Draft

Advisory Board on Radiation and Worker Health

National Institute for Occupational Safety and Health

Review of ORAUT-OTIB-0081, Revision 04, “Internal 

Coworker Dosimetry Data for the Savannah River Site” 

Contract No. 75D30119C04183

Document No. SCA-TR-2019-SEC004, Revision 0

Prepared by

Bob Barton, CHP

Ron Buchanan, PhD, CHP

Harry Chmelynski, PhD 

Rose Gogliotti, MS

Joyce Lipzstein, PhD 

SC&A, Inc.

2200 Wilson Boulevard, Suite 300

Arlington, VA 22201-3324

September 4, 2019

DISCLAIMER

This is a working document provided by the Centers for Disease Control and Prevention (CDC) 

technical support contractor, SC&A for use in discussions with the National Institute for 

Occupational Safety and Health (NIOSH) and the Advisory Board on Radiation and Worker 

Health (ABRWH), including its Working Groups or Subcommittees. Documents produced by 

SC&A, such as memorandum, white paper, draft or working documents are not final NIOSH or 

ABRWH products or positions, unless specifically marked as such. This document prepared by 

SC&A represents its preliminary evaluation on technical issues.

NOTICE: This document has been reviewed to identify and redact any information that is

protected by the Privacy Act 5 U.S.C. § 552a and has been cleared for distribution.
Effective date: 9/4/2019 Revision No. 0 (Draft) Document No. SCA-TR-2019-SEC004 Page 2 of 79

NOTICE: This document has been reviewed to identify and redact any information that is protected by the 

Privacy Act 5 U.S.C. § 552a and has been cleared for distribution.

SC&A, Inc. Technical Support for the Advisory Board on Radiation and Worker Health’s Review 

of NIOSH Dose Reconstruction Program

Document Title Review of ORAUT-OTIB-0081, Revision 04, “Internal Coworker Dosimetry 

Data for the Savannah River Site”

Document Number SCA-TR-2019-SEC004

Revision Number 0 (Draft)

Supersedes N/A

Effective Date September 4, 2019

Task Manager Joe Fitzgerald, MS, MPH [signature on file]

Project Manager John Stiver, MS, CHP [signature on file]

Document Reviewer(s) John Stiver, MS, CHP [signature on file]

Joe Fitzgerald, MS, MPH [signature on file]

Record of Revisions

Revision Number Effective Date Description of Revision

0 (Draft) 9/4/2019 Initial issue
Effective date: 9/4/2019 Revision No. 0 (Draft) Document No. SCA-TR-2019-SEC004 Page 3 of 79

NOTICE: This document has been reviewed to identify and redact any information that is protected by the 

Privacy Act 5 U.S.C. § 552a and has been cleared for distribution.

Table of Contents

List of Tables................................................................................................................... 4

List of Figures.................................................................................................................. 4

Abbreviations and Acronyms........................................................................................... 6

1 Executive Summary ................................................................................................. 9

2 Introduction and Background ................................................................................. 12

3 Coworker Data Adequacy ...................................................................................... 14

3.1 Instrumentation and measurement techniques ................................................ 14

3.2 Treatment of censored data using imputation methods ................................... 21

3.3 Use of data less than the minimum detectable activity..................................... 31

4 Coworker Data Completeness ............................................................................... 37

4.1 Completeness of NOCTS data......................................................................... 37

4.2 Completeness of laboratory logbook data........................................................ 41

5 Evaluation of Coworker Stratification ..................................................................... 43

5.1 General comments on stratification of OTIB-0081 ........................................... 43

5.2 Evaluation of the identification of workers with the appropriate strata.............. 46

6 Review of Quality Assurance Assessment............................................................. 57

6.1 Completeness of SRS claims tracking system data......................................... 57

6.2 Completeness of SRS logbook data ................................................................ 63

6.3 SRS construction worker classification QA summaries.................................... 63

6.4 Construction worker determination QA summaries .......................................... 64

6.5 Summary and conclusions ............................................................................... 65

7 References............................................................................................................. 66

Attachment A: Disposition of SC&A’s OTIB-0081, Rev. 03 (SC&A, 2017a) Findings and 

Observations ................................................................................................................. 70

Attachment B: Disposition of SC&A’s ORAUT-OTIB-0075 Review Findings................. 75

Attachment C: NOCTS Claim Numbers Associated with Arbitrary Case IDs Used in 

Section 5.2 .................................................................................................................... 78
Effective date: 9/4/2019 Revision No. 0 (Draft) Document No. SCA-TR-2019-SEC004 Page 4 of 79

NOTICE: This document has been reviewed to identify and redact any information that is protected by the 

Privacy Act 5 U.S.C. § 552a and has been cleared for distribution.

List of Tables

Table 1. Date ranges of coworker intakes by radionuclide in OTIB-0081, rev. 04......... 12

Table 2. Description of the four main facets of the NIOSH coworker implementation 

guide ............................................................................................................................. 13

Table 3. Summary of data >1 dpm/d............................................................................. 19

Table 4. ROS lognormal parameter estimates for example in figure 3 with true values 

and maximum likelihood estimates (MLEs)................................................................... 22

Table 5. ROS lognormal parameter estimates for example in figure 4 with true values 23

Table 6. Simulated mean imputed values in lower tail of lognormal distributions for 

Group 1 and Group 2 (n1 = n2 = 100,000) ..................................................................... 28

Table 7. Simulated mean imputed values in lower tail of lognormal distributions for 

Group 1 and Group 3 (n1 = n3 = 100,000) ..................................................................... 28

Table 8. Sr-90 Type F gross beta urinalyses 1955–1965 50th percentile CTW ............ 34

Table 9. Co-60 Type M gross beta urinalyses 1955–1965 50th percentile CTW .......... 34

Table 10. Np-237 Type F gross alpha urinalyses 1961–1969 50th percentile nonCTW 35

Table 11. 10% enriched 12-year aged Type M plutonium 1954–1990 50th percentile 

CTW.............................................................................................................................. 35

Table 12. 10% enriched 12-year aged Type M plutonium 1954–1990 50th percentile 

nonCTW........................................................................................................................ 35

Table 13. Uranium Type S 1954 through 1990 50th percentile CTW............................ 36

Table 14. Uranium Type S 1954 through 1990 50th percentile nonCTW...................... 36

Table 15. CTW and nonCTW job titles as contained in OTIB-0081 .............................. 47

Table 16. Summary of strata comparison between OTIB-0081 disposition and SC&A 

analysis ......................................................................................................................... 53

Table 17. [Redacted in full]............................................................................................ 54

Table 18. Summary of contents of ORAUT-OTIB-0081, rev. 04, attachment A ............ 58

Table 19. Summary of ORAUT-0081, rev. 04, attachment A completeness test results58

List of Figures

Figure 1. Coefficient of variation (%) versus reported mean results for SC&A tables 1, 2, 

and 3 data with locally-weighted polynomial (LOWESS) regression line....................... 16

Figure 2. Coefficient of variation versus reported mean results for SC&A non-DTPA 

tables 1, 2, and 3 data and separate DTPA dataset, with locally-weighted polynomial 

(LOWESS) regression lines .......................................................................................... 18

Figure 3. Example of ROS for 100 lognormal[0, 1] samples with no nondetects........... 22

Figure 4. Example of ROS for 100 lognormal[0, 1] samples with 13 nondetects........... 23

Figure 5. ROS plot with 13 imputed values plotted in lower tail (triangles).................... 24

Figure 6. ROS plot for quarterly urine samples observed in two different groups with 30 

workers.......................................................................................................................... 25

Figure 7. ROS plot with imputed samples for each group of workers............................ 26

Figure 8. Distribution of imputed data for each group of workers .................................. 27

Figure 9. Mean of imputed values in the lower tail of a lognormal distribution as 

percentage of the censoring level for eight geometric standard deviations (GSD) and 

four censoring levels (CL) ............................................................................................. 30
Effective date: 9/4/2019 Revision No. 0 (Draft) Document No. SCA-TR-2019-SEC004 Page 5 of 79

NOTICE: This document has been reviewed to identify and redact any information that is protected by the 

Privacy Act 5 U.S.C. § 552a and has been cleared for distribution.

Figure 10. Median of imputed values in the lower tail of a lognormal distribution as 

percentage of the censoring level for eight geometric standard deviations (GSD) and 

four censoring levels (CL) ............................................................................................. 31

Figure 11. Trivalent coworker bioassay values during the SEC evaluation period 

compared to the minimum detectable activity ............................................................... 32

Figure 12. Total number of covered employment years for each claimant group.......... 38

Figure 13. Percentage of total covered employment years for each claimant group..... 39

Figure 14. Approximate total number of internally monitored employment years for each 

claimant group............................................................................................................... 40

Figure 15. Percentage of total covered employment years for each claimant group..... 41

Figure 16. Comparison of available trivalent logbook data versus the reported number of 

analyzed bioassay samples .......................................................................................... 42

Figure 17. Comparison of available neptunium logbook data versus the reported 

number of analyzed bioassay samples ......................................................................... 42

Figure 18. Excerpt from an industrial hygiene evaluation included in DOL case files 

concerning maintenance supervisors............................................................................ 48

Figure 19. Example of an EEOICPA occupational history interview form, showing list of 

job titles and dates of employment................................................................................ 50

Figure 20. Example of an EEOICPA occupational history interview form, showing 

example entry of building, work activity, years of employment, and frequency ............. 51

Figure 21. Example of an employment history record displaying date and occupation . 52

Figure 22. Histogram of simulated overall error rate for attachment A tests with 95% 

confidence interval and 99% UCL ................................................................................. 66
Effective date: 9/4/2019 Revision No. 0 (Draft) Document No. SCA-TR-2019-SEC004 Page 6 of 79

NOTICE: This document has been reviewed to identify and redact any information that is protected by the 

Privacy Act 5 U.S.C. § 552a and has been cleared for distribution.

Abbreviations and Acronyms

ABRWH Advisory Board on Radiation and Worker Health 

Am americium

Am/Cm/Cf americium/curium/californium

Bq becquerel 

BRS Board Review System

BS bone surface 

CATI computer-assisted telephone interview

CCDF complementary cumulative distribution functions 

CL censoring level

Co cobalt 

CoV coefficient of variation

Cs cesium

CTW construction trade worker

CW coworker 

d day 

DOE U.S. Department of Energy 

DOL U.S. Department of Labor 

dpm disintegrations per minute

dpm/d disintegrations per minute per day 

dpm/1.5L disintegrations per minute per 1.5 liter 

DTPA diethylenetriamine pentaacetic acid

E&I electrical and instrumentation

EE energy employee 

EEOICPA Energy Employees Occupational Illness Compensation Program Act 

FP fission products 

GM geometric mean

GSD geometric standard deviation

HP health physicist

HPRED Health Physics Radiological Exposure Database

ICRP International Commission on Radiological Protection 

ID identifier
Effective date: 9/4/2019 Revision No. 0 (Draft) Document No. SCA-TR-2019-SEC004 Page 7 of 79

NOTICE: This document has been reviewed to identify and redact any information that is protected by the 

Privacy Act 5 U.S.C. § 552a and has been cleared for distribution.

IMBA Integrated Modules for Bioassay Analysis

IREP Interactive RadioEpidemiological Program

L liter

LCL lower confidence limit

LOWESS locally-weighted polynomial 

LTPD lot tolerance percent defective

mBq millibecquerel

MDA minimum detectable activity

MFP mixed fission products 

mL milliliter

MLE maximum likelihood estimate 

MPM maximum possible mean

mR/hr milliroentgen per hour 

MSM master slave manipulator

μCi/L microcurie per liter

μg/L microgram per liter

N/A not applicable

nCi nanocurie 

NIOSH National Institute for Occupational Safety and Health

NOCTS NIOSH OCAS Claims Tracking System

nonCTW non-construction trade worker

Np neptunium 

ORAUT Oak Ridge Associated Universities Team

OTIB ORAUT technical information bulletin

pCi picocurie 

POC probability of causation

PRID payroll identification number 

Pu plutonium 

QA quality assurance

RBM red bone marrow 

ROS regression on order statistics

RPRT ORAUT report

SEC Special Exposure Cohort 
Effective date: 9/4/2019 Revision No. 0 (Draft) Document No. SCA-TR-2019-SEC004 Page 8 of 79

NOTICE: This document has been reviewed to identify and redact any information that is protected by the 

Privacy Act 5 U.S.C. § 552a and has been cleared for distribution.

Sr strontium 

SRDB Site Research Database

SRS Savannah River Site 

TWOPOS time-weighted one-person-one-statistic

U uranium 

UCL upper confidence limit 

WBC whole body count 
Effective date: 9/4/2019 Revision No. 0 (Draft) Document No. SCA-TR-2019-SEC004 Page 9 of 79

NOTICE: This document has been reviewed to identify and redact any information that is protected by the 

Privacy Act 5 U.S.C. § 552a and has been cleared for distribution.

1 Executive Summary

SC&A reviewed ORAUT-OTIB-0081, revision 04, “Internal Coworker Dosimetry Data for the 

Savannah River Site” (NIOSH, 2019a; hereafter “OTIB-0081”), with a focus on its adherence to 

the principles and guidance in the National Institute for Occupational Safety and Health 

(NIOSH) document, “Draft Criteria for the Evaluation and Use of Coworker Datasets (NIOSH, 

2015a). These general criteria include data adequacy, data completeness, evaluation of the 

monitoring program, and stratification, as summarized in section 2 of this report. 

SC&A’s primary concern in relation to data adequacy involves the treatment and manipulation 

of censored data (i.e., data that are listed less than the minimum detectable activity (MDA)). For 

certain contaminants, NIOSH employed an imputation method that resulted in modeled coworker 

excretion rates that were significantly lower than one-half the MDA in some cases (see findings 

2 and 3 and observations 1 and 2). Similarly, data for trivalent actinides were reported at values 

much less than the MDA, which resulted in comparable coworker excretion rates below the 

MDA. In an individual dose reconstruction context for monitored workers, such data would be 

evaluated by applying missed dose methodologies at one-half the MDA. Use of different 

approaches for monitored and unmonitored workers raises the question of fairness and equitable 

treatment of workers under the auspices of the Energy Employees Occupational Illness 

Compensation Program Act (EEOICPA). 

In addition, SC&A still has concerns about the observed variability in trivalent actinide bioassay 

data. Though SC&A recognizes that many of the observed samples would not be used due to the 

application of chelation techniques affecting that data, SC&A remains skeptical of the 

measurement technique, as even non-chelated samples showed nearly identical variation to the 

chelated samples. In addition, the reported MDA for trivalent actinides starting in 1971 was 

approximately a factor of 3 lower than the MDA reported in 1989 by the International 

Commission on Radiation Protection (ICRP) (see finding 1).

Regarding completeness, SC&A’s review of OTIB-0081 did not attempt to address whether the 

available internal monitoring data are sufficiently representative of the potentially exposed 

population as required by NIOSH (2015a). Determinations regarding the representativeness and 

completeness of the available dataset, specifically for workers on job-specific bioassay, is an 

ongoing issue that is currently being addressed in supplemental NIOSH evaluations that will 

undergo subsequent review by the Advisory Board on Radiation and Worker Health (ABRWH). 

However, there remain completeness items that are independent from the fundamental question 

of data representativeness and completeness that remain appropriate to OTIB-0081. Therefore, 

SC&A’s discussion of completeness as it relates to OTIB-0081 necessarily assumes, but does not

affirm, that the available data are representative and complete for the purposes of this review 

only.

In evaluating completeness as it applies in this narrow context, SC&A notes that a substantial 

portion of the claimant population was not included in the original data analysis (see finding 4). 

Inclusion of such data would not only improve the completeness and accuracy of the coworker 

estimates but also may obviate the need to combine data for multiple years due to an insufficient 

number of bioassay results. Regarding the logbook data used for evaluation of trivalent and 

neptunium coworker intakes, SC&A also notes that some years had apparent gaps in the number 
Effective date: 9/4/2019 Revision No. 0 (Draft) Document No. SCA-TR-2019-SEC004 Page 10 of 79

NOTICE: This document has been reviewed to identify and redact any information that is protected by the 

Privacy Act 5 U.S.C. § 552a and has been cleared for distribution.

of available monitoring results (see observation 3). While such gaps are not explicitly discussed 

in OTIB-0081, SC&A notes that a new report was recently issued by NIOSH concerning source 

term characterization of americium that may address the issue (NIOSH, 2019d). 

SC&A’s review of the monitoring protocol and stratification aspects of the coworker model 

details the difficulties in correctly designating construction trade workers (CTWs) from nonconstruction trade workers (nonCTWs) (see findings 5–6 and observation 6). However, the 

analysis of stratification presented in section 5 of this report does not directly address whether 

the chosen strata are appropriate in a Special Exposure Cohort (SEC) context. Specifically, this 

report does not address the issues associated with subcontract workers who were intended to be 

primarily monitored via the job-specific bioassay program versus those on a routine monitoring 

schedule. Additionally, statistically significant differences in strata between the operational 

workers, prime construction workers, and subcontract workers have not been established (see 

Observation 4). 

Such issues are currently under investigation by NIOSH, SC&A, and the Savannah River Site 

(SRS) work group via the recent issuance of ORAUT-RPRT-0092, “Evaluation of Bioassay Data 

for Subcontracted Construction Trade Workers at the Savannah River Site” (NIOSH, 2019c). 

Therefore, analysis and discussion beyond general commentary is beyond the purview of this 

report (see observation 5). 

Finally, SC&A’s evaluation of the quality assurance (QA) assessment provided in support of 

OTIB-0081 was favorable (see observation 7), with the added caveat that NIOSH is correct that 

the identified payroll ID errors did not materially affect the calculated coworker distributions. 

A summary of the findings and observations resulting from SC&A’s review of OTIB-0081, 

revision 04 is provided below for ease of reference: 

Finding 1: Although SC&A recognizes that incident-based sampling involving chelation is not 

considered in final coworker modeling, the removal of DTPA-influenced samples from 

consideration in the analysis of the high variability observed in trivalent actinide bioassay results 

has not been justified sufficiently. Evidence suggests the variation among DTPA and non-DTPA 

samples is nearly identical. Furthermore, OTIB-0081 has not provided any reference to justify 

the assumption that DTPA causes heterogeneity among a single urinalysis voiding. (See 

section 3.1.1.) 

Finding 2: Use of imputed values that are less than one-half of the MDA raises a fundamental 

fairness issue in that monitored workers who have bioassay results that are less than the MDA 

are assigned a missed dose in accordance with ORAUT-OTIB-0060, “Internal Dose 

Reconstruction” (NIOSH, 2018). Per that guidance, bioassay values that are censored are 

assumed to be equal to one-half of the MDA rather than the use of an alternate imputed value 

(see section 3.2). 

Finding 3: The sample comparison of coworker intakes to a missed dose method for uranium 

showed that the coworker model derived intakes were a factor of 4 or more higher than the 

missed dose approach. This illustrates the potential for inequity between the treatment of 
Effective date: 9/4/2019 Revision No. 0 (Draft) Document No. SCA-TR-2019-SEC004 Page 11 of 79

NOTICE: This document has been reviewed to identify and redact any information that is protected by the 

Privacy Act 5 U.S.C. § 552a and has been cleared for distribution.

unmonitored workers assigned coworker intakes and monitored workers with results less than the 

detection limit in some situations (see section 3.3).

Finding 4: The coworker analysis uses the internal monitoring for claimants for which data were 

available to NIOSH in approximately August 2011 (~4,000 claims). Since that time, 

approximately 2,000 additional claims have been submitted that could be used to augment the 

coworker dataset. Inclusion of these data would be especially important for the two contaminants 

that required a combination of multiple years for analysis due to lack of a sufficient number of 

data points (uranium and cesium) (see section 4.1).

Finding 5: Classification of a “Machinist” as a nonCTW in OTIB-0081 is inconsistent with its

classification in OCAS-PER-014, “Construction Trades Workers” (see section 5.2).

Finding 6: A targeted sampling comparing the OTIB-0081 strata designation (CTW or 

nonCTW) against two alternate sources for identifying worker job classification indicated that 

just over 9 percent of the entries appear to be in conflict when comparing the NIOSH and SC&A 

analyses (see section 5.2).

Observation 1: While the multiple imputation method is mathematically correct, it has the 

potential to result in biasing the simulated bioassay results unnecessarily low. Alternate 

approaches, such as the maximum possible mean method, which replaces censored data with the 

actual censoring limit (or alternately one-half the censoring limit), would solve the issues 

associated with datasets containing a large number of censored values in a claimant-favorable 

manner (see section 3.2). 

Observation 2: A scoping assessment of the use of coworker bioassay data that are significantly 

less than the MDA versus an alternate missed dose approach concluded that, while intakes and 

doses are significantly higher using a missed dose approach in most of the sample calculations, 

the overall effect on resulting probability of causation (POC) values was relatively minor, and, in 

most cases, the coworker-derived POC bounded the missed dose evaluation. This appears to be 

due to the effect the statistical distribution has on resulting POC values, namely, the use of a 

triangular distribution for missed dose evaluation versus a lognormal distribution for coworker 

data (see section 3.3).

Observation 3: Available trivalent logbook data show notable differences with the number of 

reported samples taken in 1980 and 1982. These years, and any changes in operations, are not 

discussed specifically in OTIB-0081. However, it is noted that a future NIOSH report on 

americium exposure potential at SRS is pending that may address the apparent gaps in the data 

(see section 4.2).

Observation 4: OTIB-0081 does not provide a statistical comparison of the two stratified groups 

as prescribed in the coworker implementation guide. The various coworker models were 

stratified based on the a priori assumption that exposure potential between CTWs and nonCTWs

was different (see section 5.1).

