Prospective and early-career paleontologists deserve an accurate assessment of employment opportunities in their chosen field of study. Drawing on a wide range of sources, we have produced an admittedly incomplete analysis of the current status and recent trends of permanent academic employment in the discipline. Obtaining more complete longitudinal data on employment trends is a major difficulty; this is a challenge that needs to be addressed. The number of job seekers is far in excess of available positions. There has been a clear erosion in the number of academic paleontologists in the United States, a trend exacerbated in recent years. The decline, in constant dollars, of federal funding for paleontological research has potential strong negative impacts on future hiring. The loss of paleontology positions has also had a deleterious effect on our professional societies, which have seen a loss of regular (professional) membership, although student membership remains strong. These trends also potentially negatively impact efforts to diversify the field. Professional societies need to better coordinate their efforts to address these serious issues. Individual paleontologists also must become more effective advocates for the importance and relevance of our science.

Herbaceous perennials must annually rebuild the aboveground photosynthetic architecture from carbohydrates stored in crowns, rhizomes, and roots. Knowledge of carbohydrate utilization and storage can inform management decisions and improve control outcomes for invasive perennials. We monitored the nonstructural carbohydrates in a population of the hybrid Bohemian knotweed [Polygonum ×bohemicum (J. Chrtek & Chrtková) Zika & Jacobson [cuspidatum × sachalinense]; syn.: Fallopia ×bohemica (Chrtek and Chrtková) J.P. Bailey] and in Japanese knotweed [Polygonum cuspidatum Siebold & Zucc.; syn.: Fallopia japonica (Houtt.) Ronse Decr.]. Carbohydrate storage in crowns followed seasonal patterns typical of perennial herbaceous dicots corresponding to key phenological events. Starch was consistently the highest nonstructural carbohydrate present. Sucrose levels did not show a consistent inverse relationship with starch levels. Lateral distribution of starch in rhizomes and, more broadly, total nonstructural carbohydrates sampled before dormancy break showed higher levels in rhizomes compared with crowns. Total nonstructural carbohydrate levels in crowns reached seasonal lows at an estimated 22.6% of crown dry weight after accumulating 1,453.8 growing degree days (GDD) by the end of June, mainly due to depleted levels of stored starch, with the estimated minimum of 12.3% reached by 1,220.3 GDD accumulated by mid-June. Depletion corresponded to rapid development of vegetative canopy before entering the reproductive phase in August. Maximum starch accumulation in crowns followed complete senescence of aboveground tissues by mid- to late October. Removal of aboveground shoot biomass in late June to early July with removal of vegetation regrowth in early September before senescence would optimize the use of time and labor to deplete carbohydrate reserves. Additionally, foliar-applied systemic herbicide translocation to belowground tissue should be maximized with applications in late August through early fall to optimize downward translocation with assimilate movement to rebuild underground storage reserves. Fall applications should be made before loss of healthy leaf tissue, with the window for control typically ending by late September in Minnesota.

Objectives: People with dementia live with unmet needs due to dementia and other conditions. The EMBED-Care Framework is a co-designed app-delivered intervention involving holistic assessment, evidence-based decision- support tools and resources to support its use. Its intention is to empower people with dementia, family and practitioners to assess, monitor and manage needs. We aimed to explore the feasibility and acceptability of the EMBED-Care Framework and develop its underpinning programme theory.

Methods: A six-month single arm mixed-Methods feasibility and process evaluation, underpinned by an initial programme theory which was iteratively developed from previous studies. The settings were two community teams and two long term care facilities (LTCFs). People with dementia and family were recruited to receive the intervention for 12 weeks. Practitioners were recruited to deliver the intervention for six months. Quantitative data included candidate process and outcome measures. Qualitative data comprised interviews, focus groups and observations with people with dementia, family and practitioners. Qualitative and quantitative data were analysed separately and triangulated at the interpretation phase.

Results: Twenty-six people with dementia, 25 family members and 40 practitioners were recruited. Practitioners in both settings recognized the potential benefit for improving care and outcomes for people with dementia, and to themselves in supporting care provision. Family in both settings perceived a role in informing assessment and decisions about care. Family was integral to the intervention in community teams but had limited involvement in LTCFs. In both settings, embedding the intervention into routine care processes was essential to support its use. In community teams, this required aligning app functionality with care processes, establishing processes to monitor alerts, and clarifying team responsibilities. In LTCFs, duplication of care processes and limited time to integrate the intervention into routine care processes, affected its acceptability.

