Measuring mining safety with injury statistics:
 

Lost workdays as indicators of risk ☆
 

Patrick J. Coleman , John C. Kerkering

National Institute for Occupational Safety and Health, Spokane Research Laboratory

☆ The findings and conclusions in this report are those of the author(s)

and do not necessarily represent the views of the Centers for Disease

Control and Prevention/the National Institute for Occupational Safety

and Health.

Abstract

Problem: Mining in the United States remains one of the most hazardous industries, despite significant reductions in fatal injury rates over the

last century. Coal mine fatality rates, for example, have dropped almost a thousand fold since their peak in 1908. While incidence rates are

very important indicators, lost worktime measures offer an alternative metric for evaluating job safety and health performance. The first

objective of this study examined the distributions and summary statistics of all injuries reported to the Mine Safety and Health Administration

from 1983 through 2004. Over the period studied (1983 2004), there were 31,515,368 lost workdays associated with mining injuries, for an

equivalent of 5,700 person years lost annually. The second objective addressed the problem of comparing safety program performance in

mines for situations where denominator data were lacking. By examining the consequences of injuries, comparisons can be made between

disparate operations without the need for denominators. Total risk in the form of lost workday sums can help to distinguish between lower

and higher risk operations or time periods. Method: Our method was to use a beta distribution to model the losses and to compare

underground coal mining to underground metal/nonmetal mining from 2000 to 2004. Results: Our results showed the probability of an injury

having 10 or more lost workdays was 0.52 for coal mine cases versus 0.35 for metal/nonmetal mine cases. In addition, a comparison of injuries

involving continuous mining machines over 2001 2002 versus 2003 2004 showed that the ratio of average lossesin the later period to those in the

earlier period was approximately 1.08,suggesting increasing risksforsuch operations. Discussion: This denominator free safety measure will help

the mining industry more effectively identify higher risk operations and more realistically evaluate their safety improvement programs. Impact on

Industry: Attention to a variety of metrics concerning the performance of a job safety and health program will enhance industry's ability to manage

these programs and reduce risk.

Keywords: Mining injuries; Mining safety and health; Incidence rates; Denominator-free methods; Lost time measures; Trends; Statutory days lost; Job safety

and health metrics

1. Problem

Researchers in occupational safety and health fields who

use surveillance data rely on a small number of risk measurement methods for evaluating the performance of preventive programs. The raw numbers of reported injuries and

illnesses plotted over time provide the first indications of

higher-than-average risk problems, or lower-than-average risk

success stories. Calculating incidence rates when denominator

data (i.e., number of workers exposed) are available is a more

standardized measure, particularly if employment is changing

over time or if differently-sized sectors or risk groups need

to be compared. The severity of injuries and illnesses (i.e.,

statistics based on number of lost workdays, statutory days,

and restricted workdays per case of injury or illness charged to

an individual accident) is a less-used measure that may be

undervalued. Thisstudy examined the use of lost workdays per

case as a metric separate from the traditional ones of case

counts and incidence rates.
In the mining sector, data on reported injuries from the

Mine Safety and Health Administration (MSHA) allow

researchers to develop mine-specific and subunit-specific

incidence rates for a variety of injury types. Several reasons

for using lost workdays as an alternative metric include the

fact that denominator data are generally collected only for

the broadest and most general categories. MSHA provides

hours worked by miners at each mine location and for each

subunit that a mine operates. But hours worked are not

categorized by years of experience or the amount of training

a miner has, making it difficult to assess risk among new and

less-trained workers. Hours worked are also not categorized

by other variables of interest such as machine type, activity,

occupation, or gender.

However, MSHA also provides three different lost

workday indices: the number of workdays an injured miner

takes before returning to work, the number of days of

restricted work activity after returning to work, and the

number of statutory days lost. The latter has assigned values

or “scheduled charges” for fatalities and permanent partial or

total disabilities resulting from loss of a member.

