Background: Ventilator associated pneumonia (VAP) is associated with significant rates of morbidity and all-cause mortality. Active VAP surveillance can identify risk factors for which targeted preventive measures can be implemented. However, surveillance efforts are complicated by challenges associated with accurate VAP diagnosis. We aimed to improve the accuracy and automation of existing VAP diagnostic algorithms to better identify patients at risk. Methods: The study was conducted at NYU Langone Health from June 2022 through December 2023. We created a semi-automated VAP surveillance system using the Centers for Disease Control & Prevention (CDC) ventilator associated event (VAE) definition as a base framework (Figure 1). We modified this definition to include additional elements, such as having a sputum culture ordered within 48 hours of worsening oxygen status, regardless of culture result. Using this algorithm—followed by manual clinician reviews—we retrospectively assessed possible VAP cases to determine the ability of our surveillance system to correctly identify VAP. Results: Of the 123 possible VAP cases identified through our automated system, 75 (61%) were correctly diagnosed as VAP after clinical review. This reflects a rate of 1.5 infections per 1000 ventilation days across the system and 1.85 infections per 100 patients ventilated for greater than 2 days. Of the 48 remaining patients without VAP after clinical review, 25% (n=12) were characterized as having hospital-acquired pneumonia, 21% (n=10) as acute respiratory distress syndrome or infection at another site and 10% (n=5) as pulmonary embolism/infarction. Among all patients identified through this automated system (VAP and non-VAP), 53% experienced in-hospital death. Discussion: Our automated VAP surveillance algorithm identified 123 cases of potential VAP, 61% of which were consistent with a clinical diagnosis of VAP upon manual chart review. Our VAP rate of 1.5 infections per 1000 ventilation days was similar to published rates at other North American hospital systems. The high in-hospital mortality rate among these patients highlights the need for improved surveillance systems and earlier interventions to reduce the risk of VAP. There are several limitations to the CDC’s VAE definition, including its requirement of a positive microbiologic culture and focus on sputum quality. This potentially misses cases of culture-negative VAP in patients receiving antibiotics prior to sputum collection. Our goal is to continue to validate and improve our algorithm’s ability to correctly identify patients with clinical VAP, so that targeted prevention efforts can be focused upon the patients with the highest risk for poor outcomes.

Disclosure: Madeline DiLorenzo: Stocks - Abbvie, Amgen Inc., Becton Dickinson, Biogen Inc., Bristol Myers and Squibb, CVS Health, Davita Inc., Elevance Health, Gilead, Henry Schein, Hologic Inc., Humana Inc., Jazz Pharmaceuticals, Laboratory Corp, Merck and Co., Quest Diagnostics, ResMed Inc., Teladoc Health, Vertex Pharmaceuticals, West Pharmaceuticals

Recruiting a large number of ground workers is crucial for running effective modern election campaigns. It is unclear if party leaders can influence the quality and quantity of the unpaid rank-and-file workforce as they can with prized nominations for candidates. We analyze a field experiment conducted by an Indian party that randomized recruitment messages reaching 1% of a 13-million-person electorate to join its rank and file. Contrary to concerns that parties can only attract a few poor-quality volunteers, we show that elite efforts can shape the rank and file. In fact, specific strategies can increase the size, enhance the gender and ethnic diversity, and broaden the education and political skills of recruits. Strategies that signal gender inclusiveness have a lasting impact on some dimensions up to 3 years later. Taken together, this article provides the first causal evidence that rank-and-file recruitment is an opportunity for elites to influence long-term party development.

OBJECTIVES/GOALS: Clinical and Translational Science Award (CTSA) hubs are launching D&I Science cores to provide resources and services to promote the translation of clinical evidence into practice. We developed a D&I Science Core strategic plan reflecting our research community’s needs by assessing Implementation Science (IS) competencies. METHODS/STUDY POPULATION: The Tufts CTSI D&I Science Core was launched in early 2023. To design services that meet research community needs, we conducted a survey and key informant interviews based on Padek etal.’s list of Implementation Science (IS) competencies. The competencies are organized into four domains (Definition, Background, and Rationale; Theory and Approaches; Design & Analysis; and Practice-Based Considerations) and categorized by expertise level (beginner, intermediate, advanced). Participants who had attended or expressed interest in a D&I interest group were asked via an email survey to rate their level of confidence in completing selected IS-related research activities, about their experience with IS research or practice, and the types of resources, services and training they desired. RESULTS/ANTICIPATED RESULTS: Twenty researchers (20/65, 31%) submitted survey responses and six researchers participated in in-depth interviews. Survey respondents felt most confident in engaging stakeholders in IS research and least confident selecting a model or framework for a study. Results suggest that researcher capacity building is needed to: • Understand IS models and frameworks and their approaches, strengths, and limitations • Select and use models and frameworks in studies • Assemble IS teams and prepare grant proposals Suggestions for resources, services, and training, include: • Customized education to address diverse needs, knowledge levels, and learning styles • Promotion of D&I Core consultations and grant support services • Sharing of successful proposals to help researchers learn how to apply IS methods DISCUSSION/SIGNIFICANCE: A strategic workplan for the D&I Science Core was developed and implemented to address the findings. Initial emphasis is on developing easily accessible resources and timely consultations for investigators new to IS needing to apply these methods in current grant proposals, while also providing training resources for deeper skill building.