Conclusions: A theoretically informed co-designed digital intervention has potential to improve care processes and outcomes for people with dementia and family, and is acceptable to practitioners in community teams. Further work is required to strengthen the intervention in LTCFs to support integration into care processes and support family involvement. The programme theory detailing key mechanisms and likely outcomes of the EMBED-Care Framework is presented.

Efficient evidence generation to assess the clinical and economic impact of medical therapies is critical amid rising healthcare costs and aging populations. However, drug development and clinical trials remain far too expensive and inefficient for all stakeholders. On October 25–26, 2023, the Duke Clinical Research Institute brought together leaders from academia, industry, government agencies, patient advocacy, and nonprofit organizations to explore how different entities and influencers in drug development and healthcare can realign incentive structures to efficiently accelerate evidence generation that addresses the highest public health needs. Prominent themes surfaced, including competing research priorities and incentives, inadequate representation of patient population in clinical trials, opportunities to better leverage existing technology and infrastructure in trial design, and a need for heightened transparency and accountability in research practices. The group determined that together these elements contribute to an inefficient and costly clinical research enterprise, amplifying disparities in population health and sustaining gaps in evidence that impede advancements in equitable healthcare delivery and outcomes. The goal of addressing the identified challenges is to ultimately make clinical trials faster, more inclusive, and more efficient across diverse communities and settings.

Background: External comparisons of antimicrobial use (AU) may be more informative if adjusted for encounter characteristics. Optimal methods to define input variables for encounter-level risk-adjustment models of AU are not established. Methods: This retrospective analysis of electronic health record data included 50 US hospitals in 2020-2021. We used NHSN definitions for all antibacterials days of therapy (DOT), including adult and pediatric encounters with at least 1 day present in inpatient locations. We assessed 4 methods to define input variables: 1) diagnosis-related group (DRG) categories by Yu et al., 2) adjudicated Elixhauser comorbidity categories by Goodman et al., 3) all Clinical Classification Software Refined (CCSR) diagnosis and procedure categories, and 4) adjudicated CCSR categories where codes not appropriate for AU risk-adjustment were excluded by expert consensus, requiring review of 867 codes over 4 months to attain consensus. Data were split randomly, stratified by bed size as follows: 1) training dataset including two-thirds of encounters among two-thirds of hospitals; 2) internal testing set including one-third of encounters within training hospitals, and 3) external testing set including the remaining one-third of hospitals. We used a gradient-boosted machine (GBM) tree-based model and two-staged approach to first identify encounters with zero DOT, then estimate DOT among those with >0.5 probability of receiving antibiotics. Accuracy was assessed using mean absolute error (MAE) in testing datasets. Correlation plots compared model estimates and observed DOT among testing datasets. The top 20 most influential variables were defined using modeled variable importance. Results: Our datasets included 629,445 training, 314,971 internal testing, and 419,109 external testing encounters. Demographic data included 41% male, 59% non-Hispanic White, 25% non-Hispanic Black, 9% Hispanic, and 5% pediatric encounters. DRG was missing in 29% of encounters. MAE was lower in pediatrics as compared to adults, and lowest for models incorporating CCSR inputs (Figure 1). Performance in internal and external testing was similar, though Goodman/Elixhauser variable strategies were less accurate in external testing and underestimated long DOT outliers (Figure 2). Agnostic and adjudicated CCSR model estimates were highly correlated; their influential variables lists were similar (Figure 3). Conclusion: Larger numbers of CCSR diagnosis and procedure inputs improved risk-adjustment model accuracy compared with prior strategies. Variable importance and accuracy were similar for agnostic and adjudicated approaches. However, maintaining adjudications by experts would require significant time and potentially introduce personal bias. If findings are confirmed, the need for expert adjudication of input variables should be reconsidered.

