The growing labyrinth of laws allowing some form of marijuana use has made crafting corporate drug-free policies a real buzzkill. The task is becoming nearly as complex as drafting strategies for complying with the Family and Medical Leave Act, and that law’s numerous state offspring.
I’m exaggerating. Creating a company policy on drug use and drug-testing procedures can’t be as nightmarish as leave-law compliance.
But after reading “Marijuana in the Workplace: Guidance for Occupational Health Professionals and Employers,” I have two overriding thoughts.
One, I hope the writers saw the pun in beginning the paper’s subtitle with “Joint Guidance Statement …”
When it comes to marijuana, the days of a one-size-fits-all zero-tolerance policy are slipping away.
Two, when it comes to marijuana, the days of a one-size-fits-all zero-tolerance policy are slipping away. This is particularly true for those with operations across multiple states with varying cannabis laws.
Societal, legal and medical forces are driving a need for a greater assessment of each employer’s attitude and policies regarding marijuana use. Rapidly shifting dynamics have also increased the need to seek the guidance of legal and health care professionals when crafting corporate policies on marijuana use and drug testing.
The broader forces at play include shifting public attitude toward marijuana; increased adoption of medical or recreational marijuana laws, including some with limits on employer treatment of cannabis users and a few with discrimination protections; the federal government’s inconsistent enforcement stance on state marijuana laws; and evolving scientific evidence of marijuana’s efficacy for treating certain ailments.
At least 23 states now have medical cannabis laws, four others have legalized recreational use, and that trend is expected to continue. Meanwhile, marijuana remains the substance most often detected in workplace drug-testing programs.
The new hodgepodge of state laws includes a few protecting marijuana use outside work hours, others limiting drug-testing practices, and still others raising unknowns, including how some state regulations will interact with disability laws.
Yet employers must still protect worker and public safety, comply with regulations regarding zero tolerance for safety-sensitive positions, and guard themselves against worker impairment, productivity losses and job performance problems, etc.
Fortunately, no state law requires employers to permit workplace drug use or tolerate impairment at work, allowing companies to implement drug-free-workplace policies.
The recent jurisdictional variations in laws, coupled with the desire of many employers to use drug testing to maintain safe work environments, leave companies in a thornier weed patch than before.
“Reconciling varying and dynamic state laws in regard to legality, permitted use in the workplace, and lawful drug testing can be challenging,” the paper stated. “Every employer should consult with legal advisors to ensure that they comply with any applicable state or local laws and design their testing programs to withstand legal challenges.”
Every employer wanting to better understand marijuana, review related state and federal laws, and learn some suggestions for monitoring workers for marijuana use, might want to start by reviewing the guidance paper.
Because while marijuana users often cite relaxation and euphoria as reasons for consuming the drug, it’s obvious that employers have less to relax about.
Experts Advise More Focus for Ergo Efforts
Companies that limit their ergonomics efforts to promoting employee safety are missing an opportunity, say experts. In fact, employees in these situations may feel stressed to use a new system that may result in lower production levels.
Instead, ergonomics environments should equally promote worker well-being and improvements to organizational productivity. The result is a synergy that maximizes both outcomes.
“Implementing ergonomic principles in an occupational environment can directly benefit the worker and the organization by reducing physical and mental strain, lowering the risk of occupational-related injuries and illnesses, and improving work performance,” stated a new report.
“By embracing the principles of ergonomics, and establishing a positive ergonomics climate, organizations can enhance both operational performance and employee well-being.”
The findings are included in a study from researchers at Colorado State University and were published in the journal Applied Ergonomics.
While previous research has focused on the relationship between an organization’s value for employee well-being and workers’ self-reported pain, the authors said few, if any, studies have compared how the values for performance in addition to well-being can work together to predict work-related outcomes.
Researchers from Colorado State University conducted two rounds of questioning at a large manufacturing facility. After an initial pilot test, the authors asked questions of more than 1,000 workers. One year later, they returned to see what, if any, changes had occurred. More than 700 workers participated in the second round of questioning.
Questions reflected the ergonomics concept of designing and modifying work to improve the focus of interest, performance or well-being.
Performance-focused ergonomic climate, or PE, included things such as maximizing productivity and efficiency, quality of product or service, sustainability as a company, maintaining a competitive edge in the market, and completing the tasks necessary for the organization to succeed.
