33 S-35 Cl-36 Ca-45 Cr-51 I-125 Ce-141 Ra-226
Radioisotope
Act
ivity
(Ci)
Broad scope license possession limit
Collective sublincensee possesion limit
Actual amount on-hand
(a) Data for August 2002
Example 3: 10 Year Prospectus
$0$20$40$60$80
$100$120$140$160
1992 1994 1996 1998 2000 2002
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1992 1994 1996 1998 2000 2002Rad
Was
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Example 4In 2004, an institution initiated a comprehensive lab safety routine surveillance program. Prior to 2004, the safety program was in a reactive mode, with no regularly scheduled routine inspections being performed.
In 2004, the institution possessed 269 labs. Of these, 175 were inspected during the year. Of the 175 labs inspected, 95 did not exhibit any items of non compliance, whereas 80 labs were found to have at least one item of non-compliance that needed to be addressed
In 2005 the institution added 33 labs, bringing the total to 302 labs on campus. In 2005, all of the labs were inspected, with 280 exhibiting no items of non-compliance and 22 exhibiting at least one item of non-compliance
How would you communicate this information so that resources will be provided to continue this very worthwhile effort?
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
• 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
• 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?”
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
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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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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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Sept Oct Nov Dec Jan Feb Mar Apr May Jun Jul Aug
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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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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
Num
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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
Num
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Caused by UTHSCH Facilities workCaused by detector malfunction or dust accumulationCaused by actual smoke or fireCaused by outside contractor work
Fiscal Year 04
Results of the Great UTHSC-H Nuisance Fire Alarm Challenge
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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
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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
Losses – PersonnelReported Injuries by Population
0
200
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600
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98 99 00 01 02 03 04
Employee Resident Student
690 694 715 675623 608 511
Number of UTHSC-H First Reports of Injury, by Population Type (total population 8,832; employee population 4,425; student population 3,587; resident population 820)
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FY01 FY02 FY03 FY04 FY05 FY06 FY07
Total (n = 450)
Employees (n = 260)
Residents (n = 105)Students (n = 85)
M e di c a l S c hool Bui l di ng Ha l l wa y Oc c l usi on ( 2 0 0 4 )
0 100 200 300 400
Basemen t ( un der con st r uct ion ) - Pet e M ar t in ez
Gr oun d - Pet e M ar t in ez
1 - Jason LeBlan c
2 - M at t hew Keck
3 - Gamalial T or r es
4 - Leon Br own
5 - Dit a Gear y
6 - Selome Ayele
7 - Julie Br oussar d
Pen t house - Jason Bible
T o t a l O c c l u d e d F e e t
Feb-04
Apr -04
M ay-04
Jun-04
Jul -04
Aug-04
Sep-04
Oct -04
Dec-04
Jan-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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Feb Apr May Jun Jul Aug Sep Oct Dec Jan Feb
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2004 2005
7th
6th
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4th
3rd
2nd
1st
G
Important Caveats• Although the techniques displayed here are
powerful, there are some downsides to this approach– Time involved to create assemble data and create non-
standard 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)
37.5062.50305080October 2005
43.4856.52303969September 2005
27.0372.97205474August 2005
35.7164.29305484July 2005
48.7251.28384078June 2005
43.6256.38415394May 2005
%With Lab Violations
%Without Lab Violations
# With Lab Violations
#Without Lab Violations
Total PI’s
•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:
Comprehensive Laboratory Inspection Program (CLIP) Activities and Outcomes, 2005
Month in Number of Principle Inspections InspectionsYear 2005 Investigators Inspected Without Violations 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
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May Jun Jul Aug Sep Oct Nov DecMonths within Calendar Year 2005
No.