Disclosure: Elizabeth Dodds Ashley: Advisor- HealthTrackRx. David J Weber: Consultant on vaccines: Pfizer; DSMB chair: GSK; Consultant on disinfection: BD, GAMA, PDI, Germitec

Background: Interventions targeting urine culture stewardship can improve diagnostic accuracy for urinary tract infections (UTI) and decrease inappropriate antibiotic treatment of asymptomatic bacteriuria. We aimed to determine if a clinical decision support (CDS) tool which provided guidance on and required documentation of the indications would decrease inappropriately ordered urine cultures in an academic healthcare network that already uses conditional (e.g. reflex) urine testing. Methods: In October 2022, four hospitals within one academic healthcare network transitioned to a new electronic health record (EHR). We developed an embedded CDS tool that provided guidance on ordering either a urinalysis (UA) with reflex to urine culture or a non-reflex urine culture (e.g. for pregnant patients) based on the indication for testing (Figure 1). We compared median monthly UA with reflex culture and non-reflex urine culture order rates pre- (8/2017–9/2022) and post- (10/2022–9/2023) intervention using the Wilcoxon rank-sum test. We used interrupted time-series analyses allowing a one-month time window for the intervention effect to assess changes in monthly UA with reflex culture, non-reflex urine culture, and total urine culture order rates associated with the intervention. Using SAS 9.4, we generated Durbin-Watson statistics to assess for autocorrelation and adjusted for this using a stepwise autoregressive model. Result: The median monthly UA with reflex culture order rates per 1000 patient-days were similar pre- and post- intervention at 36.7 (interquartile range [IQR]: 31.0–39.7) and 35.4 (IQR: 32.8–37.0), respectively (Figure 2). Non-reflex and total urine culture rates per 1000 patient-days decreased from 8.5 (IQR: 8.1–9.1) to 4.9 (IQR: 4.7–5.1) and from 20.0 (IQR: 18.9–20.7) to 14.4 (IQR: 14.0–14.6) post-intervention, respectively. Interrupted time-series analyses revealed that the intervention was associated with a decrease in the monthly non-reflex urine culture by 4.8 cultures/1000 patient-days (p< 0.001) and in the total urine culture monthly order rates by 5.0 cultures/ 1000 patient-days (p < 0 .001) [Figures 3a and b]. The UA with reflex order rate did not significantly change with the intervention (not pictured). Conclusion: In an academic healthcare network that already employed conditional urine testing, the implementation of an EHR-based diagnostic stewardship tool led to additional decreases in both non-reflex and total urine cultures ordered.

OBJECTIVES/GOALS: Identify causes for clinical research professional turnover Define data collection methods for exit interviews Provide institutions with resources to collect and analyze exit interviews Employ strategies to maximize the impact of exit interviews on retention METHODS/STUDY POPULATION: The Clinical Research Professional Taskforce (CRPT) exit interview Subgroup has met monthly since January 2023. Action items were agreed to and minutes were kept and reviewed at subsequent virtual working meetings. All members were given opportunity to speak and contribute. After a landscape analysis, conducted via survey, five institutions agreed to provide examples of their exit interview questions. Members spoke at length about goals, methods, collection techniques, institutional involvement, lessons learned and practical applications that could become best practices. RESULTS/ANTICIPATED RESULTS: The Subgroup aggregated all questions into categories and developed sample questions incorporating all data without using any word for word. In order to allow for quantitative assessment and standardized reporting the Subgroup formulated questions to be responded to utilizing a Likert scale with free text fields for select questions where further information is needed. The Subgroup developed best practices describing decision-making metrics, understanding reasons for turnover and reporting data back to leadership. Practical aspects such as method and time of survey collection, anonymity, and training staff are also included. DISCUSSION/SIGNIFICANCE: We are hopeful that sample questions and best practices will be helpful and widely utilized. Understanding the causes and impacts of CRP turnover are critical to meeting the current needs of clinical research. Further work is being done to calculate the cost of turnover to make the business case.

State Medical Boards (SMBs) can take severe disciplinary actions (e.g., license revocation or suspension) against physicians who commit egregious wrongdoing in order to protect the public. However, there is noteworthy variability in the extent to which SMBs impose severe disciplinary action. In this manuscript, we present and synthesize a subset of 11 recommendations based on findings from our team’s larger consensus-building project that identified a list of 56 policies and legal provisions SMBs can use to better protect patients from egregious wrongdoing by physicians.