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Frontiers in Health Services· 2026Q1

Sanal Uygulama Topluluğu, Uzun COVID Tedavisinde Klinisyen Becerilerini Artırıyor

Effectiveness of an Extension for Community Health Outcomes case-based virtual community of practice model on clinician outcomes for the management of long COVID and fatiguing illnesses: a randomized control trial

Alexandra Zuber, Jonathan Rothwell, Jane C. Samaniego, Sydney Sharp ve diğerleri

Kısa özet

Sanal bir uygulama topluluğu modeli (ECHO), klinisyenlerin Uzun COVID ve ilgili hastalıkları yönetme konusundaki bilgilerini (%0.77) ve güvenlerini (%0.48) önemli ölçüde artırdı ve ayrıca uzman sevklerini %44 oranında (b=-0.44) azalttı.

Yapay zekâ ile başlık ve abstract'tan üretildi; tam metin okunmaz.

Ana noktalar

  • ECHO sanal uygulama topluluğu modeli, Uzun COVID ve ilgili durumları yönetmede klinisyenlerin bilgisini 0.77 ve güvenini 0.48 oranında iyileştirdi.
  • Müdahale grubundaki klinisyenler, hasta başına uzman sevklerini %44 (b=-0.44) azalttı.
  • Sanal oturumlara katılım, bilgi, güven ve uygulama değişikliklerinin önemli bir göstergesiydi.
  • Model, ziyaret süresini veya hasta yükünü önemli ölçüde değiştirmedi.

Yapay zekâ ile başlık ve abstract'tan üretildi; tam metin okunmaz.

Özet (abstract)

Introduction Patients with Long COVID and other infection-associated chronic conditions (IACC) often face barriers to accessing specialist care, prompting the need to strengthen primary care capacity to manage these complex conditions. Our study evaluated the effectiveness of an ECHO case-based virtual community of practice model for improving clinician knowledge, confidence, and practice for Long COVID and other IACC in a randomized controlled trial (RCT) [Clinicaltrials.gov (NCT05167227)]. Methods The study was a two-arm, single-blind, cluster RCT; intervention clinicians were invited to participate in weekly case-based, interactive, expert-led virtual learning sessions focused on patient care for individuals with Long COVID and other IACC. Intervention and control groups were also invited to monthly interactive webinars and quarterly short courses. Virtual learning occurred on Zoom videoconferencing software. Data were collected from routine clinician surveys, participation records, and electronic health records. The analysis identified treatment effects using generalized linear models predicting scaled scores for knowledge, changes to practice, and confidence in the management of patients with Long COVID and other IACC. Results Adjusting for baseline controls, the intervention group achieved significantly higher levels of knowledge (standardized beta coefficient: b = 0.77, 95% CI 0.20 to 1.33) and confidence (b = 0.48, 95% CI 0.09 to 0.88), but not changes to practice (b = 0.52, 95% CI -0.08 to 1.12). The number of sessions attended significantly predicted all three outcomes. As hypothesized, these improvements coincided with a reduction in specialist referrals by intervention group clinicians, per patient assigned to them (b = −0.44, 95% CI −0.62 to -.26), with no significant difference in visit duration or patient load. Discussion Our findings provide randomized trial evidence that the ECHO case-based virtual community of practice model can generate improvements to clinician knowledge and confidence in the care of patients with IACC and decreased reliance on specialist referrals. This offers a promising strategy for strengthening primary care capacity to address these complex conditions. Clinical Trial Registration Clinicaltrials.gov, identifier NCT05167227.

Yazarların özeti; kaynağından alınmıştır. Frontiers in Health Services, 2026 · DOI ↗

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