2. Literature review

The use of statistics in job safety and health has a long

history, and in particular, MSHA's use of so-called statutory

days has its origin in a 1920 Bureau of Labor Statistics

Bulletin No. 276, Standardization of Industrial Accident

Statistics (U.S. Bureau of Labor Statistics, 1920). The

authors felt there was a need for a uniform system for

assigning lost work time to disabling injuries and deaths. The

results included, for example, a statutory charge of 6,000 lost

workdays for a fatal injury and for certain non-fatal but

permanently disabling injuries such as loss of both eyes.

Other impairments were assigned statutory days lost based

on a percentage of permanent total disabilities. The Z16

Committee was formed in 1926 to revise the standard, and

adopted the Bulletin's table and chart referring to scheduled

charges or statutory days lost for specific bodily impairments. The Bulletin also details the rationale for assigning

the values found in the table. Later revisions of the American

National Standards Institute (ANSI) Z16 standards through

Z16.1-1967 maintained the same table and chart (United

States of America Standards Institute, 1968), which are now

used by the U.S. Department of Labor Mine Safety and

Health Administration (MSHA, 1986).

Researchers in mining safety and health have examined

lost workdays in a variety of studies in mining. Coal miners

with impaired respiratory health were hypothesized to

experience greater numbers of disability days due to job

injury, but the analysis did not support the hypothesis (Ames

& Trent, 1985). Five mines in northeast England were

studied for days lost due to skin disorders over a 6-year

period. Summary measures (means, medians, and incidence

rates) were reported, showing that foot dermatitis in coal

mines accounted for some of the longest lost day measures (Puttick, 1990). Small mines with high incidence

rates of transport injuries have a greater share of fatal

and permanently disabling injuries, while larger mines

have a greater share of injuries involving no lost time

(Hunting & Weeks, 1993). Lost workdays have also been

used to develop risk indices for specific mining tasks. Using

detailed microanalysis of task components, injuries incurred, injury severity, and time spent per component, risk

analysis can pinpoint the specific task component with the

highest risk of injury and the highest risk of loss of

worktime (Grayson, Layne, Althouse, & Klishis, 1992).

Grayson et al. later updated and expanded their microanalysis approach to produce an index number for ranking job

titles by priority of intervention (Grayson, Althouse, Winn

& Klishis, 1998), which relies on MSHA's lost workday

statistics.

Research in other high-risk industries has also studied lost

workdays, primarily as severity indices. Construction

injuries that occurred during the construction of the Denver

International Airport in Denver, Colorado, between 1990 and

1994 were analyzed and data presented on lost-work-time

claims, their incidence and median days lost. Specific types

of work were tabulated by median number of days lost,

among other measures. The authors concluded that lost

workday estimates reported by BLS are likely to underestimate those derived from workers' compensation insurance

data (Lowery et al., 2000). Construction industry injuries in

the Australian state of Victoria during 1996–1998 were

analyzed to determine occupations, tasks, and activities in

terms of priorities for intervention and prevention. A fourpart injury severity index, including indicators for days

compensated, hospital days and costs, maiming (compensation for temporary or permanent impairment), and a fracture

or amputation indicator, was developed for this purpose

(Larsson & Field, 2002). These authors also point out that a

summary measure, ‘harm,’ which is the number of claims

multiplied by the injury severity, has been used in the

transportation safety field.

Lost-worktime distributions were summarized in Mital,

Pennathur, and Kansal (1999) using Bureau of Labor

Statistics reports on OSHA-reportable cases by type of

accident, source of injury, and part of body injured. These

results demonstrate the utility of comparing selected groups

of injuries by amount of time lost and enable identification of

the type and nature of the accident and the parts of the body

injured that account for the largest percentages of cases in

which 21 or more days of work were lost. Unfortunately,

cases with no lost workdays are not included in the table,

making it difficult to understand the complete form of the

distributions.

