Radiation Safety Measures And Metrics That Matter! - HPS Chapters
Radiation Safety Measures and Metrics That Matter! Robert Emery, DrPH, CHP, CIH, CSP, RBP, CHMM, CPP, ARM Assistant 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
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 radiationrelated, 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 Annual radiation dose in millirem 6,000 Occupational dose limit 5,000 mrem/yr, beyond 360 mrem/yr background dose level 5,000 4,000 3,000 2,000 General public limit 100 mrem/yr beyond background dose level of 360 mrem/yr 1,000 Background radiation dose level 360 mrem/yr 0 North wall East wall South wall West wall Location of monitoring device on inside of vault wall
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) 20 19 18 17 16 15 14 Activity (Ci) 13 Broad scope license possession limit 12 Collective sublincensee possesion limit 11 10 Actual amount on-hand 9 8 7 6 5 4 3 2 1 0 H-3 N-13 C-14 Na-22 P-32 P-33 S-35 Cl-36 Radioisotope (a) Data for August 2002 Ca-45 Cr-51 I-125 Ce-141 Ra-226
Example 3: 10 Year Prospectus
1996 1998 2000 2002 700 600 500 400 300 200 100 0 1992 1994 1996 1998 2000 2002 Number of Authorized Users 1994 Rad Waste Expenditures 1992 # o f D o sim eters Issu ed Research Expenditures (Millions ) 160 140 120 100 80 60 40 20 0 250 200 150 100 50 0 1992 1994 1996 1998 2000 2002 1998 2000 2002 250,000 200,000 150,000 100,000 50,000 0 1992 1994 1996
Example 4 In 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 noncompliance 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 Number of Alarms 8 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 Number of Alarms 8 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
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) 1.00 0.90 0.80 0.70 0.60 0.50 UT Health Center Tyler (0.45) 0.40 UT Medical Branch Galveston (0.35) 0.30 UT HSC San Antonio (0.25) UT Southwestern Dallas (0.20) UT HSC Houston (0.16) UT MD Anderson Cancer Center (0.11) 0.20 0.10 0.00 2002 2003 2004 2005 2006 3 year period upon which premium is calculated 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 UTHSC-H First Reports of Injury, by Population Type (total population 8,832; employee population 4,425; student population 3,587; resident population 820) 800 700 600 500 Total (n 450) 400 300 Employees (n 260) 200 Residents (n 105) Students (n 85) 100 0 FY01 FY02 FY03 FY04 FY05 FY06 FY07
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 ) Pen t house - Jason Bibel 7 - Julei Br oussar d Feb-04 Apr -04 6 - Selome Ayele M ay-04 5 - Dit a Gear y Jun-04 Jul -04 4 - Leon Br own Aug-04 3 - Gamalai lTor r es Sep-04 Oct-04 2 - M at t hew Keck Dec-04 1 - Jason LeBlan c Jan-05 Feb-05 Gr oun d - Pet e M ar t ni ez Basemen t ( un der con st r uct oi n ) - Pet e M ar t ni ez 0 100 200 T ot a l Occl ude d Feet 300 400
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 Feb Apr May Jun Jul 2004 Aug Sep Oct Dec Jan Feb 2005
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
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. 0 Ja n Fe b M ar ch Ap ril M ay Ju ne Ju ly Au g Se pt O ct No v De c Number of Cases 25 Month
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
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
Figure 1: Laboratory Waste verses Total Waste Generated 200,000 180,000 160,000 140,000 120,000 100,000 80,000 60,000 40,000 20,000 0 1999 2000 2001 W astes Generated from Laboratory Operations W aste Generated from Administrative Departments W aste Generated from Renovation Projects Total W aste Generatation 2002 2003 2004 2005
Figure 1: Hazardous Waste Generation in Pounds by Type of Institutional Activity 200,000 Total hazardous waste generation in pounds 180,000 Weight in Pounds 160,000 140,000 120,000 Amount from laboratory operations 100,000 80,000 Amount from renovation projects 60,000 40,000 Amount from administrative departments 20,000 0 1999 2000 2001 2002 2003 2004 Fiscal Year 2005 2006 2007 2008
Figure 1: Laboratory Waste verses Total Waste Generated 300,000 250,000 200,000 150,000 100,000 50,000 0 FY00/01 FY01/02 FY02/03 FY03/04 Cost of W astes Generated from Laboratory Operations Cost of W aste Generated from Administrative Departments Cost of W aste Generated from Renovation Projects Total Cost of W aste Generatated by the University of Delaw are FY04/05 FY05/06
Figure 2: Annual Hazardous Waste Disposal Cost by Type of Institutional Activity 300,000 Total cost 250,000 Cost of waste from lab operations Dollars 200,000 150,000 100,000 Cost of waste from renovation projects Cost of waste from administrative departments 50,000 0 2001 2002 2003 2004 2005 Fiscal Year 2006 2007 2008
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 140 123 610 583 600 120 559 529 106 523 498 484 500 100 457 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 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 1990 2010 1995 2005 2010 Years 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 400 350 300 250 200 EPA Limit 150 100 50 0 ppm Quanternary Ammonium Chloride ppm Quanternary Ammonium Chloride 400 350 300 250 200 EPA Limit 150 100 50 0 0 15 30 45 60 75 0 Time in minutes *Towels removed and rinsed at each interval 15 30 45 Time in minutes 60 75
ANNUAL SPH FACULTY ACTIVITIES PEER REVIEW RESULTS FOR ROBERT EMERY 15% FACULTY APPOINTMENT Outstanding 10 9 Excellent 8 Good 7 Acceptable YEAR 6 1 2 3 1999 2000 2001 TEACHING 8.86 8.33 8.16 RESEARCH 8.56 9.33 8.85 SERVICE 8.78 8.33 9.06 OVERALL 8.62 8.5 8.78 4 5 Note: Emery ranked as Assistant Professor 1999-2000, promoted to Associate Professor in 2002. 6 7 8 2002 2003 2004 8.25 8.5 8.85 8.65 8.44 6.75 9.28 9.2 8.6 8.63 8.8 8.09
Annual SPH Faculty Activities Peer Review Results for Emery (15% Faculty Appointment) Teaching Outstanding 10 Excellent Good Acceptable Asst Professor Research Assoc Professor 10 9 9 8 8 7 7 6 6 1999 2000 2001 2002 2003 2004 2005 1999 2000 Service 10 9 9 8 8 7 7 6 6 2001 2002 2003 2004 2005 Overall 10 1999 2000 2001 2002 2003 2004 2005 1999 2000 2001 2002 2003 2004 2005
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
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