radiation safety measures and metrics that matter! robert emery, drph, chp, cih, csp, rbp, chmm,...

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?


• 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?


• 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

• 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?”

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

0

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Contractor Smoke/Fire

Spontaneous Maintenance


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Contractor Smoke/Fire Spontaneous Maintenance


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Sept Oct Nov Dec Jan Feb Mar Apr May Jun Jul Aug

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of A

larm

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Nu

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MaintenanceSpontaneousSmoke/FireContractor

Results of the Great UTHSC-H Nuisance Fire Alarm Challenge (FY04)

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Nu

mb

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of A

larm

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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


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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)

0

200

400

600

800

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

Ann

ual r

adia

tion

dose

in m

illire

m

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

Upper management for various backgrounds does not understand the concept of a “broad license”

Such understanding is important for continued funding for both permit fees and support activities

Fig. 1 Summary of UTHSCH Broad Scope Radioactive Material License Possession Limits,

Collective Sublicensee Possession Limits and Actual On-hand Collective Inventory(a)

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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

ivit

y (C

i)

Broad scope license possession limit

Collective sublincensee possesion limit

Actual amount on-hand

(a) Data for August 2002

Example 3: 10 Year Prospectus

Various stakeholders don’t understand radiation safety program activities and how they relate to research enterprise

$0$20$40$60$80

$100$120$140$160

1992 1994 1996 1998 2000 2002

Res

earc

h E

xpen

dit

ure

s(M

illio

ns

$)

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1992 1994 1996 1998 2000 2002

Num

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of A

utho

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d U

sers

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1992 1994 1996 1998 2000 2002# of

Dos

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Issu

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$0

$50,000

$100,000

$150,000

$200,000

$250,000

1992 1994 1996 1998 2000 2002Rad

Was

te E

xpen

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ure

s

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)

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

•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

0

10

20

30

40

50

60

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May Jun Jul Aug Sep Oct Nov Dec

Months within Calendar Year 2005

No.

of P

rinci

pal I

nves

itgat

or In

spec

tions

Number without violations

Number with violations

Figure 3. Receipt of Radioactive Material

0

1000

2000

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4000

5000

6000

FY00 FY01 FY02 FY03 FY04

Nu

mb

er

of

Re

ce

ipts

Non-Medical

Medical

Total

Fig. 3. Receipts of Radioactive Materials

0

1,000

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6,000

FY 00 FY 01 FY 02 FY 03 FY 04 FY 05 FY 06

Fiscal Year

Nu

mb

er

of r

ece

ipts

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 Routine Lab Inspection Program, 2003 to 2005

0

50

100

150

200

250

300

350

2003 2004 2005 2006 2007

Calendar Year

Num

ber o

f Lab

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.

Average Cost of Workers Compensation Claims By CausePeriod FY01 - FY06

$0.00$5,000.00

$10,000.00$15,000.00$20,000.00$25,000.00$30,000.00$35,000.00$40,000.00$45,000.00

Slip/tr

ip a

nd/o

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l – o

uts..

.

Slip/tr

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nd/o

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l – in

sid...

Strikin

g ob

ject

(inclu

ding.

..

Liftin

g/han

dling

obj

ect –

n..

Ove

ruse

/ove

rext

ensio

n/...

Illnes

s – d

ue to

repe

ate...

Type of Claim

Co

st o

f C

laim

Avg/Claim

#

$0

$5,000

$10,000

$15,000

$20,000

$25,000

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$35,000

$40,000

$45,000

Slips, trips, falls – inside

Cumulative trauma

Overextension, twisting

Slips, trips, falls – outside

Lifting/handling

Uncontrolled object

Average Cost of Workers Compensation Claims, by Cause, for Period FY01 - FY06

Average cost from total of 3 events




Average cost from total of 10

events

Average cost from total of 4

events

2006 Dental Injuries by Type

0

5

10

15

20

25

July

Augus

t

Septe

mbe

r

Octobe

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Novem

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Decem

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ch

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May

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Total

Month

Nu

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er o

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xpo

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s

Puncture cutlaceration

Needlestick

Reported Sharps Injuries by Type for Academic Year 2006 (total n = 22)

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JUL AUG SEP OCT NOV DEC JAN FEB MAR APR MAY JUN

Month of academic year 2006

Nu

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of r

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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

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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

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Num

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Required Portable Fire Extinguishers

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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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1999 2000 2001 2002 2003 2004 2005 2006 2007 2008

Fiscal Year

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igh

t in

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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

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$200,000

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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

$50,000

$100,000

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$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

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Month

Nu

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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

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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

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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

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19

90

19

91

19

92

19

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19

99

20

00

20

01

20

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05

20

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20

07

20

08

Fiscal Year

Nu

mb

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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)

Gulf Worker Benzene Exposure

0 10 20 30 40 50 60 70 80

0.0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1.0

1.1

1.2

OSHA Permissible ExposureLimit 1 ppm (maximum exposureallowed over 8 hour timeframe)

OSHA Action level 0.5 ppm(harmful level requiringprotection for workers )

Cristina Alvarez Graphic Assignment

Time Sample Taken (hours post leak event)

Sam

plin

g R

es

ult

(p

pm

)

radiation safety measures and metrics that matter! robert emery, drph, chp, cih, csp, rbp, chmm,...

Documents

radiation safety measures

radiation safety programs

radiation safety professionals

data display excellence

exploratory data analysis

interpreting multivariate

art of effective data

rates radiation dose