3. Methods

The following background on MSHA reporting requirements and practices are important for understanding this

study. Underground and surface mining are part of the
extraction industries in the United States. The general

categories of commodities mined are coal, metal, nonmetal,

stone, and sand and gravel. The accident data for this study

were collected by MSHA, part of the Department of Labor.

MSHA has collected mine accident data for many years,

providing public access to data from 1983 forward on its

website. The mine must report an incident to MSHA if there

is a work stoppage of 30 minutes or more or if there is an

injury or fatality connected with the incident.

More severe injuries, including fatalities, are investigated

by MSHA. The accident information is coded into a database

for that particular calendar year at MSHA's office in Denver.

There are 48 variables recorded in the accident-injury-illness

database for each incident. MSHA also has other databases

that include mine employment and address information, and

narrative descriptions of each incident. Mine employers are

classified according to whether they mine coal (anthracite or

bituminous), metal, nonmetal, stone, or sand and gravel. The

term “metal/nonmetal” is sometimes used to designate all

non-coal mining (i.e., metal, nonmetal, stone, sand and

gravel). Mines are further subdivided into surface and

underground mining.

Lost time due to accidents is recorded in three categories:

actual lost days from work, statutory days charged, and

restricted activity workdays. The lost workday variable can

have a value of zero if no time away from work occurred due

to the accident, such as when a roof-fall stops work for 30

minutes or more but no injuries occur. It can also be zero if

an injury occurs without death, days away, or restricted

activity. In these cases, if the injured miner loses less than 1

day of work, the case is coded as having zero lost workdays. The lost time data attributed to an accident are

not considered final until the injured worker returns to work

or is permanently transferred or terminated. The employer

updates each open case by submitting a final form with

total days lost to MSHA. MSHA issues a closed or completed

database for a particular year after May 15 of the following

year, to record the final disposition of cases still open.

While days lost from work and days with restricted

work activity depend on healing times, the nature of the

work being done, and other factors, the statutory days

charged are more a reflection of attempts to quantify the

“future loss of productive time brought about by an

employee's permanent loss of a body member or

permanent impairment of function” (MSHA, 1986).

MSHA publishes the tables and charts used to determine

statutory days lost on their website. The origin of the

estimates in these tables and charts is the 1920 bulletin

mentioned above (BLS, 1920), and they may also be found

in the ANSI Method of Recording and Measuring Work

Injury Experience Z16.1 (ANSI, 1967). The decision to

include this measure along with the other two was guided

by a desire for a measure that reflected the full range of

injury outcomes from minor injuries to fatalities.

For this study, the reported measures for each case were

summed to arrive at a total time-lost measure.

To find the distributions of the days lost by sector,

standard distributions, such as the beta, gamma, Weibull,

lognormal, exponential, and Pareto, were examined (Hogg &

Klugman, 1983). Because the distribution of lost workdays

by case has a large proportion with zero days lost on the low

end and a significant proportion of cases with 6,000 days lost

corresponding to fatal injuries on the high end, the beta

distribution was selected because of its flexibility in

modeling the U-shape of the histogram. The beta distribution

is also defined on a closed interval, which matches the

MSHA data in having lost workday outcomes of 0 to

6,000 days. Least-squares techniques were used to develop

the fitted distributions, and to test goodness-of-fit, the

Kolmogorov-Smirnov D-statistic test (K-S D-statistic) was

used (Conover, 1980).

Statistical and related programs used for thisstudy included

Excel (Microsoft Office Excel 2003, Redmond, WA), SPSS

Ver. 11.5 (SPSS Inc., Chicago, IL), Mathematica Ver. 5.1

(Wolfram Research, Inc., Chicago, IL), and The SAS System

for Windows, Ver. 9.00 (SAS Institute, Cary, NC).

4. Results

4.1. Summary of lost workday trends

For the period 1983 through 2004, MSHA received

321,011 case reports of nonfatal injuries with lost workdays.

A total of 2,215 fatal injuries was also reported in this period.

