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Objectives Partial gland ablation (PGA) therapy is an emerging treatment modality that targets specific areas of biopsy-proven prostate cancer (PCa) to minimize treatment-related morbidity by sparing benign prostate. This qualitative study aims to explore and characterize perceptions and attitudes toward PGA in men with very-low-risk, low-risk, and favorable intermediate-risk PCa on active surveillance (AS).Design 92 men diagnosed with very-low-risk, low-risk, and favorable intermediate-risk PCa on AS were invited to participate in semistructured telephone interviews on PGA.Setting Single tertiary care center located in New York City.Participants 20 men with very-low-risk, low-risk, and favorable intermediate-risk PCa on AS participated in the interviews.Main outcome measures Emerging themes on perceptions and attitudes toward PGA were developed from transcripts inductively coded and analyzed under standardized methodology.Results Four themes were derived from 20 interviews that represent the primary considerations in treatment decision-making: (1) the feeling of psychological safety associated with low-risk disease; (2) preference for minimally invasive treatments; (3) the central role of the physician; (4) and the pursuit of treatment options that align with disease severity. Eleven men (55%) expressed interest in pursuing PGA only if their cancer were to progress, while nine men (45%) expressed interest at the current moment.Conclusions Although an emerging treatment modality, patients were broadly accepting of PGA for PCa, with men primarily debating the risks versus benefits of proactively treating low-risk disease. Additional research on men’s preferences and attitudes toward PGA will further guide counseling and shared decision-making for PGA.

OBJECTIVES/GOALS: Health care systems are complex, dynamic, and varied. Advances in artificial intelligence (AI) are enabling healthcare systems to use their own data to elicit patterns and design suitable interventions. To realize this potential, computer scientists and clinicians need an effective, practical, and replicable approach to collaboration METHODS/STUDY POPULATION: In this study, computer scientists partnered with clinicians to investigate predictors of avoidable emergency department use. The team sought an approach to computational medicine that could increase the relevance and impact of prediction to solve pressing problems in the health system. The team adopted an emergent architecture that engaged system leaders, computer scientists, data scientists, health services researchers, and practicing clinicians with deep ambulatory and inpatient knowledge to form the initial questions that shaped the prediction model; to understand nuances of coding and recording in source data and the implications for models; and to generate insights for promising points of intervention. The team recorded decisions and challenges as it progressed to analyze its function. RESULTS/ANTICIPATED RESULTS: Most avoidance models focus on a narrow time period around target events, or on high cost patients and events. This interdisciplinary team used their insights into the health system’s workflows and patient population to adopt a longitudinal approach to their prediction models. They used AI to build models of behavior in the system and consider prevention points across clinical units, time, and place. The holistic, systemwide focus enabled the team to generate insights that the system leaders and subsequently specific clinical units could apply to improve value and outcomes. A facilitated team process using learning system and cooperative network principles allowed a large and modular interdisciplinary team to build a transparent AI modeling process that yielded actionable insights into hypercomplex workflows. DISCUSSION/SIGNIFICANCE OF IMPACT: An architecture for involving diverse stakeholders in computational medicine projects can increase the relevance and impact of AI for solving care delivery problems in complex health systems. Translational science and computational medicine programs can foster this type of engagement and encourage a whole system perspective.

Compared with previous generations in the United States, men today are starting families later in life and having fewer children. As a result birthrates in the United States have dropped sharply, and some men never make the transition into parenthood. Using data from the 2006-2010 National Survey of Family Growth, this study examines the characteristics of childless men in the United States between the ages of 15 and 44 ( N = 6,168) and whether these men want to have a child sometime in the future. Our main finding is that the majority of childless men want a child someday; however, by the age of 45 more than 1 in 7 still remain childless.