R&D | Consulting
Verdi Technology’s mission is to offer the world a scalable, highly affordable, fully configurable (meaning ‘out of the box’) platform targeted to meet the day-to-day needs and challenges of small- to medium-sized organizations, and bigger ones that need ‘lean and mean’ approaches, to manage health and safety as an essential business process.
To get there, we’ve self-funded our development of the webOSCAR™ platform and its powerful data analytics through consulting Research & Development (R&D) projects.
Read the case studies below to learn why “the big boys” chose Verdi Technology when they ‘already had a solution,’ and how our technology and expertise has helped them solve real-world environmental, health and safety problems their enterprise EHS systems do not address.
Our Foray into Reality
Our customers are the largest companies in their industry and were (and still are) using ‘enterprise’ EHS platforms or content-focused (“silo”) software - our “competitors.” While C-Suite executive decision-makers may feel comfort or confidence that paying millions of dollars and devoting extensive internal resources to customization, set up and learning, and ongoing support fees will ‘ensure compliance’ and ‘control risk’, the reality is different for their technical managers - the people who are actually responsible for solving problems and ensuring employees’ health is effectively protected.
What professional technical managers often discover is these big, expensive, “customized” enterprise systems or silo applications are ‘clunky’ to use and do little more than collect individual results, calculate sums and averages, and tabulate and report this basic summary information and lists. Beyond the customized menus, ‘mobile apps,’ the array of fancy pie charts and ‘pareto’ graphs, and ‘configurable’ dashboards, they are basically providing a glorified version of Microsoft Excel!
When called upon to solve their complex problems, our world-class expert technical team of Occupational Medicine, Statistics, Industrial Hygiene, and Data Management professionals devised statistically-based solutions that organize and analyze raw data to turn it into actionable aggregate data--the information companies really need to make critically important decisions and Best Practices policies that directly safeguard their employees’ health and substantively reduce risk.
Verdi Technology beta-tested our patent-pending, OSHA/NIOSH Noise Challenge Finalist-awarded dBw metric and analytics in one of North America’s largest and oldest gold mines, owned by one of the world’s largest gold mining companies.
Noise is a significant, difficult-to-control hazard in precious metal mining. Noise-induced hearing loss (NIHL) is the most prevalent and disabling occupational disease in the world. The mine has conducted audiograms on its workforce for many years, with results compiled in an industry-leading software “database.” However, this software and the company did nothing more with the data than report individual results and compliance “threshold shifts.” The company’s senior industrial hygienist wanted know the mine’s testing performance (whether and to what extent audiograms being conducted consistently and on-time) and understand the aggregate trends or outcomes of whether and to what extent NIHL was being effectively prevented within and among similar exposure groups (SEGs). After months of labor-intensive, error-prone work importing this basic database into their corporate EHS platform, neither the in-house team of occupational nurses, physicians and industrial hygienists nor their consulting audiologist could even begin to answer these two fundamentally important questions.
Verdi Technology uploaded, cleaned up and analyzed this entire historical database using our proprietary dBw metric and trend analytics to detect and predict employees at increased risk for noise-induced hearing loss (NIHL), and measure the comparative and overall effectiveness of their HCP in preventing NIHL. This approach was developed into a proposed corporate Best Practices program for noise medical surveillance. These beta-tested analytics are now being embedded into our webOSCAR Noise module.
Verdi Technology transformed a biological monitoring program from a one-employee-one-test-at-a-time approach using arbitrarily determined interpretation thresholds into a Best Practices, population-based medical surveillance program using statistically-based sampling and data analytics.
Arsenic is a significant, difficult-to-control hazard in certain underground mining operations. Chronic arsenic exposure is associated with increased risk for lung and other forms of cancer. Standard industrial hygiene air monitoring measurements do not effectively stratify internal exposure levels and long-term disease risk, particularly when respiratory protection and other exposure controls are variably utilized.
Like in many hazardous industries, for this company the value of biological monitoring as a biomarker to assess long-term internal exposure and population risk remains limited because the ‘standard operating procedure’ is unreliable, inefficient, and expensive. Specifically, the conventional but unproven method of sampling a biomarker in every employee’s urine at a recurring frequency, arbitrarily adjusting for creatinine without knowing how much error is introduced, comparing individual test results to a single numerical biological exposure index (BEI), and temporarily removing those employees whose tests exceed this threshold results in significant operational disruption without objectively reducing risk.
The company’s corporate ‘occupational health and industrial hygiene’ software platform collected air monitoring and biological monitoring raw data, but did nothing more with it than produce tabulations and charts of individual results, averages, and maximums. The company’s industrial hygienists struggled to create their own data analyses using separate Excel spreadsheets. The mine’s senior industrial hygienists needed methods and tools to analyze their aggregate longitudinal biological monitoring data to objectively inform them whether or to what extent exposure controls are effective in reducing employees’ long-term health risks. They realized and acknowledged their expensive EHS platform couldn’t do this, and could potentially take many years and a lot more money to build a ‘one-off’ customization.
Verdi Technology devised a population-based Best Practice approach to inorganic arsenic biological monitoring, transforming an inefficiently conducted biological monitoring program into a real medical surveillance program. We developed a statistically-based sampling and aggregate data analysis and interpretation strategy and methodology, which is now being tested in a pilot study in preparation for facility-wide implementation. Controllable components of biomarker variability are being quantified and changes are measured over time to evaluate the overall and relative effectiveness of exposure controls within and among similar exposure groups (SEGs). Statistical outliers (true positives) can be accurately identified, investigated and systematically addressed at the individual or group level.
These analytics are now being embedded into our webOSCAR’s biological monitoring modules, including arsenic and other heavy metals and other substances.
The webOSCAR technology platform was developed by an Occupational Medicine physician with over 25 years’ experience providing medical and compliance consultation services to highly regulated, hazardous industries.