The sum of lost workdays, statutory days lost, and days of

restricted work activity for all of these cases was 31,515,368

over 22 years, or the equivalent of more than 5,700 personyears lost annually.

For consistency with MSHA's convention, and for

comparison with its published data, the overall loss data

were separated into four groups: coal mine operators, coal

mine contractors, metal/nonmetal mine operators, and metal/

nonmetal contractors. From 1989 to the present, coal mine

and metal/nonmetal mine operators, and metal/nonmetal

contractors, have reduced the incidence rates of lost

workday cases (Fig. 1), some more than others. Coal mine

contractors reported increases about as often as decreases

from year to year, reaching their lowest rates in 2003–2004.

The ratio of incidence rates for lost workday cases for coal

mine operators to the average incidence rates for the other

three sectors was consistently 1.5 to 2.0 during the period

and was at its highest from 1987 through 1998. While three

of the four groups demonstrated long-term reductions in lost

workday case incidence rates it should be noted that the

large increase in incidence rates for coal mine operators in

1986 through 1988 may be a reporting artifact resulting

from an MSHA initiative. In December of 1986, MSHA

released a program circular titled “Report on 30 CFR Part

50” to clarify and increase enforcement of the reporting

regulations (MSHA, 1986; Fig. 1). The remaining groups

demonstrate less dramatic increases during or after the same

period, in apparent response to the initiative.
Fig. 1. U.S. Mining Nonfatal Lost Workday Case, Incidence Rates, 1983 - 2004.

Figs. 2–5 (see Appendix A for actual data) illustrate the

trendsin lost workdays associated with each of the four groups.

For coal mine operators, the total number of lost days steadily

decreased until the last 2 years, when the number increased

slightly (Fig. 2). The figures for coal mine contractors show

greater variability, but overall the pattern has been relatively

steady (Fig. 3). Metal/nonmetal operators showed a modest

reduction in total days lost over the period, while metal/

nonmetal contractorsshowed a long-term trend toward a higher

number of total days lost, also with increasing variability.

For both coal groups, the use of restrictions on work

activity for those recovering from injury appears to be low,

that is, the number of days spent on restricted work activities

averages 1% to 2% of total lost days over the period. By

contrast, more metal/nonmetal mine operators assigned

recovering workers to restricted work activity; restrictedactivity days averaged 2% to 8% of total lost workdays. As a

percentage of total days lost, restricted-activity days increased for the metal/nonmetal mining trades (trends significant at pb0.0001).

Fig. 2. Lost Workdays for Nonfatal Injuries - Coal Mine Operators.
Fig. 3. Lost Workdays for Nonfatal Injuries - Coal Mine Contractors.

Notice also that the possible reporting artifact identified

in Fig. 1 is less evident in the total lost workday trends of

Figs. 2–5.

4.2. Distributions of lost work days

The average values of lost workdays are useful measures

of overall safety performance in a mine, since they can reflect

factors such as the use of personal protective equipment, the

effective use of first aid and rapid access to medical care,

or company policies concerning return-to-work practices. To

study the empirical distributions of lost work time, reported

cases with no lost time (degree= 6) were incorporated.

Fig. 6a–b illustrate the distribution of cases by lost workdays

for the underground coal and metal/nonmetal sectors during

2000–2004. The figure shows only the initial and final

segments of the graph; the large segment in the middle has

low frequencies for each sector. Graphing both coal and

metal/nonmetal on opposite y-axes emphasizesthe noticeable

similarity between the two sectors' lost workday patterns.

Fig. 4. Lost Workdays for Nonfatal Injuries - Metal/Nonmetal⁎ Mine Operators.
Fig. 5. Lost Workdays for Nonfatal Injuries - Metal/Nonmetal⁎ Mine Contractors.

For coal, 24.3% of the cases reported no days lost,

while decreasing percentages make up the heavy tail. While

the 97 severe cases (94 fatalities, 3 permanent total disabilities) in this period constituted 5% of the cases, the

lossesfor the severe cases accounted for 41% of the total lost

workdays.