Observation 5: SC&A believes a quantitative assessment of available job plans, rather than a 

qualitative basis, is appropriate to determine that prime contractor and subcontractor CTWs are 
Effective date: 9/4/2019 Revision No. 0 (Draft) Document No. SCA-TR-2019-SEC004 Page 12 of 79

NOTICE: This document has been reviewed to identify and redact any information that is protected by the 

Privacy Act 5 U.S.C. § 552a and has been cleared for distribution.

part of the same exposure strata. Such an assessment has been performed by NIOSH, and a 

report of their findings has recently been issued (NIOSH, 2019d) (see section 5.1). 

Observation 6: SC&A acknowledges that there are inherent difficulties in correctly associating 

individual workers with the correct CTW/nonCTW strata. This is particularly true for job titles 

that could potentially be included in either stratum (e.g., 

). SC&A suggests a scoping analysis in which such borderline job 

titles are removed to ascertain the effect on the resulting distributions. Such an analysis would 

help determine whether current strata designations are sufficient or a more rigorous approach to 

individual job classification is warranted (see section 5.2). 

Observation 7: The results shown in attachment A of OTIB-0081 demonstrate a high degree of 

confidence that the acceptable error rates are within the goals established for each test. However, 

this conclusion is dependent on the assumption that payroll ID issues identified would not affect 

the resulting coworker distributions (see section 6.5).

2 Introduction and Background

NIOSH approved revision 04 of ORAUT-OTIB-0081, “Internal Coworker Dosimetry Data for 

the Savannah River Site,” on March 13, 2019 (NIOSH, 2019a). Hereafter, this document is 

alternately referred to as “the coworker model” in this report. Per the publication record provided 

in the coworker model, revision 04 was initiated to provide coworker intake rates for plutonium, 

uranium, neptunium, cesium, cobalt, and mixed fission products (MFP) in accordance with the 

coworker development and implementation guidelines documented in NIOSH 2015a (hereafter 

referred to as the “implementation guide”). The previous revision of the coworker model

(revision 03, NIOSH, 2016a) had developed similar coworker intake values for americium, 

thorium and tritium, which also appear in revision 04. SC&A previously reviewed revision 03 of 

the coworker model in March 2017 (SC&A, 2017a); attachment A discusses the resulting 

findings and observations from that review. Table 1 shows the date range for the calculated 

coworker intake values for each contaminant of interest.

Table 1. Date ranges of coworker intakes by radionuclide in OTIB-0081, rev. 04

Contaminant of 

interest Date range of coworker intakes Relevant sections of OTIB-0081, rev. 04

Americium 1/1/1964–12/31/1989 (nonCTW and CTW) 4.1, 5.1, F.1

Tritium 1/1/1954–12/31/1990 (nonCTW and CTW) 4.2, 5.2

Plutonium 1/1/1955–12/31/1990 (nonCTW and CTW) 4.3, 5.3, F.2

Uranium (as U-234) 1/1/1953–12/31/1990 (nonCTW)

1/1/1955–12/31/1990 (CTW)

4.4, 5.4, F.3

Uranium (as U-233) 1/1/1961–9/30/1972 (nonCTW and CTW) 4.4, 5.4, F.3

Mixed Fission Products * 1/1/1955–12/31/1990 (nonCTW and CTW) 4.5, 5.5, 4.7, 5.7, F.4, 

F.6

Cobalt 1/1/1955–12/31/1970 (nonCTW and CTW) 4.6, 5.6, F.5

Cesium 1/1/1966–12/31/1990 (nonCTW and CTW) 4.7, 5.5, F.6

Neptunium 1/1/1961–12/31/1989 (nonCTW and CTW) 4.8, 5.8, F.7

Thorium 10/1/1972–12/31/1989 (nonCTW and CTW) 4.9, 5.9, F.8

* Due to changing monitoring practices of MFPs at SRS, Sr-90 is used for intake assessment from January 1, 1955, 

to December 31, 1965, and Cs-137 is used for intake assessment from January 1, 1966 to December 31, 1990. 
Effective date: 9/4/2019 Revision No. 0 (Draft) Document No. SCA-TR-2019-SEC004 Page 13 of 79

NOTICE: This document has been reviewed to identify and redact any information that is protected by the 

Privacy Act 5 U.S.C. § 552a and has been cleared for distribution.

Although none of the intake assessments were extended past 1990, OTIB-0081 notes the 

following: 

The intake rates or dose for the last year listed may be extended to subsequent 

years as a measure favorable to the claimants. [NIOSH, 2019a, p. 90] 

It is SC&A’s understanding that this language was included so that the coworker methodology 

presented in OTIB-0081 could still be applied to the time period after 1990. This is common 

practice in dose reconstruction and is permitted provided it has been sufficiently established that 

doses did not increase following the coworker model. However, the potential for expansion of 

the coworker assessments into these later years will be considered by NIOSH pending 

acceptance of the current coworker methods in OTIB-0081. 

As noted previously, revisions 03 and 04 of the coworker model were initiated to assess 

coworker intakes in accordance with the guidelines and criteria developed in NIOSH 2015a. As 

the first of such coworker models developed using these criteria, the methods and resulting 

intakes calculated in OTIB-0081 can be considered the pilot study of the coworker 

implementation guide. 

The coworker implementation guide can be broken down into four main facets: data adequacy, 

data completeness, evaluation of the internal monitoring program, and worker stratification. 

These four facets, as described in NIOSH 2015a, are shown in table 2 with a brief description of 

the category as provided in that document. 

Table 2. Description of the four main facets of the NIOSH coworker implementation guide

Category Implementation guide description

Data adequacy “The measurement techniques employed must be evaluated to ensure that they are 

capable of quantitatively measuring the exposure of interest” (NIOSH, 2015a, p. 4).

Data 

completeness

“The amount of available monitoring data must be evaluated to determine if there 

are sufficient measurements to ensure that the data are either bounding or 

representative of the exposure potential for each job/exposure category at the 

facility” (NIOSH, 2015a, p. 5).

Evaluation of 

monitoring 

program

“A review of the program should be conducted to determine the basis for the 

selection of program participants. It must be established who was monitored and 

why they were monitored” (NIOSH, 2015a, p. 8).

Worker 

stratification

“The distribution of a potentially more highly exposed population should be 

evaluated as a separate standalone distribution in situations where: 1) accurate job 

categories and/or descriptions can be obtained for all workers making up the 

general coworker dataset; 2) there is reason to believe that one of the job 

categories is more highly exposed; and, 3) there were unmonitored workers in this 

job category” (NIOSH, 2015a, p. 10).

SC&A’s review of the coworker model is structured based on issues related to the four main 

facets of coworker model development rather than a radionuclide-specific review. However, 

radionuclide-specific issues are discussed under the individual coworker implementation 

categories as appropriate. Section 3 addresses standard data adequacy review concerning 

bioassay/in vivo measurement techniques. However, the adequacy issue also includes a 

substantive discussion of the use and manipulation of the available internal monitoring data in 

relation to the intended (and unintended) consequences under the auspices of the EEOICPA. 
Effective date: 9/4/2019 Revision No. 0 (Draft) Document No. SCA-TR-2019-SEC004 Page 14 of 79

NOTICE: This document has been reviewed to identify and redact any information that is protected by the 

Privacy Act 5 U.S.C. § 552a and has been cleared for distribution.

Section 4 evaluates and discusses the data completeness of the two primary data sources used in 

the coworker model development: claimant internal monitoring records and sitewide laboratory 

logbook records. Quality control related to data transcription and other issues is included as part 

of the coworker implementation guide under the category of data completeness. However, due to 

the extensive nature of QA procedures and reported results associated with the coworker model, 

the review of these methods is found separately in section 6. 

Section 5 addresses both the issues of the monitoring program evaluation and worker 

stratification. However, it should be recognized that issues regarding the veracity of the available 

coworker data are highly dependent on a pending evaluation by NIOSH concerning the exposure 

potential and job-specific monitoring protocols for subcontractors. Therefore, issues specifically 

associated with monitoring protocols and data representativeness are only discussed in a cursory 

manner. The review in section 5 mainly concentrates on stratification issues that are independent 

of any potential issues related to the validity of the monitoring program. 

Finally, attachments A and B discuss the findings and observations associated with previous 

SC&A reviews of revision 03 of the coworker model and ORAUT-OTIB-0075, “Use of 

Claimant Datasets for Coworker Modeling” (NIOSH, 2009), respectively (SC&A, 2017a; 

SC&A, 2010). These attachments are provided for ease of reference, with review comments and 

recommendations provided in the narrow context of their applicability to the SRS coworker 

models developed in OTIB-0081, revision 04. 

3 Coworker Data Adequacy

This section discusses issues related to measurement techniques and evaluates the available 

dataset and its manipulation in arriving at the contaminant intake values presented in the 

coworker model. Section 3.1 provides an overview of the measurement techniques used for each 

contaminant of interest and also contains an in-depth discussion of the issue of observed 

variation among available measurements of trivalent actinides. This issue has been discussed 

multiple times by the SRS and SEC Issues Work Groups, including meetings in February 2014 

(SRS Work Group, 2014b), March 2015 (SEC Issues Work Group, 2015), and August 2017 

(SRS Work Group & SEC Issues Work Group, 2017). 

Section 3.2 discusses the method used in the coworker model development of imputing bioassay 

values when a large portion of the dataset has been censored (i.e., a large portion of the available 

bioassay is reported as less than the MDA). Section 3.3 provides a set of sample calculations to 

evaluate the effect of using numerical values (whether imputed or actual reported values) that are 

significantly less than the MDA in comparison to missed dose approaches. 

3.1 Instrumentation and measurement techniques

3.1.1 Americium

Urinalysis of trivalent actinides dates back to at least to the mid-1960s. The earlier reporting 

levels varied from 1 to 3 disintegrations per minute per 1.5 liter (dpm/1.5L). In 1964, solid-state 

surface barrier detectors replaced the previous counting method for using alpha track counting 

(NIOSH, 2019a). The value of 3 disintegrations per minute per day (dpm/d) (1.35 picocuries 

(pCi)/d or 0.05 becquerel (Bq)/d) is noticeably high. If the urine concentration is 3 dpm/d for a 
Effective date: 9/4/2019 Revision No. 0 (Draft) Document No. SCA-TR-2019-SEC004 Page 15 of 79

NOTICE: This document has been reviewed to identify and redact any information that is protected by the 

Privacy Act 5 U.S.C. § 552a and has been cleared for distribution.

sample taken after continuous intake during 1 year of exposure, the corresponding committed 

equivalent dose to bone surface (BS) would be about 300 rem (also 17 rem to liver and 7 rem 

effective dose). 

In 1971, gross alpha counting on solid-state detectors was used, and reporting levels were listed 

as 0.3 dpm/1.5L (0.135 pCi/d, 0.005 Bq/1.5L, or 3E-3Bq/L). This reporting level is much lower 

than the one referenced by ICRP Publication 54 (ICRP, 1989; hereafter “ICRP 54”), which 

suggests a detection limit of 1E-2 Bq/L in urine using alpha spectrometry. By comparison, the 

reported MDAs for other U.S. Department of Energy (DOE) sites are: 

• 1.35 pCi/d at Los Alamos National Laboratory for 1958–1982 using chemical extraction 

and proportional counting (an order of magnitude higher than the reported SRS limit) 

(NIOSH, 2013) 

• 0.34 pCi/d at Rocky Flats Plant for 1971–1977 (a factor of 3 higher than the reported 

SRS limit) (NIOSH, 2014a) 

Such large differences between the reported measurement levels for SRS, ICRP 54, and other 

DOE sites is troubling for at least part of the 1970s. 

In 1990, a change in radiochemical processing resulted in an MDA of 0.15 dpm/d (0.068 pCi/d, 

0.0025 Bq/d, or 0.0017 Bq/L), which is even lower than the one specified in ICRP 54 (ICRP, 

1989). In 1995, alpha spectrometry was used for routine samples, and the MDA was 0.064 

dpm/L (1E-3 Bq/L or 0.029 pCi/L), the same as suggested in ICRP Publication 78 (ICRP, 1997; 

hereafter “ICRP 78”). 

One very specific concern voiced in previous discussions of data adequacy is the observed 

variability in multiple measurements of the same aliquot among the trivalent actinide (i.e., 

americium/curium/californium (Am/Cm/Cf)) bioassay measurements. An SC&A memorandum 

of February 24, 2014, to the SRS Work Group contained an examination of the raw americium, 

curium, and californium urinalysis data used to calculate thorium intakes for the SRS internal 

dose coworker study (SC&A, 2014). The logbooks contain multiple counts for each urine sample

beginning in 1969 and extending into the late 1980s. The examination focused on results greater 

than the MDA that exhibited a large variability between multiple counts of the same sample, or 

where the reported result was inconsistent with the individual sample counts. 

The SC&A review noted that individual urine samples might be counted anywhere from 1 to 10 

times, with 2 or 4 times being common. Large variability was observed in the results of these 

repeated counts of the same sample. SC&A also noted inconsistent reported results where the 

reported result does not match the average of the individual counts of the sample. The SC&A 

memorandum highlighted results with inconsistency or large variability in tables 1, 2, and 3 of 

the memorandum. Table 1 examined the counting data for recorded mean results greater than 

3 dpm/1.5L; table 2 for recorded mean results between 1 and 3 dpm/1.5L; and table 3 for 

recorded mean results between 0.32 and 1 dpm/1.5L. The tables include all data with recorded 

means greater than the MDA 
Effective date: 9/4/2019 Revision No. 0 (Draft) Document No. SCA-TR-2019-SEC004 Page 16 of 79

NOTICE: This document has been reviewed to identify and redact any information that is protected by the 

Privacy Act 5 U.S.C. § 552a and has been cleared for distribution.

The log-log plot in figure 1 shows an overview of the variability of data in the SC&A tables with 

more than 1 count per sample. The coefficient of variation (CoV), defined as the ratio of the 

standard deviation to the mean, is commonly used as a measure of the variability. The CoV is 

plotted on the vertical axis and is expressed in percentage terms. The recorded mean results in 

each table are plotted on the horizontal axis on the figure. 

The horizontal line at “CoV=100%” indicates a relatively high level of variability when the 

standard deviation of the counts is equal in size to the mean of the sample counts. Except for the 

data in table 3 with recorded mean result below 1 dpm/1.5L, only a small percentage of the 

samples show a CoV over 100 percent. The distribution of CoV is relatively constant at all levels 

of the mean. 

Figure 1. Coefficient of variation (%) versus reported mean results for SC&A tables 1, 2, and 3

data with locally-weighted polynomial (LOWESS) regression line

Attachment D of ORAUT-0081, revision 04 evaluates the results highlighted in the SC&A 

memorandum to determine the potential significance of this variability to the SRS coworker 

study. The evaluation addressed the impacts of removing data from chelated individuals. NIOSH 

summarized the rational for removing the chelated individuals as follows: 
Effective date: 9/4/2019 Revision No. 0 (Draft) Document No. SCA-TR-2019-SEC004 Page 17 of 79

NOTICE: This document has been reviewed to identify and redact any information that is protected by the 

Privacy Act 5 U.S.C. § 552a and has been cleared for distribution.

Chelation accelerates the removal of actinides from the body by chemically 

binding with the actinide, which produces a chemical compound more readily 

eliminated through urine or feces (or both). This chemical process perturbs the 

normal bodily excretion of actinides and can also result in heterogeneity of the 

actinide concentration in the urine. SRS commonly analyzed small aliquots of 

urine samples using a sample volume of 5 or 10 mL. When a small aliquot is 

taken from a urine sample, this heterogeneity can result in markedly different 

radionuclide concentrations in comparison with a different aliquot from the same 

urine sample. . . . 

Urinalysis results influenced by administration of DTPA have been removed from 

this revision of the coworker study. Therefore, the data from any other individuals 

whose urinalysis results were influenced by administration of DTPA do not need 

any further evaluation because they are excluded. [NIOSH, 2019a, pp. 151, 152] 

Figure 2 provides an overview of the variability of the diethylenetriamine pentaacetic acid

(DTPA)-influenced samples versus the non-DTPA-influenced samples. The plot in figure 2 is 

similar to the one in figure 1, except the data are divided into two sub-populations: DTPA and 

non-DTPA samples. Although NIOSH argues that the exclusion of the DTPA-influenced 

samples is due to their variability, figure 2 shows that the variability of the DTPA-influenced 

samples appears almost identical to the variability of the non-DTPA samples.
Effective date: 9/4/2019 Revision No. 0 (Draft) Document No. SCA-TR-2019-SEC004 Page 18 of 79

NOTICE: This document has been reviewed to identify and redact any information that is protected by the 

Privacy Act 5 U.S.C. § 552a and has been cleared for distribution.

Figure 2. Coefficient of variation versus reported mean results for SC&A non-DTPA tables 1, 2, 

and 3 data and separate DTPA dataset, with locally-weighted polynomial (LOWESS) regression 

lines

After removing data from chelated workers, the NIOSH evaluation only looked at results 

significantly greater than the MDA (greater than 1 dpm/d) to identify results with significant 

variation in multiple counts from the same sample. Results with significant variability were 

investigated further to attempt to determine the reason for this variability. 

The results of the analysis are presented in table D-1 of attachment D, reproduced here for 

convenience of the reader (see table 3). This table summarizes a subset of the data SC&A 

reviewed that was greater than 1 dpm/d and had high variability. 
Effective date: 9/4/2019 Revision No. 0 (Draft) Document No. SCA-TR-2019-SEC004 Page 19 of 79

NOTICE: This document has been reviewed to identify and redact any information that is protected by the 

Privacy Act 5 U.S.C. § 552a and has been cleared for distribution.

Table 3. Summary of data >1 dpm/d

Sample type

Total # of 

samples

# of samples with high 

variability (a)

All samples >3 dpm/d 220 28

Samples > 3 dpm/d w/o chelation 21 2

All samples between 1 and 3 dpm/d 116 29 (b)

Samples between 1 and 3 dpm/d w/o chelation 31 0

Source: NIOSH, 2019a, table D-1 

(a) Excluding high variability due to data entry issues.

(b) 14 of these 29 samples are from one person.

After exclusion of urinalysis results influenced by administration of DTPA, NIOSH reports that 

only 4 of the 52 samples that were >1 dpm/d and were unaffected by chelation had high 

variability. Two of those were characterized as highly variable due to data entry issues rather 

than with the site’s bioassay program. The remaining two cases of high variability (less than 

4 percent of samples that were above the MDA and not affected by chelation) had high 

variability due to potential issues with the site’s bioassay program. 

Based on this result, NIOSH concludes the following. 

The conclusion of the evaluation is that the occurrence of samples with significant 

intra-count variation is limited and that inclusion of these samples has an 

insignificant effect on the overall results. . . . 

 This low percentage of individual disc variability and uncertainty is subsumed 

under the statistical analysis of all the samples collectively. All of the 

uncertainties discussed by SC&A are much less than the minimum GSD of 3.0 

used for coworker study intakes. Therefore, the conclusion is that aliquot 

variability has an insignificant effect on the overall results and the data can be 

used as is. [NIOSH, 2019a, pp. 41, 153] 

After removing all DTPA-related samples, NIOSH has reduced the scope of the variability 

review to a handful of samples with no clear evidence of a problem. It should be noted that 

SC&A’s review of revision 03 of the coworker mode had requested that references be provided 

that demonstrate the effect of DTPA on the homogeneity of a single urinalysis voiding (see 

SC&A’s previous observation 1 in attachment A from the review of revision 03 of OTIB-0081).

Finding 1: Although SC&A recognizes that incident-based sampling involving chelation is not 

considered in final coworker modeling, the removal of DTPA-influenced samples from 

consideration in the analysis of the high variability observed in trivalent actinide bioassay results 

has not been justified sufficiently. Evidence suggests the variation among DTPA and non-DTPA 

samples is nearly identical. Furthermore, OTIB-0081 has not provided any reference to justify 

the assumption that DTPA causes heterogeneity among a single urinalysis voiding.

Finally, SC&A notes that the MDA reported for trivalent actinides at SRS starting in 1971 was 

approximately a factor of 3 lower than the MDA reported by ICRP in 1989 and Rocky Flats up 

until 1977. The reported SRS MDA is also factor of 10 lower than that reported at Los Alamos 
Effective date: 9/4/2019 Revision No. 0 (Draft) Document No. SCA-TR-2019-SEC004 Page 20 of 79

NOTICE: This document has been reviewed to identify and redact any information that is protected by the 

Privacy Act 5 U.S.C. § 552a and has been cleared for distribution.

National Laboratory. Based on these comparisons, such a low MDA should be only achievable 

from alpha spectrometry (see section 3.1.1). 

3.1.2 Tritiated water

According to OTIB-0081, in 1958, liquid scintillation counting was initiated, and the reporting 

level was 1 microcuries per liter (μCi/L) until February 1981, when it was reduced to 0.5 μCi/L. 

The reporting level was further reduced to 0.1 μCi/L in January 1986. ICRP Publication 10 

(ICRP, 1968; hereafter “ICRP 10”) suggests the use of liquid scintillation counting for 

measurement of tritium, with a limit of detection of 0.1 μCi/L. The reporting level given in the 

1990 technical basis manual is 0.02 μCi/L (740 Bq/L) (WSRC, 1990). ICRP 54 suggests a 

detection limit of 400 Bq/L for tritium (ICRP, 1989), and ICRP 78 suggests 100 Bq/L as the 

detection limit for tritium using liquid scintillation counting (ICRP, 1997). 

