Clifford S. Mitchell’s research while affiliated with University of Maryland, Baltimore and other places

This paper describes the work-related information collected in several important U.S. national health and behavior surveys, to highlight data gaps that prevent identifying responses by vulnerable workers in the gig economy, with emphasis on the growing digital platform sector of the work force. The national information systems used to understand health status and health behaviors, including drug use, rely on outdated census categories for self-employed workers. This paper describes the importance of understanding the needs of this growing part of the labor sector and describes how some of the most well-known and utilized national surveys fail to meet this need. For the agencies conducting national health and behavior surveys, we propose revisions to the categories used to classify type of worker and recommend adoption of a new Worker-Employer Relationship Classification model.

Objective Opioid-related overdose deaths (OROD) increase annually, yet little is known about workplace risk factors. This study assessed differences in OROD rates across industry and occupation in Maryland, in addition to demographic differences within industry and occupation. Methods The 2018 State Unintentional Drug Overdose Reporting System (SUDORS) was used to compare OROD between industries and occupations. Results The leading industries in OROD included: construction, manufacturing, and transportation and warehousing. Occupational groups were similar: construction and extraction, production, and transportation and material moving. There were also differences by sex (greater rates in men), age (greater rates in older workers), and race/ethnicity (varied patterns in rates). Conclusion Employers and state leaders should work collaboratively to target prevention and intervention for workplaces at highest risk for OROD. Construction was highest and needs supports that respond to the workplace culture.

Background Prescription Drug Monitoring Programs (PDMPs) are electronic databases that track controlled substance prescriptions in a state. They are underused tools in preventing opioid abuse. Most PDMP education research measures changes in knowledge or confidence rather than behavior. Objective To evaluate the impact of online case-based training on healthcare provider use of the Maryland (USA) PDMP. Methods We used e-mail distribution lists to recruit providers to complete a brief educational module. Using a pre-training and post-training survey in the module, we measured self-reported PDMP use patterns and perceived PDMP value in specific clinical situations and compared pre- and post-training responses. Within the module, we presented three fictional pain cases and asked participants how they would manage each, both before, and then after presenting prescription drug history simulating a PDMP report. We measured changes in the fictional case treatment plans before and after seeing prescription history. Finally, we measured and compared how often each participant accessed the Maryland PDMP database before and after completing the educational module. We used multivariate logistic regression to measure the effect of the intervention on actual PDMP use frequency. Results One hundred and fifty participants enrolled and completed the training module, and we successfully retrieved real-world PDMP use data of 137 of them. Participants’ decisions to prescribe opioids changed significantly after reviewing PDMP data in each of the fictional cases provided in the module. In the months following the training, the rate of PDMP use increased by a median of four use-cases per month among providers in practice for less than 20 years (p = 0.039) and two use-cases per month among infrequent opioid prescribers (p = 0.014). Conclusion A brief online case-based educational intervention was associated with a significant increase in the rate of PDMP use among infrequent opioid prescribers and those in practice less than 20 years.

Background Infections with nontyphoidal Salmonella cause an estimated 19,336 hospitalizations each year in the United States. Sources of infection can vary by state and include animal and plant-based foods, as well as environmental reservoirs. Several studies have recognized the importance of increased ambient temperature and precipitation in the spread and persistence of Salmonella in soil and food. However, the impact of extreme weather events on Salmonella infection rates among the most prevalent serovars, has not been fully evaluated across distinct U.S. regions. Methods To address this knowledge gap, we obtained Salmonella case data for S. Enteriditis, S. Typhimurium, S. Newport, and S. Javiana (2004-2014; n = 32,951) from the Foodborne Diseases Active Surveillance Network (FoodNet), and weather data from the National Climatic Data Center (1960-2014). Extreme heat and precipitation events for the study period (2004-2014) were identified using location and calendar day specific 95th percentile thresholds derived using a 30-year baseline (1960-1989). Negative binomial generalized estimating equations were used to evaluate the association between exposure to extreme events and salmonellosis rates. Results We observed that extreme heat exposure was associated with increased rates of infection with S. Newport in Maryland (Incidence Rate Ratio (IRR): 1.07, 95% Confidence Interval (CI): 1.01, 1.14), and Tennessee (IRR: 1.06, 95% CI: 1.04, 1.09), both FoodNet sites with high densities of animal feeding operations (e.g., broiler chickens and cattle). Extreme precipitation events were also associated with increased rates of S. Javiana infections, by 22% in Connecticut (IRR: 1.22, 95% CI: 1.10, 1.35) and by 5% in Georgia (IRR: 1.05, 95% CI: 1.01, 1.08), respectively. In addition, there was an 11% (IRR: 1.11, 95% CI: 1.04-1.18) increased rate of S. Newport infections in Maryland associated with extreme precipitation events. Conclusions Overall, our study suggests a stronger association between extreme precipitation events, compared to extreme heat, and salmonellosis across multiple U.S. regions. In addition, the rates of infection with Salmonella serovars that persist in environmental or plant-based reservoirs, such as S. Javiana and S. Newport, appear to be of particular significance regarding increased heat and rainfall events.

