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APPENDIX A: EXAMPLES OF STRATEGIES USED BY SC&A IN 

REVIEWING THE COMPLETENESS OF AVAILABLE SITE-SPECIFIC 

RECORDS IN AN SEC CONTEXT

As stated previously in this document, two of the most important aspects in making an SEC 

determination are the “adequacy” and the “completeness” of available data sources. In this 

context, “adequacy” refers to the ability to use available data to accurately reflect real and 

meaningful exposures incurred by the worker population with sufficient accuracy. For example, 

during its review of thorium in-vivo (chest count) data for use in reconstructing internal 

exposures to Th-232 and associated daughter products, the Advisory Board determined that 

measurements given in units of “milligrams of thorium” were not “adequate” for the purposes of 

dose reconstruction. The basis of this determination was the lack of raw data and defined 

analytical methods that were used in arriving at the values of mg of thorium.

2

In this way, the 

dataset was not “adequate” to establish real and meaningful exposures for the exposed worker 

population. 

“Completeness” of available datasets does not address the technical accuracy of the data, but 

rather how well the available records are representative of the potentially exposed worker 

population. The issue of data completeness is the subject of this appendix. The three most 

important facets of data completeness can be summarized by the following:

 Temporal coverage: Do the records cover the necessary time periods evaluated by the 

SEC?

 Job type coverage: Are the highest exposed job types covered by the available records?

 Work area coverage: Are the work areas of highest exposure potential represented by the 

available monitoring data?

Obviously, these facets are not mutually exclusive and are usually interdependent. For example, 

a particular dataset may have “complete” data as regards the chronology of the site, but is 

missing data for the highest job types and/or plant areas during some of those years. It must be

noted that decisions regarding the “completeness” of a particular dataset in an SEC context are

ultimately a judgment call. As such, there is no quantitative way to definitely determine whether 

particular monitoring records are complete. However, analytical methods have been used by 

SC&A in the past, which build a “weight of evidence” argument to assist the Advisory Board in 

making such determinations.

This appendix provides examples of some of the analytical approaches that have been used for 

SEC deliberations previously for four different sites (Hanford, Fernald, Nevada Test Site (NTS),

and Mound). The examples were chosen to reflect many of the different scenarios and potential 

problems encountered by the Advisory Board in making SEC recommendations. The four 

chosen examples include analysis of an extensive electronic database (Example 1), compilation 

 

2 Th-232 cannot be measured directly in the lung and so must be inferred from the relative measurements of 

associated daughter products. The original daughter product measurements were not available, nor was the exact 

procedure used in calculating the lung burden of thorium.
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of site-wide data from hardcopy records (Example 2), sampling of claimant dosimetry records 

(Example 3), and use of workplace monitoring in the absence of adequate bioassay records 

(Example 4). 

Example 1: Electronic Internal Dosimetry Database for the Hanford Site

Background Summary:

In 2011, SC&A was tasked with performing a review of the most recent Hanford Site Profile 

(ORAUT 2010a–2010f) with a focus on remaining SEC issues for the period of July 1, 1972,

3

through December 31, 1990. One aspect of this site profile review was to assess the data 

completeness of internal monitoring records during this period. Hanford is somewhat unique, in 

that it has a very extensive electronic database (known as the Radiological Exposure or “REX” 

Database) of worker records, which are available for analysis. As described below, SC&A used 

the REX database to assess the extent of worker monitoring for individual radionuclides as it 

relates to temporal considerations, job title, and work location. The basic methodology and 

information available are described below. For the full results of the completeness analysis, the 

reader is referred to SC&A 2011, Appendix A.

Analytical Approach Taken:

SC&A 2011 states the purpose of the completeness analysis as follows:

The purpose of this report is to examine the internal monitoring records 

contained in the Radiological Exposure Database (REX) for adequacy and 

suitability in constructing the coworker model presented in Appendix C of the 

Hanford Site internal dose TBD (ORAUT 2010e). Specifically, this report will 

seek to identify monitoring practices, exposure potential, and potential gaps as 

they pertain to worker job categories, as well as periods of production and 

exposure potential during the SEC period. (SC&A 2011)

As specified previously, a rather extensive database (REX) contains worker monitoring records 

for the Hanford Site. The REX database itself is made up of nearly 70 individual files; some of 

these files contain monitoring data, while most others represent reference tables that can be used 

to interpret the dosimetry files. As an example, the reference files 

“REX_DOE_OCCUPATION” and “REX_HAN_FACILITY” provide individual codes for job 

title and some individual work areas to be used in other database files. These reference files are 

necessary in order to be able to decode and associate the appropriate job titles and work locations 

with specific workers and monitoring results.