3.1.3 Plutonium

According to OTIB-0081, in 1968 and in 1970, the positive result level was 0.1 dpm/1.5L 

(0.045 pCi/1.5L). ICRP 10 suggests a detection limit for plutonium-239 (Pu-239) of 0.06 pCi/d 

(ICRP, 1968), which is similar to the SRS positive result level. OTIB-0081 describes the use of

alpha spectroscopy in the 1980s with reporting levels of 0.05 dpm/1.5L for Pu-238 

(0.55E-3 Bq/L) and 0.07 dpm/1.5L (0.77E-3 Bq/L) for Pu-239. Those limits of detection are 

much lower than the ones suggested in ICRP 54 of 1E-2 Bq/L (ICRP, 1989) and similar to the 

ones suggested in ICRP 78 of 1E-3 Bq/L (ICRP, 1997). Today the typical detection limit for 

Pu-238 and Pu-239 using alpha spectrometry is 0.3 millibecquerel per liter (mBq/L) (European 

Commission, 2018). 

3.1.4 Uranium

According to OTIB-0081, from the start up to the mid-1960s, uranium was measured in urine 

samples using gross alpha and alpha track counting with a reporting level of 0.15 dpm/1.5L 

(0.045 pCi/L), one half of the detection limit of 0.1 pCi/L suggested for uranium-233 (U-233), 

U-234, and U-235 in ICRP 10 (ICRP, 1968). The limits from the mid-1960s to 1982, using gross 

alpha on solid state detector, are more credible (1 dpm/1.5L or 0.3 pCi/L). From 1954 to 1982, 

both depleted and natural uranium were measured by fluorophotometric analysis, with a limit of 

detection similar to the one listed in ICRP 10 of 5 micrograms per liter (μg/L) (ICRP, 1968). 

From 1982 to 1986, delayed neutron analysis was adopted, but the detection limits for U-235 did 

not change (i.e. 1 dpm/L). From 1990 to 1994, the detection limit for enriched uranium was 

0.4 pCi/L (0.015 Bq/L), which is similar to the detection limits from the mid-1960s to 1982, and 

similar to the detection limit suggested for U-235 in ICRP 54 of 0.01 Bq/L (ICRP, 1989). From 

1994 to the present, the MDA is 0.036 pCi/L for U-235 and 0.032 pCi/L (0.0012 Bq/L) for 

U-234 and U-238 using alpha spectrometry. Those limits are similar to the ones suggested in 

ICRP 78, which reports 10 mBq/L for U-234, U-235, and U-238 (ICRP, 1997). 

3.1.5 Fission products (strontium-90)

OTIB-0081 states that from 1959 to 1966, the reporting levels for strontium-90 (Sr-90) were 

60 dpm/1.5L (1.8E-5 μCi/L). This reporting level is similar to the one suggested in ICRP 10 of 

1E-5 μCi/L (ICRP, 1968). 
Effective date: 9/4/2019 Revision No. 0 (Draft) Document No. SCA-TR-2019-SEC004 Page 21 of 79

NOTICE: This document has been reviewed to identify and redact any information that is protected by the 

Privacy Act 5 U.S.C. § 552a and has been cleared for distribution.

3.1.6 Cobalt-60

OTIB-0081 gives the cobalt-60 (Co-60) MDA as 0.5 nanocurie (nCi)/1.5L (12 Bq/L) for 1966–

1970, somewhat higher than the limit of 5 Bq/L suggested in ICRP 54 (ICRP, 1989). ICRP 10 

does not give limits of detection for Co-60 in urine. 

3.1.7 Cesium-137

According to OTIB-0081, cesium was measured using the SRS Whole Body Counting Facility, 

and the limit of detection was 1 nCi, which is 10 times lower than the limit of detection 

suggested in ICRP 10 (ICRP, 1968). 

3.1.8 Neptunium 

Neptunium was not really measured in urine at SRS after 1970. Up until 1970, the positive level 

was 0.1 dpm/1.5L (0.045 pCi/1.5L). ICRP 10 only gives whole body limits for neptunium 

detection. However, ICRP 78 gives a limit of detection of neptunium-237 (Np-237) in urine of

1E-3 Bq/L using alpha spectrometry (ICRP, 1997), which is equivalent to the positive level used 

at SRS.

3.2 Treatment of censored data using imputation methods

Bioassay results below a given threshold, which is often referred to as an MDA or a reporting 

threshold, are usually reported as less than that dose, or “less-than” doses. In statistics, the lessthan-MDA or less-than-reporting threshold data are said to be “censored.” Censored data are 

problematic because the result at a given time is not unambiguously defined if some of the data 

are censored. For example, table 4-5 of OTIB-0081, revision 04 lists the reporting levels of an 

enriched uranium urinalysis in the mid-1960s through 1982 to be 1 dpm/1.5 L. That means that 

results below the reporting threshold of 1 dpm/1.5 L were reported as <1 dpm/1.5 L, so if a true 

sample were 0.8 dpm/1.5L, it would be analyzed and reported as <1 dpm/1.5 L. When 

interpreting this result, it is impossible to know what the true concentration in a sample is 

because the “<” symbol indicates a range of possible values. Multiple censoring levels (CLs) are 

present in the coworker data.

To address the uncertainties introduced into the data due to the presence of censored data, 

NIOSH used a technique documented in ORAUT-RPRT-0096 (NIOSH, 2019b) for multiple 

imputation. Imputation is a technique that uses other values in the dataset and a model that

incorporates random variation to predict the value of the censored result. Repeating this 

imputation step multiple times, then averaging the results is known as multiple imputation. The 

method specified in ORAUT-RPRT-0096 has not to SC&A’s knowledge been applied to other 

internal coworker models in support the EEOICPA mission. ORAUT-RPRT-0096 was issued on 

January 24, 2019, and has not been formally reviewed by SC&A. Full review of this document is 

outside of the scope of this current evaluation; however, it was necessary to evaluate the method 

used in this document in the context that it is applied for developing the coworker models for 

SRS in OTIB-0081, revision 04. Multiple imputation was used to model censored results for the 

uranium, plutonium, fission products, and neptunium—but not americium—models. 

ORAUT-RPRT-0071, revision 00 (NIOSH, 2015b), first introduced the new procedure, utilizing 

multiple imputation methods for calculating external doses for workers who have censored data. 

ORAUT-RPRT-0071 applies the procedure to external coworker exposures. This document has 
Effective date: 9/4/2019 Revision No. 0 (Draft) Document No. SCA-TR-2019-SEC004 Page 22 of 79

NOTICE: This document has been reviewed to identify and redact any information that is protected by the 

Privacy Act 5 U.S.C. § 552a and has been cleared for distribution.

not been reviewed by SC&A. ORAUT-RPRT-0096 applies the multiple imputation methodology 

to internal exposures at three example facilities: uranium activity data at Y-12 for 1950 to 1984; 

uranium mass data at Fernald for 1970 to 1985; and americium-241 data at SRS for 1994 to 

2000. 

The multiple imputation procedure uses regression on order statistics (ROS) to fit a lognormal 

distribution to the uncensored data, then uses the fitted model to randomly impute values in the 

lower tail of the lognormal distribution as a substitute for the missing censored data. SC&A

examined the R code that does the imputation and duplicated the algorithm on a Microsoft Excel 

spreadsheet to determine its suitability for coworker model dose estimates in the presence of 

censored data. 

Figure 3 shows an example of using ROS to fit a lognormal distribution with no censored data. 

This plot is a logged version of the normal probability paper plots that were used before 

computers were available. After plotting the data, a line that best fits the data was drawn though 

the points to obtain estimates of the slope and the intercept of the regression line. In figure 3, 

Excel is used to obtain the same results. Table 4 shows the parameter estimates obtained with 

ROS, the true values of the parameters, and the maximum likelihood estimates (MLEs). There is 

good agreement between the MLEs and the ROS estimates.

Figure 3. Example of ROS for 100 lognormal[0, 1] samples with no nondetects

Table 4. ROS lognormal parameter estimates for example in figure 3 with true values and 

maximum likelihood estimates (MLEs)

Regression 

parameter

Estimate 

(log 

scale)

Lognormal 

parameter

ROS 

estimate

True 

value MLE

Slope 1.095 GSD 2.990 2.718 2.998

Intercept -0.084 GM 0.919 1 0.919
Effective date: 9/4/2019 Revision No. 0 (Draft) Document No. SCA-TR-2019-SEC004 Page 23 of 79

NOTICE: This document has been reviewed to identify and redact any information that is protected by the 

Privacy Act 5 U.S.C. § 552a and has been cleared for distribution.

Figure 4 shows an example of the ROS regression in the presence of censored data below the 

limits of detection of the measuring device. This procedure is not based on maximum likelihood, 

but it can be used with censored data. Table 5 shows the parameter estimates obtained with ROS 

and the true values of the parameters. Note that the MLEs cannot be computed due to the missing 

data. Note that the R2 for the regressions are not included in the tables because the x and y data 

pairs used in the ROS regression procedure are not independent. There is only one set of data, 

not two. The data have been sorted so that the y values (now called the “order statistics”) are 

always non-decreasing, and the x values are a function of the ranks of the data. As a result, yi | x

is not independent of yj | x. If i < j, then yi <= yj always, which is not the usual case for regression. 

Figure 4. Example of ROS for 100 lognormal[0, 1] samples with 13 nondetects

Table 5. ROS lognormal parameter estimates for example in figure 4 with true values

Regression 

parameter

Estimate 

(log scale)

Lognormal 

parameter

ROS 

estimate

True 

value MLE

Slope 1.103 GSD 3.012 2.718 NA

Intercept -0.088 GM 0.916 1 NA

Figure 5 shows an example of using the ROS regression estimates to randomly generate values

in the lower tail of the fitted lognormal distribution as a substitute for censored data below the 

CL. The R code provided by NIOSH was used for the imputation. The triangles in the lower tail 

of the distribution show these imputed values. ORAUT-RPRT-0096 uses an iterative procedure 

where one random imputed value is substituted into the dataset in place of each censored value; 

the time weighted one-person-one-statistic (TWOPOS) calculations are done for each worker. 

The procedure is then repeated K times with different random imputed tail values in each 

iteration to obtain K TWOPOS estimates. These estimates are averaged for each worker to obtain 

the final TWOPOS results for use in the next step of intake modeling. 
Effective date: 9/4/2019 Revision No. 0 (Draft) Document No. SCA-TR-2019-SEC004 Page 24 of 79

NOTICE: This document has been reviewed to identify and redact any information that is protected by the 

Privacy Act 5 U.S.C. § 552a and has been cleared for distribution.

Figure 5. ROS plot with 13 imputed values plotted in lower tail (triangles)

Figure 6 shows lognormal plots of simulated censored urinalysis data from two different 

hypothetical groups of 30 workers each over four quarters, for a total of 120 data points in each 

dataset. These groups may represent workers at two different facilities or in two different years at 

the same facility. Group 1 is assigned a lognormal[0, 1] distribution. The median for Group 2 is 

the same as the median for Group 1. The geometric standard deviation (GSD) for Group 2 was 

selected so the expected value for Group 2 is twice the expected value of Group 1. The data were 

censored at a CL of 0.5 dpm/1.5L, and only the uncensored data plotted in figure 6 are available 

to the intake modeling analyst.
Effective date: 9/4/2019 Revision No. 0 (Draft) Document No. SCA-TR-2019-SEC004 Page 25 of 79

NOTICE: This document has been reviewed to identify and redact any information that is protected by the 

Privacy Act 5 U.S.C. § 552a and has been cleared for distribution.

Figure 6. ROS plot for quarterly urine samples observed in two different groups with 30 workers

Figure 7 shows the application of the ROS multiple imputation procedure for these workers. 

Since these data were generated using a lognormal distribution, the regression lines fit the data 

very well. This is not usually the case. Although the shape of the distribution below the CL is 

unknown, the ROS procedure has the implicit assumption built in that the logarithm of the data is 

symmetrically distributed about the median. For example, if 5 percent of the workers are exposed 

at 10 times the median or higher in the upper tail of the distribution, NIOSH assumes, due to logsymmetry, that the 5 percent of workers in the lower tail of the distribution were exposed at a 

factor of 10 times below the median or lower. There is no obvious physical explanation for the 

assumption of log-symmetry. 
Effective date: 9/4/2019 Revision No. 0 (Draft) Document No. SCA-TR-2019-SEC004 Page 26 of 79

NOTICE: This document has been reviewed to identify and redact any information that is protected by the 

Privacy Act 5 U.S.C. § 552a and has been cleared for distribution.

Figure 7. ROS plot with imputed samples for each group of workers 

The imputation procedure is mathematically correct, if we assume that the unobserved values 

below the CL follow the same lognormal distribution that is fit to the detected values above the 

CL. Looking only at the detected values in plotted in figure 7, the assumption of symmetry about 

the median is not obvious. This crucial assumption of log-symmetry about the median is the 

basis for the imputation procedure. 

The imputed data in the lower tail of the distribution are depicted with hollow circles and 

triangles. Note that due to the assumption of symmetry, the substituted values for the Group 2 

workers are almost always below the substituted values for the Group 1 workers. Although the 

two groups of workers have the same median exposure, workers with censored data in Group 2 

are assigned lower imputed values than workers with censored values in Group 1 simply because 

they worked with other workers who had high exposures. This illogical outcome is the direct 

result of the assumption of symmetry. 

Figure 8 shows the distribution of imputed values for the two groups of workers. All values are 

below the CL of 0.5 dpm/1.5L. The value of CL/2 is shown with a broken line in the middle of 

the plots. The mean imputed value for the Group 1 workers is twice as high as the mean imputed 

value for the Group 2 workers. The outcome depicted in figure 8 is a result of one round of 

substituting an imputed value for each censored value for these workers. 
Effective date: 9/4/2019 Revision No. 0 (Draft) Document No. SCA-TR-2019-SEC004 Page 27 of 79

NOTICE: This document has been reviewed to identify and redact any information that is protected by the 

Privacy Act 5 U.S.C. § 552a and has been cleared for distribution.

Figure 8. Distribution of imputed data for each group of workers 

The above example led to a comparison of the true mean values in the lower tails of the two 

lognormal distributions. The mean value of the lower tail of the lognormal distribution does not 

have a simple formula for direct calculation. SC&A performed a simulation by selecting 100,000 

samples in the tail of each distribution and computing the sample mean for five different CL 

values. The procedure was repeated K = 30 times. Then, the average and standard deviations of 

the K mean values were calculated. The standard deviations were very small due to the large 

sample size used in the simulation. The resulting expected values for the lower tail of the two 

lognormal distributions and the ratio of these estimates are reported in table 6. At all CLs, the 

mean of the values imputed for Group 1 workers are about 30 percent higher than the mean of 

the values imputed for Group 2. Although these ratios are lower than the factor of 2 observed in 

the small-sample outcome in figure 7, the systematic bias of lower imputed values for Group 2 

workers remains due to the assumption of symmetry. 
Effective date: 9/4/2019 Revision No. 0 (Draft) Document No. SCA-TR-2019-SEC004 Page 28 of 79

NOTICE: This document has been reviewed to identify and redact any information that is protected by the 

Privacy Act 5 U.S.C. § 552a and has been cleared for distribution.

Table 6. Simulated mean imputed values in lower tail of lognormal distributions for Group 1 and 

Group 2 (n1 = n2 = 100,000)

CL Mean 

Group 1

Mean 

Group 2

Ratio of means 

(Group 1/Group 2) 

0.1 0.0741 0.0582 1.273

0.25 0.169 0.130 1.300

0.5 0.305 0.233 1.309

0.75 0.422 0.323 1.307

1 0.523 0.404 1.295

A third group of workers with the same median as Groups 1 and 2 but with an expected value 

that is three times the expected value of Group 1 was created for this simulation. Table 7 shows a 

comparison of the results for Group 1 and Group 3. The higher expected value for Group 3 

results in an increased disparity between these two groups. The ratios in the right-hand column 

indicate that the imputed values for the censored doses in Group 1 range from 40 percent to 

45 percent greater than the imputed values for the censored doses in Group 3. 

Table 7. Simulated mean imputed values in lower tail of lognormal distributions for Group 1 and 

Group 3 (n1 = n3 = 100,000)

CL Mean 

Group 1

Mean 

Group 3

Ratio 

Group 1/Group 3 

0.1 0.0741 0.0525 1.411

0.25 0.169 0.117 1.444

0.5 0.305 0.209 1.459

0.75 0.422 0.291 1.450

1 0.523 0.365 1.433

One scenario is that Group 1 and Group 2 are the same workers in two different years with the 

same median exposure in both years. Assume in the first year no workers had unusually high 

exposures, but in the second year some workers did have high exposures. The multiple 

imputation model will assign lower imputed doses to workers with censored data in the second 

year than to workers with censored data in the first year due to symmetry because a few 

coworkers had high doses in the second year. If a worker has censored data in both years, the 

average of the imputed values for the censored data in year 2 will be lower than in year 1, all due 

to the assumption of symmetry and that there were more coworkers with high exposures in 

year 2. 

From a more distant perspective, imputing dose estimates below the MDA may lead to cases 

where a worker’s unmonitored dose is unduly biased low because of the current imputation 

method. Use of the maximum possible mean (MPM) for TWOPOS, which was first introduced 

in ORAUT-RPRT-0053 (NIOSH, 2014b), is a more claimant-favorable approach. When 

applying TWOPOS with the MPM method, the CL is substituted for each censored value. Using 

the MPM solves the censored data problem in a very claimant-favorable way without imputing 

(i.e., substituting hypothetical simulated) numbers. Substituting the CL/2 for censored values is 
Effective date: 9/4/2019 Revision No. 0 (Draft) Document No. SCA-TR-2019-SEC004 Page 29 of 79

NOTICE: This document has been reviewed to identify and redact any information that is protected by the 

Privacy Act 5 U.S.C. § 552a and has been cleared for distribution.

less claimant favorable, but both approaches would lead to more equitable treatment of workers 

in Groups 1 and 2. 

Observation 1: While the multiple imputation method is mathematically correct, it has the

potential to result in biasing the simulated bioassay results unnecessarily low. Alternate 

approaches, such as the maximum possible mean method, which replaces censored data with the 

actual censoring limit (or alternately one-half the censoring limit), would solve the issues 

associated with datasets containing a large number of censored values in a claimant-favorable 

manner. 

Aside from the evaluation of the imputation method itself, the use of such methods to derive 

coworker urinalysis results that are less than the MDA creates a basic conflict between how data 

are used and interpreted for monitored and unmonitored workers. The basic underlying concept 

of a coworker model is that the unmonitored worker should have been monitored and thus should 

be assigned equivalent unmonitored doses as for the monitored worker. For a monitored worker, 

bioassay values that are censored are treated as missed doses and are evaluated at one-half of the 

MDA rather than an imputed value that falls somewhere between zero and one-half of the MDA.

Finding 2: Use of imputed values that are less than one-half of the MDA raises a fundamental 

fairness issue in that monitored workers who have bioassay results that are less than the MDA 

are assigned a missed dose in accordance with ORAUT-OTIB-0060 (NIOSH, 2018). Per that 

guidance, bioassay values that are censored are assumed to be equal to one-half of the MDA

rather than an alternate imputed value. 

There is no simple closed-form solution for the mean value of the imputed values in the lower 

tail of a lognormal distribution below the CL. SC&A performed a Monte Carlo integration to 

determine the mean of the imputed values in the lower tail of a lognormal distribution with a 

median value of 1 and seven different GSDs. All lognormal distributions may be scaled to have a 

median of 1 with a corresponding scaling of the CL. The integration procedure used 100 

iterations. In each iteration, 100,000 imputed values were selected randomly in the lower tail of 

the distribution. The 100 means of the imputed values from each iteration were then averaged to 

estimate the expected value. The mean values are bounded between 0 and the CL. Results are 

reported in figure 9, where the estimated mean is expressed as a percentage of the CL and is 

plotted as a function of the GSD for four CLs. The selected values of the CL range from 

25 percent of the median up to 100 percent of the median. 

The upper two plots are for CLs equal to 25 percent or 50 percent of the median. The two lower 

plots are for CLs equal to 75 percent or 100 percent of the median. The estimated mean is 

expressed as a percentage of the CL and is plotted as a function of the GSD. The mean of 

imputed values is higher than one-half of the CL for GSDs less than or equal to 3, and less than 

one-half of the CL for GSDs greater than or equal to 4 (or greater than or equal to 5 for 

CL = 0.25). Note that the mean imputed value always decreases as a function of the GSD at all 

CLs. The mean imputed value at a GSD of 15 is much smaller than the mean imputed value at a 

GSD of 1.5 or 2 at all CLs. This result corroborates the results noted in the Group 1/Group2 

analysis above. If there are two groups of workers with the same median, the workers with 

missing data in the group with a lower GSD will be assigned higher imputed values on average 

than workers with missing data in the group with a higher GSD. 
Effective date: 9/4/2019 Revision No. 0 (Draft) Document No. SCA-TR-2019-SEC004 Page 30 of 79

NOTICE: This document has been reviewed to identify and redact any information that is protected by the 

Privacy Act 5 U.S.C. § 552a and has been cleared for distribution.

Figure 9. Mean of imputed values in the lower tail of a lognormal distribution as percentage of 

the censoring level for eight geometric standard deviations (GSD) and four censoring levels 

(CL)

SC&A performed another simulation to evaluate the median imputed values. The results of this 

analysis are shown in figure 10. In the upper two plots for CLs equal to 25 percent or 50 percent

of the median imputed values are higher than CL/2 except for GSD = 5 in the upper right-hand 

plot. The lower two plots are for CLs equal to 75 percent or 100 percent of the median. The 

median imputed values are higher than CL/2 for GSDs of 3 or less and are less than CL/2 for the 

higher GSDs. Again, the median imputed value always decreases as a function of the GSD at all 

CLs. The median imputed value at a GSD of 15 is much smaller than the mean imputed value at 

a GSD of 1.5 or 2 at all CLs. At the higher GSDs, the median imputed value is less than CL/5 

(i.e., less than 20 percent of the CL). 
Effective date: 9/4/2019 Revision No. 0 (Draft) Document No. SCA-TR-2019-SEC004 Page 31 of 79

NOTICE: This document has been reviewed to identify and redact any information that is protected by the 

Privacy Act 5 U.S.C. § 552a and has been cleared for distribution.