The metal/nonmetal sector had a larger percentage of zero

lost workday cases (36%). The 22 fatal cases with assigned

statutory days lost accounted for 0.8% of the total case count

and 65% of the total lost workdays.

The beta distribution has the probability density function

C að þ bÞ a - 1 b - 1 f xð ; a; bÞ 1⁄4 x ð1 xÞ C að ÞC bð Þ

where alpha and beta are shape parameters. The beta

was fitted to both the underground metal/nonmetal and

underground coal sectors. To facilitate the fitting, values on

the lost workday axis were divided by 6,000, resulting in a

range of 0 to 1 for the transformed values. Table 1 shows the

estimated parameter values for each group of injuries.

Graphically the fitted beta curves are close to the observed data, but the K-S D-statistic for the underground coal

data suggests a possibly poor fit, while the metal/nonmetal

fitting can be considered acceptable (Table 1). The discussion section below includes comments on this.

To assess the risk values associated with each sector and

estimate the difference in risk, the cumulative form of the

fitted curve F(x, α, β) was first calculated. For convenience

in representing the probability of a loss exceeding a given

value, the form 1-F(x, α, β) was used for plotting (Fig. 7).

For each curve, the value plotted for a given magnitude of

loss represents the probability of a case having more lost

workdays than the given magnitude. For example, for the

metal/nonmetal sector for the period studied, the probability

of a case exceeding 10 lost workdays is 0.35, while for the

underground coal sector, the probability is 0.52.

As a summary measure, which we termed “normalized

risk,” the integral of the function 1-F(x, α, β) over the interval

(0,1) was calculated. For any cumulative distribution function

defined on the interval (0,1), the value of this integral lies

between 0 and 1. The area under this function is analogous to

average risk for the group of cases modeled. Fig. 7

demonstrates clearly that the metal/nonmetal sector experience corresponds to the safer sector, since for each loss on the

horizontal axis, the probability of a greater loss is higher for

coal than for metal/nonmetal. The normalized risks, obtained

for each sector by integrating the corresponding function,

show that “smaller” area corresponds to a “safer” sector,

condition, or population. Confidence intervals for the

normalized risks were obtained by integrating “confidence

curves” banding the observed and fitted curves using the

associated Kolmogorov-Smirnov tabled value (Massey,

1951).

Table 2 compares the traditional measures of safety for

the underground coal and underground metal/nonmetal

sectors.

As Table 2 demonstrates, the sectors are disparate in

size, number of cases, and lost workday totals. The two

measures using denominators – fatal and nonfatal case

incidence rates – show that coal has slightly higher rates.

The lost workday distribution comparisons, however,

suggest graphically and without denominators that the

risks associated with coal mining exceed those for the

metal/nonmetal sector across a significant portion of the

lost workday range (Fig. 7).
Fig. 6. a. U.S. underground coal and metal/nonmetal injury lost workday distributions, 2000 - 2004, b. U.S. underground coal and metal/nonmetal injury lost

workday distributions, 2000 - 2004.

A final example compares the lost time of miners killed

and injured in accidents associated with the operation of

continuous mining machines, which are used primarily in

underground coal operations. Note that machine-specific

incidence rates cannot be computed, since hours worked are

not specific to time spent working with or near a particular

mining machine. The total losses of cases associated with

continuous miners in 2001–2002 were compared to those

reported in 2003–2004. After fitting beta curves (Table 3) to

the loss distributions of these cases for the two periods, the

assessment showed that cases occurring in 2003–2004 had a

larger total loss. In this example, the Kolmogorov–Smirnov

test statistics show good fits for each period.

