Enhancing detection of labor violations in the agricultural sector: A multilevel generalized linear regression model of H-2A violation counts.

Agricultural workers are essential to the supply chain for our daily food, and yet, many face harmful work conditions, including garnished wages, and other labor violations. Workers on H-2A visas are particularly vulnerable due to the precarity of their immigration status being tied to their employer. Although worksite inspections are one mechanism to detect such violations, many labor violations affecting agricultural workers go undetected due to limited inspection resources. In this study, we identify multiple state and industry level factors that correlate with H-2A violations identified by the U.S. Department of Labor's Wage and Hour Division using a multilevel zero-inflated negative binomial model. We find that three state-level factors (average farm acreage size, the number of agricultural establishments with less than 20 employees, and higher poverty rates) are correlated with H-2A violations. These findings offer valuable insights into where H-2A violations are being detected at the state and industry levels.

Expanding Our Understanding of Traffickers and Their Operations: A Review of the Literature and Path Forward.

Human trafficking is a serious crime and violation of human rights that results in numerous harms. Although the phenomenon is not new, scholarship on the issue has grown substantially since the first legal framework was passed in 2000. However, the existing literature has been criticized for its skewed focus on victims, among other things. The dearth of information on traffickers and their operations limits our ability to reduce or prevent perpetration. The current study presents a comprehensive and critical review of the existing literature focused on traffickers to synthesize what is already known and highlight the key gaps. Twenty-nine articles met the inclusion criteria of (1) focusing on traffickers and their operations and (2) relying on data either directly from traffickers or sources that contained detailed information about criminal cases against traffickers. We used an iterative process to identify relevant studies, which included collecting articles of which we were already familiar or were identified in existing reviews, searching their reference lists, and conducting cited-by searches until saturation was reached. Topics found in the extant literature included: characteristics of traffickers, relationships between traffickers and victims, organizational characteristics and networks, operations, connections with other crimes, motivations, perceptions of behavior, and risks associated with trafficking. It concludes with recommendations for future research and a discussion of how bridging gaps in the literature could support more rigorous mathematical modeling that is needed to identify and assess promising perpetration prevention and intervention strategies.

A discrete event simulation to evaluate impact of radiology process changes on emergency department computed tomography access.

BACKGROUND: Hospitals face the challenge of managing demand for limited computed tomography (CT) resources from multiple patient types while ensuring timely access. METHODS: A discrete event simulation model was created to evaluate CT access time for emergency department (ED) patients at a large academic medical center with six unique CT machines that serve unscheduled emergency, semi-scheduled inpatient, and scheduled outpatient demand. Three operational interventions were tested: adding additional patient transporters, using an alternative creatinine lab, and adding a registered nurse dedicated to monitoring CT patients in the ED. RESULTS: All interventions improved access times. Adding one or two transporters improved ED access times by up to 9.8 minutes (Mann-Whitney (MW) CI: [-11.0,-8.7]) and 10.3 minutes (MW CI [-11.5, -9.2]). The alternative creatinine and RN interventions provided 3-minute (MW CI: [-4.0, -2.0]) and 8.5-minute (MW CI: [-9.7, -8.3]) improvements. CONCLUSIONS: Adding one transporter provided the greatest combination of reduced delay and ability to implement. The projected simulation improvements have been realized in practice.

Life and expectations post-kidney transplant: a qualitative analysis of patient responses.