The dual challenges of COVID-19 and the opioid epidemic have heightened the need of Maryland workplaces for accessible resources and supports. This paper describes efforts of the Workplace PROSPER (Partnering to Reduce Opioid Stigma and Support Employment in Recovery) project team to explore opioid-related state employment needs from Key Stakeholder perspectives. Discussion revealed significant overlap between the needs identified by stakeholders and pre-existing recovery friendly initiatives in other states. However, this convening identified the need for increased training of medical professionals in communicating about work capacity and safety as well as for resources to support family members of individuals with Opioid Use Disorder and model programs for hiring individuals in recovery. Next steps include the creation and dissemination of a survey to obtain a broader base of feedback and the development of a robust set of online recovery resources for Maryland employers and employees.

An edible cannabis product (ECP) manufactured with food ingredients is subject to the same types of contamination as any conventional food product. Physical, microbial, and chemical hazards are a potential threat to anyone consuming cannabinoid-containing products by mouth. Preventing the unintentional ingestion of ECPs is also a concern for public health professionals. An analysis of the regulatory landscape in the United States (US) was conducted to identify best practices specific to ECPs and to pinpoint preventative safety measures that had not been extensively implemented. Widespread adoption of some of the more useful precedents set by US jurisdictions, as examined in this work, could be of great value in protecting public health.

Importance Ongoing climate change is affecting the health of communities across the globe. While direct consequences, including morbidity and mortality tied to increases in the frequency of extreme weather events, have received significant attention, indirect health effects, particularly those associated with climate change–driven disruptions in ecosystems, are less understood. Objective To investigate how ongoing changes in the timing of spring onset related to climate change are associated with rates of asthma hospitalization in Maryland. Design, Setting, and Participants This cross-sectional study of 29 257 patients with asthma used general additive (quasi Poisson) and mixed-effect (negative binomial) models to investigate the association between changes in the timing of spring onset, detected using satellite observations, and the risk of asthma hospitalization in Maryland from 2001 to 2012. Data analysis was conducted from January 2016 to March 2019. Exposures Phenology data, derived from the National Aeronautics and Space Administration’s Moderate Resolution Imaging Spectroradiometer, were used to calculate location-specific median dates for start of season from 2001 to 2012. How the start of season for a given year and location deviated from the long-term average was calculated and categorized as very early, early, normal, or late. Main Outcomes and Measures Daily asthma hospitalization in Maryland during the spring season (ie, March to May). Results There were 108 358 total asthma hospitalizations during the study period, of which 29 257 (27.0%; 14 379 [49.1%] non-Hispanic black patients; 17 877 [61.1%] women) took place during springtime. In the unadjusted model, very early (incident rate ratio [IRR], 1.17; 95% CI, 1.07-1.28) and late (IRR, 1.07; 95% CI, 1.00-1.15) onset of spring were associated with increased risk of asthma hospitalization. When the analysis was adjusted for extreme heat events and concentrations of particulate matter with an aerodynamic diameter less than 2.5 μm, the risk remained significant for very early spring onset (IRR, 1.10; 95% CI, 1.02-1.20) but not for late spring onset (IRR, 1.03; 95% CI, 0.97-1.11). Conclusions and Relevance These results suggest that ongoing changes in the timing of spring onset, which are related to climate variability and change, are associated with asthma hospitalization. Given the high burden of allergic diseases and the number of individuals sensitized to tree pollen, these findings serve as a wake-up call to public health and medical communities regarding the need to anticipate and adapt to the ongoing changes in the timing and severity of the spring allergy season.

A Pseudomonas aeruginosa outbreak was investigated in a neonatal intensive care unit that had experienced a prior similar outbreak. The 8 cases identified included 2 deaths. An investigation found the cause of the outbreak: tap water from contaminated hospital plumbing which was used for humidifier reservoirs, neonatal bathing, and nutritional preparation. Our findings reinforce a recent Centers for Medicare & Medicaid Services memo recommending increased attention to water management to improve awareness, identification, mitigation, and prevention of water-associated, health care-associated infections.

Maryland's response to climate change has included creation of the Maryland Commission on Climate Change in 2007, and initiatives across many State agencies. The Commission coordinates these initiatives through the State Climate Action Plan. The Maryland Department of Health has partnered with the School of Public Health at the University of Maryland College Park to develop the 2016 Climate and Health Profile report, which estimates the health impacts of climate change in Maryland. Using historical health data and climate model projections, the report found that climate change will have a disproportionate impact on certain populations across the state. For example, extreme heat and extreme precipitation events during summer months increased the risk of hospitalization for asthma in Maryland by 22% and 11% respectively. But the extreme heat related risk for asthma hospitalization was more pronounced among non-Hispanic whites (33%) than non-Hispanic blacks (20%). Based on these findings, the Department and School have begun to engage with community organizations and various stakeholders to develop interventions and adaptations aimed at increasing resilience and mitigating some of the health impacts. Through these partnerships and projects, Maryland is using health data, climate projections, and the State Climate Action Plan to assist local communities and regional partners in climate adaptation activities.