Development and Validation of a Machine Learning Model for Early Detection of Untreated Infection.

Background: Early diagnostic uncertainty for infection causes delays in antibiotic administration in infected patients and unnecessary antibiotic administration in noninfected patients.

Objective: To develop a machine learning model for the early detection of untreated infection (eDENTIFI), with the presence of infection determined by clinician chart review.

Derivation Cohort: Three thousand three hundred fifty-seven adult patients hospitalized between 2006 and 2018 at two health systems in Illinois, United States.

Identifying infected patients using semi-supervised and transfer learning.

Objectives: Early identification of infection improves outcomes, but developing models for early identification requires determining infection status with manual chart review, limiting sample size. Therefore, we aimed to compare semi-supervised and transfer learning algorithms with algorithms based solely on manual chart review for identifying infection in hospitalized patients.

Materials And Methods: This multicenter retrospective study of admissions to 6 hospitals included "gold-standard" labels of infection from manual chart review and "silver-standard" labels from nonchart-reviewed patients using the Sepsis-3 infection criteria based on antibiotic and culture orders.

Determining the Electronic Signature of Infection in Electronic Health Record Data.

Objectives: Recent sepsis studies have defined patients as "infected" using a combination of culture and antibiotic orders rather than billing data. However, the accuracy of these definitions is unclear. We aimed to compare the accuracy of different established criteria for identifying infected patients using detailed chart review.

Association of a New Trauma Center With Racial, Ethnic, and Socioeconomic Disparities in Access to Trauma Care.

This observational study assesses the association of a new trauma center with transport times for trauma patients as a measure of prompt access to care and specifically examines changes in racial, ethnic, and income disparities in transport times.

Development of International Outcomes Instrument for Hand and Upper Extremity Burn Scar Contracture Release.

Burn scar contractures remain a common source of severe disability in resource-limited countries. However, existing outcome measurements are unable to fully capture the impact of the scar contracture and surgical attempts at correction. To that end, we have developed a new outcome instrument, the Stanford-ReSurge Burn Scar Contracture Scale-Upper Extremity that can be used as a measurement of disability and reconstructive procedure outcomes.