BACKGROUND: The effect of a kidney transplant on a recipient extends beyond the restoration of kidney function. However, there is limited qualitative analysis of recipient perspectives on life following transplantation, particularly in the United States. To understand the full patient experience, it is necessary to understand recipient views on life adjustments after kidney transplantation, medical management, and quality of life. This could lead to improvements in recipient care and sense of well-being. METHODS: We conducted a paper-based survey from March 23 to October 1, 2015 of 476 kidney transplant recipients at the University of Michigan Health System in Ann Arbor, Michigan. We analyzed their open-ended responses using qualitative research methods. This is a companion analysis to a previous quantitative report on the closed-ended responses to that survey. RESULTS: Common themes relating to changes following transplantation included: improvements in quality of life, a return to normalcy, better health and more energy. Concerns included: duration of graft survival, fears about one day returning to dialysis or needing to undergo another kidney transplant, comorbidities, future quality of life, and the cost and quality of their healthcare. Many recipients were grateful for their transplant, but some were anxious about the burdens transplantation placed on their loved ones. CONCLUSIONS: While most recipients reported meaningful improvements in health and lifestyle after kidney transplantation, a minority of participants experienced declines in energy or health status. Worries about how long the transplant will function, future health, and cost and quality of healthcare are prevalent. Future research could study the effects of providing additional information, programs, and interventions following transplantation that target these concerns. This may better prepare and support kidney recipients and lead to improvements in the patient experience.

Comparison of patient and provider goals, expectations, and experiences following kidney transplantation.

OBJECTIVE: This study examined whether kidney transplant recipients' post-transplant goals and expectations align with those as perceived by their healthcare providers. METHODS: Post-transplant goals and expectations across four domains were assessed via a descriptive survey of healthcare providers (N=72) and kidney transplant recipients (N=476) at the University of Michigan from March 23 - October 1, 2015. Demographic and transplant-related data were collected via a retrospective review of medical records, and survey responses were compared using Chi-square tests, Wilcoxon two-sample tests, and logistic regression. RESULTS: Patients expressed higher quality of life (mean Neuro-QOL T-score 60.2 vs. 52.7), were less likely to report that they were currently experiencing complications (11% vs. 24%), and anticipated their transplants to last longer (median 25 vs. 15 years) and to live longer (median 80 vs. 71 years) than providers expected for their typical patient. However, provider perceptions of patients' future ability to feel well, perform daily activities and work were significantly higher than those expressed by patients (all p<0.05). CONCLUSION: Kidney transplant patient and provider expectations differ in significant ways. PRACTICE IMPLICATIONS: Identified areas of discordance may provide opportunities for patients and providers to better evaluate treatment option tradeoffs in post-transplant clinical interactions.

Development of data integration and visualization tools for the Department of Radiology to display operational and strategic metrics.

Visualizing process metrics can help identify targets for improvement initiatives. Dashboards and scorecards are tools to visualize important metrics in an easily interpretable manner. We describe the development of two visualization systems: a dashboard to provide real-time situational awareness to frontline coordinators, and a scorecard to display aggregate monthly performance metrics for strategic process improvement efforts. Both systems were designed by a multidisciplinary team of physicians, allied health staff, engineers and information technology specialists. We describe the process of defining important metrics, gathering and cleaning data, and designing the visualization interfaces. We also describe some improvement initiatives that stemmed. These systems were implemented in our hospital and improved the availability of data to our staff and leadership, making performance gaps visible and generating new targets for quality improvement projects.

Incorporating nurse absenteeism into staffing with demand uncertainty.

Increased nurse-to-patient ratios are associated negatively with increased costs and positively with improved patient care and reduced nurse burnout rates. Thus, it is critical from a cost, patient safety, and nurse satisfaction perspective that nurses be utilized efficiently and effectively. To address this, we propose a stochastic programming formulation for nurse staffing that accounts for variability in the patient census and nurse absenteeism, day-to-day correlations among the patient census levels, and costs associated with three different classes of nursing personnel: unit, pool, and temporary nurses. The decisions to be made include: how many unit nurses to employ, how large a pool of cross-trained nurses to maintain, how to allocate the pool nurses on a daily basis, and how many temporary nurses to utilize daily. A genetic algorithm is developed to solve the resulting model. Preliminary results using data from a large university hospital suggest that the proposed model can save a four-unit pool hundreds of thousands of dollars annually as opposed to the crude heuristics the hospital currently employs.