Table 4 summarizes the available traditional measures as

well as the distribution-based measures. The ratio of average

Table 1

Beta distribution curve parameters for lost workdays, underground mines,

2000 - 2004

Shape parameter Coal Metal/nonmetal

Α 0.307419 0.2162522

Β 40.00770373 54.96983

N 19,236 2,864

Goodness-of-fit (K-S D-statistic) 0.049 0.029

Critical value for p 0.05 0.009 0.024
Fig. 7. Lost Workday Fitted Distributions for Underground Coal and Underground Metal/Nonmetal Mining, 2000 - 2004.

losses for 2001–2002 to those of 2003–2004 was 0.925,

suggesting that recent continuous miner operations are less

safe than earlier ones(Fig. 8). Because the confidence intervals

for normalized risk overlap, the difference is not statistically

significant, however.

Table 2
 

Safety measures comparing two underground mining industry sectors,
 

2000 2004
 

MeasureCoal Metal/nonmetal

Average number of employees per year 46,011 13,167
 

Number of employee hours 379,939,113 93,462,088
 

Number of injuries (degrees 1 6) 19,236 2,864
 

Number of fatalities (degree 1) 94 22
 

Number of permanent disabilities 187 24
 

(degree 2)

Actual days lost from work 764,330 43,296

Days of restricted work activity 31,770 21,023

Statutory days lost 646,940 138,660

Total days lost 1,443,040 202,979

Fatal case incidence rate 49.48 47.08

(no./100,000/year)

Nonfatal case incidence rate 10.08 6.08

(no./100/year)

Table 3
 

Beta distribution curve parameters for lost workdays, continuous mining
 

machines, 2001 2002, 2003 2004
 

Shape parameter2001 - 2002 2003 - 2004
 

Α 0.26221 0.300873
 

Β 22.2116 23.5436
 

N 429 337
 

Goodness-of-fit (K-S D statistic) 0.028 0.059
 

Critical value for p 0.05 0.066 0.074
 

5. Discussion

It's well known that surveillance data of occupational

injuries and illnesses for U.S. industries in general have

significant limitations. Researchers are frequently faced with

drawing conclusions from data that has been collected primarily for purposes other than research, including regulatory,

administrative, and legal requirements. Public health practitioners are constantly faced with decisions that require prioritizing activities and interventions in the face of incomplete

and less-than-ideal information, and the collection of surveillance data is no exception.

Mining in the United States has an advantage over other

industries in that the long-term development of safety and

health regulations, including injury and illness reporting

Table 4
 

Safety measures comparing continuous mining machine injuries in two
 

periods, 2001 2002 and 2003 2004
 

Measure2001 - 2002 2003 - 2004
 

Number of fatalities (degree 1) 12 7
 

Number of permanent disabilities 2 6
 

(degree 2)
 

Number of non-fatal injuries 415
 324
 

(degrees 3 6)
 

Total days lost 99,146 63,363
 

Actual days lost from work 20,001 18,373
 

Days of restricted work activity 995 654
 

Statutory days lost 78,150 44,535
 

Percentage of total losses for 61% 39%
 

the two periods

Comparison of distributions 0.012 0.013
 

(normalized risk)
 

95% confidence intervals(0.007, 0.018) (0.008, 0.019)

for normalized risks
Fig. 8. Lost Workday Fitted Distributions for Continuous Coal Mining Machines in 2001 - 2002 vs. 2003 - 2004.

requirements, has resulted in a very detailed, relatively

consistent case series. The risks faced by miners have historically been such that the mining industry has generally

complied with stringent reporting requirements, and the

industry, research, and regulatory agencies have benefited.

Combined with hours-worked reports, the MSHA accidentinjury-illness database can be analyzed to determine highpriority research needs as well astrendsthat help in evaluating

intervention effectiveness.

This study suggests that methods of analysis can be

extended to include comparisons based on differences in

accident outcomes such as lost workdays. These methods

allow comparisons of disparate operations for almost any

grouping of categories in the MSHA database.

The curve-fitting process is one that deserves further

exploration. In the first example above, the beta curve fitted

to the underground coal losses had a K-S D-statistic of 0.049,

which exceeded the tabled values for both the 0.05 and

0.01 p-levels. We chose to use the fitted curve despite this for

two reasons: (a) graphically the beta appeared to fit the

observed data well; and (b) the unusually large sample size

for the underground losses (19,236 cases over the 5-year

period 2000–2004) produced a very low cutoff value for the

D-statistic. Additional work is planned for this and related

questions.