Well-being focused ergonomic climate, or WE, referred to a focus on ensuring the employees were healthy and happy, including reducing their injury and illness risks, addressing quality of work and life issues, improving job satisfaction and supporting work-life balance.
“Employees may resist a new tool or process that reduces injury if they think it will cause them to work more slowly and miss production targets.”
“Through a series of steps we developed the ergonomics climate assessment,” they wrote, “then piloted, refined and obtained preliminary validation evidence for this new assessment.”
Four common factors identified as central to organizational climates that involve ergonomics were management commitment, employee involvement, job hazard analysis, and training and knowledge.
The questions consisted of an equal number targeted to PE and WE, placed side by side. The workers were also asked if they had experienced work-related pain within the prior 12 months. The researchers hypothesized:
- Both WE and PE facets of an ergonomics climate assessment will be negatively related to work-related pain.
- If both WE and PE facets were rated low, self-reported pain would be higher, and vice versa. They looked at situations in which each was higher than the other.
- When employees perceive a discrepancy between the facets, those who said PE was promoted more would report more pain than if the situation were reversed.
“Good ergo practice involves understanding that the whole is usually greater (more useful, powerful, functional) than the sum of the parts,” the authors wrote. “This understanding is consistent with our findings that PE and WE facets of ergonomics climate were conceptually distinct but interrelated so much so that incongruence between the two resulted in poor outcomes.”
The perception that either well-being or performance was favored can result in work-related stress and create symptoms of work-related pain, according to the study. For example, a company that emphasizes facets of performance sends a message to workers that production is more important than their own well-being. Emphasizing well-being over performance can be equally as stressful.
“This may cause stress if an improvement is seen as a threat to productivity,” the study said. “For example, employees may resist a new tool or process that reduces injury if they think it will cause them to work more slowly and miss production targets.”
Companies should employ ergonomics improvements that look equally at a worker’s performance and his overall well-being, the authors advised. This systems approach to occupational ergonomics designs and implements productivity gains concurrently with worker well-being goals.
As an example, they said that manually attaching hydraulic hosts to a subassembly with a hand wrench can be performed faster by increasing the expected yield of the worker, which would likely lead to greater hand fatigue, work stress, and poorer quality.
By using a systems approach to ergonomics, a redesign may include the use of a power driven wrench that results in greater output, less physically demanding hand motions, and less worker stress.
Creating and implementing such a system can help companies identify areas for improvement. In the case of the manufacturing facility used for the study, the first round of questions revealed a poor ergonomics climate assessment score in one production department. The company undertook an intervention of engineering and administrative changes to correct the problem.
Personnel involved included a team of production operators, maintenance and engineering staff and management.
The results of the second round of questioning indicated “a significant increase in both PE and WE facets of ergonomics climate for that production department,” the authors wrote.
“Thus the ergonomics climate assessment may be a practical and useful tool for organizations looking to understand and improve their ergonomics climate. This tool can be used as a baseline to assess the effectiveness of organizational efforts focused on improving ergonomics as well as a measure to assist in the prioritization of ergonomics interventions during periods of limited resources.”
6 Truths about Predictive Analytics
Predictive data analytics is coming out of the shadows to change the course of claims management.
But along with the real benefits of this new technology comes a lot of hype and misinformation.
A new approach, ACE 4D, provides the tools and expertise to capture, analyze and leverage both structured and unstructured claims data. The former is what the industry is used to – the traditional line-item views of claims as they progress. The latter, comprises the vital information that does not fit neatly into the rows and columns of a traditional spreadsheet or database, such as claim adjuster notes.
ACE’s recently published whitepaper, “ACE 4D: Power of Predictive Analytics” provides an in-depth perspective on how to leverage predictive analytics to improve claims outcomes.
Below are 6 key insights that are highlighted in the paper:
1) Why is predictive analytics important to claims management?
Because it finds relationships in data that achieve a more complete picture of a claim, guiding better decisions around its management.
The typical workers’ compensation claim involves an enormous volume of disparate data that accumulates as the claim progresses. Making sense of it all for decision-making purposes can be extremely challenging, given the sheer complexity of the data that includes incident descriptions, doctor visits, medications, personal information, medical records, etc.
