8
original 2017 version of Safety Pays in Mining, the 2022
data includes fewer injury counts, but the pattern and per-
cent of injury associated with mine worker activity and
common injuries are similar.
Within this NCCI mining-related injury cost dataset,
the mean was always higher than the 50th percentile, and
for about half of the injuries, the mean was higher than the
75th percentile. The mean would generally overestimate
injury costs, as the mean alone does not fully represent a
distribution of costs. Variability and skewness must also
be taken into account. Showing percentiles of the direct
costs helps show the distribution of this injury cost data.
Additionally, percentiles require no distributional assump-
tions. The cost data is less skewed than the data used in the
2017 version of Safety Pays in Mining. In that cost data,
the mean was always higher than the 75th percentile, and
for about half of the injuries, the mean was higher than
the 90th percentile (Heberger, 2018). This is likely because
the NCCI data used for Safety Pays in Mining v2.0 has
nearly nine times the claims used from the original web
app and includes data from 35 states while the original web
app only used data from Ohio. The original version also
adjusted costs from a ten-year period (2001–2011) into
2015 dollars (Heberger, 2018).
There are two main reasons why a mine might want
to use different percentiles rather than the 50th percentile,
or median, which is usually the most familiar. The median
provides a good estimate for a single “typical” claim because
half of the claims have higher costs and half of them have
lower costs. One reason to select a cost higher than the
median is related to the total number of claims that are
expected. If a mine is expecting more than one claim, the
chances of having a very expensive claim increase. As a
result, if expecting two to ten claims, using the 75th per-
centile for each claim will lead to a better estimate for total
costs. When the number of claims exceeds fifteen, the
90th percentile for each claim provides a better estimate
(Heberger, 2018).
Another reason to select a cost higher than the median
is concern about the risk of having a high-cost claim that
costs much more than the typical claim. There is substan-
tial risk that claims will cost much more than the “typical”
claim, as illustrated by the cost of claims at the 90th percen-
tile and above. Even if a mine has a single claim, there is a
10% chance that the claim will exceed the 90th percentile
cost. Tables 5a and 5b show why different percentiles are
used. For a lower leg injury, the median (50th percentile)
cost is $29,579 but the mean is $105,095, which is much
too high an estimate for a typical injury. The skewness in
the cost data indicates that every injury has a few cases of
extremely high costs. Generally, costs will be between the
first and third quartiles, but it is important to be aware
that there are also those high-cost cases (95th percentile).
Allowing the web app user to choose direct cost percentile
based on number of injuries or their own risk profile allows
users to explore the various costs per injury and how these
costs can impact the financial success of a company.
The costs are difficult to compare between the origi-
nal 2017 version of Safety Pays in Mining and the updated
Safety Pays in Mining v2.0. The main reason is because the
original version used all claim types and did not differenti-
ate between medical-only and lost-time claims. The lost-
time claim costs are much higher than medical-only claims
for the same types of injuries. Finger lacerations in v2.0 are
all from medical-only claims and the direct cost percentile
values are similar to the original. When looking at back
strains in v2.0, the claim types include medical-only and
lost-time claims. The medical-only claim cost percentiles
are much lower than the 2017 Safety Pays in Mining costs
for back strain/sprain, but the lost-time claims are much
higher. The two versions also have slightly different catego-
rizations of injury, especially for the part of body, nature of
injury, and injury cause combinations. This is partly due to
the different WC datasets, but also the v2.0 data had many
more claims allowing costs to be generated for very specific
injuries.
Safety Pays in Mining v2.0 is intended for mine manag-
ers, safety managers, consultants, researchers, government
agencies, and students—or anyone who is interested in the
costs of specific injuries in the mining industry. Mines can
benefit the most from Safety Pays in Mining v2.0, as it can
help them prioritize safety and health interventions and
focus on areas for improvement. Mines may want to focus
on eliminating the higher-cost injuries first. By showing the
additional sales needed to cover the injury cost and provid-
ing examples of how money could be spent instead of pay-
ing for an injury, the web app presents the same information
in different terms, which can be useful for safety manag-
ers who do not have experience analyzing financial aspects
of the industry. They can also use the web application to
assist with cost-benefit analysis for safety budget allocations
to help justify purchasing personal protective equipment
(PPE), enrolling in safety programs, or obtaining engineer-
ing controls to reduce exposure to injury (Heberger, 2018).
LIMITATIONS
A primary limitation of the total cost calculation comes
from the estimate of indirect costs by using the indirect
cost ratio. There is not a universally accepted method for
estimating indirect cost ratios (Manuele, 2011). The survey
original 2017 version of Safety Pays in Mining, the 2022
data includes fewer injury counts, but the pattern and per-
cent of injury associated with mine worker activity and
common injuries are similar.