Inspection of the available REX Database files identified five main database files to be used in 

the internal completeness analysis. These files are described in Table A-1. The first file listed, 

REX_WORK_HIST, does not actually contain any monitoring data; however, it enables the 

tracking of individual workers (via an individual ID number) and their respective employment 

 

3 On October 20, 2009, the Advisory Board accepted the NIOSH recommendation to extend the Hanford 

SEC to cover all workers who meet the eligibility criteria up to June 30, 1972.
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periods across the three internal dosimetry files of interest: ‘INV_RESULT,’ 

‘INV_ISO_RESULT,’ and ‘EXC_RESULT.’ The last file in Table A-1, 

‘DOS_SUM_RESULTS,’ is related to external dosimetry; however, it also contains individual 

worker job title information, which can be used to supplement job title information contained in

the internal dosimetry files.

Table A-1: Description of REX Database Files Used in Completeness Study

DATABASE NAME DESCRIPTION

REX_WORK_HIST Identifies workers by a ‘REX ID,’ which allows for the tracking of individual workers 

across the different database files. Also contains employment start and end dates.

INV_RESULT

Lists in-vivo counting samples by REX ID and date, and assigns a tracking number to 

each in-vivo sample, which can be used to obtain the results of the count in 

‘INV_ISO_RESULT’ described in the next row.

INV_ISO_RESULT Uses the tracking number from ‘INV_RESULT’ and provides the radionuclides and 

result of the in-vivo sample.

EXC_RESULT Contains the urinalysis data for workers listed by REX ID.

DOS_SUM_RESULTS

Contains external monitoring results, which are not part of this analysis; however, the 

database also contains job title information, which can be linked to the internal 

database files by REX ID

In many instances in the database, work location and/or job title are not specified for each 

individual internal monitoring result. For example, a worker might have dozens of urinalysis 

data points available, but only one of those results specifies the job title and work area. SC&A 

2011 states the following on this issue:

Because taking this information at face value (i.e., only considering worker 

employment periods with a job title specified or only internal monitoring results 

that specify a work area) would severely limit the amount of data available for 

analysis, an approximate approach was developed, so that as much data as 

possible could be included. To this end, it has been assumed that, if a worker is 

identified with a specific job title, they held that job title throughout their SEC 

employment. Similarly, if a worker is identified with a specific area of work, it is 

assumed they spent their entire employment at that location. (SC&A 2011)

Clearly this type of approach would result in some “double counting” for cases in which a 

worker may have held more than one job title or worked in more than one area of the site. 

SC&A 2011 explored the potential issue of double counting in its completeness study. For 

example, it was found that over 93% of the surveyed workers were associated with only one job 

title in the REX_Database. Less than 1% had more than two job titles, and no worker had more 

than 4 job titles. The effect on work location analyses was less easily quantified; however, it was 

deemed that the assumption of grouping workers into specific areas for the length of their 

employment was more beneficial than any potential loss in accuracy.

Using this assumption and available information on job title and work location scattered 

throughout the database, SC&A was able to modify the information in REX so that the majority 
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of internal monitoring results could be used in the completeness study. The subsequent analysis 

was able to draw some of the following conclusion/findings:

4

(1) For the main radionuclides analyzed (Am, Cs, MFP, Pu, and U), workers associated with 

the 200 Tank Farms were most likely to be monitored during their employment.

(2) ‘Radiation monitors,’ ‘electricians,’ ‘operators,’ ‘pipefitters,’ and ‘science technicians’

were consistently among the five job titles most likely to be monitored during their SEC 

employment.

(3) In general, the most commonly monitored job titles by area and year were ‘managers and 

administrators’ (for the 100, 100-N, 200, and 300 Areas), ‘operators’ (for the 200, 200 

Tank Farms, and 300 Area), and ‘scientists’ (for the 300 Area).