Figure 10. Median of imputed values in the lower tail of a lognormal distribution as percentage 

of the censoring level for eight geometric standard deviations (GSD) and four censoring levels 

(CL)

3.3 Use of data less than the minimum detectable activity

As discussed previously in section 3.2, NIOSH has developed methods to impute numerical 

bioassay values when the data are reported as less than the limit of detection. In addition to 

imputed values for uranium, plutonium, fission products, neptunium, trivalent actinide data 

(Am/Cm/Cf) were reported in the source records at values less than the detection limit. The use 

of imputed values and recorded values that are less than the detection limit results in estimates of 

coworker excretion rates that are sometimes much less than the detection limit. For example, 

figure 11 shows the calculated coworker excretion rates for Am/Cm/Cf at the 50th percentile as 

compared to the MDA. For individual dose reconstructions involving monitored workers, 

bioassay values that are less than the limit of detection are treated as a “missed dose” per the 

guidelines in ORAUT-OTIB-0060 (NIOSH, 2018). 
Effective date: 9/4/2019 Revision No. 0 (Draft) Document No. SCA-TR-2019-SEC004 Page 32 of 79

NOTICE: This document has been reviewed to identify and redact any information that is protected by the 

Privacy Act 5 U.S.C. § 552a and has been cleared for distribution.

Figure 11. Trivalent coworker bioassay values during the SEC evaluation period compared to 

the minimum detectable activity

To better understand the effect of using bioassay values less than the detection limit (whether 

imputed or actual), SC&A performed sample calculations using the coworker data developed in 

OTIB-0081 compared to the alternate method of evaluating missed dose as outlined in ORAUTOTIB-0060. This section summarizes SC&A’s analyses of coworker verses missed intakes, 

doses, and POC values for several radionuclides and target organs.

To compare the results of using coworker data versus assigning missed dose in a potential dose 

reconstruction process for workers at SRS, SC&A used coworker data and one-half the recorded 

bioassay MDA values in the Integrated Modules for Bioassay Analysis (IMBA) program to 

predict intakes. SC&A then used these predicted intakes in IMBA to derive annual organ doses 

and then used these organ doses in Interactive RadioEpidemiological Program (IREP) tables to 

determine POC values. SC&A performed these analyses for two hypothetical workers at SRS 

working side by side for the same time period: one without any bioassay data (i.e., coworker data 

would be used in a dose reconstruction for this worker), and one monitored yearly with all results 

<MDA for the radionuclide of interest (i.e., missed dose would be assigned in a dose 

reconstruction for this worker). SC&A analyzed a beta emitter (Sr-90), a gamma/beta emitter 

(Co-60), and alpha emitters (Np-237, uranium, and plutonium). SC&A used CTW and nonCTW 

data. SC&A used a variety of target organs, both systemic and nonsystemic. SC&A performed 

the following steps in these analyses.
Effective date: 9/4/2019 Revision No. 0 (Draft) Document No. SCA-TR-2019-SEC004 Page 33 of 79

NOTICE: This document has been reviewed to identify and redact any information that is protected by the 

Privacy Act 5 U.S.C. § 552a and has been cleared for distribution.

3.3.1 Derivation of intake values

CW data: SC&A used annual urine excretion 50th percentile values from OTIB-0081 tables 4-7, 

4-8, and 4-11 for Sr-90, Co-60, and Np-237, respectively, as bioassay data input into IMBA to 

confirm NIOSH’s coworker intake values in table F-14 for Sr-90, table F-17 for Co-60, and table 

F-21 for Np-237. Intake values for uranium and plutonium were selected from table 5-8, 

table 5-11, and table 5-4. The isotopic composition of plutonium was assumed to be 10 percent

12-year aged plutonium using guidance from table 4.1.1-3 of the SRS site profile (NIOSH, 

2005).

Missed intakes using MDA data: SC&A used one-half the most appropriate (and/or averaged) 

MDA values from recorded bioassay data for 1955–1969 that were available in the SRS files on 

the ABRWH server as bioassay input into IMBA to derive the projected annual intake values for 

Sr-90, Co-60, and Np-237 for a worker with all bioassay results less than the MDA value. 

Additionally, SC&A modeled intakes from 1955–1990 using half of the reporting values from 

the SRS site profile table 4.1.1-4 assuming 100 percent U-234 and table 4.1.1-1 for 10 percent

12-year aged plutonium (NIOSH, 2005). 

The missed intakes derived using one-half the MDA values were approximately 1.5 to 2.5 times 

the value derived using coworker data, depending on the radionuclide. 

3.3.2 Derivation of organ dose

CW data: SC&A used the derived Sr-90 intake values for CTWs (table 4-7 of OTIB-0081) for 

the period 1955–1965 to calculate the annual doses and total dose to the red bone marrow 

(RBM), BS, colon, and skin. SC&A used the derived Co-60 intake values for CTWs (table 4-8 of 

OTIB-0081) for the period 1955–1965 to calculate the annual doses and total dose to the RBM, 

BS, liver, and kidneys. SC&A used the derived Np-237 intake values for nonCTWs (table 4-11 

of OTIB-0081) for the period 1961–1969 to calculate the annual doses and total dose to the 

RBM, liver, colon, and skin. 

SC&A used the derived Type S uranium 50th percentile intake rates from table 5-8 (for 

nonCTW) and table 5-11 (for CTW) for 1955 through 1990 to calculate the annual organ doses 

assuming a diagnosis date 10 years following the last exposure. Similarly, SC&A used the 50th 

percentile Type M plutonium intake values for nonCTWs and CTWs from table 5-4 for 1955 

through 1990 to calculate the annual organ doses assuming a diagnosis date 10 years following 

the last exposure. Dose was modeled to the skin, RBM, colon, and kidney for both uranium and 

plutonium exposures. 

Missed dose: SC&A used the derived Sr-90 intake values for CTWs (derived from using onehalf the recorded bioassay MDA values) for the period 1955–1965 to calculate the annual doses 

and total dose to the RBM, BS, colon, and skin. SC&A used the derived Co-60 intake values for 

CTWs (derived from using one-half the recorded bioassay MDA values) for the period 1955–

1965 to calculate the annual doses and total dose to the RBM, BS, liver, and kidneys. SC&A 

used the derived Np-237 intake values for nonCTWs (derived from recorded bioassay MDA 

values) for the period 1961–1969 to calculate the annual doses and total dose to the RBM, liver, 

colon, and skin. SC&A used the intake values derived from the reporting levels for uranium and 
Effective date: 9/4/2019 Revision No. 0 (Draft) Document No. SCA-TR-2019-SEC004 Page 34 of 79

NOTICE: This document has been reviewed to identify and redact any information that is protected by the 

Privacy Act 5 U.S.C. § 552a and has been cleared for distribution.

plutonium CTW and nonCTWs from 1955 through 1990 to calculate the annual doses and the 

total dose to the skin, RBM, colon, and kidneys. 

The organ missed dose values calculated using one-half the MDA or reporting level values were 

approximately 0.12 to 5.1 times the organ dose values calculated using coworker data, depending 

on the radionuclide and organ involved (a summary of this information is provided in tables 1 

through 7). 

3.3.3 Derivation of POCs

POCs from CW data: SC&A used the calculated annual dose values (from coworker data) for 

each organ in an IREP table in conjunction with NIOSH-IREP v.5.8.1 to derive the POC for each 

organ for each radionuclide. The doses were assigned with a lognormal distribution with an 

uncertainty of 3 (OTIB-0081, section 5.0, p. 90) in the IREP tables.

POCs from missed dose: SC&A used the calculated annual missed dose values (derived from 

one-half the MDA values in the recorded bioassay data) for each organ in an IREP table in 

conjunction with NIOSH-IREP v.5.8.1 to derive the POC for each organ for each radionuclide. 

The doses were assigned as a triangular distribution with a minimum of 0, a mode based on onehalf the MDA, and a maximum based on the MDA (ORAUT-OTIB-0060, section 2.5.2, p. 14) in 

the IREP tables.

Tables 8–14 summarize the results of SC&A’s analyses of the total dose and POC values 

obtained using coworker data verses total dose and POC values obtained from missed dose using 

one-half the recorded bioassay MDA values for various organs and radionuclides.

Table 8. Sr-90 Type F gross beta urinalyses 1955–1965 50th percentile CTW

Organ 

CW data

total dose 

(rem)

Total 

missed 

dose (rem)

Dose ratio 

missed/CW

CW data

POC

POC based 

on missed 

dose

POC ratio 

missed 

dose/CW

RBM 0.085 0.210 2.5 0.11% 0.13% 1.2

Bone 0.183 0.452 2.5 0.33% 0.41% 1.2

Skin 3.13E-04 7.76E-04 2.5 0.00% 0.00% 1.0

Colon 2.04E-03 5.05E-03 2.5 0.01% 0.01% 1.0

As shown in table 8, the Sr-90 POC values derived using missed dose were the same, or slightly 

greater, than the POC values derived using coworker data, even though the doses using coworker 

data were a factor of 2.5 higher. 

Table 9. Co-60 Type M gross beta urinalyses 1955–1965 50th percentile CTW

Organ 

CW data

total dose 

(rem)

Total 

missed 

dose (rem)

Dose ratio 

missed/CW

CW data

POC

POC based 

on missed 

dose

POC ratio 

missed 

dose/CW

RBM 1.90E-03 9.72E-03 5.1 0.00% 0.01% N/A

Bone 1.77E-03 9.04E-03 5.1 0.00% 0.01% N/A

Liver 3.81E-03 1.95E-02 5.1 0.04% 0.09% 2.3

Kidneys 1.85E-03 9.49E-03 5.1 0.00% 0.01% N/A
Effective date: 9/4/2019 Revision No. 0 (Draft) Document No. SCA-TR-2019-SEC004 Page 35 of 79

NOTICE: This document has been reviewed to identify and redact any information that is protected by the 

Privacy Act 5 U.S.C. § 552a and has been cleared for distribution.

Table 9 indicates that the Co-60 POC values derived using either missed dose or coworker data 

were so low (near zero) that a meaningful comparison was not possible for the organs analyzed. 

In general, the POC values derived using missed dose were the same, or slightly greater, than the 

POC values derived using coworker data. It should be noted that the doses using the missed dose

method were over a factor of 5 higher than the coworker estimates. 

Table 10. Np-237 Type F gross alpha urinalyses 1961–1969 50th percentile nonCTW

Organ 

CW data

total dose 

(rem)

Total 

missed 

dose (rem)

Dose ratio 

missed/CW

CW data

POC

POC based 

on missed 

dose

POC ratio 

missed 

dose/CW

RBM 1.628 2.305 1.4 3.20% 2.71% 0.8

Liver 6.654 9.481 1.4 49.81% 44.70% 0.9

Skin 0.050 0.072 1.4 0.14% 0.12% 0.9

Colon 0.051 0.073 1.4 0.23% 0.18% 0.8

Table 10 shows that the POC values derived for Np-237 using missed dose were all slightly less 

than the POC values derived using coworker data.

Table 11. 10% enriched 12-year aged Type M plutonium 1954–1990 50th percentile CTW

Organ 

CW data

total dose 

(rem)

Total 

missed 

dose (rem)

Dose ratio 

missed/CW

CW data

POC

POC based 

on missed 

dose

POC ratio 

missed 

dose/CW

RBM 2.424 4.515 1.86 4.87 4.73 0.97

Kidney 0.243 0.456 1.88 1.16% 1.13% 0.97

Skin 0.080 0.144 1.81 0.26 0.24 0.92

Colon 0.081 0.146 1.81 0.37 0.35 0.95

Table 12. 10% enriched 12-year aged Type M plutonium 1954–1990 50th percentile nonCTW

Organ 

CW data

total dose 

(rem)

Total 

missed 

dose (rem)

Dose ratio 

missed/CW

CW data

POC

POC based 

on missed 

dose

POC ratio 

missed 

dose/CW

RBM 2.842 4.515 1.59 5.68% 4.73% 0.83

Kidney 0.285 0.456 1.60 1.35% 1.13% 0.84

Skin 0.094 0.144 1.54 0.31% 0.24% 0.77

Colon 0.095 0.146 1.54 0.43% 0.35% 0.81

As shown in tables 11 and 12, the POC values derived for plutonium using missed dose were all 

slightly less than the POC values derived using coworker data, even though the calculated doses 

for the missed dose method were approximately 50–90 percent higher than the coworker doses.
Effective date: 9/4/2019 Revision No. 0 (Draft) Document No. SCA-TR-2019-SEC004 Page 36 of 79

NOTICE: This document has been reviewed to identify and redact any information that is protected by the 

Privacy Act 5 U.S.C. § 552a and has been cleared for distribution.

Table 13. Uranium Type S 1954 through 1990 50th percentile CTW

Organ 

CW data

total dose 

(rem)

Total 

missed 

dose (rem)

Dose ratio 

missed/CW

CW data

POC

POC based 

on missed 

dose

POC ratio 

missed 

dose/CW

RBM 0.041 0.032 0.77 0.09% 0.03% 0.08

Kidney 0.165 0.137 0.83 0.82% 0.32% 0.39

Skin 0.011 0.006 0.59 0.04% 0.01% 0.25

Colon 0.036 0.029 0.82 0.24% 0.08% 0.33

Table 14. Uranium Type S 1954 through 1990 50th percentile nonCTW

Organ 

CW data

total dose 

(rem)

Total 

missed 

dose (rem)

Dose ratio 

missed/CW

CW data

POC

POC based 

on missed 

dose

POC ratio 

missed 

dose/CW

RBM 0.186 0.032 0.17 0.46% 0.03% 0.07

Kidney 0.691 0.137 0.20 3.91% 0.32% 0.08

Skin 0.054 0.006 0.12 0.29% 0.01% 0.03

Colon 0.116 0.029 0.25 0.75% 0.08% 0.11

Tables 13 and 14 indicate that for uranium, the POC values derived using missed dose were each

less than the POC values derived using coworker data. The difference in POC values derived 

using MDA and coworker data were even more pronounced in the sample calculation because 

the uranium coworker intakes were actually greater than those derived from MDA values in 

those examples. 

Except for uranium, the derived intake and dose values were greater using missed dose from 

recorded bioassay data compared to using coworker data. However, assigning a triangular 

distribution for missed dose values and assigning a lognormal distribution for coworker dose at 

the 50th percentile resulted in the POC values being similar for the conditions, radionuclides, 

and organs used in these analyses. The coworker intakes for uranium for both CTW and 

nonCTW were generally greater than half the MDA values; therefore, the resulting doses and 

POC values were consistently greater when compared to those derived using MDA data. 

Examination of several of the previous scenarios using the 95th percentile derived coworker 

intakes with the doses assigned as a constant resulted in greater POC values than using either the 

50th percentile coworker intakes or a missed dose approach. It is important to note that 

individual claim conditions have a large impact on the dose and POC assigned in a case. The 

above scenarios do not encompass the range of conditions seen in the dose reconstruction 

process and are intended to quantify the impact for sample scenarios.

Observation 2: A scoping assessment of the use of coworker bioassay data that are significantly 

less than the MDA versus an alternate missed dose approach concluded that, while intakes and 

doses are significantly higher using a missed dose approach in most of the sample calculations, 

the overall effect on resulting POC values was relatively minor and, in most cases, the coworkerderived POC bounded the missed dose evaluation. This appears to be due to the effect the 

statistical distribution has on resulting POC values, namely, the use of a triangular distribution 

for missed dose evaluation versus a lognormal distribution for coworker data. 
Effective date: 9/4/2019 Revision No. 0 (Draft) Document No. SCA-TR-2019-SEC004 Page 37 of 79

NOTICE: This document has been reviewed to identify and redact any information that is protected by the 

Privacy Act 5 U.S.C. § 552a and has been cleared for distribution.

Finding 3: The sample comparison of coworker intakes to a missed dose method for uranium 

showed that the coworker model derived intakes were a factor of 4 or more higher than the 

missed dose approach. This illustrates the potential for inequity between the treatment of 

unmonitored workers assigned coworker intakes and monitored workers with results less than the 

detection limit in some situations. 

4 Coworker Data Completeness

As noted in section 3.1 of OTIB-0081, two main data sources were used in the development of 

coworker intake assignments:

1. individual claimant internal monitoring data as found in the NIOSH OCAS Claims 

Tracking System (NOCTS)

2. laboratory logbooks containing americium and neptunium urinalysis results

For the case of the first dataset, NIOSH assumed the portion of the available claimant records 

used is a representative sample of the full dataset of worker monitoring records for SRS per the 

conclusions of ORAUT-OTIB-00751

 (NIOSH, 2009). Section 4.1 discusses the completeness of 

the NOCTS dataset. For the second dataset, the laboratory logbooks are considered the complete 

set of available monitoring records for the entire SRS worker population and are discussed in 

section 4.2. 

1 Some findings related to ORAUT-OTIB-0075 are still under discussion by the SRS and SEC Issues Work 

Groups. These findings are provided in attachment B for ease of reference.

4.1 Completeness of NOCTS data

Individual claimant records in NOCTS were evaluated for coworker assignment in OTIB-0081 

for six of the eight contaminants of interest: tritium, plutonium, uranium, MFPs, Co-60, and 

cesium-137 (Cs-137). As stated in section 3.1 of the coworker model, claimant records were 

used because a sitewide electronic database of internal monitoring records is not available for 

SRS until approximately 1991, which corresponds to the advent of the Health Protection 

Radiation Exposure Database. While the NOCTS compilation is not a complete set of SRS 

worker data, OTIB-0081 notes that NOCTS was “the best available compilation of data in a 

usable form (i.e., electronic spreadsheet or database)” (NIOSH, 2019a, p. 25).

It was noted in OTIB-0081 that claim numbers for SRS up to Claim 34999 were used in the 

coworker analysis. This corresponds to a total of 4,117 claimants; however, some claimants in 

this total would not be included due to the lack of internal monitoring or the temporal constraints 

of the covered employment (e.g., employed after 1990). This cutoff point was likely chosen 

based on the number of claims with internal dosimetry files available at the time the coworker 

assessment was first undertaken and corresponds to roughly August 2011. 

As of the writing of this report, an additional 2,133 claims have been submitted for SRS with 

individual monitoring records compiled and supplied by DOE. At face value, this could 

potentially represent a 50 percent increase in the available internal monitoring data for analysis 

in the coworker model. Therefore, it is important to understand the covered years of employment 

 
Effective date: 9/4/2019 Revision No. 0 (Draft) Document No. SCA-TR-2019-SEC004 Page 38 of 79

NOTICE: This document has been reviewed to identify and redact any information that is protected by the 

Privacy Act 5 U.S.C. § 552a and has been cleared for distribution.

and potential internal monitoring coverage represented by this latter group of claims. SC&A 

compared the covered employment years for both the analyzed group of claims (Claims 0–

34999) and the latter group of claims that could potentially be used to augment the coworker 

analysis (Claims 35000+). Figure 12 shows the number of years of covered employment for each 

group; figure 13 displays the same data as a percentage of the total for both groups. Interestingly, 

the number of claims with covered employment per year in the original group remained 

somewhat consistent throughout the period of interest, while the latter group of claims remained

consistent until the early 1970s, when a significant increase in covered years was observed for 

each subsequent year. While one might expect that claims filed more recently would have 

covered employment that was slightly biased toward later years, the significant increase in 

frequency is more likely driven by the granting of SEC Petition 103, which extends from 

January 1, 1953, through September 30, 1972. During the years after the SEC, the percentage of 

the total covered years of employment represented by the latter group ranged from roughly 

18 percent in 1973 to over 44 percent in 1990. 

Figure 12. Total number of covered employment years for each claimant group
Effective date: 9/4/2019 Revision No. 0 (Draft) Document No. SCA-TR-2019-SEC004 Page 39 of 79

NOTICE: This document has been reviewed to identify and redact any information that is protected by the 

Privacy Act 5 U.S.C. § 552a and has been cleared for distribution.

Figure 13. Percentage of total covered employment years for each claimant group

In addition to the comparison of covered employment between the original analyzed group 

(Claims 0–34999) and the latter group (Claims 35000+), SC&A performed a scoping tally of the 

number of claims in each group that had internal monitoring records during the period of interest. 

Similar to figures 12 and 13, figures 14 and 15 show the total number of claims with internal 

monitoring by year for each group and also the percentage of the total internally monitored years 

for both groups combined. SC&A did not attempt to parse the available internal monitoring data 

by contaminant or monitoring method (urinalysis versus whole body count). Not surprisingly, the 

trends in monitoring data closely mirror the observed trends in covered employment. 

While the effect of adding the additional claimant data since August 2011 to the current 

coworker distributions is not possible to quantify at this time, the evaluation of such data would 

clearly be beneficial from a completeness standpoint, given that a full analysis of the SRS

monitored population is not currently feasible prior to 1991. Furthermore, claimant data in 

NOCTS are already in an electronically useable format for analysis per OTIB-0081 (cited at the 

start of this section). 

Finally, the inclusion of additional claimant data into the coworker analysis may obviate the need 

to combine multiple years for evaluation. This is especially true for CTW analysis of uranium 

data in the 1980s because the additional claimant monitoring data are biased toward these later 

years. The additional data may also have an effect on the analysis of whole body counts for 
Effective date: 9/4/2019 Revision No. 0 (Draft) Document No. SCA-TR-2019-SEC004 Page 40 of 79

NOTICE: This document has been reviewed to identify and redact any information that is protected by the 

Privacy Act 5 U.S.C. § 552a and has been cleared for distribution.

cesium, though the years with limited data for that contaminant and analysis were prior to 1974. 

Evaluating coworker data on a year-by-year basis, or a shorter period if available, is preferable to 

combining years for analysis due to an insufficient number of workers in a given period. 