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Number with violations
2005 Collaborative Laboratory Inspection Program (CLIP) Inspection Activities and Compliance Findings
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May Jun Jul Aug Sep Oct Nov DecMonths within Calendar Year 2005
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Number without violations
Number with violations
Figure 3. Receipt of Radioactive Material
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FY00 FY01 FY02 FY03 FY04
Num
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Non-MedicalMedicalTotal
Fig. 3. Receipts of Radioactive Materials
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FY 00 FY 01 FY 02 FY 03 FY 04 FY 05 FY 06
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Number of medical use radioactive material receipts
Number of non-medical use radioactive material receipts
Fig. 3. Receipts of Radioactive Materials
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FY 00 FY 01 FY 02 FY 03 FY 04 FY 05 FY 06
Fiscal Year
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Number of medical use radioactive material receipts
Number of non-medical use radioactive material receipts
OSHA LAB STANDARD & EPA COMPLIANCE
0255075
100125150175200225250275300325350
2004 2005
labs audited Total # of labs # in compliance
Results of University EH&S Lab Inspection Program, 2003 to 2005
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2003 2004 2005 2006 2007
Calendar Year
Num
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s
Number of labs inspected and no violations detected
Number of labs inspected and one or more violation detected
Number of labs existing but not inspected
Note: 33 labs added to campus in 2005, increasing total from
269 to 302.
2005 Workers' Compensation by Injury Type
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Burn/ScaldCaught InCut, Puncture, ScrapeFall, Slip, TripMVAStrainStrike AgainstStruck ByRub/AbradedMisc.
2005 Total Number of Monthly Workers Compensation Claims inclusive of the three most frequent identifiable classes of injuries
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Building Related Programs
-100
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Fire Ext. SystemsFire ExtinguishersFire Related IncidentsAsbestos Projects
Fire Extinguisher Systems
Fire Extinguishers Fire Related Incidents
AsbestosProjects
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
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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
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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
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$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
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2001 2002 2003 2004 2005 2006 2007 2008
Fiscal Year
Dol
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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
0
5
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Care
er F
TE
1990
1992
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Fiscal Year
EH&S Staffing Trends
EHS StaffBudget AugmentsBudget Cuts
UCR EH&S Staff, Extramural Research Funding and Grant Awards
418
457
498484
559
529 523
583
622 619 610
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
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EHS Staff; Extram
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ards-Million $
Number of Awards
Grants in Millions $
EHS Career Staff
Campus Sq. Footage & EHS Staffing
72,964
55,200
29,700
20,000
30,000
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50,000
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70,000
1990 2005 2010
Fiscal YearG
SF in Tens of Thousands
10.00
20.00
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EHS
FTE
EHS Staffing & Student Growth
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15,666
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-
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20,000
1990 2005 2010
Fiscal Year
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All Students
EHS Staff
UCR Campus Growth Indicators Compared to EH&S Staffing
Campus Gross Square Footage
0
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1990 1995 2000 2005 2010
Years
Squ
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Student Population
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1990 1995 2000 2005 2010
Years
Num
bers
of S
tude
nts
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
Dol
lars
EH&S Staffing
0
5
10
15
20
25
1990 1995 2000 2005 2010
Years
Num
ber o
f Sta
ff
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
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400
0 15 30 45 60 75Time in minutes
ppm
Qua
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Am
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0
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0 15 30 45 60 75Time in minutes
ppm
Qua
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Am
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ium
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e
EPA Limit EPA Limit
*Towels removed and rinsed at each interval
6
7
8
9
10
ANNUAL SPH FACULTY ACTIVITIES PEER REVIEW RESULTS FOR ROBERT EMERY 15% FACULTY APPOINTMENT
YEAR 1999 2000 2001 2002 2003 2004
TEACHING 8.86 8.33 8.16 8.25 8.5 8.85
RESEARCH 8.56 9.33 8.85 8.65 8.44 6.75
SERVICE 8.78 8.33 9.06 9.28 9.2 8.6
OVERALL 8.62 8.5 8.78 8.63 8.8 8.09
1 2 3 4 5 6 7 8Note:Emery ranked as Assistant Professor 1999-2000, promoted to Associate Professor in 2002.
Outstanding
Excellent
Good
Acceptable
Annual SPH Faculty Activities Peer Review Results for Emery(15% Faculty Appointment)
Teaching
6
7
8
9
10
1999 2000 2001 2002 2003 2004 2005
Service
6
7
8
9
10
1999 2000 2001 2002 2003 2004 2005
Overall
6
7
8
9
10
1999 2000 2001 2002 2003 2004 2005
Research
6
7
8
9
10
1999 2000 2001 2002 2003 2004 2005
Outstanding
Excellent
Acceptable
Good
Asst Professor Assoc Professor