(4) In-vivo records analysis for americium, cesium, mixed fission products, and uranium 

monitoring showed a significant decrease in worker sampling in 1975 (generally less than 

1% of the worker population was monitored). Other significant decreases in worker 

monitoring include 1974 (iodine), 1976–1977 (mixed fission products), and 1985 

(cesium). Thorium-232 was sparsely monitored throughout the period, and there are very 

few data points overall. No significant decreases in worker monitoring were identified 

for plutonium.

(5) Exotic radionuclides with sparsely available records include thorium, iodine, polonium, 

neptunium, radium, curium, californium/berkelium, and ‘total actinides.’ Polonium, 

curium, and ‘total actinides’ were mostly periodic sampling, while radium and neptunium

appear to be incident related.

Finding 1 demonstrates that one of the known areas of highest exposure potential, the 200 Tank 

Farms, had a higher percentage of workers monitored compared to the other areas. Finding 2 

shows that high exposure potential jobs, such as ‘operators’ and ‘technicians,’ were often 

monitored more frequently than many of the other job types. However, Finding 3 also notes that 

‘managers and administrators’ were the most commonly monitored job title for the 100 Area,

and it is not likely that they would be among the highest potentially exposed job types.

Finding 4 notes where there are significant temporal gaps by radionuclide. It is important in the 

context of completeness to establish whether a greater risk for potential exposure might have 

occurred in those years. As part of its completeness review, SC&A also established what years 

and areas particular radionuclides are known to have been handled, so parallels can be drawn 

between any data gaps and any “off-normal” operations. Finally, Finding 5 notes that the 

available records for some of the more exotic radionuclides are sparse and likely not suitable for 

the development of a coworker model from a completeness standpoint.

Example 1 Discussion:

One of the major advantages to this type of approach of a completeness evaluation is the sheer 

amount of information and data contained in the REX database. Though certain assumptions had 

 

4

It must be noted that findings are meant to be summary conclusions and that much more quantitative 

information is contained in SC&A 2011 than is appropriate to include here.
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to be made when applying the information (such as presumed job title and work location), this 

allowed for the inclusion of the vast majority of data available and provided a very good 

overview of the monitoring practices of the site as applied to nearly all workers (nearly 50,000 

workers and their associated bioassay records were included in the completeness study). 

However, the advantages of this type of “site-wide” approach can also be viewed as a drawback,

since issues such as the inconsistency of reporting the work location and job type require that 

workers be “grouped” based on the available information. This results in some “double 

counting,” which can potentially cause the accuracy of conclusions regarding monitoring 

practices to suffer (for example, if one particular job title was ‘reported’ more often in the REX 

database).

One potential solution to this difficulty would be to perform both types of analyses: 

 One analysis that only considers job and area information directly related to an individual 

monitoring result and ignores all other results for that worker

 A second analysis that associates job and area information with a particular worker for 

their entire employment (as was done in SC&A 2011)

The combined findings and observations from both analyses would likely provide a sufficiently 

solid analytical base from which to draw conclusions about the completeness of the available 

records. It should be noted that on May 31, 2012, NIOSH recommended that the SEC class be 

expanded to also cover the period from July 1, 1972, to December 31, 1983, on the basis of 

insufficient information to reconstruct doses to enriched uranium, U-233, neptunium or thorium. 

The Advisory Board agreed with this recommendation during its July 2012 meeting. 

Example 2: Fernald In-Vivo Lung Count for Thorium

Background Summary:

While the majority of processing at Fernald concerned uranium compounds, thorium compounds 

were also processed at the site, at least up until 1979 and perhaps afterwards in a minimal 

capacity. Fernald also became the Department of Energy’s (DOE’s) national repository for 

thorium compounds beginning in 1972. Therefore, even after the end of most processing in 

1979, exposure potential would have existed through stewardship and repackaging operations up 

through the end of the SEC period in 1989.

From 1953 up through 1967, Fernald utilized Daily Weighted Exposure (DWE) studies to 

characterize the alpha contamination present in the worker’s breathing zone as a way of 

controlling radiation intakes. Starting in 1968, Fernald began receiving periodic visits from the 

Mobile In-Vivo Radiation Monitoring Laboratory (MIVRML), which was a mobile lung counter 

developed at Y-12. Once the MIVRML arrived on site, the practice of performing DWE studies 

ceased and monitoring for thorium deposition, along with uranium, was assigned to the mobile 

counter. The MIVRML went through two different periods of reporting conventions for 

thorium; from 1968–1978, thorium measurements were reported in “milligrams of thorium,” 

while post-1978 thorium measurements were reported as the daughter products of Ac-228 and 

