At the AIHA Fall Conference last October, I co-presented a half-day workshop that highlighted trends in technology such as smartphone sound-measurement apps and low-cost sensors. The workshop also described how IHs can achieve increased confidence in their exposure assessment results through large-scale data aggregation and crowdsourcing. 
So the “near-future” tools for exposure assessment look really exciting. But what about the realities of collecting and utilizing quality noise exposure data
today?
Are we using the tools we have to their maximum effectiveness, and applying the results in a correct and positive manner?
The data on compensation claims suggest otherwise. While hearing loss compensation claims in all of private industry have fallen from 3.2 cases to 2.2 per 10,000 workers from 2004 through 2010, according to a Bureau of Labor Statistics economist quoted in an April 2013
article
in
The Hearing Journal
, some industries still have far higher rates. Primary metal manufacturing, for example, declined over the same period, but only to a relatively high rate of 33.8 cases per 10,000.
In the same article, John Ratliff, CIH, CSP, MSPH, a former chair of the AIHA Noise Committee, stated that he suspects a lot of employees with hearing impairments retire without filing a claim “because they don't know that they can.” Lack of awareness or reluctance to file during economically stressful times may play a role in these downward trends, as might other factors such as tightened rules for filing enacted by some states. Regardless, according to NIOSH, an estimated $242 million is spent annually on workers’ comp for hearing loss disability. Actual monetary award data proves elusive, and as the current work force ages there may be an upward trend in claims, not all of which will have been caused by occupational exposure. These realities place greater importance on ensuring that occupational noise exposure is sampled and reported correctly.
Responsible Dosimetry
Let’s set aside compensation costs for the moment. Is any amount of work-related noise-induced hearing loss consistent with the values and culture of organizations that truly embrace Corporate Social Responsibility (CSR) initiatives? Many companies with strong CSR agendas have already set exposure limits that are more protective than the regulations require. Then again, there’s no ignoring the fact that today’s workers confront more sources of high noise exposure off the job, given the proliferation of earbuds and the sheer amount of time people interact with high-volume electronics and engage in other noisy pastimes such as riding recreational vehicles, attending sporting events and concerts, and recreational shooting.
Adoption of new technology always brings challenges as well as benefits. Despite developers’ best efforts, adding lots of “features” can sometimes be counterproductive, depending on the quality of implementation. In noise dosimetry, for example, instruments calculate exposure values to multiple global standards even though the user might want only the one or two basic sets of metrics needed to comply with regulatory requirements. 
The noise dosimeters and sound-level meters of thirty years ago were bulky, heavy instruments difficult to configure, calibrate, and use, and they provided only the bare minimum of exposure dose information. Today, these devices have evolved into miniature, sleek designs with capacity to generate countless noise metrics and huge data files of highly resolved time-history data. This alone can be problematic: users can be overwhelmed by their ability to produce multiple iterations of the same data through combinations of settings that were impossible to achieve in older instruments. The power of today’s instruments increases the likelihood of a busy IH inadvertently misapplying a calculated metric and mistakenly including (or excluding) a worker from the Hearing Conservation Program (HCP). The negative ramifications of either incorrect outcome are obvious. 
One common misapplication of exposure results has to do with the way dosimeters and SLMs calculate average levels (often labelled Lavg, although there is some variation in labelling among manufacturers) and time-weighted averages (TWAs). This error is especially likely when dosimeters are worn for less than the full work shift. Here’s an example: A seven-hour test on an eight-hour shift with a constant noise level of 85 dB(A) will produce a TWA value of 84.0 dB(A) and an Lavg value of 85 dB(A). (See Figure 1 for a similar example using a 90 dB reference value.) But since the goal of the HCP is to include anyone who would be exposed to a level of 85 dB or more for
eight hours
, using the TWA value
may be incorrect
. If you’re sure the last hour of the day was much quieter than the first seven hours and did not contribute to the worker’s dose, then perhaps TWA would be a representative value to apply. However, that’s often not the case. Since we tend to think of TWAs as the value we want to apply for personal exposures to agents other than noise, it can lead us to mischaracterize the employee’s risk and incorrectly include or exclude them from the program.
Hearing Loss and Noise Exposure Assessment
Why Getting It Right Matters
By Rob Brauch
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