Figure 14. Approximate total number of internally monitored employment years for each 

claimant group 
Effective date: 9/4/2019 Revision No. 0 (Draft) Document No. SCA-TR-2019-SEC004 Page 41 of 79

NOTICE: This document has been reviewed to identify and redact any information that is protected by the 

Privacy Act 5 U.S.C. § 552a and has been cleared for distribution.

Figure 15. Percentage of total covered employment years for each claimant group

Finding 4: The coworker analysis uses the internal monitoring for claimants for whom data were

available to NIOSH in approximately August 2011 (~4,000 claims). Since that time, 

approximately 2,000 additional claims have been submitted that could be used to augment the 

coworker dataset. Inclusion of these data would be especially important for the two contaminants 

that required a combination of multiple years for analysis due to lack of a sufficient number of 

data points (uranium and cesium). 

4.2 Completeness of laboratory logbook data 

Laboratory logbook results were used in OTIB-0081 for coworker modeling of trivalent actinides 

(Am/Cm/Cf) and also for a portion of the period when neptunium monitoring was performed 

primarily by urinalysis (up to 1969). As opposed to the completeness issues associated with 

using only claimant internal monitoring records, the use of laboratory logbooks should contain a 

complete dataset of the entire monitored population at SRS. 

The most informative completeness test is to compare the number of bioassay results available 

for analysis to the number of bioassays that were reported to have been conducted during a given 

year. Figure 16 shows this comparison for trivalent actinides, and figure 17 for neptunium. 
Effective date: 9/4/2019 Revision No. 0 (Draft) Document No. SCA-TR-2019-SEC004 Page 42 of 79

NOTICE: This document has been reviewed to identify and redact any information that is protected by the 

Privacy Act 5 U.S.C. § 552a and has been cleared for distribution.

Figure 16. Comparison of available trivalent logbook data versus the reported number of 

analyzed bioassay samples

Figure 17. Comparison of available neptunium logbook data versus the reported number of 

analyzed bioassay samples
Effective date: 9/4/2019 Revision No. 0 (Draft) Document No. SCA-TR-2019-SEC004 Page 43 of 79

NOTICE: This document has been reviewed to identify and redact any information that is protected by the 

Privacy Act 5 U.S.C. § 552a and has been cleared for distribution.

For americium, the number of samples available for coworker modeling actually exceeded the 

number of reported bioassay samples in available health physics reports (the average over all 

years was 105 percent of the reported samples). Specific to the post-SEC period (after September 

1972), the number of available samples closely matched the number of reported samples. The 

notable exceptions occur in 1980 and 1982, when only 70 percent and 74 percent of the reported 

samples were identified in the available logbooks, respectively. These years are not specifically 

addressed in OTIB-0081, revision 04. 

Observation 3: Available trivalent logbook data show notable differences with the number of 

reported samples taken in 1980 and 1982. These years, and any changes in operations, are not 

discussed specifically in OTIB-0081. However, a future NIOSH report on americium exposure 

potential at SRS is pending that may address the apparent gaps in the data. 

The percentage of available neptunium urinalysis data shown in figure 17 shows that there is a 

significant completeness issue in 1963, when only 61 percent (544 of 898) of the reported 

urinalysis results were available. In addition, no comparison could be made for the years 1961 

and 1962 because the total neptunium bioassay samples analyzed in these years was not 

available. However, SC&A would note that this period is also covered by SEC-00103; thus, any 

deficiencies in completeness would only result in the proposed internal dose methodologies 

becoming invalid for noncompensable claims. For periods outside the established SEC, 

OTIB-0081 uses claimant whole body count data available in NOCTS. The completeness of 

NOCTS data is discussed in section 4.1 of this report. 

5 Evaluation of Coworker Stratification

The stratification of coworker models into different subgroups at a specific work site must be 

carefully evaluated when there is reason to believe that the different subgroups have appreciably 

different exposure potential. The coworker models developed in OTIB-0081 have elected to 

stratify the available coworker models into CTWs and nonCTWs. The following two subsections 

provides SC&A’s review and discussion of the stratification of the SRS coworker models. 

Section 5.1 provides general comments on the decisions and assumptions underlying NIOSH’s

decision to stratify calculated coworker intakes into the two subgroups. Section 5.2 describes 

SC&A’s evaluation of the ability to effectively identify workers and assign their internal 

monitoring results with the appropriate stratified dataset.

5.1 General comments on stratification of OTIB-0081

As noted in the introduction, the coworker implementation guide (NIOSH, 2015a) requires that 

coworker model stratification (i.e., the development of separate coworker distributions) must be 

evaluated when the following conditions exist: 

1) accurate job categories and/or descriptions can be obtained for all workers 

making up the general coworker dataset; 2) there is reason to believe that one of 

the job categories is more highly exposed; and, 3) there were unmonitored 

workers in this job category. [NIOSH, 2015a, p. 10] 

NIOSH (2015a) also states that once the distributions for each coworker strata have been 

developed, they must be evaluated to determine if there is an actual significant statistical 
Effective date: 9/4/2019 Revision No. 0 (Draft) Document No. SCA-TR-2019-SEC004 Page 44 of 79

NOTICE: This document has been reviewed to identify and redact any information that is protected by the 

Privacy Act 5 U.S.C. § 552a and has been cleared for distribution.

difference between the two (or more) worker populations. For the development of OTIB-0081, 

NIOSH has elected to use the a priori assumption that CTWs2

 and nonCTWs represent different 

exposure profiles. The decision to stratify the coworker data into CTW and nonCTW was based 

primarily on the following two qualitative observations:

2 The construction trade worker category includes energy employees for both the prime contractor and 

subcontractors operating at SRS.

• NonCTWs generally perform what is considered operational work, which involves 

handling large quantities of radioactive material on a routine basis. However, this work is 

conducted with much more stringent procedural and engineering controls in place to limit 

internal exposure potential.

• CTWs generally perform what is considered off-normal work, which potentially involves 

contact with smaller relative quantities of radioactive material and on a less routine basis. 

However, because of the nature of the work, there is considerably more procedural 

uncertainty, and established engineering controls might have been purposely breached or 

otherwise rendered ineffective. 

Observation 4: OTIB-0081 does not provide a statistical comparison of the two stratified groups 

as prescribed in the coworker implementation guide. The various coworker models were 

stratified based on the a priori assumption that exposure potential between CTWs and nonCTWs 

was different.

Another important assumption in OTIB-0081 is that subcontractor CTWs do not have a different 

exposure potential that prime contractor CTWs. This is an important assumption because it 

allows for both types of CTWs to be subsumed into a single coworker distribution for each 

contaminant of interest (see section 3.2.1 of OTIB-0081 for a discussion). NIOSH bases this 

assumption largely on a review of a subset of job plans and radiological surveys. Based on this 

review, NIOSH concluded that: 

it is clear that multiple types of crafts workers participated on the same type of 

jobs with common exposure potential. [NIOSH, 2019a, p. 28] 

OTIB-0081 provides three examples of job plans exhibiting these characteristics, with additional 

examples in appendix B. SC&A does not find these limited qualitative examples to be 

compelling evidence that subcontractor workers and prime contract workers were doing the same 

exact jobs and thus had the same exposure potential. 

In the first example, one set of workers is cutting a section of an old abandoned drain line to 

obtain a sample for analysis, and one set of workers is connecting a drain line. The operations 

were in two separate areas, and two different general external dose rates were measured (though 

the differences were admittedly small). 

However, assuming the external dose rates listed on the job plan are reflective of the work 

environment, the differences in the external dose rates associated with the second example

involving master slave manipulator (MSM) work are a more than a factor of 10 different 

 
Effective date: 9/4/2019 Revision No. 0 (Draft) Document No. SCA-TR-2019-SEC004 Page 45 of 79

NOTICE: This document has been reviewed to identify and redact any information that is protected by the 

Privacy Act 5 U.S.C. § 552a and has been cleared for distribution.

(3 milliroentgen per hour (mR/hr) and 30–50 mR/hr). In addition, OTIB-0081 states the 

following about MSM work: 

Repair of the Master/Slave Manipulator (MSM) arms were almost exclusively a 

maintenance operation as shown in Figure 3-3. There are multiple job plans for 

this type of work as the repairs appeared to be routine . . . . In general, very few 

construction operations mention the MSMs. [NIOSH, 2019a, pp. 29–30] 

The implication from this excerpt is that these types of jobs were almost always done by routine 

maintenance workers (presumably the prime contractors), which is at odds with the assumption 

that subcontractor and prime contractor CTWs worked side by side on the same jobs. 

Finally, the third example provided states the following: 

Portions of three Job Plans for a set of connected work in Building 773-A 

Rooms C-135/C-139 are shown in Figure 3-5. Work was performed by 

construction Carpenters, E&I Mechanics, and Maintenance Mechanics, which 

supports the premise that both DuPont and subcontracted CTWs performed 

similar work for short periods across SRS. [NIOSH, 2019a, p. 34] 

In this case, the job tasks were performed on completely different days and involved different 

work: 

• Job Plan 1: Construction carpenters drilling catch pans and performing line breaks to 

install hoses.

• Job Plan 2: Electrical and Instrumentation (E&I) Mechanics removing a light fixture in a 

shielded area. Afterwards, construction carpenters would erect scaffolding to perform a 

new drill line installation. 

• Job Plan 3: Repair a handle on a glove box dust damper (the worker type is not indicated 

on the job plan). 

The only commonality between the three jobs appears to be the location. 

Per prior discussions in November and December 2017 (SRS Work Group, 2017, and ABRWH, 

2017, respectively) about subcontractor workers, in particular those monitored by job-specific 

bioassay, SC&A feels that a more quantitative analysis of job plans is warranted to assure that 

prime contractor CTWs and subcontractor CTWs worked side by side on the same jobs and thus 

had the same potential for exposure. This is particularly important when considering the 

likelihood that prime contractors were on a routine monitoring schedule while many 

subcontractors may have been on a job-specific monitoring schedule. NIOSH is currently 

evaluating a significantly larger set of job plans in order to make such quantitative assessments. 

However, that evaluation was not available at the time of this review; therefore, further 

discussion of the appropriateness of subsuming all CTWs into a single coworker distribution is 

not warranted in this report.
Effective date: 9/4/2019 Revision No. 0 (Draft) Document No. SCA-TR-2019-SEC004 Page 46 of 79

NOTICE: This document has been reviewed to identify and redact any information that is protected by the 

Privacy Act 5 U.S.C. § 552a and has been cleared for distribution.

Observation 5: SC&A believes a quantitative assessment of available job plans, rather than a 

qualitative basis, is appropriate to determine that prime contractor and subcontractor CTWs are 

part of the same exposure strata. Such an assessment has been performed by NIOSH, and a 

report of their findings has recently been issued (NIOSH, 2019d).

5.2 Evaluation of the identification of workers with the appropriate strata

As described in section 5.1 above, three general criteria are provided in the coworker 

implementation guide to indicate when stratification must be considered in coworker 

development. The first criterion requires that accurate job categories and/or descriptions can be 

obtained for all workers making up the general coworker dataset. This criterion becomes 

especially important when operating under the premise that the two or more groups identified for 

stratification evaluation have sufficiently different exposure potential. For example, if it is 

known (or strongly suspected) that “group A” has a higher exposure potential than “group B,” 

then any inadvertent inclusion of group B worker monitoring results with the group A strata may 

incorrectly bias the resulting coworker intakes low for group A (and vice versa for group B). 

For SRS coworker models, the chosen strata are delineated as CTWs and nonCTWs. However, 

in a more a practical sense, the actual chosen strata are the delineation between workers involved 

in nonroutine work and routine work. Examples of nonroutine work would include (but are not 

limited to): new construction in contaminated areas, renovation work, maintenance on 

instrumentation and other equipment, and decontamination and decommissioning work. 

Examples of routine work are generally described as production work that is performed using

existing shielding, glove boxes, and other semipermanent engineering controls that have been 

specifically designed for the established procedure and radiological process. The coworker 

model provides a listing of job types that it considers to be CTWs and nonCTWs in table 3-2,

which is reproduced here as table 15.
Effective date: 9/4/2019 Revision No. 0 (Draft) Document No. SCA-TR-2019-SEC004 Page 47 of 79

NOTICE: This document has been reviewed to identify and redact any information that is protected by the 

Privacy Act 5 U.S.C. § 552a and has been cleared for distribution.

Table 15. CTW and nonCTW job titles as contained in OTIB-0081 

CTW occupations nonCTW occupations

Boilermaker

Carpenter

Concrete worker

Construction worker

Driver

E&I Tech 

Electrician

Heavy equipment operator

Insulator

Ironworker

Laborer

Maintenance

Mechanic

Painter

Rigger

Sheetmetal worker

Welder

Administrative Assistant

Assistant

Cafeteria

Clerical

Crane Process Operator

Engineer

Escort

HP [health physicist]

Human Resources

Instructor

Laundry

Layout

Machinist

Manager

Pilot

QA

Reactor Operator

Security

Specialist

Supervisor

Source: NIOSH, 2019a, table 3-2.

It should be noted that “Machinist” is considered a nonCTW in the coworker model; however, it 

is considered a CTW in OCAS-PER-014 (NIOSH, 2007), which deals with external coworker 

dose assignment for CTWs. This inconsistency should be discussed and resolved; otherwise, the 

potential exists for a claimant to receive a CTW coworker assignment for external dose but a 

nonCTW coworker assignment for internal dose. 

Finding 5: Classification of a “Machinist” as a nonCTW in OTIB-0081 is inconsistent with its 

classification in OCAS-PER-014. 

While the above characterization of the chosen strata as shown in table 15 is clear and rather 

simplistic, the identification of workers within each stratum becomes much more complex when 

considering workers who have job types that (by default) might involve routine or nonroutine 

work (or potentially both) during a given time period. Some general examples of ambiguous job 

designations might include: 

• Supervisor/Foreman: Such work may be indicative of an energy employee (EE) who is 

“hands off” and generally only observes the nonroutine work or whose duties mainly 

include administrative duties related to the nonroutine work. Alternately, a 

supervisor/foreman (in particular, a first line supervisor) may be performing “hands on” 

work with a relatively small crew of workers all doing the same task. For this particular 

job type, the stratification decision may also have a temporal component. Individual 

evaluations of industrial hygiene exposures in many U.S. Department of Labor (DOL) 

files indicate the role of supervisors in relation to chemical hazards may have changed in 

the early 1970s. It is logical that a similar characterization existed for radiological 

hazards. Figure 18 below shows an example of an industrial hygiene record displaying 

this boilerplate information. 
Effective date: 9/4/2019 Revision No. 0 (Draft) Document No. SCA-TR-2019-SEC004 Page 48 of 79

NOTICE: This document has been reviewed to identify and redact any information that is protected by the 

Privacy Act 5 U.S.C. § 552a and has been cleared for distribution.

• Assistant/Helper: This category is especially broad, as it could potentially represent an

assistant to a number of different CTW-type workers (e.g., welding assistant, carpenter’s 

assistant) in which working conditions would be expected to be sufficiently similar to the 

CTW category. Alternately, assistant may refer to nonCTW-type work, such as an 

administrative assistant, laboratory assistant, technical assistant, project assistant, 

engineering assistant, etc.

• Operator: In general, this category would typically be associated with nonCTWs 

performing production work (such as a “Chemical Operator”). However, SC&A observed 

evidence that the term “Operator” may also have been used by the site to represent CTWtype jobs, such as Heavy Equipment Operator, Truck Driver, and nonproduction Crane 

Operator. This appears especially problematic for workers whose specific job title is

“General Service Operator.” Further confounding the strata designation are EEs whose 

work is described simply as “operations,” which could mean the standard Production 

Operator category or alternately an E&I Mechanic who performed maintenance activities

in operational areas.

For some illustrative examples of these ambiguities identified during SC&A’s analysis, please 

refer to table 17 in the discussion of SC&A’s independent evaluation of worker designation later 

in this section.

Figure 18. Excerpt from an industrial hygiene evaluation included in DOL case files concerning 

maintenance supervisors

Source: Case , DOL Initial Case, p. 302

In addition to the ambiguous job types described above, care must be taken for workers who 

transitioned from clear CTW job categories to nonCTW job categories during their career. A 

typical example observed by SC&A includes a Maintenance Mechanic who transitioned to the 

job titles of project assistant and then project engineer. In these cases, it becomes important to 

understand the temporal change in job duties so that the individual’s internal monitoring records 

are correctly divided between the two strata.

The coworker model strata designation is primarily based on a payroll number identification 

system that is unique to SRS. This methodology is described in section 3.2 of OTIB-0081 and 

not repeated in this report. In addition to the payroll identifiers, a secondary source of 

information used to buttress the strata identification in certain cases was the actual occupation 

listed for the individual. SC&A assumes that this information is extracted directly from the 

NOCTS listing for the individual EE.
Effective date: 9/4/2019 Revision No. 0 (Draft) Document No. SCA-TR-2019-SEC004 Page 49 of 79

NOTICE: This document has been reviewed to identify and redact any information that is protected by the 

Privacy Act 5 U.S.C. § 552a and has been cleared for distribution.

To assess the effectiveness of accurately placing workers in the correct strata, SC&A performed 

a two-step independent evaluation of worker designation for a subset of targeted workers where 

the risk of inadvertently including a worker in the incorrect stratum is likely the highest (i.e., the 

somewhat ambiguous job titles and workers with multiple designations as discussed above). The 

first step in the evaluation can be considered more of a qualitative assessment of job duties. For 

the second step, SC&A extracted the job title information (and by extension the CTW/nonCTW 

designation) associated with each EE’s in vitro and in vivo result found in the NIOSH databases 

provided to SC&A3 for quantitative comparison against alternate sources. 

3 These databases are titled, “SRS combined in-vitro data 0901818 with CTW.xls” and “SRS combined in-vivo 

data subset 092518 with CTW.xls.”

For the first step, SC&A based its evaluation on specific information in the individual claimant’s 

NOCTS documentation, such as the computer-assisted telephone interview (CATI) and DOL

case files. The CATI document often contains specific statements by the EE related to the work 

they performed and, in some cases, actual dates of different job duties and work locations that 

provide a more complete picture of which stratum is likely correct for the EE. The DOL case 

files can contain a number of different references, including (but not limited to) additional 

statements by the claimant, individual resumes, work performance evaluations, industrial 

hygiene evaluation summaries, and disability reports. In addition to these, the most useful 

reference in the DOL case file is the “EEOICPA Occupational History Interview,” which has a 

listing of job types and an entry for dates in each category (see figure 19). In addition, the 

EEOICPA Occupational History Interview contains an additional section for the EE to add 

further description, such as building location and a description of duties for each of the entry 

dates (see figure 20).

 
Effective date: 9/4/2019 Revision No. 0 (Draft) Document No. SCA-TR-2019-SEC004 Page 50 of 79

NOTICE: This document has been reviewed to identify and redact any information that is protected by the 

Privacy Act 5 U.S.C. § 552a and has been cleared for distribution.

Figure 19. Example of an EEOICPA occupational history interview form, showing list of job titles 

and dates of employment
Effective date: 9/4/2019 Revision No. 0 (Draft) Document No. SCA-TR-2019-SEC004 Page 51 of 79

NOTICE: This document has been reviewed to identify and redact any information that is protected by the 

Privacy Act 5 U.S.C. § 552a and has been cleared for distribution.

Figure 20. Example of an EEOICPA occupational history interview form, showing example entry 

of building, work activity, years of employment, and frequency

SC&A analyzed claimants who had been characterized as both a CTW and a nonCTW during 

their monitored employment. Based on a review of the NOCTS documentation, SC&A 

determined whether there was evidence of both routine and nonroutine work during the EE’s 

employment. SC&A identified 327 claimants who had been classified as both a CTW and a 

nonCTW during their relevant employment. SC&A found that approximately 65 percent of these 

targeted claimants displayed evidence of both types of jobs (routine and nonroutine during their 

employment), while the remaining 35 percent appear to only have performed work relevant to 

one of the established strata. 

SC&A then analyzed claimants categorized as one of the ambiguous job titles discussed above. 

SCA identified and evaluated 172 claimants designated as a supervisor/foreman (this represents 

just 17 percent of the total available for review in this job category). Approximately 57 percent

of these supervisory positions were associated with CTWs, 30 percent were associated with 

nonCTWs, and the remaining 13 percent were characterized as indeterminate due to lack of 

information. Of the supervisory positions associated with CTWs, less than one-third contained 

information to designate them as “hands on” versus “hands off,” which would allow for a more 

definitive determination of the appropriate strata.

Regarding the job title “Operator,” SC&A reviewed 157 total claim files (just 20 percent of the 

total available for review with that job title). Of the reviewed population, SC&A determined that 

approximately 45 percent may have been incorrectly associated with nonCTW/routine type work 

duties. Several examples of this are provided in table 17 at the end of this discussion. Many of 

these apparent contradictions may be related to the job title “general service operator,” as 

discussed further in this section. 

Finally, SC&A reviewed 129 claimant files associated with the “Assistant/Helper” category. 

Approximately 53 percent of the reviewed claims designated as an “Assistant/Helper” appear to 
Effective date: 9/4/2019 Revision No. 0 (Draft) Document No. SCA-TR-2019-SEC004 Page 52 of 79

NOTICE: This document has been reviewed to identify and redact any information that is protected by the 

Privacy Act 5 U.S.C. § 552a and has been cleared for distribution.

be associated with nonCTW job duties, 22 percent were associated with CTW job duties, and the 

remaining were judged indeterminate due to lack of additional information. 

SC&A acknowledges that the results of the first step of the evaluation are informative but 

ultimately qualitative for a number of reasons: 

• Much of the information is reliant on the EE or their survivor’s memory. 

• Information provided may be skewed toward those job duties in which the EE recalls a 

definite exposure potential, while the bioassay monitoring may have included periods 

when little or no exposure potential was perceived by the EE. 