Pb-212.
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In March 2008, NIOSH released its coworker model for thorium exposure entitled, Thorium In 

Vivo Coworker Study for FEMP – A Proposed Attachment for ORAUT-TKBS-0017-5, Revision 1

(ORAUT 2008). On April 26, 2012, the Advisory Board determined that Th-232 internal doses 

cannot be reconstructed with sufficient accuracy for the 1968 to 1978 period (when thorium lung 

burdens were reported in mg of Th). Therefore, the following completeness study example will 

focus on the later period of thorium in-vivo monitoring (1979–1988).

Analytical Approach Taken:

No electronic database previously existed to characterize in-vivo monitoring at Fernald. 

Therefore, ORAUT 2008 developed its coworker model using site-specific hardcopy logbooks,

which would document the in-vivo results for individual workers. These logbooks contained the 

worker’s name, a badge number, date of the measurement, number of days off, measurement 

result, and in most cases the work location (by plant) and job title. An example of a typical 

logbook is shown in Figure A-1. One vital piece of evidence that the logbooks do not contain is 

which workers might have handled thorium, and how the in-vivo measurements might reflect 

these potential exposures. The available hardcopy logbooks contained both claimants and nonclaimants, and were compiled into an electronic database by NIOSH/ORAUT. 

Figure A-1. Example of Thorium Logbooks used in ORAUT 2008

Because the practice of reporting the job title and work area was so prevalent, the approach and 

assumptions utilized in Example 15 were not deemed necessary. The first step in the 

completeness evaluation involved looking at an overview of records by year to determine the 

number and relative magnitude of the results. The purpose of this is to determine if there are 

years with significantly less monitoring, but which might have shown greater exposure potential 

via the magnitude of available sampling. An example of this analysis is shown in Table A-2,

which displays the relative magnitude of results by counting the number of results above the 

minimum detectable activity (MDA). As seen in the table, the number of total samples generally 

increased from 1979 onward, with a significant jump in 1984. Meanwhile, the number of 

“positive” samples decreased from 1979 onward, although they still only constituted a small 

 

5 The approach taken in Example 1 assumed that if a worker was associated with a specific job title/work 

area that they held that title and location for their entire employment.
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percentage of the overall monitored population. There do not appear to be significant gaps in the 

number of samples on an annual basis. Based on historical records for Fernald, the large 

increase in frequency of sampling in the mid-1980s is likely due to the increased focus on 

radiological protection, which generally coincided with the change in management from National 

Lead of Ohio to Westinghouse.

Table A-2: Overview of Available In-Vivo Data 1979–1988

Year # Samples

# Samples with 

both Ac and Pb 

Results above the 

MDA

# Samples with 

Only the Ac 

Result above the 

MDA

# Samples with 

Only the Pb 

Result above the 

MDA

# Samples with 

no Results 

above the MDA

1979 177 26 (14.7%) 4 (2.3%) 2 (1.1%) 145 (81.9%)

1980 188 13 (6.9%) 14 (7.4%) 1 (0.5%) 160 (85.1%)

1981 141 8 (5.7%) 3 (2.1%) 1 (0.7%) 129 (91.5%)

1982 180 8 (4.4%) 1 (0.6%) 5 (2.8%) 166 (92.2%)

1983 169 4 (2.4%) 1 (0.6%) 1 (0.6%) 163 (96.4%)

1984 371 9 (2.4%) 3 (0.8%) 0 (0.0%) 359 (96.8%)

1985 382 2 (0.5%) 3 (0.8%) 4 (1.0%) 373 (97.6%)

1986 463 4 (0.9%) 2 (0.4%) 5 (1.1%) 452 (97.6%)

1987 562 4 (0.7%) 1 (0.2%) 5 (0.9%) 552 (98.2%)

1988 108 1 (0.9%) 1 (0.9%) 0 (0.0%) 106 (98.1%)

All In-Vivo Data 

(1979–1988) 2741 79 (2.9%) 34 (1.2%) 24 (0.9%) 2604 (95.0%)

The next step in the completeness study was to break down the in-vivo records by job title to see 

which jobs were sampled the most frequently and how their results compare to other lessmonitored job types. The results are shown in Table A-3, which demonstrate that the most 

commonly monitored job title (Chemical Operator) also had the highest results among any other 

job title. This demonstrates that monitoring was generally focused on the job types with higher 

exposure potential. However, as mentioned previously, the inability to actually identify which 

workers handled thorium and to what extent they are reflected in the monitoring records is still 

somewhat of a concern.

