Validation of administrative health data for the identification of endometriosis diagnosis.

Study Question: How do endometriosis diagnoses and subtypes reported in administrative health data compare with surgically confirmed disease?

Summary Answer: For endometriosis diagnosis, we observed substantial agreement and high sensitivity and specificity between administrative health data-International Classification of Diseases (ICD) 9 codes-and surgically confirmed diagnoses among participants who underwent gynecologic laparoscopy or laparotomy.

What Is Known Already: Several studies have assessed the validity of self-reported endometriosis in comparison to medical record reporting, finding strong confirmation. We previously reported high inter- and intra-surgeon agreement for endometriosis diagnosis in the Endometriosis, Natural History, Diagnosis, and Outcomes (ENDO) Study.

Rates of Concurrent Computed Tomography Imaging Following Ultrasound for Pediatric Patients With Appendicitis.

Introduction: Imaging guidelines recommend an ultrasound (US)-first approach to evaluate appendicitis to minimize radiation. However, the association between US and computed tomography (CT) utilization remains unclear. We aimed to determine how increased US utilization correlated with the rate of CT evaluation of pediatric acute appendicitis.

An explainable long short-term memory network for surgical site infection identification.

Background: Currently, surgical site infection surveillance relies on labor-intensive manual chart review. Recently suggested solutions involve machine learning to identify surgical site infections directly from the medical record. Deep learning is a form of machine learning that has historically performed better than traditional methods while being harder to interpret.