• Temporal information related to the described job duties is not always provided. 

Therefore, SC&A performed a more rigorous quantitative analysis that only considered the 

NOCTS documentation that includes specific temporal information. In addition to the NOCTS 

documentation, SC&A used a second source that includes specific temporal information: the 

individual worker’s employment history record (an example is shown in figure 21). 

Figure 21. Example of an employment history record displaying date and occupation

SC&A analyzed a subset of individual worker strata designations against each of these two 

sources (when available) to identify any temporal discrepancies in job title assignment. For this 

comparison, the job titles identified for the CTW and nonCTW categories in OTIB-0081 were 

used without modification. Furthermore, only the strata designation (and not the actual job title) 

was used to establish a “match,” since the stratification of the coworker model is currently only 

dependent on correct identification as a CTW versus a nonCTW. The following are some 

illustrative examples of how this comparison was done: 

• Example 1: The NOCTS temporal result indicated the job title of “Project Assistant” 

(nonCTW), though the available information for that period actually described work 
Effective date: 9/4/2019 Revision No. 0 (Draft) Document No. SCA-TR-2019-SEC004 Page 53 of 79

NOTICE: This document has been reviewed to identify and redact any information that is protected by the 

Privacy Act 5 U.S.C. § 552a and has been cleared for distribution.

consistent with a “Pipefitter.” The OTIB-0081 designation for the same date indicated the 

EE was an assistant. This would be considered a match in the analysis below because a 

“Project Assistant” and an “Assistant” are both considered nonCTWs per OTIB-0081. 

• Example 2: The employment history record indicates the job title of “General Service 

Operator.” The OTIB-0081 designation indicates “Laborer” during the same period. This 

would not be considered a match even if additional evidence (e.g., NOCTS references) 

indicated the job duties were consistent with a laborer.4 

4 As noted in this section, adjustments were made for situations in which the employment history record and the 

NOCTS strata designation were conflicting.

• Example 3: The employment history record indicates the job title of supervisor, the 

NOCTS designation indicates project engineer, and the OTIB-0081 designation is as an 

operator. This combination would be considered a match, since all three job designations 

represent nonCTW work categories in OTIB-0081. 

The subset of workers for which SC&A performed this analysis included workers with multiple 

CTW/nonCTW designations but also the subset of 157 operators discussed previously in this 

section. A total of 15,244 internal monitoring data points used in OTIB-0081 were checked 

against SC&A’s independent compilation of employment history record information and 

temporal-based NOCTS documentation. The results are shown as an unadjusted total and an 

adjusted total in table 16. The unadjusted totals indicate situations in which either the 

employment history record or the NOCTS temporal designation was in apparent conflict with the 

coworker model designation. The adjusted total accounts for situations in which the coworker 

model designation is in conflict with one of the SC&A references, but not both (e.g., the 

OTIB-0081 designation agrees with the NOCTS designation but not the employment history 

designation). As seen in table 16, the total adjusted percentage of conflicts identified between the 

targeted sample of OTIB-0081 strata designations and the two temporal-based resources used by 

SC&A was just over 9 percent. A little less than one-third of the adjusted conflicts reflected 

situations in which both the temporal NOCTS data and the employment history were in conflict 

with the NIOSH strata definition. 

Table 16. Summary of strata comparison between OTIB-0081 disposition and SC&A analysis

Category of conflict with OTIB-0081 rev. 04 worker 

stratification designation

Unadjusted total 

(%)

Adjusted total 

(%)

Conflict with both NOCTS and employment history 417 (2.74%) 417 (2.83%)

Conflict with employment history only (NOCTS information 

not available) 594 (3.90%) 454 (3.09%)

Conflict with NOCTS only (employment history information 

not available) 866 (5.68%) 473 (3.22%)

Total conflicts 1,877 (12.31%) 1,344 (9.14%)

No conflict 13,367 (87.69%) 13,367 (90.86%)

 
Effective date: 9/4/2019 Revision No. 0 (Draft) Document No. SCA-TR-2019-SEC004 Page 54 of 79

NOTICE: This document has been reviewed to identify and redact any information that is protected by the 

Privacy Act 5 U.S.C. § 552a and has been cleared for distribution.

Finding 6: A targeted sampling comparing the OTIB-0081 strata designation (CTW or 

nonCTW) against two alternate sources for identifying worker job classification indicated that 

just over 9 percent of the entries appear to be in conflict when comparing the NIOSH and SC&A 

analyses.

During the course of this temporal comparison, SC&A noted several cases that illustrate the 

difficulties and potential issues with correctly identifying a worker with the appropriate stratum. 

These cases are discussed in table 17. Each case was assigned an arbitrary alphabetical 

designation that does not reflect the actual EE in any identifiable way. Claim numbers associated 

with the arbitrary case designations are provided in attachment C for reference. 

Table 17. [Redacted in full]

[Table 17 on pages 54–55 is withheld in its entirety to prevent disclosure of Privacy-Actprotected information.] 
Effective date: 9/4/2019 Revision No. 0 (Draft) Document No. SCA-TR-2019-SEC004 Page 55 of 79

NOTICE: This document has been reviewed to identify and redact any information that is protected by the 

Privacy Act 5 U.S.C. § 552a and has been cleared for distribution.

[Table 17 on pages 54–55 is withheld in its entirety to prevent disclosure of Privacy-Actprotected information.] 

As seen in the table, Cases indicate a potential issue with strata designation in which the 

job title assignment may have been temporally flipped. For Case , the OTIB-0081 designation 

indicates the start of monitored employment as an before moving to positions 

and ending as a . Conversely, evaluation of the NOCTS documentation indicates work 

started as a before moving on to positions in the (a seemingly more 
Effective date: 9/4/2019 Revision No. 0 (Draft) Document No. SCA-TR-2019-SEC004 Page 56 of 79

NOTICE: This document has been reviewed to identify and redact any information that is protected by the 

Privacy Act 5 U.S.C. § 552a and has been cleared for distribution.

logical career path). Similarly, OTIB-0081 indicates Case started out as an and ended 

their career in , which is the contrary to what the NOCTS documentation indicated. 

Case presents an example in which was assigned for OTIB-0081 analysis; 

however, the employment history and NOCTS files indicate work as a 

. Cases illustrate the issues associated with classifying workers who are 

designated as a “ .” In these cases, the correct job title was likely a 

 rather than an actual . However, SC&A 

also observed cases where a “ ” involved other job duties, such as a 

 or a ( designations). 

Case involved a period designated as an that was surrounded by periods as a 

. The employment history and NOCTS documentation indicated that the EE’s work 

was entirely as a . Case showed a roughly -year period in which 

“ ” and “ ” were used interchangeably. The employment history indicated the 

job assignment was entirely as a “ ” during this period. 

The cases referenced and discussed in table 17 illustrate the difficulty of correctly classifying 

certain workers as either CTW or nonCTW. This is particularly true with job titles that could 

potentially belong to either group, such as , and 

intermediate management positions such as a . Incorrect characterization of these 

borderline job titles has the potential to “wash out” the actual exposure potential differences 

between CTWs and nonCTWs. 

One potential test that may provide quantitative information would be to remove the monitoring 

results associated with borderline job titles and see what effect this has on the resulting CTW and 

nonCTW distributions. If the effect on the resulting distributions is negligible, then inclusion of 

the borderline job titles “as is” could be considered sufficient. However, if there is a noticeable 

difference in the magnitude of the resulting CTW and nonCTW distributions, then a more 

rigorous evaluation of individual strata classifications may be warranted. 

Observation 6: SC&A acknowledges that there are inherent difficulties in correctly associating 

individual workers with the correct CTW/nonCTW strata. This is particularly true for job titles 

that could potentially be included in either stratum (e.g., 

). SC&A suggests a scoping analysis in which such borderline job 

titles are removed to ascertain the effect on the resulting distributions. Such an analysis would 

help determine whether current strata designations are sufficient or a more rigorous approach to 

individual job classification is warranted.
Effective date: 9/4/2019 Revision No. 0 (Draft) Document No. SCA-TR-2019-SEC004 Page 57 of 79

NOTICE: This document has been reviewed to identify and redact any information that is protected by the 

Privacy Act 5 U.S.C. § 552a and has been cleared for distribution.

6 Review of Quality Assurance Assessment

Attachment A of OTIB-0081 contains an assessment of the QA tests applied to various facets of 

the coworker model development per the criteria and guidelines in ORAUT-RPRT-0078 

(NIOSH 2016b; “RPRT-0078”) and ORAUT-RPRT-0086 (NIOSH, 2017; “RPRT-0086”). This 

section discusses SC&A’s review of the QA test results 

6.1 Completeness of SRS claims tracking system data

The NOCTS bioassay samples collected from SRS employees are used as the primary data 

sources for the coworker study for all radionuclides except americium and neptunium. 

Laboratory logbooks are used for the latter two radionuclides due to insufficient NOCTS 

bioassay data. Completeness of the NOCTS database and the logbook data is addressed in the 

studies reported in attachment A of ORAUT-0081. 

Attachment A contains 13 parts, shown in table 18 below.5 Each part of the attachment reports 

the results of a QA analysis done in support of one section in the main body of ORAUT-0081, 

revision 04. Table 18 shows the OTIB-0081 section numbers and titles, along with the 

attachment A title, completion date, and OTIB-0081 page number reference for the QA analysis. 

The completeness studies for the NOCTS in vitro and in vivo data are parts 1 and 2 of table 18, 

respectively. The remaining parts of the table show results for logbook data completeness and 

CTW determination studies. The logbook data sources are discussed in the radionuclide-specific 

sections of this review below. 

5 Attachment A of OTIB-0081 does not specifically number individual sections; however, SC&A ascribed section 

numbers for ease of cross-reference between this review and OTIB-0081. 

NIOSH conducted three NOCTS studies for the in vitro bioassay data, the in vivo whole body or 

chest count data, and the tritium data. The first NOCTS study (dated May 5, 2017) addressed 

completeness of NOCTS in vitro bioassay data. The second (dated August 7, 2017) addressed the 

in vivo data obtained from whole body or chest counts. These two studies are listed as parts 1 

and 2 of table 18, respectively. The NOCTS tritium study (dated May 16, 2016) is found in part 

12 of attachment A (p. 128) and is shown in part 12 of table 18, immediately before the other 

tritium study.

Table 19, parts 1, 2, and 12 summarize the attachment A results for the three NOCTS 

completeness studies. The table includes a short title for each part of attachment A, the statistical 

method used in the analysis, the type of fields that were checked, and a summary of the statistical 

results reported for the study. The following sections discuss the statistical results for the

NOCTS studies.

 
Effective date: 9/4/2019 Revision No. 0 (Draft) Document No. SCA-TR-2019-SEC004 Page 58 of 79

NOTICE: This document has been reviewed to identify and redact any information that is protected by the Privacy Act 5 U.S.C. § 552a and has been cleared for 

distribution.

Table 18. Summary of contents of ORAUT-OTIB-0081, rev. 04, attachment A

Part

OTIB-0081 

pages Attachment A title of QA analysis Date

OTIB-0081 

section Referencing section of OTIB-0081

1 108–110 Savannah River Site Internal 

Coworker In Vitro Completeness 

Check

5/5/2017 3.1.1 Completeness of Claims Tracking System Data 

2 111–113 SRS In Vivo Completeness Report 8/7/2017 3.1.1 Completeness of Claims Tracking System Data

3 114–115 Savannah River Site Internal 

Coworker In Vitro Completeness 

Check – Neptunium (Np)

3/7/2018 4.8.2.1 Data Completeness and Quality 

4 116 SRS NOCTS In Vitro Data QA 

Summary

5/9/2017 3.1.2 Accuracy of Claims Tracking System Data

5 117 SRS Am QA Summary 6/16/2016 3.2.3 Worker Classification Quality Assurance, table 3-3

6 118–119 SRS Np Logbooks QA Summary 2/26/2018 3.2.3 Worker Classification Quality Assurance, table 3-3

7 120–121 SRS NOCTS WBC QA Summary 6/3/2016 3.1.2 Accuracy of Claims Tracking System Data

8 122–123 SRS Mixed FP Gamma QA 

Summary

6/6/2016 3.2.3 Worker Classification Quality Assurance, table 3-3

9 124 SRS In Vivo CTW QA Summary 10/5/2017 3.2.3 Worker Classification Quality Assurance, table 3-4

10 125 SRS In Vitro CTW QA Summary 6/1/2017 3.2.3 Worker Classification Quality Assurance, table 3-4

11 126–127 SRS Np Logbook CTW QA 

Summary

3/6/2018 3.2.3 Worker Classification Quality Assurance, table 3-4

12 128 SRS Tritium QA Summary 5/16/2016 4.2.2 Data Validation 

13 129 SRS Tritium CTW QA Summary 7/14/2016 3.2.3 Worker Classification Quality Assurance, table 3-4

Table 19. Summary of ORAUT-0081, rev. 04, attachment A completeness test results

Part Pages Short title Method Fields 

checked

LTPD * 

(%)

Number 

of 

claims

Claims 

sampled

Items 

checked

Number 

of 

misses

Note

Error 

rate 

(%)

LCL 

(%)

UCL 

(%)

1 108–

110

In Vitro 

Completeness 

Check

sequential 

sampling critical 95% 

UCL<5 2,875 30 1,762 14 — 0.79 0.03 3.99

2a 111–

113

In Vivo 

Completeness 

Report: Round 1

sequential 

sampling — 95% UCL<5 2,823 101 840 31 — 3.69 0.37 12.89
Effective date: 9/4/2019 Revision No. 0 (Draft) Document No. SCA-TR-2019-SEC004 Page 59 of 79

NOTICE: This document has been reviewed to identify and redact any information that is protected by the Privacy Act 5 U.S.C. § 552a and has been cleared for 

distribution.

Part Pages Short title Method Fields 

checked

LTPD * 

(%)

Number 

of 

claims

Claims 

sampled

Items 

checked

Number 

of 

misses

Note

Error 

rate 

(%)

LCL 

(%)

UCL 

(%)

2b 111–

113 Round 2 RPRT-0086 — 5 2,823 410 4,048 26 — 0.64 0.25 1.35

3 114–

115

In Vitro 

Completeness 

Check – Np

complete 

census

critical 5 382 100% 1,082 25 — 2.31 N/A N/A

4a 116

NOCTS In Vitro 

Data QA 

Summary

RPRT-0078 critical 1 — — 4,386 11 — 0.25 0.13 0.45

4b 116

NOCTS In Vitro 

Data QA 

Summary

RPRT-0078 all fields 5 — — 874 4 — 0.46 0.13 1.17

5a 117 Am QA Summary RPRT-0078 critical 1 — — 4,242 25 — 0.59 0.39 0.86

5b 117 Am QA Summary RPRT-0078 all fields 5 — — 873 6 — 0.69 0.25 1.49

6a

118–

119

Np Logbooks QA 

Summary RPRT-0078 critical 1 — — 3,148 27 (a) 0.86 0.61 1.18

6b 118–

119

Np Logbooks QA 

Summary RPRT-0078 — — — — — 21 — 0.67 0.45 0.96

6c

118–

119

Np Logbooks QA 

Summary RPRT-0078 all fields 5 — — 932 8 — 0.86 0.38 1.67

7a

120–

121

NOCTS WBC QA 

Summary RPRT-0078 critical 1 — — 4,375 535 (b) 12.23 11.29 13.22

7b 120–

121

NOCTS WBC QA 

Summary RPRT-0078 — — — — — 27 — 0.62 0.41 0.89

7c

120–

121

NOCTS WBC QA 

Summary RPRT-0078 all fields 5 — — 874 45 (c) 5.15 3.78 6.83

7d 120–

121

NOCTS WBC QA 

Summary RPRT-0078 — — — — — 19 — 2.17 1.31 3.37

8a

122–

123

Mixed FP 

Gamma QA 

Summary

RPRT-0078 critical 1 — — 3,282 1,980 (d) 60.33 58.88 61.75

8b 122–

123

Mixed FP 

Gamma QA 

Summary

RPRT-0078 — — — — — 14 — 0.43 0.27 0.67
Effective date: 9/4/2019 Revision No. 0 (Draft) Document No. SCA-TR-2019-SEC004 Page 60 of 79

NOTICE: This document has been reviewed to identify and redact any information that is protected by the Privacy Act 5 U.S.C. § 552a and has been cleared for 

distribution.

Part Pages Short title Method Fields 

checked

LTPD * 

(%)

Number 

of 

claims

Claims 

sampled

Items 

checked

Number 

of 

misses

Note

Error 

rate 

(%)

LCL 

(%)

UCL 

(%)

8c 122–

123

Mixed FP 

Gamma QA 

Summary

RPRT-0078 all fields 5 — — 849 89 (e) 10.48 8.52 12.73

8d 122–

123

Mixed FP 

Gamma QA 

Summary

RPRT-0078 — — — — — 1 — 0.12 0.004 0.65

9 124 In Vivo CTW QA 

Summary RPRT-0078 all fields 5 — — 847 25 — 2.95 1.93 4.30

10 125 In Vitro CTW QA 

Summary RPRT-0078 all fields 5 — — 873 16 — 1.83 1.05 2.95

11 126–

127

Np Logbook CTW 

QA Summary RPRT-0078 all fields 5 — — 709 8 — 1.13 0.55 2.10

12a 128 Tritium QA 

Summary RPRT00-78 critical 1 — — 4,383 14 — 0.32 0.18 0.53

12b 128 Tritium QA 

Summary RPRT-0078 all fields 5 — — 874 2 — 0.23 0.03 0.82

13 129 Tritium CTW QA 

Summary RPRT-0078 all fields 5 — — 874 6 — 0.69 0.25 1.49

Total — — — — — — — 40,127 303 (f) 0.76 0.60 0.94

* Lot tolerance percent defective (LTPD) for RPRT-0078 tests or confidence interval requirement for sequential sampling.

(a) Count includes as errors 6 payroll prefix and other payroll ID issues that would have no impact on data use.

(b) Count includes as errors 508 payroll prefix and other payroll ID issues that would have no impact on data use.

(c) Count includes as errors 26 payroll prefix and other payroll ID issues that would have no impact on data use.

(d) Count includes as errors 1,966 payroll prefix and other payroll ID issues that would not affect use of the data for CTW determination or for proper identification 

of the person.

(e) Count includes as errors 88 payroll prefix and other payroll ID issues that would not affect use of the data for CTW determination or for proper identification of 

the person.

(f) Items noted by a, b, c, d, and e are not included in error count total. A 95 percent confidence interval is obtained by simulation (see text).
Effective date: 9/4/2019 Revision No. 0 (Draft) Document No. SCA-TR-2019-SEC004 Page 61 of 79

NOTICE: This document has been reviewed to identify and redact any information that is protected by the 

Privacy Act 5 U.S.C. § 552a and has been cleared for distribution.

6.1.1 NOCTS in vitro completeness check

The NOCTS data contain over 260,000 tritium bioassay results and over 100,000 non-tritium 

in vitro bioassay results for samples submitted by more than 1,500 workers between 1954 and 

1990. The completeness review was performed on the data entry process that was used to build 

the NOCTS electronic database from the hardcopy records. The completeness review was 

performed in two steps. This review was conducted by selecting a random sample of the NOCTS 

claims with bioassay data and verifying that all the data in the hardcopy records were included in 

the electronic dataset. 

Due to the random sampling of claims, each claim has the same probability of selection. 

However, each claim contains a variable number of bioassay data. Thus, the individual data 

elements do not have the same probability of selection. This type of sampling (called cluster 

sampling) requires a statistical analysis to determine the proper weight to assign to each data 

element when interpreting the results of the matching to hardcopy data. NIOSH has addressed 

this type of sampling in RPRT-0086 (NIOSH, 2017). Much of the work on ORAUT-0081 was 

completed prior to the publication of RPRT-0086, and the methods recommended for cluster 

sampling were not used in the work for part 1 of attachment A. This issue also affects the 

analysis of the part 2 in vivo body count data discussed below. 

A detailed page-by-page review of the selected claims was conducted to ensure all pertinent data 

were entered correctly. The counting technique focused on three critical fields: sample date, 

radionuclide, and the numerical result. If any of these three fields were missing, that entire line 

of data was counted as not matching the electronic database. A list of 30 claims was selected 

randomly from the original set of 2,875. The 30 claim files were checked, and a line was called 

missing if any of the three critical fields were missing. Out of the 1,762 lines of data that were 

checked, 14 lines were missing from the electronic dataset.

The results of the analysis are shown at the right in the first row of table 19. The error rate in 

matching the lines of data was very low at 0.79 percent. The 95 percent upper confidence limit 

(UCL) for the error rate is reported to be about 4 percent. No details are provided for the 

calculation of the confidence interval in the report. However, NIOSH has indicated that the 

procedures in RPRT-0086 were used to compute the confidence interval, but not the sample size. 

A Wald plot is shown, which interprets the results in terms of a sequential sampling approach. 

Due to the lack of equal probability of selection, this interpretation is not correct. 

Despite the problems of unequal weighting, the very low estimated error rate (less than 

1 percent) for the in vitro completeness test makes it unlikely that the 95 percent UCL would 

exceed the 5 percent success criterion.

6.1.2 NOCTS in vivo bioassay data 

The NOCTS data contain records of almost 15,000 in vivo whole body counts or chest counts. 

Two separate completeness reviews were conducted for the in vivo data, referred to as part 2 

round 1 and round 2 in table 19. The first round of analysis used a procedure identical to that 

used in part 1 for the NOCTS in vitro data analysis. The review was conducted by selecting a 

random sample of the NOCTS claims with counting data and matching lines of data in these 

claims to the electronic dataset. 
Effective date: 9/4/2019 Revision No. 0 (Draft) Document No. SCA-TR-2019-SEC004 Page 62 of 79

NOTICE: This document has been reviewed to identify and redact any information that is protected by the 

Privacy Act 5 U.S.C. § 552a and has been cleared for distribution.