A similar analysis was performed based on plant area; however, the results were less conclusive. 

It is worth noting that a large portion of the results were associated with “other areas” of the site 

(not Plants 1–9). Repackaging and redrumming operations at Fernald were not generally carried 

out inside any of the main plants, so these “other areas” likely cover some of the places where 

these stewardship activities occurred.
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Table A-3: Comparison of In-Vivo Results by Job Title (1979–1988)

Job Title # of Samples (%of Total)

Magnitude of Results

95th Percentile*

(Ac-228)

95th Percentile*

(Pb-212)

Chemical Operator 1207 (55.0%) 0.387 0.330

Unknown 549 (25.0%) 0.150 0.160

Construction Trades 248 (11.3%) 0.096 0.056

Other Operator 156 (7.1%) 0.278 0.194

Millworker 141 (6.4%) 0.100 0.020

Engineer/Technician 81 (3.7%) 0.100 0.030

Supervisor 73 (3.3%) 0.186 0.200

ITO 68 (3.1%) 0.120 0.113

Laborer 59 (2.7%) 0.104 0.071

Inspection/QA 53 (2.4%) 0.084 0.050

Oiler/Degreaser 28 (1.3%) 0.097 0.070

Health and Safety 21 (1.0%) 0.090 0.260

Administrative 20 (0.9%) 0.061 0.057

Mechanic 16 (0.7%) 0.073 0.040

Security 12 (0.5%) 0.183 0.282

Laundry 10 (0.5%) 0.081 0.000

*95th percentile evaluated using Microsoft Excel’s Percentile Function

The last analysis performed for this completeness evaluation involved gaining insight into how 

workers were selected for counting regardless of job type or work area. Specifically, the analysis 

sought to determine if workers who displayed “positive” lung counts were scheduled to be 

monitored more frequently than workers whose results were less than the detection limit. It was 

found that geometric mean number of days that passed between counts for workers with results 

below the detection limit was nearly a year (364 days), while the number of days for workers 

with positive results was only 36, nearly 1/10th the time elapsed when compared to results less 

than the MDA. 

In summary, the completeness analysis was able to determine that (1) there were no significant 

gaps in the monitoring data on an annual basis, (2) higher potential job types (such as chemical 

operator) were sampled more frequently, and (3) the time elapsed between samples for workers 

with positive results was approximately 1/10th the elapsed time of those with no positive result. 

While the work area analysis was generally inconclusive, it also did not demonstrate a bias

towards sampling areas with lower exposure potential. SC&A concluded that the dataset was 

suitably complete for the purposes of dose reconstruction, though cautioned that the 

implementation of any coworker model should account for the inability to identify the specific 

workers who handled thorium.
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Example 2 Discussion:

This approach used a large cross section of workers (not just claimants, as shown in the next 

example) and had reasonably extensive work location and job type information included in the

hardcopy records. Given these characteristics of the dataset, it is reasonable to conclude that any 

quantitative analysis including the job and work area was accurate for the group of monitored 

workers. However, it is not clear to what extent these records reflect the entire affected worker 

population. As stated previously, the lack of information identifying which workers actually 

handled thorium and to what extent they were monitored is not currently available. However, 

reasonable claimant-favorable assumptions regarding the implementation and assignment of 

thorium intakes using this dataset likely obviates this uncertainty from an SEC perspective.

Example 3: Internal Dose to Workers at Nevada Test Site during the Underground Testing 

Period (1963–1990)

Background Summary:

The NTS operated from 1951 until 1992 and was one of the primary sites for testing nuclear 

explosive devices during that time. From the beginning of site operations until 1963, the United 

States conducted more than 100 aboveground nuclear tests, at which point all further nuclear 

testing was conducted underground until radiological operations ceased in 1992. In April of 

2006, NIOSH evaluated the period of atmospheric testing (1951–1962) and determined that it 

could not reconstruct doses with sufficient accuracy. The Advisory Board accepted NIOSH’s 

findings and the SEC was granted in May of 2006.

