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Acute Limb Ischemia (ALI) is a morbid and deadly diagnosis. However, existing epidemiologic studies describing ALI predate the introduction of the Affordable Care Act in 2010 and direct oral anticoagulants in 2011. Thus, we synergized the National Inpatient Sample (NIS) and United States (U.S.) Census to define contemporary trends in the incidence, treatment, and outcomes of ALI in the US.

In a real-world implementation of a machine-learning (ML)-based sepsis early warning system (EWS), Adams et al.1,2found that timely provider response to an alert was associated with improved mortality, highlighting the potential utility of these systems in patient care.

IMPORTANCE: A cornerstone of precision medicine is the identification and use of biomarkers that help subtype patients for targeted treatment. Such an approach requires the development and subsequent interrogation of large-scale biobanks linked to well-annotated clinical data. Traditional means of creating these data-linked biobanks are costly and lengthy, especially in acute conditions that require time-sensitive clinical data and biospecimens. OBJECTIVES: To develop a virtually enabled biorepository and electronic health record (EHR)–embedded, scalable cohort for precision medicine (VESPRE) and compare the feasibility, enrollment, and costs of VESPRE with those of a traditional study design in acute care. DESIGN, SETTING, AND PARTICIPANTS: In a prospective cohort study, the EHR-embedded screening alert was generated for 3428 patients, and 2199 patients (64%) were eligible and screened. Of these, 1027 patients (30%) were enrolled. VESPRE was developed for regulatory compliance, feasibility, internal validity, and cost in a prospective cohort of 1027 patients (aged =18 years) with sepsis-3 within 6 hours of presentation to the emergency department. The VESPRE infrastructure included (1) automated EHR screening, (2) remnant blood collection for creation of a virtually enabled biorepository, and (3) automated clinical data abstraction. The study was conducted at an academic institution in southwestern Pennsylvania from October 17, 2017, to June 6, 2019. MAIN OUTCOMES AND MEASURES: Regulatory compliance, enrollment, internal validity of automated screening, biorepository acquisition, and costs. RESULTS: Of the 1027 patients enrolled in the study, 549 were included in the proof-of-concept analysis (305 [56%] men); median (SD) age was 59 (17) years. VESPRE collected 12?963 remnant blood and urine samples and demonstrated adequate feasibility for clinical, biomarker, and microbiome analyses. Over the 20-month test, the total cost beyond the existing operations infrastructure was $39?417.50 ($14?880.00 project management, $22?717.50 laboratory supplies/staff, and $1820.00 data management)—approximately $39 per enrolled patient vs $239 per patient for a traditional cohort study. CONCLUSIONS AND RELEVANCE: Results of this study suggest that, in a large US health system that collects data using a common EHR platform and centralized laboratory system, VESPRE, a large-scale, inexpensive EHR-embedded infrastructure for precision medicine can be used. Tested in the sepsis setting, VESPRE appeared to capture a high proportion of eligible patients at low incremental cost.