Within this NCCI mining-related injury cost dataset,
the mean was always higher than the 50th percentile, and
for about half of the injuries, the mean was higher than the
75th percentile. The mean would generally overestimate
injury costs, as the mean alone does not fully represent a
distribution of costs. Variability and skewness must also
be taken into account. Showing percentiles of the direct
costs helps show the distribution of this injury cost data.
Additionally, percentiles require no distributional assump-
tions. The cost data is less skewed than the data used in the
2017 version of Safety Pays in Mining. In that cost data,
the mean was always higher than the 75th percentile, and
for about half of the injuries, the mean was higher than
the 90th percentile (Heberger, 2018). This is likely because
the NCCI data used for Safety Pays in Mining v2.0 has
nearly nine times the claims used from the original web
app and includes data from 35 states while the original web
app only used data from Ohio. The original version also
adjusted costs from a ten-year period (2001–2011) into
2015 dollars (Heberger, 2018).
There are two main reasons why a mine might want
to use different percentiles rather than the 50th percentile,
or median, which is usually the most familiar. The median
provides a good estimate for a single “typical” claim because
half of the claims have higher costs and half of them have
lower costs. One reason to select a cost higher than the
median is related to the total number of claims that are
expected. If a mine is expecting more than one claim, the
chances of having a very expensive claim increase. As a
result, if expecting two to ten claims, using the 75th per-
centile for each claim will lead to a better estimate for total
costs. When the number of claims exceeds fifteen, the
90th percentile for each claim provides a better estimate
(Heberger, 2018).
Another reason to select a cost higher than the median
is concern about the risk of having a high-cost claim that
costs much more than the typical claim. There is substan-
tial risk that claims will cost much more than the “typical”
claim, as illustrated by the cost of claims at the 90th percen-
tile and above. Even if a mine has a single claim, there is a
10% chance that the claim will exceed the 90th percentile
cost. Tables 5a and 5b show why different percentiles are
used. For a lower leg injury, the median (50th percentile)
cost is $29,579 but the mean is $105,095, which is much
too high an estimate for a typical injury. The skewness in
the cost data indicates that every injury has a few cases of
extremely high costs. Generally, costs will be between the
first and third quartiles, but it is important to be aware
that there are also those high-cost cases (95th percentile).
Allowing the web app user to choose direct cost percentile
based on number of injuries or their own risk profile allows
users to explore the various costs per injury and how these
costs can impact the financial success of a company.
The costs are difficult to compare between the origi-
nal 2017 version of Safety Pays in Mining and the updated
Safety Pays in Mining v2.0. The main reason is because the
original version used all claim types and did not differenti-
ate between medical-only and lost-time claims. The lost-
time claim costs are much higher than medical-only claims
for the same types of injuries. Finger lacerations in v2.0 are
all from medical-only claims and the direct cost percentile
values are similar to the original. When looking at back
strains in v2.0, the claim types include medical-only and
lost-time claims. The medical-only claim cost percentiles
are much lower than the 2017 Safety Pays in Mining costs
for back strain/sprain, but the lost-time claims are much
higher. The two versions also have slightly different catego-
rizations of injury, especially for the part of body, nature of
injury, and injury cause combinations. This is partly due to
the different WC datasets, but also the v2.0 data had many
more claims allowing costs to be generated for very specific
injuries.
Safety Pays in Mining v2.0 is intended for mine manag-
ers, safety managers, consultants, researchers, government
agencies, and students—or anyone who is interested in the
costs of specific injuries in the mining industry. Mines can
benefit the most from Safety Pays in Mining v2.0, as it can
help them prioritize safety and health interventions and
focus on areas for improvement. Mines may want to focus
on eliminating the higher-cost injuries first. By showing the
additional sales needed to cover the injury cost and provid-
ing examples of how money could be spent instead of pay-
ing for an injury, the web app presents the same information
in different terms, which can be useful for safety manag-
ers who do not have experience analyzing financial aspects
of the industry. They can also use the web application to
assist with cost-benefit analysis for safety budget allocations
to help justify purchasing personal protective equipment
(PPE), enrolling in safety programs, or obtaining engineer-
ing controls to reduce exposure to injury (Heberger, 2018).
LIMITATIONS
A primary limitation of the total cost calculation comes
from the estimate of indirect costs by using the indirect
cost ratio. There is not a universally accepted method for
estimating indirect cost ratios (Manuele, 2011). The survey