Using human factors principles to redesign a 3D lab workflow during the COVID-19 pandemic.

BACKGROUND: Like most hospitals, our hospital experienced COVID-19 pandemic-related supply chain shortages. Our additive manufacturing lab's capacity to offset these shortages was soon overwhelmed, leading to a need to improve the efficiency of our existing workflow. We undertook a work system analysis guided by the Systems Engineering Initiative for Patient Safety (SEIPS) construct which is based on human factors and quality improvement principles. Our objective was to understand the inefficiencies in project submission, review, and acceptance decisions, and make systematic improvements to optimize lab operations. METHODS: Contextual inquiry (interviews and workflow analysis) revealed suboptimal characteristics of the system, specifically, reliance on a single person to facilitate work and, at times, fractured communication with project sponsors, with root causes related to the project intake and evaluation process as identified through SEIPS tools. As interventions, the analysis led us to: 1) enhance an existing but underused project submission form, 2) design and implement an internal project scorecard to standardize evaluation of requests, and 3) distribute the responsibility of submission evaluation across lab members. We implemented these interventions in May 2021 for new projects and compare them to our baseline February 1, 2018 through - April 30, 2021 performance (1184 days). RESULTS: All project requests were submitted using the enhanced project submission form and all received a standardized evaluation with the project scorecard. Prior to interventions, we completed 35/79 (44%) of projects, compared to 12/20 (60%) of projects after interventions were implemented. Time to review new submissions was reduced from an average of 58 days to 4 days. A more distributed team responsibility structure permitted improved workflow with no increase in staffing, allowing the Lab Manager to devote more time to engineering rather than administrative/decision tasks. CONCLUSIONS: By optimizing our workflows utilizing a human factors approach, we improved the work system of our additive manufacturing lab to be responsive to the urgent needs of the pandemic. The current workflow provides insights for labs aiming to meet the growing demand for point-of-care manufacturing.

Novel use of a virtual driving assessment to classify driver skill at the time of licensure.

Motor vehicle crash rates are highest immediately after licensure, and driver error is one of the leading causes. Yet, few studies have quantified driving skills at the time of licensure, making it difficult to identify at-risk drivers before independent driving. Using data from a virtual driving assessment implemented into the licensing workflow in Ohio, this study presents the first population-level study classifying degree of skill at the time of licensure and validating these against a measure of on-road performance: license exam outcomes. Principal component and cluster analysis of 33,249 virtual driving assessments identified 20 Skill Clusters that were then grouped into 4 major summary "Driving Classes"; i) No Issues (i.e. careful and skilled drivers); ii) Minor Issues (i.e. an average new driver with minor vehicle control skill deficits); iii) Major Issues (i.e. drivers with more control issues and who take more risks); and iv) Major Issues with Aggression (i.e. drivers with even more control issues and more reckless and risk-taking behavior). Category labels were determined based on patterns of VDA skill deficits alone (i.e. agnostic of the license examination outcome). These Skill Clusters and Driving Classes had different distributions by sex and age, reflecting age-related licensing policies (i.e. those under 18 and subject to GDL and driver education and training), and were differentially associated with subsequent performance on the on-road licensing examination (showing criterion validity). The No Issues and Minor Issues classes had lower than average odds of failing, and the other two more problematic Driving Classes had higher odds of failing. Thus, this study showed that license applicants can be classified based on their driving skills at the time of licensure. Future studies will validate these Skill Cluster classes in relation to their prediction of post-licensure crash outcomes.

Licensing Examination and Crash Outcomes Postlicensure in Young Drivers.

Importance: Despite US graduated driver licensing laws, young novice driver crash rates remain high. Study findings suggest comprehensive license policy that mandates driver education including behind-the-wheel (BTW) training may reduce crashes postlicensure. However, only 15 states mandate BTW training. Objective: To identify differences in licensing and crash outcomes for drivers younger than 18 years who are subject to comprehensive licensing requirements (graduated driver licensing, driver education, and BTW training) vs those aged 18 to 24 years who are exempt from these requirements. Design, Setting, and Participants: This prospective, population-based cohort study used Ohio licensing data to define a cohort of 2018 license applicants (age 16-24 years, n = 136 643) and tracked licensed driver (n = 129 897) crash outcomes up to 12 months postlicensure. The study was conducted from January 1, 2018, to December 31, 2019, and data analysis was performed from October 7, 2019, to February 11, 2022. Main Outcomes and Measures: Licensing examination performance and population-based, police-reported crash rates in the first 2 months and 12 months postlicensure across age groups, sex, and census tract-level sociodemographic variables were measured. Poisson regression models compared newly licensed driver crash rates, with reference to individuals licensed at 18 years, while controlling for census tract-level sociodemographic factors, time spent in the learner permit period, and licensing examination performance measures. Results: Of 136 643 novice drivers, 69 488 (50.9%) were male and 67 152 (49.1%) were female. Mean (SD) age at enrollment (age at first on-road examination) was 17.7 (2.1) years. License applicants aged 16 and 17 years performed best on license examinations (15 466 [21.6%] and 5112 [30.9%] failing vs 7981 [37.5%] of applicants aged 18 years). Drivers licensed at 18 years had the highest crash rates of all those younger than 25 years. Compared with drivers licensed at 18 years, crash rates were 27% lower in individuals aged 16 years and 14% lower in those aged 17 years during the first 2 months postlicensure when controlling for socioeconomic status, time spent in learner permit status, and license examination performance measures (adjusted relative risk [aRR] at age 16 years: 0.73; 95% CI, 0.67-0.80; age 17 years: aRR, 0.86; 95% CI, 0.77-0.96). At 12 months postlicensure, crash rates were 19% lower for individuals licensed at age 16 years (aRR, 0.81; 95%, CI, 0.77-0.85) and 6% lower at age 17 years (aRR, 0.94; 95% CI, 0.89-0.99) compared with individuals aged 18 years. Conclusions and Relevance: In Ohio, drivers younger than 18 years who are subject to graduated driver licensing and driver education, including BTW training requirements, had lower crash rates in the first year postlicensure compared with those aged 18 years, with controls applied. These findings suggest that it may be fruitful for future work to reconsider the value of mandated driver license policies, including BTW training, and to examine reasons for delayed licensure and barriers to accessing training.

Why do breast cancer survivors decline a couple-based intimacy enhancement intervention trial?

Recruitment challenges hinder behavioral intervention research in cancer survivors. The purpose was to examine the reasons for declining and intervention preferences of study-eligible breast cancer survivors declining a trial of a four-session couple-based Intimacy Enhancement intervention (refusers) and explore whether refusers differed from participants on key characteristics. Partnered, post-treatment breast cancer survivors reporting sexual concerns who were eligible for but declined participation in the intervention trial were approached to complete a standardized 5-min telephone survey assessing reasons for declining and support preferences. Demographic, clinical, and sexual concerns information were collected during screening. Trial participants and refusers were compared on key variables of age, race, hormone therapy use, time since treatment, level of sexual concerns, and recruitment method using t-tests or chi-square tests. Among the 31 women who declined the trial and completed the survey, the most common reasons for declining were time commitment (74%) and partner noninterest (32%). Most (61%) reported that the telephone format played little to no role in their refusal. Eighty-one percent wanted their partners involved in a program addressing sexual concerns. The two most preferred resources were informational websites (45%) and meeting with a professional (26%). Trial participants and refusers did not differ on any key factors examined. Developing intimacy interventions that are very brief, partner-optional, or that use stepped care may bolster uptake. The methods used to examine study-eligible candidates' needs and preferences could be employed in other health populations, thus having broader implications for research design.