The review of the selected claims focused on four critical fields: sample date, nuclide, numerical 

result, and MDA data. If any of these four fields were missing, that entire line of data was 

counted as not matching the electronic database. A list of 101 claims was selected randomly 

from the original set of 2,823 claims with count data. The 101 claim files were checked, and a 

line was called missing if any of the four critical fields were missing. 

Due to the random sampling of claims, each claim has the same probability of selection. 

However, each claim contains a variable number of lines of data. As with the in vitro data 

analysis, the sampled lines of data do not have the same probability of selection. The first round 

completeness review in part 2 was completed prior to the publication of RPRT-0086, and the 

methods recommended there for cluster sampling were not used in round 1 on the in vivo 

analysis. 

Out of the 840 lines of data that were checked in round 1, there were 31 lines with errors. Of 

these errors, 30 were due to 2 claims of the 101 sampled claims. The estimated error rate for the 

round 1 review was 3.56 percent, and the 95 percent UCL was 12.89 percent. Since the UCL was 

well above the 5 percent success criteria, an additional test was warranted. Corrections were 

made to the 31 errors found during round 1, and the cluster sampling procedure recommended in

RPRT-0086 was applied in the second round of the in vivo completeness test. In the cluster 

sampling procedure, the unequal probabilities of selection are accounted for by using weights 

inversely proportional to the probability of selection.

In the round 2 of the in vivo completeness test, a new list of 410 claims were randomly chosen 

from the set of 2,823 claims. The claim files for these 410 claims were checked, and a row was 

counted missing if any of the four pieces of necessary information were missing. Of the 4,048 

lines of data checked for missing data, 26 errors were noted. The results of the round 2 analysis 

are shown in table 19. The error rate in matching the lines of data was very low at 0.64 percent. 

The 95 percent UCL for the error rate is 1.35 percent, well below the 5 percent success criterion.

6.1.3 NOCTS in vitro data QA summary

Part 4 of attachment A and tables 18 and 19 include a data transcription test for the NOCTS 

in vitro dataset. The data transcription accuracy of the in vitro bioassay data was checked in 

accordance with RPRT-0078 (NIOSH, 2016b). The nuclide, numerical result, and “<” fields 

were checked with a maximum 1 percent allowable error rate. The QA check resulted in an 

estimated error rate of 0.25 percent with a 95 percent UCL of 0.45 percent. The error rate is well 

below the acceptance criterion for critical fields of 1 percent.

A second data transcription test was conducted for all fields with a maximum 5 percent

allowable error rate. This test resulted in an estimated error rate of 0.46 percent with a 95 percent

UCL of 1.17 percent. The error rate is well below the acceptance criterion for all fields of 

5 percent. 

6.1.4 NOCTS tritium data QA summary

Part 12 of attachment A and tables 18 and 19 describe results of the data transcription test for the 

NOCTS tritium dataset. The data transcription accuracy of the tritium bioassay data was checked 

in accordance with the lot acceptance procedures described in RPRT-0078. The numerical 

sample result fields were evaluated with a maximum 1 percent allowable error rate. The QA 
Effective date: 9/4/2019 Revision No. 0 (Draft) Document No. SCA-TR-2019-SEC004 Page 63 of 79

NOTICE: This document has been reviewed to identify and redact any information that is protected by the 

Privacy Act 5 U.S.C. § 552a and has been cleared for distribution.

check resulted in an estimated error rate of 0.32 percent with a 95 percent UCL of 0.53 percent, 

as shown in in part 12a of table 19. The completeness test result is well within the acceptance 

criterion for critical fields of 1 percent. The study authors note that 4 of the 14 critical field errors 

are results from the same claim entered as <0.05 that should be <0.5. 

All fields were evaluated for tritium with a maximum 5 percent allowable error rate. The QA 

check estimate error rate was 0.23 percent with a 95 percent UCL of 0.82 percent, as shown in 

part 12b of table 19. The completeness test result is well within the acceptance criterion for all 

fields of 5 percent. 

6.2 Completeness of SRS logbook data

Attachment A includes several parts that address radionuclide-specific completeness tests for 

SRS logbook data for neptunium, americium, and MFPs. These completeness tests were 

performed in accordance with the lot acceptance procedure described in RPRT-0078. Two 

acceptance criteria were used for data transcription, one for critical fields and another for all 

checked fields. Typical critical fields were the reported result, nuclide, and payroll identification 

number (PRID). The acceptance criterion for all checked fields was a 5 percent maximum 

allowable error rate, while a stricter 1 percent maximum allowable error rate was applied for 

critical fields.

6.2.1 Completeness of SRS neptunium logbook data 

Urinalysis was the primary method of checking for neptunium intakes at SRS during the 1960s. 

These results were generally recorded in separate, stand-alone neptunium logbooks. Around 

1970, neptunium started to be measured using whole body counts, and neptunium urinalysis was 

no longer routinely performed at the site. A list of SRS NOCTS Claim IDs with at least 1 day of 

employment before 1991 was developed and reviewed for the presence of at least 1 neptunium 

result. This review revealed 382 claims containing neptunium results in both the transcribed 

logbook database and NOCTS claim data. These 382 claims were used for the neptunium 

completeness test. Although only the post-1969 neptunium urinalysis data will be used in the 

coworker study, NIOSH checked all 382 claims in the neptunium in vitro datasets. Since a 

census of all the claims was done, no sampling was required for this part of attachment A.

Results of the neptunium logbook completeness analysis are shown in part 3 of table 19. A total 

of 1,082 lines of data were checked, and 25 lines had missing data for an error rate of 

2.31 percent. There is no sampling error because this was a complete census of the population.

6.3 SRS construction worker classification QA summaries

The classification of workers as CTWs or nonCTWs workers was compiled from four data 

sources: americium logbook data, neptunium logbook data, NOCTS whole body count data, and 

ORAUT-RPRT-0058 (NIOSH, 2012) in vitro data. The data entry accuracy for each of these 

sources was evaluated in accordance with lot acceptance procedures presented in RPRT-0078. 

Critical fields were defined as the fields containing the PRID and the numerical sample result. 

Critical fields were evaluated with a maximum 1 percent allowable error rate. All other fields 

were evaluated with a maximum 5 percent allowable error rate. 
Effective date: 9/4/2019 Revision No. 0 (Draft) Document No. SCA-TR-2019-SEC004 Page 64 of 79

NOTICE: This document has been reviewed to identify and redact any information that is protected by the 

Privacy Act 5 U.S.C. § 552a and has been cleared for distribution.

The results of these four analyses are shown in parts 5 through 8 of tables 18 and 19. The 

americium in part 5 passed the QA check with estimated error rates and the 95 percent UCL 

below 1 percent for critical and well below 5 percent for all-fields analyses. 

The neptunium QA check in part 6 shows two sets of entries for the critical-fields analysis. Part 

6a is marked with note (a). As explained in the note, the count of 27 errors includes six payroll 

prefix and other payroll ID issues that would have no impact on data use in the coworker model. 

When these errors are included, the 95 percent UCL is 1.18 percent, which exceeds the 1 percent

acceptance criterion for critical fields. 

Examples of these payroll ID errors are described and dismissed as follows: 

Examples of prefix issues that have no impact on the data use are using “0-,” “1-,” 

“T-,” or no prefix interchangeably; presence of a prefix when there was not a 

prefix on the source data and vice versa (although present in other locations and 

accurate); and substitution of craft codes for a Roll code of 4-, 5-, or 6- or vice 

versa. Because these errors have no effect on the usability of the data, they were 

excluded from the calculation of the error rate. [NIOSH, 2019a, p. 119] 

When these payroll ID issues are excluded from the error count, the 95 percent UCL is reduced 

to 0.96 percent, which now meets the 1 percent acceptance criterion for critical fields.

The NOCTS whole body count and MFP tests shown in parts 7 and 8 of tables 18 and 19 also 

show two sets of results for both critical fields and all fields. The initial results for each analysis 

(notes (b), (c), (d), and (e) show very high error rates, with estimates ranging from 5 percent to 

over 60 percent. These estimates exceed the acceptance criteria by a wide margin. As discussed 

for the neptunium data above, these high error rates were found to be due to large numbers of 

payroll prefix and other payroll ID issues that would have no impact on data use in the coworker 

model. After removing these payroll ID errors, the estimated error rates and the 95 percent UCLs 

all meet the respective acceptance criteria. 

6.4 Construction worker determination QA summaries

The accuracy of the CTW determinations obtained from the Master Occupation Table were 

checked against the NOCTS in vivo bioassay dataset, the NOCTS in vitro bioassay dataset, the 

NOCTS tritium bioassay dataset, and the neptunium logbook bioassay dataset. The results are 

summarized in parts 9, 10, 11, and 13 of tables 18 and 19. CTW determinations based on the 

Master Occupation Table and the CTW Designation Instructions were checked against the 

worker history cards, or CATI or personnel dosimetry quarterly reports using the lot acceptance 

procedures described in RPRT-0078. These all-fields analyses were evaluated with a maximum 

5 percent allowable error rate as the acceptance criterion.

The results of these four analyses are shown in parts 9, 10, 11, and 13 of table 19. Each analysis 

passed the QA check with estimated error rates and the 95 percent UCL below 5 percent. The 

study authors note that most classification errors observed were due to individuals changing 

occupations from CTW to nonCTW, or vice versa, during their career.
Effective date: 9/4/2019 Revision No. 0 (Draft) Document No. SCA-TR-2019-SEC004 Page 65 of 79

NOTICE: This document has been reviewed to identify and redact any information that is protected by the 

Privacy Act 5 U.S.C. § 552a and has been cleared for distribution.

6.5 Summary and conclusions

NIOSH has used a variety of procedures to conduct the series of completeness tests reported in 

ORAUT-0081, attachment A. Table 19 summarizes the results of these tests. The estimated 

percentage error rates shown in the table are within the stated goals for each test, except for 

round 1 of the part 2a in vivo completeness test and the table 19 rows noted by (a), (b), (c), (d), 

and (e). In part 2a, round 1, a small sample size resulted in a 95 percent UCL that did not meet 

the stated goal of less than a 5 percent error rate. A follow-up test in round 2 (table 19, part 2b) 

was conducted using the cluster sampling methodology recommended in RPRT-0086. This test 

resulted in an almost 5-fold increase in the sample size and a test result that meets the stated 

goal. 

In the table 19 rows noted by (a), (b), (c), (d), and (e) the estimated error rates exceed the goal 

for the test. This is due to a large number of payroll prefix-matching errors and other PRID 

issues. The test results obtained, after these errors are corrected, are within the stated goal in each 

case.

The last row of table 19 shows the total number of items checked without including the rows 

noted by (a), (b), (c), (d), and (e). The total combines test results for the critical field tests and the 

all-fields tests. Out of 40,127 items checked, a total of 303 errors were found (refer to note (f)). 

The estimated overall error rate is 0.76 percent. It is difficult to calculate the 95 percent UCL for 

the overall test result using a formula, but the information in table 19 (less the rows indicated by 

notes (a), (b), (c), (d), and (e)) is sufficient to estimate the 95 percent confidence interval for the 

overall error rate of attachment A using Monte Carlo simulation. 

The estimated error rate in each row is assigned a triangular distribution with endpoints at the 

upper and lower 96 percent confidence limits and a mode at the estimated error rate. In the 

simulation for each row, an error rate pi is drawn from the triangular distribution. The number of 

errors for that row is assigned a binomial distribution with parameters pi and ni, where ni is the 

number of items checked in table 19. The procedure was iterated 100,000 times, and the results 

are shown in figure 22 and in the totals row of table 19. The 95 percent LCL for the overall test 

result is 0.60 percent, and the 95 percent UCL for the overall test result is 0.94 percent. The 

simulated 99 percent UCL for the overall test result is also shown in figure 22. The estimate is 

0.994 percent, slightly less than the 1 percent overall error rate used as a goal for critical field 

matching in many of the attachment A tests.

In conclusion, the results shown in attachment A of OTIB-0081 demonstrate a high degree of 

confidence that the acceptable error rates are within the goals established for each test. This 

conclusion is based on the presumption that the large number of payroll prefix-matching errors 

and other PRID issues encountered in the noted rows of table 19 would not affect the outcome of 

coworker modeling or the CTW/nonCTW classification of workers. Were this presumption not 

true, the favorable conclusion reached here would be reversed. 

Observation 7: The results shown in attachment A of OTIB-0081 demonstrate a high degree of 

confidence that the acceptable error rates are within the goals established for each test. However, 

this conclusion is dependent on the assumption that payroll ID issues identified would not affect 

the resulting coworker distributions.
Effective date: 9/4/2019 Revision No. 0 (Draft) Document No. SCA-TR-2019-SEC004 Page 66 of 79

NOTICE: This document has been reviewed to identify and redact any information that is protected by the 

Privacy Act 5 U.S.C. § 552a and has been cleared for distribution.

Figure 22. Histogram of simulated overall error rate for attachment A tests with 95% confidence 

interval and 99% UCL

7 References

Advisory Board on Radiation and Worker Health (ABRWH). (2017). Advisory Board on 

Radiation and Worker Health 120th meeting Wednesday, December 13, 2017 [Transcript]. 

Albuquerque, NM. Retrieved from https://www.cdc.gov/niosh/ocas/pdfs/abrwh/2017/tr121317-

508.pdf

European Commission. (2018). Technical recommendations for monitoring individuals for 

occupational intakes of radionuclides (Radiation Protection No. 188, ISSN 2315-2826). 

Retrieved from https://ec.europa.eu/energy/sites/ener/files/rp_188.pdf 

International Commission on Radiological Protection (ICRP). (1968). Report of Committee IV on 

evaluation of radiation doses to body tissues from internal contamination due to occupational 

exposure (Publication 10). Oxford: Pergamon Press.
Effective date: 9/4/2019 Revision No. 0 (Draft) Document No. SCA-TR-2019-SEC004 Page 67 of 79

NOTICE: This document has been reviewed to identify and redact any information that is protected by the 

Privacy Act 5 U.S.C. § 552a and has been cleared for distribution.

International Commission on Radiological Protection (ICRP). (1989). Individual monitoring for 

intakes of radionuclides by workers (Publication 54). Ann. ICPR, 19(1-3). 

International Commission on Radiological Protection (ICRP). (1997). Individual monitoring for 

internal exposure of workers (Publication 78). Ann. ICRP, 27(3-4). 

National Institute for Occupational Safety and Health (NIOSH). (2005). Savannah River Site

(ORAUT-TKBS-0003, rev. 03). Retrieved from 

https://www.cdc.gov/niosh/ocas/pdfs/tbd/srs3.pdf 

National Institute for Occupational Safety and Health (NIOSH). (2007). Construction trades 

workers (OCAS-PER-014, rev. 00). Retrieved from 

https://www.cdc.gov/niosh/ocas/pdfs/pers/oc-per14-r0.pdf

National Institute for Occupational Safety and Health (NIOSH). (2009). Use of claimant datasets 

for coworker modeling (ORAUT-OTIB-0075, rev. 00). Retrieved from SRDB Ref. ID 67223 

National Institute for Occupational Safety and Health (NIOSH). (2012). A comparison of mixed 

fission and activation product coworker models at the Savannah River Site (ORAUT-RPRT0058, rev. 00). Retrieved from https://www.cdc.gov/niosh/ocas/pdfs/orau/oraurpts/or-rprt-58-

r0.pdf

National Institute for Occupational Safety and Health (NIOSH). (2013). Los Alamos National 

Laboratory – occupational internal dose (ORAUT-TKBS-0010-5, rev. 02). Retrieved from 

https://www.cdc.gov/niosh/ocas/pdfs/tbd/lanl5-r2.pdf

National Institute for Occupational Safety and Health (NIOSH). (2014a). Rocky Flats Plant – 

occupational internal dose (ORAUT-TKBS-0011-5, rev. 03). Retrieved from 

https://www.cdc.gov/niosh/ocas/pdfs/tbd/rocky5-r3.pdf 

National Institute for Occupational Safety and Health (NIOSH). (2014b). Analysis of stratified 

coworker datasets (ORAUT-RPRT-0053, rev. 02). Retrieved from 

https://www.cdc.gov/niosh/ocas/pdfs/orau/oraurpts/or-rprt-53-r2.pdf 

National Institute for Occupational Safety and Health (NIOSH). (2015a). Draft criteria for the 

evaluation and use of coworker datasets (rev. 4.1). Cincinnati, OH: Division of Compensation 

Analysis and Support, NIOSH. 

National Institute for Occupational Safety and Health (NIOSH). (2015b). External dose 

coworker methodology (ORAUT-RPRT-0071, rev. 00). Retrieved from SRDB Ref. ID 145135 

National Institute for Occupational Safety and Health (NIOSH). (2016a). Internal coworker 

dosimetry data for the Savannah River Site (ORAUT-OTIB-0081, rev. 03). Retrieved from 

https://www.cdc.gov/niosh/ocas/pdfs/tibs/or-t81-r3.pdf

National Institute for Occupational Safety and Health (NIOSH). (2016b). Technical basis for 

sampling plan (ORAUT-RPRT-0078, rev. 00). Retrieved from 

https://www.cdc.gov/niosh/ocas/pdfs/orau/oraurpts/or-rprt-78-r0-508.pdf
Effective date: 9/4/2019 Revision No. 0 (Draft) Document No. SCA-TR-2019-SEC004 Page 68 of 79

NOTICE: This document has been reviewed to identify and redact any information that is protected by the 

Privacy Act 5 U.S.C. § 552a and has been cleared for distribution.

National Institute for Occupational Safety and Health (NIOSH). (2017). Internal dosimetry 

coworker data completeness test (ORAUT-RPRT-0086, rev. 00). Retrieved from SRDB Ref. ID 

167778 

National Institute for Occupational Safety and Health (NIOSH). (2018). Internal dose 

reconstruction (ORAUT-OTIB-0060, rev. 02). Retrieved from 

https://www.cdc.gov/niosh/ocas/pdfs/tibs/or-t60-r2-508.pdf 

National Institute for Occupational Safety and Health (NIOSH). (2019a). Internal coworker 

dosimetry data for the Savannah River Site (ORAUT-OTIB-0081, rev. 04). Retrieved from 

https://www.cdc.gov/niosh/ocas/pdfs/tibs/or-t81-r4-508.pdf

National Institute for Occupational Safety and Health (NIOSH). (2019b). Multiple imputation 

applied to bioassay coworker models (ORAUT-RPRT-0096, rev. 00). Retrieved from SRDB 

Ref. ID 175396 

National Institute for Occupational Safety and Health (NIOSH). (2019c). Evaluation of bioassay 

data for subcontracted construction trade workers at the Savannah River Site (ORAUT-RPRT0092, rev. 00). Retrieved from SRDB Ref. ID 176739 

National Institute for Occupational Safety and Health (NIOSH). (2019d). Evaluation of 

Savannah River Site americium-241 source terms between 1971 and 1999 using bioassay 

frequency tables (ORAUT-RPRT-0091, rev. 00). Retrieved from 

https://www.cdc.gov/niosh/ocas/pdfs/orau/oraurpts/or-rprt-91-r0-508.pdf 

SC&A, Inc. (2010). Review of ORAUT-OTIB-0075: Use of claimant datasets for coworker 

modeling for construction workers at Savannah River Site. Retrieved from 

https://www.cdc.gov/niosh/ocas/pdfs/abrwh/scarpts/sca-ortib75-r0.pdf 

SC&A, Inc. (2014, February 24). Discussion items and clarifications for February 26th work 

group meeting [Memorandum]. Retrieved from 

https://www.cdc.gov/niosh/ocas/pdfs/abrwh/scarpts/sca-srswg-022414.pdf

SC&A, Inc. (2017a). Focused review on the concurrence of ORAUT-OTIB-0081, revision 03, 

and the draft coworker implementation criteria (SCA-TR-2017-SEC005, rev. 0). Retrieved from 

https://www.cdc.gov/niosh/ocas/pdfs/abrwh/scarpts/sca-tib81r3dcic-r0.pdf

SC&A, Inc. (2017b). SC&A’s evaluation of ORAUT-OTIB-0075, revision 01, “Use of claimant 

datasets for coworker modeling” (SCA-TR-2017-PR011, rev. 0). Retrieved from

https://www.cdc.gov/niosh/ocas/pdfs/abrwh/scarpts/sca-ortib75r1-r0.pdf

SEC Issues Work Group. (2015). U.S. Department of Health and Human Services, Centers for 

Disease Control, National Institute for Occupational Safety and Health, Advisory Board on 

Radiation and Worker Health, SEC Issues Work Group, Tuesday, March 10, 2015. [Transcript of 

teleconference meeting]. Retrieved from 

https://www.cdc.gov/niosh/ocas/pdfs/abrwh/2015/wgtr031015.pdf 
Effective date: 9/4/2019 Revision No. 0 (Draft) Document No. SCA-TR-2019-SEC004 Page 69 of 79

NOTICE: This document has been reviewed to identify and redact any information that is protected by the 

Privacy Act 5 U.S.C. § 552a and has been cleared for distribution.

