National attention continues to be captured by the widespread issue of lead in our schools and the environment. The Government Accounting Office (GAO) recently issued a report finding lead-based paint continues to pose a health risk in our nation’s schools even four decades after its use was banned. Lead dust emanating from peeling paint and/or exposed as part of renovations has been proven to slow growth and development, damage hearing and speech, and cause permanent learning disabilities in children.
The GAO survey found that only 12 percent of school districts nationwide were inspected for lead-based paint in 2016-2017. Of those districts, nearly half found lead-based paint. Similarly, another report found that only 43 percent of school districts nationwide tested for lead in their schools’ drinking water in 2016 and 2017. Of those that were tested, 37 percent had elevated lead levels. The lead exposure our children are getting in schools around the country is frightening.
Lawmakers are calling for wider testing of schools to get a handle on the true scope of lead exposure. It’s a complicated issue as lead from the paint can seep into the soil contaminating the ground children play on and impacting the water supply. There’s also the use of lead in plumbing impacting water supply. With so many areas to test for lead levels, it’s not surprising that progress on testing all schools has been slow. This is of course not an excuse to continue the slow pace.
Digitally enabled, data-driven inspection processes were developed to help inspection teams become more efficient to conduct very necessary yet very complex, large-scale inspections. The reliance on paper-based processes requiring significant in-office time for manual data entry does not meet the inspection needs of public health. Yet, digitizing the inspection process needs to be more than putting a form on a tablet. Organizations need to take a serious look at inspections as part of their overall modernization plans that involve implementing artificial intelligence (AI), machine learning, blockchain, analytics, and more. Regulatory inspections with entrenched, manual, paper-based processes are fertile ground for organizations to implement and see quick results from automation investments. In this way, inspection teams can serve as a prototype for wider modernization efforts across organizations. Inspection processes can be modernized in months, not years, and at a fraction of the cost of other programs.
For lead inspections, a mobile inspection application can build in the steps needed to examine paint, soil, and water at a given school. All of this data, collected and analyzed together, can create a holistic picture of the impact lead and other contaminants are having on the overall health of the building and its students. The back office portal used to manage collection from the mobile devices can pull in other data sources, such as information from the local environmental protection agency and/or building code information, to prioritize the order in which to inspect schools. Dashboards and analytics can also be integrated to help visualize the data for decision-making by agencies and officials as well as provide a way to easily communicate findings to the public at large.
Interested in learning how to better use data to increase inspection efficiency for lead or other harmful contaminants to improve public safety? Drop me a line, or a comment and visit us at: www.ARInspect.com.