Subsequent to this Advisory Board recommendation, NIOSH produced a new evaluation report 

covering the period of 1963 through 1992 (NIOSH 2007). In this evaluation report, NIOSH 

proposed an internal dose coworker model based on the bioassay data from a group of 100 

claimants with evidence of radiological exposure at NTS. Specifically, NIOSH 2007 states:

NIOSH examined the records supplied by DOE for 100 NS claimants with 

significant total external whole-body photon exposures (cumulative above 

1.0 rem). The nature of the potential exposure scenarios at NTS makes it most 

likely that significant internal exposure would be associated with significant 

external exposure. (NIOSH 2007)

At the time, DOE had supplied records for 1,287 total claims for NTS, and over 400 of those 

claims contained some internal dosimetry data.

Analytical Approach Taken:

In this example, the proposed coworker model is based on a sample of 100 claimants, which 

differs from the first two examples that contained an expansive electronic radiological database 

(Example 1) or site-wide hardcopy records that represent both claimants and non-claimants 

(Example 2). It must be noted that at the time of the initial evaluation report (NIOSH 2007), no 

electronic database was known to be available that would encompass a larger portion of the 
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workers at NTS. It is the absence of a radiological database that necessitated the approach of 

using claimant records to attempt to characterize the potential dose at NTS.

Since the group of claimants chosen for the basis of the coworker model (henceforth referred to 

as the “NIOSH 100”) only comprise 25% of the NTS claimants with internal dosimetry 

information, the first step taken in evaluating this approach was to construct an alternate group of 

claimants for comparison. In order to get a sense for the exposure potential for different job 

categories, SC&A randomly selected 20 claimants each from 6 job classifications (radiological 

safety, laborers, welders, wiremen, miners, and security guards). This semi-randomly selected 

group is comprised of 120 claimants and can be referred to as the “SC&A 120.” It should be 

noted that since the claimants were randomly selected, some of the claimants were included in 

both the NIOSH 100 and SC&A 120 sampling groups.

SC&A then compiled radiological information provided in the claimant records for both the 

NIOSH 100 and SC&A 120. From this compilation and analysis, it became clear that the 

internal monitoring program at NTS was biased, from a frequency standpoint, towards the job 

titles of radiological safety and security guard. However, there was no evidence from this 

analysis that those job types exhibited a higher exposure potential than other job types at NTS. 

Also apparent was the fact that many claimants in the remaining trades analyzed (laborer, 

welder, wireman, and miner) did not have any available bioassay data.

Subsequent to this comparison, a large electronic database was discovered that contained a 

significant amount of bioassay data (over 122,000 samples in the evaluated SEC period) which 

were not previously available to ORAUT. This database did not specify job title; however,

SC&A was able to identify the claimants in the database by their social security number and 

assign them their job titles based on information in the individual claim files. By doing this, 

SC&A was able to expand on the number of sampled workers in the six job categories of 

interest. SC&A then analyzed the database by the four major types of internal monitoring at 

NTS: beta/gross fission products, gamma, plutonium, and tritium. Similar trends to the previous 

analysis were apparent, in that radiological safety and security guards were sampled much more 

frequently than the other job types. 

An example of the analysis results is shown for tritium in Table A-4, which presents an overview 

of the frequency that the particular job titles were monitored, as well as providing some 

indication of the magnitude of the actual results. As shown, though radiological safety workers 

only compromised 13 of the 134 claimants identified with 1 of the 6 job titles, they accounted for 

over 50% of the samples taken. Figure A-2 shows a rank order plot of the magnitude of tritium 

results (MI/cc) for the job categories surveyed. As can be seen, the job categories that had the 

highest results for tritium were actually the miners, wiremen, and laborers, even though they had 

significantly less samples present in the dataset. In fact, the magnitude of tritium bioassay for 

radiological safety was slightly lower than the “all claimant average” at most percentiles and 

lower than the “all worker average” at the upper percentiles. Similar findings were observed for 

the other major bioassay categories (beta/gross fission products, gamma, and plutonium); the 

reader is referred to SC&A 2010 for the full analysis.
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Based on this review of job-specific bioassay results, it can reasonably be concluded that the 

monitoring program was not focused on the most highly exposed workers, and often times did 

not include those job designations in the sampling program. On January 25, 2010, NIOSH 

recommended to the Advisory Board that the class of employees at NTS from 1963 through 

