AOCOPM 2022 Midyear Educational Conference-217747

Video Transcription

Video Summary

Dr. Tony Ansky-Decker delivered the Loren Hatch Memorial Lecture in Occupational Medicine, discussing Workplace Toxicology, False Testing, and Substance Abuse. Dr. Loren Hatch was a pioneer in the field, actively contributing to occupational and environmental medicine. This annual lecture honors individuals dedicated to advancing these fields. Dr. Decker, the Medical Director of clinics in Northern Arizona, focuses on veterans' healthcare, specializing in chronic pain and addiction therapy. During his lecture, he highlighted the impact of chronic pain, citing that over 20% of adults experience it, with considerable implications for the workplace. He discussed the high prevalence of substance use disorders, often leading to workplace challenges, injury, and absence.<br /><br />Addressing toxicology testing methods, he evaluated advantages and disadvantages of urine, oral fluid, sweat, blood, hair, nail, and breath analysis for substance detection, emphasizing the importance of sensitive and specific tests. He noted challenges associated with such testing and discussed the significant burden of chronic pain and rising overdose rates, especially among veterans. Dr. Decker highlighted the Association of Pain Management policies contributing to the opioid crisis, urging practitioners to carefully manage chronic opioid prescriptions to avoid patient distress and potential suicide or overdose following abrupt cessation. Looking forward, Dr. Decker stressed the importance of removing stigma around addiction, enhancing provider education on addiction treatments, and balancing clinical care with accurate substance testing to support patient recovery. His approach encourages cultural sensitivity and empathy in handling substance use in occupational settings.

Keywords

Occupational Medicine

Workplace Toxicology

Substance Abuse

Chronic Pain

Addiction Therapy

Toxicology Testing

Opioid Crisis

Veterans Healthcare

Provider Education

Substance Detection