Impact of Anatomic Site, Specimen Collection Timing, and Patient Symptom Status on Neisseria gonorrhoeae Culture Recovery.

BACKGROUND: Neisseria gonorrhoeae culture is required for antimicrobial susceptibility testing, but recovering isolates from clinical specimens is challenging. Although many variables influence culture recovery, studies evaluating the impact of culture specimen collection timing and patient symptom status are limited. This study analyzed urogenital and extragenital culture recovery data from Centers for Disease Control and Prevention's Strengthening the US Response to Resistant Gonorrhea (SURRG) program, a multisite project, which enhances local N. gonorrhoeae culture and antimicrobial susceptibility testing capacity. METHODS: Eight SURRG jurisdictions collected gonococcal cultures from patients with N. gonorrhoeae-positive nucleic acid amplification test (NAAT) results attending sexually transmitted disease and community clinics. Matched NAAT and culture specimens from the same anatomic site were collected, and culture recovery was assessed. Time between NAAT and culture specimen collection was categorized as same day, 1 to 7 days, 8 to 14 days, or ≥15 days, and patient symptoms were matched to the anatomic site where culture specimens were collected. RESULTS: From 2018 to 2019, among persons with N. gonorrhoeae-positive NAAT, urethral infections resulted in the highest culture recovery (5927 of 6515 [91.0%]), followed by endocervical (222 of 363 [61.2%]), vaginal (63 of 133 [47.4%]), rectal (1117 of 2805 [39.8%]), and pharyngeal (1019 of 3678 [27.7%]) infections. Culture recovery was highest when specimens were collected on the same day as NAAT specimens and significantly decreased after 7 days. Symptoms were significantly associated with culture recovery at urethral (P = <0.0001) and rectal (P = <0.0001) sites of infection but not endocervical, vaginal, or pharyngeal sites. CONCLUSIONS: Culture specimen collection timing and patient symptomatic status can impact culture recovery. These findings can guide decisions about culture collection protocols to maximize culture recovery and strengthen detection of antimicrobial-resistant infections.

Digital supervision in the clinical learning environment: Characterizing teamwork in the electronic health record.

BACKGROUND: Attending physicians in academic hospitals work in supervisory team structures with medical residents to provide patient care. How attendings utilize the electronic health record (EHR) to support learning through supervision is not well understood. OBJECTIVE: To compare EHR behavior on teaching versus direct care, including evidence of supervisory calibration to learners. METHODS: Cross-sectional study analysis of EHR metadata from 1721 shifts of hospital medicine faculty at a large, urban academic medical center, January to June 2022. Measures included total EHR time per shift, EHR time outside shift, and time spent on: note-writing, note review/attestation, order entry, and other clinical review. We assessed within physician differences across these service types and used multilevel modeling to determine whether these behaviors varied with resident physicians' experience, accounting for physician-specific signature behavior patterns. RESULTS: Attendings spent substantially less time in the EHR while on teaching service than on direct service (129 vs. 240 min; p < .001) and apportioned their work differently throughout the day. Physicians were less behaviorally consistent and varied more than their peers when on teaching service. Attendings calibrated their supervision to learners. Attendings logged 12.7% less EHR time when paired with more senior residents than postgraduate year 2 (PGY2) residents (137 vs. 120 min, p = .002). PGY1 presence was also associated with reduced EHR time, suggesting some delegation of supervision to senior trainees. CONCLUSION: EHR behaviors on teaching service are highly variable and differ substantially from direct care; a lack of consistency suggests important opportunities to establish best practices for EHR-based supervision and create an effective clinical learning environment.