1992 be included in the SEC. In May of 2010, the Advisory Board accepted NIOSH’s 

recommendation.
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Table A-4: Analysis of Electronic Database for Tritium Data Including Data Overview and Characteristics

Tritium Data

Claims

All Workers RadSafe Laborers Welders Wireman Miners Security All Claimant 

Pu

Data Overview 

Total Samples 1985 221 39 37 817 826 4977 42748

# Individuals 13 17 9 13 48 34 244 4724

Urine Samples 1900 (95.72%) 207 (93.67%) 35 (89.74%) 31 (83.78%) 757 (92.66%) 764 (92.49%) 4673 (93.89%) 40253 (94.16%)

Whole Body Counts 85 (4.28%) 14 (6.33%) 4 (10.26%) 6 (16.22%) 60 (7.34%) 62 (7.51%) 304 (6.11%) 2495 (5.84%)

Data Characteristics

Number of Positive 

Results 1718 (86.55%) 202 (91.40%) 29 (74.36%) 28 (75.68%) 717 (87.76%) 755 (91.40%) 4320 (86.80%) 36805 (86.10%)

Number of Results 

Listed as 

‘Less than’

148 (7.46%) 3 (1.36%) 2 (5.13%) 2 (5.41%) 23 (2.82%) 3 (0.36%) 276 (5.55%) 2447 (5.72%)

Number of Negative 

Results 21 (1.06%) 1 (0.45%) 4 (10.26%) - 1 (0.12%) 6 (0.73%) 41 (0.82%) -

Number of Zero 

Results 13 (0.65%) - - - 2 (0.24%) - 19 (0.38%) 135 (0.32%)

Number of Results 

listed as 

‘No Detectable’

- - - - - - - -

Number of Blank 

Results 85 (4.28%) 15 (6.79%) 4 (10.26%) 7 (18.92%) 74 (9.06%) 62 (7.51%) 321 (6.45%) 3361 (7.86%)
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Rank Ordered Tritium Concentration in Urine

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

1.1

1.00E-08 1.00E-07 1.00E-06 1.00E-05 1.00E-04 1.00E-03 1.00E-02 1.00E-01

Concentration (MI/cc) Rank Order

All Claimants

Radsafe

Laborers

Welders

Wireman

Miners

Security

All Workers

Figure A-2. Rank Ordered Tritium Concentration in Urine (MI/cc) for Surveyed Job Titles
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Example 3 Discussion:

The approach described above was clearly an iterative process due to the unavailability of an 

electronic database in the beginning stages of the completeness evaluation process. 

Nevertheless, the methodology of using claimant samples can be an effective instrument in 

gathering information and insight into the monitoring practices of a particular site. This is 

illustrated by the corroborating analysis of the electronic database later uncovered, though care 

must be taken to put such claimant sample-based analyses in their proper frame of reference. 

Though it is always preferable to analyze data that are representative of the workforce as a 

whole, absent the availability of such information, claimant sampling is a useful tool to gain 

insight into the completeness of available data in an SEC context.

Example 4: Bounding Internal Exposures to Stable Metal Tritides at the Mound Plant

Background Summary:

Stable metal tritides (SMTs) are a form of insoluble tritium that do not metabolize from the lung 

like normal tritiated compounds, and, as a result, it is not possible for traditional bioassay 

methods, such as urinalysis, to accurately reflect the actual exposure to SMTs. It has been 

established that SMTs were handled in specific known areas of the Mound Plant, and it is also 

known who the primary workers are who handled the material. Air monitoring data are

available; however, it is equally problematic, because this material would have been caught in 

the air filters prior to being counted by the detector.

Since it is known who the primary handlers of the material were, maximizing assumptions can be 

made to adjust those individual urinalysis results to effectively bound the potential exposure to 

these workers. However, this type of bounding model would be inappropriate to use on ancillary 

or support workers whose exposure to the material would likely have been infrequent and the 

potential for intake minimal. Therefore, an alternate method was constructed, which used area 

swipe samples to model the resuspension and intake of the tritiated material. This method was 

finalized in the NIOSH report: Potential Stable Metal Tritide Exposures at the Mound 

Laboratory (NIOSH 2012a).

Analytical Approach Taken:

As stated in the previous section, the proposed model is not based on actual bioassay or in-vivo 

monitoring of workers, but rather workplace sampling in the form of swipe data. Though the 

specific areas/rooms where the work was performed are known, there is still the potential that 

particular areas of the room may not have been sufficiently monitored via swipe samples. 