Predictive analytics alters this paradigm, offering the means to distill and assess all the aforementioned claims information. Such analytical tools can, for instance, identify previously unrecognized potential claims severity and the relevant contributing factors. Having this information in hand early in the claims process, a claims professional can take deliberate actions to more effectively manage the claim and potentially reduce or mitigate the claim exposures.
2) Unstructured data is vital
The industry has long relied on structured data to make business decisions. But, unstructured data like claim adjuster notes can be an equally important source of claims intelligence. The difficulty in the past has been the preparation and analysis of this fast-growing source of information.
Often buried within a claim adjuster’s notes are nuggets of information that can guide better treatment of the claimant or suggest actions that might lower associated claim costs. Adjusters routinely compile these notes from the initial investigation of the claim through subsequent medical reports, legal notifications, and conversations with the employer and claimant. This unstructured data, for example, may indicate that a claimant continually comments about a high level of pain.
With ACE 4D, the model determines the relationship between the number of times the word appears and the likely severity of the claim. Similarly, the notes may disclose a claimant’s diabetic condition (or other health-related issue), unknown at the time of the claim filing but voluntarily disclosed by the claimant in conversation with the adjuster. These insights are vital to evolving management strategies and improving a claim’s outcome.
3) Insights come from careful analysis
Predictive analytics will help identify claim characteristics that drive exposure. These characteristics coupled with claims handling experience create the opportunity to change the course of a claim.
To test the efficacy of the actions implemented, a before-after impact assessment serves as a measurement tool. Otherwise, how else can program stakeholders be sure that the actions that were taken actually achieved the desired effects?
Say certain claim management interventions are proposed to reduce the duration of a particular claim. One way to test this hypothesis is to go back in time and evaluate the interventions against previous claim experience. In other words, how does the intervention group of claims compare to the claims that would have been intervened on in the past had the model been in place?
An analogy to this past-present analysis is the insight that a pharmaceutical trial captures through the use of a placebo and an actual drug, but instead of the two approaches running at the same time, the placebo group is based on historical experience.
4) Making data actionable
Information is everything in business. But, unless it is given to applicable decision-makers on a timely basis for purposeful actions, information becomes stale and of little utility. Even worse, it may direct bad decisions.
For claims data to have value as actionable information, it must be accessible to prompt dialogue among those involved in the claims process. Although a model may capture reams of structured and unstructured data, these intricate data sets must be distilled into a comprehensible collection of usable information.
To simplify client understanding, ACE 4D produces a model score illustrating the relative severity of a claim, a percentage chance of a claim breaching a certain financial threshold or retention level depending on the model and program. The tool then documents the top factors feeding into these scores.
5) Balancing action with metrics
The capacity to mine, process, and analyze both structured and unstructured data together enhances the predictability of a model. But, there is risk in not carefully weighing the value and import of each type of data. Overdependence on text, for instance, or undervaluing such structured information as the type of injury or the claimant’s age, can result in inferior deductions.
A major modeling pitfall is measurement as an afterthought. Frequently this is caused by a rush to implement the model, which results in a failure to record relevant data concerning the actions that were taken over time to affect outcomes.
For modeling to be effective, actions must be translated into metrics and then monitored to ensure their consistent application. Prior to implementing the model, insurers need to establish clear processes and metrics as part of planning. Otherwise, they are flying blind, hoping their deliberate actions achieve the desired outcomes.
6) The bottom line
While the science of data analytics continues to improve, predictive modeling is not a replacement for experience. Seasoned claims professionals and risk managers will always be relied upon to evaluate the mathematical conclusions produced by the models, and base their actions on this guidance and their seasoned knowledge.
The reason is – like people – predictive models cannot know everything. There will always be nuances, subtle shifts in direction, or data that has not been captured in the model requiring careful consideration and judgment. People must take the science of predictive data analytics and apply their intellect and imagination to make more informed decisions.
Please download the whitepaper, “ACE 4D: Power of Predictive Analytics” to learn more about how predictive analytics can help you reduce costs and increase efficiencies.
This article was produced by the R&I Brand Studio, a unit of the advertising department of Risk & Insurance, in collaboration with ACE Group. The editorial staff of Risk & Insurance had no role in its preparation.