SRS Work Group. (2014a). U.S. Department of Health and Human Services, Centers for Disease 

Control, National Institute for Occupational Safety and Health, Advisory Board on Radiation 

and Worker Health, Savannah River Site (SRS) Work Group, Wednesday, February 5, 2014

[Transcript]. Hebron, KY. Retrieved from 

https://www.cdc.gov/niosh/ocas/pdfs/abrwh/2014/wgtr020514.pdf 

Savannah River Site (SRS) Work Group. (2014b). U.S. Department of Health and Human 

Services, Centers for Disease Control, National Institute for Occupational Safety and Health, 

Advisory Board on Radiation and Worker Health, Savannah River Site Work Group, Wednesday, 

February 26, 2014 [Transcript of teleconference meeting]. Retrieved from 

https://www.cdc.gov/niosh/ocas/pdfs/abrwh/2014/wgtr022614.pdf

Savannah River Site (SRS) Work Group. (2017). U.S. Department of Health and Human 

Services, Centers for Disease Control, National Institute for Occupational Safety and Health, 

Advisory Board on Radiation and Worker Health, Work Group on Savannah River Site, Tuesday, 

November 14, 2017 [Transcript], Hebron, KY. Retrieved from 

https://www.cdc.gov/niosh/ocas/pdfs/abrwh/2017/wgtr111417-508.pdf 

Savannah River Site (SRS) Work Group & Special Exposure Cohort (SEC) Issues Work Group. 

(2017). U.S. Department of Health and Human Services, Centers for Disease Control, National 

Institute for Occupational Safety and Health, Advisory Board on Radiation and Worker Health, 

Savannah River Site (SRS) Work Group and the Special Exposure Cohort (SEC) Issues Work 

Group, Wednesday, August 16, 2017 [Transcript of teleconference meeting]. Retrieved from 

https://www.cdc.gov/niosh/ocas/pdfs/abrwh/2017/wgtr081617-508.pdf

Westinghouse Savannah River Corporation (WSRC). (1990). Internal dosimetry technical basis

manual (WSRC-IM-90-139). Retrieved from SRDB Ref. ID 11266
Effective date: 9/4/2019 Revision No. 0 (Draft) Document No. SCA-TR-2019-SEC004 Page 70 of 79

NOTICE: This document has been reviewed to identify and redact any information that is protected by the 

Privacy Act 5 U.S.C. § 552a and has been cleared for distribution.

Attachment A: Disposition of SC&A’s OTIB-0081, Rev. 03 

(SC&A, 2017a) Findings and Observations

Findings

SC&A (2017a) Finding 1 

The analysis of the completeness of trivalent logbook records provided in [OTIB0081, revision 03] ends in 1981, though the proposed coworker analysis of 

trivalent bioassay extends through 1989. It would be beneficial to extend the 

completeness analysis to all years in which trivalent urinalysis data is being 

proposed for coworker evaluation. This is particularly important because the 

current completeness analysis suggests that the available logbook data totals are 

less than those reported in monthly and annual health physics summaries 

beginning in 1969. 

SC&A recommended disposition 

Internal monitoring data for trivalent radionuclides are provided up through 1987, with intake 

estimates provided up through 1989 in section 5.0 of OTIB-0081, revision 04. In addition, it was 

noted that many of the totals associated with available logbook data had been inadvertently 

reported low due to the original tallies not including samples that had been excluded from the 

coworker model for valid reasons, such as samples “lost in process.” Additional discussion of the 

completeness of Am/Cm/Cf logbook results can be found in section 4.2 of this report. SC&A 

finds that this issue has been addressed in the context of the OTIB-0081, rev. 03 review and 

recommends closure.

SC&A (2017a) Finding 2

SC&A does not find the discrepancies between reported bioassay totals of 

Am/Cm/Cf and available logbook results to be credibly explained by the inclusion 

of fecal results beginning in 1969. Evidence suggests that fecal results were 

tabulated separately, as shown in a Works Technical Report from January 1972. 

SC&A recommended disposition

No additional information concerning this issue is provided other than previous statements 

hypothesizing that inclusion of fecal results, among other uncertainties, caused the discrepancy 

between reported bioassay totals and available logbook results. Am/Cm/Cf bioassay data 

completeness is discussed in section 4.2 of this report. SC&A considers this finding to remain 

open pending further work group discussion. 

SC&A (2017a) Finding 3

The combination of multiple years of trivalent actinide bioassay data during the 

1980s was not sufficiently justified with a corresponding discussion of site 

activities and/or associated exposure potential at SRS as mandated in [NIOSH, 

2015a]. Group or cohort monitoring may justify the appropriate combination of 

annual data; however, this practice was not sufficiently established in 

[OTIB-0081, revision 03]. 
Effective date: 9/4/2019 Revision No. 0 (Draft) Document No. SCA-TR-2019-SEC004 Page 71 of 79

NOTICE: This document has been reviewed to identify and redact any information that is protected by the 

Privacy Act 5 U.S.C. § 552a and has been cleared for distribution.

SC&A recommended disposition

No further justification based on site activities and/or associated exposure potential at SRS was 

presented in revision 04 to justify the combination of multiple years for TWOPOS analysis. 

Therefore, SC&A believes this finding should remain open. However, SC&A notes that a new 

NIOSH report concerning americium exposures is imminent, which is expected to address this 

issue.

SC&A (2017a) Finding 4

The SRS bioassay procedures for routinely monitored workers during the early 

periods (1954–1970 for tritium and 1964–1967 for exotic trivalent actinides) are 

not addressed in [OTIB-0081, revision 03]. SC&A’s review of the Bioassay 

Control Reports referenced for this period did not find any sampling schedules or 

bioassay procedures listed. Therefore, it would be advantageous to have 

additional information about the bioassay requirements for the early periods. 

SC&A recommended disposition

OTIB-0081, revision 04, page 46 added two paragraphs concerning tritium bioassay frequency 

with Site Research Database (SRDB) references added for 1964–1966 and 1959–1971; SC&A 

agrees that this addressed the tritium issue. However, OTIB-0081, revision 04 did not provide 

any additional information about the bioassay requirement for the exotic trivalent actinides for 

the early period of 1964–1967; therefore, this part of the finding is still open. However, SC&A 

notes that a new NIOSH report concerning americium exposures is imminent, which is expected 

to address this issue.

SC&A (2017a) Finding 5

While evaluating monitoring practices related directly to thorium is not possible 

because SRS did not directly monitor for thorium, a discussion of the relationship 

between trivalent actinide monitoring practices and thorium exposure potential is 

warranted to establish that Am/Cm/Cf urinalysis data are an appropriate surrogate 

for thorium exposures. It does not appear that a verification demonstrating that a 

sufficient percentage of known thorium workers were included in the Am/Cm/Cf 

coworker dataset was performed, as was requested at the February 5, 2014, 

meeting of the SRS Work Group [SRS Work Group, 2014a]. 

SC&A recommended disposition

No additional information concerning thorium exposure was included in revision 04 of 

OTIB-0081. However, NIOSH has provided additional information in the Board Review System 

(BRS) for work group discussion. Therefore, this finding can be considered in progress.

SC&A (2017a) Finding 6

Derived coworker intakes were stratified into construction and non-construction 

workers for each of the three revised coworker models. However, [OTIB-0081, 

revision 03] does not present the statistical basis used to determine that 

stratification is necessary for each radionuclide of interest and for each time 

period as detailed in ORAUT-RPRT-0053, Revision 02, Analysis of Stratified 
Effective date: 9/4/2019 Revision No. 0 (Draft) Document No. SCA-TR-2019-SEC004 Page 72 of 79

NOTICE: This document has been reviewed to identify and redact any information that is protected by the 

Privacy Act 5 U.S.C. § 552a and has been cleared for distribution.

Coworker Datasets [NIOSH, 2014b], as well as in the implementation guide 

[NIOSH, 2015a]. 

SC&A recommended disposition

OTIB-0081, revision 04, pages 26–27 provided additional information concerning stratification 

of CTWs versus nonCTWs. While some of the coworker data in section 5.0 of OTIB-0081, 

revision 04 indicate similar intake values for CTWs as for nonCTWs, the additional 

radionuclides addressed in revision 04 of OTIB-0081 illustrate that there were noticeable 

differences in intake for CTWs versus nonCTWs for some other radionuclides. The basis for 

stratification is subsumed by the discussion in section 5 of this report; therefore, SC&A 

recommends that finding 6 be considered closed in the context of OTIB-0081, revision 03. 

Observations

Observation 1

SC&A requests clarification and/or documentation of the analytical chemistry 

phenomenon in which chelation treatment causes heterogeneity of contaminants 

for aliquots of a single bioassay voiding. 

SC&A recommended disposition

SC&A could find no significantly new information concerning this issue in revision 04 of 

OTIB-0081; NIOSH uses approximately the same wording on pages 21, 43, 54, 83, 139, 140, 

151, 152, 153, and 156 as in revision 03 of OTIB-0081. Section 3.1 of this report provides 

additional discussion in a statistical context of the issue of measurement variability among 

aliquots of the same sample. Therefore, this observation is considered in progress but can likely 

be subsumed under finding 1 of this report. 

Observation 2

Derived coworker tritium doses appear to increase substantially beginning in 

1958, which coincides with the change in bioassay analysis for tritium. The cause 

for the apparent change in exposure potential should be discussed to determine if 

the prior method to detect tritium intakes was insufficient or if actual exposures 

markedly increased during this time, which would explain the increase in 

coworker doses. 

SC&A recommended disposition 

SC&A could find no significantly new information concerning this issue in revision 04 of 

OTIB-0081. However, the issue had been discussed and closed during work group discussions in 

August 2017 (SRS Work Group & SEC Issues Work Group, 2017). 

Observation 3

It is unclear based on [OTIB-0081, revision 03] how NIOSH intends to 

reconstruct intakes of exotic trivalent actinides and thorium post-1989 (e.g., 

extension of 1989 derived coworker intake rates, use of electronic Health Physics 

Radiological Exposure Database [HPRED] data, or application of some fraction 

of the derived air concentration). 
Effective date: 9/4/2019 Revision No. 0 (Draft) Document No. SCA-TR-2019-SEC004 Page 73 of 79

NOTICE: This document has been reviewed to identify and redact any information that is protected by the 

Privacy Act 5 U.S.C. § 552a and has been cleared for distribution.

SC&A recommended disposition

SC&A could find no significantly new information concerning this issue in revision 04 of 

OTIB-0081. Approximately the same wording (“may be extended”) is used on page 90 of 

revision 04 as on page 31 of revision 03 of OTIB-0081. However, it is SC&A’s understanding 

that this issue will be addressed in the future on an as-needed basis and pending acceptance of 

current dose reconstruction methods. SC&A considers this observation in abeyance. 

Observation 4

Discrepancies between the number of available exotic trivalent logbook entries 

and health physics summary reports prior to 1969 are not discussed in 

[OTIB-0081, revision 03]. Documentation of the internal monitoring in 1967 may 

indicate that health physics summary reports did not include Construction Trade 

Workers (CTWs). 

SC&A recommended disposition

SC&A could find no significantly new information concerning this issue in revision 04 of 

OTIB-0081 as compared to revision 03. NIOSH’s position, as stated on the BRS, is that the 

agreement between the number of logbook entries and reported results shows “quite good 

agreement.” Furthermore, the comparison is only qualitative due to uncertainty in the 

interpretation of such reports. However, work group deliberations on the observation have not 

been finalized. Therefore, this observation can be considered in progress.

Observation 5

It is not clear to SC&A why the date of the bioassay sample is not considered a 

“critical field” for the purposes of performing quality assurance (QA) tests on the 

transcribed dataset for trivalent actinides as well as tritium. The date of the sample 

is a crucial component to correctly performing the time-weighted one person-one 

sample (TWOPOS) calculation for Am/Cm/Cf and thorium as well as the annual 

dose for tritium. 

SC&A recommended disposition

OTIB-0081, page 109 of revision 04 includes three items in the critical field (date of bioassay, 

radionuclide, and results). This item was discussed during the SRS Work Group meeting on 

August 16, 2017, and it was decided that the date of the sample does not qualify as a “critical 

field.” The work group closed the observation at that time (SRS Work Group & SEC Issues 

Work Group, 2017). 

Observation 6

SC&A requests clarification on what aspects of the tritium coworker model 

analysis were subject to the QA criteria described in Section 2.0 of [NIOSH, 

2015a] and proceduralized in ORAUT-RPRT-0078, Technical Basis for Sampling 

Plan [NIOSH, 2016b]. Based on SC&A’s interpretation of the analysis in 

[NIOSH, 2016b], it appears that only the delineation between construction and 

non-construction workers was tested for quality assurance. 
Effective date: 9/4/2019 Revision No. 0 (Draft) Document No. SCA-TR-2019-SEC004 Page 74 of 79

NOTICE: This document has been reviewed to identify and redact any information that is protected by the 

Privacy Act 5 U.S.C. § 552a and has been cleared for distribution.

SC&A recommended disposition

OTIB-0081, page 48, section 4.2.2 added information concerning this issue, and pages 108–116 

in attachment A of revision 04 contains a transcription of the complete QA test results that were 

not in revision 03. Therefore, SC&A considers this observation sufficiently addressed and 

recommends closure.

Observation 7

The available CTW bioassay data for subcontractors has yet to be validated and 

verified; i.e., it has yet to be demonstrated that the majority of the subcontractor 

CTW bioassay data has been located and has correctly been transcribed to the 

databases used to create the coworker model intakes. This validation and 

verification activity is currently being undertaken at the direction of the SRS 

Work Group. 

SC&A recommended disposition

This additional evaluation by NIOSH and the SRS work group is still ongoing; therefore, this 

issue can be considered in progress. 

Observation 8 

[OTIB-0081, revision 03] appears to contradict itself on whether prime CTWs 

represent a similar monitoring protocol as subcontractor CTWs. Prime 

construction workers are described as being exposed “temporarily but frequently 

for short periods” but also on an annual bioassay schedule specified by the 

bioassay control procedures. Subcontractor workers were monitored on a case-bycase basis depending on the localized requirements of the job. 

SC&A recommended disposition 

There is additional information in section 3.2, pages 26–33, of revision 04 related to this issue. 

Additionally, current evaluations in progress by SC&A and NIOSH concerning subcontractor 

CTW bioassays compared to primary contractor CTW bioassays are intended to address this 

issue further. Therefore, SC&A recommends closure of this observation in relation to its review 

OTIB-0081, revision 03.
Effective date: 9/4/2019 Revision No. 0 (Draft) Document No. SCA-TR-2019-SEC004 Page 75 of 79

NOTICE: This document has been reviewed to identify and redact any information that is protected by the 

Privacy Act 5 U.S.C. § 552a and has been cleared for distribution.

Attachment B: Disposition of SC&A’s ORAUT-OTIB-0075 Review 

Findings

SC&A had 13 findings (SC&A, 2010) concerning ORAUT-OTIB-0075, “Use of Claimant 

Datasets for Coworker Modeling,” revision 00 (NIOSH, 2009; “OTIB-0075”). In 2017, SC&A 

revisited the 13 findings subsequent to the issuance of revision 01 of OTIB-0075 for relevance to 

SEC-00103 and found that findings 1, 6, and 7 were applicable to the National Security Complex 

(Y-12), findings 2 and 8 were applicable to Mound Laboratory, and findings 3, 4, 5, 9, 10, 11, 

12, and 13 were applicable to SRS (SC&A 2017b). This attachment presents an updated review 

of the SRS findings to determine if the recently released revision 04 of OTIB-0081 contains new 

or additional information that may resolve any of the original SC&A findings for SRS from the 

original review of OTIB-0075. 

SC&A (2010) Finding 3

At SRS, the complete (all-worker) and claimant datasets for annual tritium doses 

from 1991 to 2001 show no significant difference at the annual level of 

aggregation, but the sample size is very small and the regression results were 

dominated by a single year with high exposure, 1991. If this year is omitted, the 

complete and claimant datasets for annual tritium doses period from 1992 through 

2001 again show no significant difference at the annual level of aggregation. 

SC&A 2019 comment

This was a statement that SC&A concurred with NIOSH’s results but cautioned that they cannot 

be extrapolated to other radionuclides and time periods. Therefore, this presently would be 

considered an observation instead of a finding. However, issues associated with the 

representativeness of claimant datasets to the sitewide worker population is beyond the scope of 

this report and will be addressed separately.

SC&A (2010) Finding 4 

At SRS, OTIB-0075 includes data only for tritium from 1991 to 2001 in 

comparing the claimant population to that of all workers. No analysis of uranium 

or plutonium exposures at SRS was possible, because the available hardcopy data 

have not been reduced to electronic form. Similarly, no analysis of uranium or 

fission product exposures regarding the validity of the central hypothesis of 

OTIB-0075 for SRS could be done for any period. No analysis of tritium 

exposures before 1991 was done for the same reason. Furthermore, the tritium 

conclusion cannot be back-extrapolated in time, since the production and work 

conditions relating to tritium were different in earlier periods.

SC&A 2019 comment

OTIB-0081 provides coworker intake values for uranium and fission products as well as annual 

tritium doses. However, these intakes/doses were developed under the assumption that claimant 

datasets are representative of the full monitored workforce. Issues associated with the 

representativeness of claimant datasets to the sitewide worker population is beyond the scope of 

this report and thus should be addressed separately.
Effective date: 9/4/2019 Revision No. 0 (Draft) Document No. SCA-TR-2019-SEC004 Page 76 of 79

NOTICE: This document has been reviewed to identify and redact any information that is protected by the 

Privacy Act 5 U.S.C. § 552a and has been cleared for distribution.

SC&A (2010) Finding 5 

Data for the entire SRS were aggregated by year for the NIOSH analysis, with no 

detail by work area or by job type. The proposed NIOSH coworker model for 

SRS construction workers includes no analysis of these details.

SC&A 2019 comment

OTIB-0081, revision 04, has stratified the SRS workers into the two categories of nonCTW and 

CTW, and further work is currently in process concerning the exposure potential and monitoring 

practices for prime CTW and subcontract CTW. Additional discussion on this issue is presented 

in section 5.2 of this report concerning individual strata designation. However, this does not fully 

address the issue of differences in exposure potential among different work areas and specific job 

types rather than general classification. SC&A recognizes that further stratification according to 

work areas of the already stratified nonCTW and CTW coworker data and radionuclides could 

potentially result in large uncertainties and/or the lack of sufficient data points due to the

diminishing number of bioassay results available for each subcategory. However, if a unique 

situation is identified in a given area in which a specific radionuclide may have presented a much 

larger than normal intake than sitewide monitoring would indicate, then that exposure potential 

would have to be addressed on an individual basis. Such area- and job-specific analysis 

indicating the potential for further stratification is beyond the scope of this report and will be 

addressed separately. 

SC&A (2010) Finding 9 

At SRS, the 84th percentile of exposures to tritium, plutonium, uranium, and other 

radionuclides for non-construction workers in specific work areas show 

considerable differences from the 84th percentile of exposures to non-construction 

workers site-wide. Similar results are observed for the corresponding ratio of the 

GSDs.

SC&A 2019 comment

Same as for the SC&A (2010) finding 5 recommendation. 

SC&A (2010) Finding 10

At SRS, the 84th percentile of exposures to tritium, plutonium, and other 

radionuclides for construction workers in specific work areas show considerable 

differences from the 84th percentile of exposures to all [non] construction workers 

site-wide. Similar results are observed for the corresponding ratio of the GSDs. 

SC&A 2019 comment

Same as for the SC&A (2010) finding 5 recommendation. 

SC&A (2010) Finding 11

At SRS, the 84th percentile of exposures to tritium and plutonium for construction 

workers in specific work areas show large differences from the 84th percentile of 

site-wide exposures to construction workers. Similar results are observed for the 
Effective date: 9/4/2019 Revision No. 0 (Draft) Document No. SCA-TR-2019-SEC004 Page 77 of 79

NOTICE: This document has been reviewed to identify and redact any information that is protected by the 

Privacy Act 5 U.S.C. § 552a and has been cleared for distribution.

corresponding ratio of the GSDs. In many cases, there are insufficient data for 

construction workers to make a comparison for uranium, enriched uranium, and 

fission products.

SC&A 2019 comment

Same as for the SC&A (2010) finding 5 recommendation. 

SC&A (2010) Finding 12

At SRS, the 84th percentile of exposures to tritium for construction workers in 

specific crafts shows large differences from the 84th percentile of exposures to all 

construction workers. Similar results are observed for the corresponding ratio of 

the GSDs.

SC&A 2019 comment

Same as for the SC&A (2010) finding 5 recommendation. 

SC&A (2010) Finding 13

At SRS, the 84th percentile of exposures to tritium for construction workers in 

specific crafts shows large differences from the 84th percentile of site-wide 

exposures for non-construction workers. Similar results are observed for the 

corresponding ratio of the GSDs. 

SC&A 2019 comment

Same as for the SC&A (2010) finding 5 recommendation. 
Effective date: 9/4/2019 Revision No. 0 (Draft) Document No. SCA-TR-2019-SEC004 Page 78 of 79

NOTICE: This document has been reviewed to identify and redact any information that is protected by the 

Privacy Act 5 U.S.C. § 552a and has been cleared for distribution.

Attachment C: NOCTS Claim Numbers Associated with Arbitrary 

Case IDs Used in Section 5.2

Arbitrary 

case ID

NOCTS 

claim #

A [redacted]

B [redacted]

C [redacted]

D [redacted]

E [redacted]

F [redacted]

G [redacted]

H [redacted]

I [redacted]

J [redacted]

K [redacted]

L [redacted]

M [redacted]

N [redacted]

O [redacted]

P [redacted]

Q [redacted]

R [redacted]

S [redacted]

T [redacted]

U [redacted]

V [redacted]

W [redacted]

X [redacted]

Y [redacted]

Z [redacted]

AA [redacted]

AB [redacted]

C [redacted]

AD [redacted]

AE [redacted]

AF [redacted]

AG [redacted]

AH [redacted]

AI [redacted]

AJ [redacted]

AK [redacted]

AL [redacted]

AM [redacted]
Effective date: 9/4/2019 Revision No. 0 (Draft) Document No. SCA-TR-2019-SEC004 Page 79 of 79

NOTICE: This document has been reviewed to identify and redact any information that is protected by the 

Privacy Act 5 U.S.C. § 552a and has been cleared for distribution.

Arbitrary 

case ID

NOCTS 

claim #

AN [redacted]

AO [redacted]

AP [redacted]

AQ [redacted]