Fortunately, the original swipe sample reports are available and inspection of these reports shows

that swipes were taken all over the rooms of interest (an example of one such report is shown in 

Figure A-3). Therefore, it is not likely that an area within the room had significantly higher 

contamination and was routinely missed by the swipe sampling program.
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Figure A-3. Example of a Swipe Sample Report Showing the Layout of the Room 

and Areas that were Sampled

The primary handlers of the SMT material have been identified and a bounding approach has 

already been developed; therefore, the proposed resuspension model only applies to ancillary or 

support workers. Since it is not possible to identify which of these workers might have been 

exposed, the model applies to all workers who entered radiological areas. At Mound, if a worker 

entered a radiological area, then a tritium urinalysis sample was mandatory. As a result, anyone 

with tritium bioassay is considered to have been potentially exposed to SMTs. Therefore, any 

evaluation of the completeness of the proposed approach need only consider the temporal 

coverage of the available swipe results and not the job types and areas of interest (which are both 

known).

SC&A presented its completeness study in SC&A 2012 and found that there were significant 

temporal gaps in the available swipe data. One example is shown in Figure A-4, which plots the 

number of available swipe samples for Room R-108 during the period of interest. As seen in the 

figure, there is a gap in the swipe data that extends over 2 years, as well as a few other smaller 

data gaps. It is important to determine whether a surrogate data approach is appropriate to use 

during these gaps in data coverage, and that no off-normal operations involving SMTs occurred. 

Any off-normal operations or conditions might have posed a higher exposure potential, which 

would make using surrogate data from surrounding periods problematic. 
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Source: SC&A 2012

Figure A-4. Number of Samples by Year for Room R-108 during the Period of Interest

NIOSH 2012b addressed these gaps in the data using two different approaches. First, NIOSH 

conducted further interviews with former workers who had direct knowledge of the SMT 

operations. These workers were shown the gaps in the available data and were asked if there was 

any reason to believe that operations would differ from the periods when swipe data were

available. NIOSH 2012b states:

Interviews with the research chemists and radiological health personnel that have 

firsthand knowledge of the operations were specifically asked if any working 

situations occurred or they were made aware of that would have caused the 

missing swipe data to be different than the data on either side of the gap. The 

overall agreement was the data from both sides of the gaps should be adequate to 

extrapolate the data within the gaps.

In the second approach, NIOSH analyzed the tritium urinalysis data during the entire period of 

interest, which included the periods with swipe data gaps. Though tritium urinalysis data are not 

indicative of exposure to SMTs, they do indicate whether site-wide tritium operations might have 

increased during the periods with no swipe data. This type of indirect test helps build a weight 

of evidence argument, since it is not unreasonable to assume that operations involving SMTs 

would generally parallel the other tritium operations at the site from a production and exposure 

standpoint. An example of this is shown in Figure A-5 for Room R-108, which essentially takes 

the plot shown in Figure A-4 and overlays the average tritium doses during the period. As seen 

in the figure, overall tritium doses at the site during periods with swipe data gaps were not 
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significantly different than the periods with swipe data. In fact, the period with the highest 

tritium doses (late 1985) is covered by the swipe data. Therefore, reasonable application of 

surrogate data is likely appropriate to bound SMT exposures during the periods with no data. 

Similar results were found for the other room of interest (SW-8) that had identified data gaps.

Source: NIOSH 2012b

Figure A-5. Number of Swipe Samples Plotted against the Average Dose 

Based on Tritium Urinalysis

Example 4 Discussion:

While it is always preferable to use worker bioassay data to reconstruct doses and develop 

coworker models, in some situations, the bioassay information is unavailable or is not adequate 

for the task. In the case of Mound, urinalysis data are available, but are inappropriate for the 

purpose of reconstructing doses to the support workers. Therefore, the alternate approach of 

using workplace monitoring was adopted to bound doses to this group of workers.

This type of approach still requires the ability to identify the specific areas and workers that were 

involved in the operation of interest. Fortunately in this case, the pertinent information was 

available. Therefore, the main concern from a completeness perspective is the temporal 

considerations. Although there were significant data gaps identified, worker interviews and 

characterization of the overall site production during the gap mitigate any potential issues arising 

from the unavailability of swipe data.