6. Data and methodology limitations

The limitations of the MSHA data deserve some discussion. Specifically, the use of statutory days as a measure

of injury severity raises several questions. Are the assignments of statutory days charged based on scientific methodology? Does MSHA arbitrarily assign such values to each

applicable case? In practice, the tables and charts that explain

the assignment of lost workday equivalents to specific

impairments of body parts are based on medical histories and

the opinions of medical professionals. MSHA includes

instructions that require the physician treating the case to

estimate the loss of use of an amputated member, or an

enucleated eye, for example.

While the origin of the tables adopted by MSHA is

not specifically addressed in the ANSI Z16 standards,

modern developments of the methodology have focused on

more comprehensively assessing and rating an individual's

permanent impairment (Cocchiarella & Andersson, 2005). A

person's disability, or activity limitations, is often related to

an impairment, but in a nonlinear fashion. More information,

including the person's skills, education, job history, adaptability, age, and environmental requirements, is needed to

assess disability level. To the extent that the ANSI standard

reflects a cumulative history based on population averages,

the statutory days charged can be a meaningful index of lost

work time. One advantage of the MSHA data is that statutory

days are consistently defined over the period of data collection, and therefore serve as a useful surrogate measure of

diminished working lifetimes.

Long-term trends in injury incidence and in lost time

measures are subject to reporting practices and rules. Injury

data for the period 1984–1986 show a possible artifact of

reporting due to MSHA initiating an effort to clarify the

reporting process and increase enforcement of the reporting

regulations in December 1986 with the release of the

“Yellow Jacket” Report on 30 CFR Part 50. Although no

clear cause and effect conclusions can be proven, there was a

coincident 20–40% increase in reports of lost-time injuries.

Given that coal mine operators may have contributed to

the artifact mentioned earlier, with the apparent increase in

incidence rates of almost 50% for 1986 through 1988, the

relatively steady decline in rates for 1989 through 2004 is

likely to represent a true reduction in risk over the period.

An alternative explanation is that the decline represents a

progressive return to under-reporting. This is less likely,
since the fatal incidence rate for coal mine operators has also

trended downward quite dramatically over the period 1966

through 2004.

While the downward trends are encouraging, this study

did not explore the factors responsible for the downtrends.

We can assume with some confidence that improvements in

evolving mining technology have played major roles. Based

on the assessments of an expert consultant, the following

factors were identified:

• An ongoing increase in the level of mining mechanization

• An increase in health and safety emphasis by mining

companies

• Work once done by contractors is increasingly done by

salaried workers

• Consolidation of mines by bigger companies – smaller,

more hazardous operations are fewer in number

• Improvements in mining systems and designs

Improvementsin undergroundmining technology specifically include a shift from jackleg drills to drill jumbos, coupled

with improvementsin roof control mechanizations. Ore removal

(mucking) operations done with load-haul-dump vehicles are

replacing older, more hazardous techniques (using slushers,

overshot muckers), especially in small operations (personal

communication, William Hustrulid, Ph D., April 6, 2007).

7. Summary

This study was motivated by the search for a wider set of

indicators for the effectiveness of safety program performance in mines. MSHA maintains a very thorough and

detailed database of job injuries and illnesses reported by

mining companies and contractors. However, denominators

in the form of hours worked are not sufficiently detailed

by category to allow traditional estimates of risk to be

calculated for a variety of variables. Without denominators

and the incidence rate calculations they allow, it is difficult

to state with any certainty that machine A is safer to work

with than machine B, or that one period of years for a given

group of mines was safer than another period.

The lost workday outcomes from mining injuries are valuable indicators of a number of aspects of job safety programs.

While traditional measures of preventive program performance

are still needed, including total case counts and incidence rates,

lost time measures offer the possibility of comparing important

aspects of safety program performance among various sectors

and time periods without relying on denominators. In

particular, the distribution of lost workdays can be modeled

statistically and the models can be used to quantify losses for

more effective tracking of what works and what doesn't.

8. Impact on Industry

As in the use of balanced score cards in business management (Kaplan & Norton, 1996), a wider variety of measures

can help to ensure that programs are performing as intended.

In mining, as well as in other industries, job injuries are not

only lagging indicators, but are often too infrequent to be

used as day-to-day indices of program performance. While

lost time measures do not provide more frequent indications,

they can help the mining industry improve important aspects

of their safety programming, including attention to personal

protective equipment, timeliness of rescue efforts, and in

general, management of the post-injury phase (Haddon,

1968).

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Appendix A

Lost time data for Figs. 2–5

1983 1984 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005

Coal Mine OperatorsLost Workdays 314679 359,184 353,287 303,175 375,635 374,043 342,491 438,779 446,454 334,097 277,432 318,667 264,028 195,722 190,952 195,897 189,019 158,516 200,954 206,001 211,800 192,179 173,425Statutory Days Lost 603,719 947,140 640,798 782,131 567,284 437,855 519,457 592,880 476,196 336,412 297,102 316,164 317,498 317,502 252,713 240,878 225,996 237,340 347,171 189,975 200,491 238,401 172,603Days of Restricted Work Activity 3,819 4,202 5,172 5,793 9,076 9,055 8,149 10,877 14,516 10,816 11,383 13,038 15,334 13,149 16,441 15,248 12,440 9,576 12,554 9,458 9,941 11,111 10,339Coal Mine ContractorsLost Workdays 8,284 8,107 11,487 8,001 6,638 6,856 8,198 13,862 15,389 13,587 12,396 21,822 12,307 13,374 12,573 16,230 20,765 19,832 33,436 32,830 30,684 27,653 27,643Statutory Days Lost 24,800 69,050 29,560 38,985 39,425 74,695 42,345 68,560 73,385 71,695 72,495 64,000 71,690 24,310 53,680 34,850 36,685 73,575 40,315 50,620 55,160 45,445 64,505Days of Restricted Work Activity 83 318 51 105 74 193 197 149 228 542 436 609 355 498 970 940 1,330 518 1,353 936 1,152 2,021 1,844Metal/Nonmetal Mine OperatorsLost Workdays 119,283 138,299 165,104 127,043 141,957 190,468 166,915 180,405 176,664 153,650 148,921 145,380 126,579 105,824 93,640 107,050 111,737 93,650 122,080 102,608 104,450 104,719 102,619Statutory Days Lost 465,338 563,984 416,715 374,556 551,959 401,920 428,179 565,101 444,888 310,893 351,374 445,523 432,135 330,045 380,173 328,760 339,230 364,265 242,120 307,635 279,250 197,410 302,080Days of Restricted Work Activity 10,975 13,083 14,305 12,407 19,840 31,646 28,956 38,920 39,336 41,504 46,051 50,605 51,282 48,414 51,704 58,079 59,016 56,451 69,452 57,130 63,969 64,533 70,553Metal/Nonmetal Mine ContractorsLost Workdays 6,513 6,916 8,853 5,296 9,835 16,364 10,863 11,932 12,152 8,417 7,412 16,895 11,392 14,205 10,583 9,088 12,961 10,753 12,320 7,957 11,322 13,153 14,985Statutory Days Lost 66,110 66,630 67,995 53,036 74,580 89,450 95,220 100,850 71,761 66,610 82,040 48,960 108,085 80,495 146,790 98,180 127,875 86,365 97,475 40,220 31,225 73,365 31,140Days of Restricted Work Activity 542 222 467 277 209 857 1,917 1,227 2,562 1,324 1,819 4,262 3,631 3,346 2,213 3,048 3,305 3,831 2,936 4,034 2,728 4,639 5,176