Cracking the code: an integrated electronic medical record approach to early diagnosis of genetic kidney disease in children with microscopic haematuria.

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Tác giả: Gráinne Butler, Jim Buttery, Yoni Elbaum, Joshua Kausman, Catherine Quinlan, Saravanan Satkumaran, Ahuva Segal, Josiah Shanks, Ella Wilkins

Ngôn ngữ: eng

Ký hiệu phân loại: 636.0885 Animal husbandry

Thông tin xuất bản: Germany : Pediatric nephrology (Berlin, Germany) , 2025

Mô tả vật lý:

Bộ sưu tập: NCBI

ID: 58519

BACKGROUND: Microscopic haematuria (MH) is a common incidental finding in childhood that typically resolves spontaneously but, if persistent, can be a sign of underlying genetic kidney disease. Best practice indicates that all MH samples should be followed up to ensure resolution. Repeat sampling often does not occur, and an opportunity to diagnose and manage genetic kidney disease is missed, with substantial resultant preventable morbidity. The quality gap between recommended follow-up and actual practice represented an opportunity to improve care. METHODS: A retrospective audit of the electronic medical record (EMR) was carried out to identify patients with documented MH but in whom follow-up results within the reference range were lacking. Digital tools were used to link bulk communication functions within the EMR. Families were contacted and offered repeat testing. Persistent findings of MH were referred to the Kidney Genomics Clinic (KGC). RESULTS: There were 1,335 children/families contacted. The overall response rate was 21%. Two hundred sixty-two children had normal repeat urinalysis. There were 16 children with MH. Fifteen underwent genomic testing. Five children were diagnosed with Alport syndrome (AS), and subsequently, two family members were. CONCLUSIONS: It is feasible to support the early diagnosis of genetic kidney disease using digital health tools. The lack of true interoperability within healthcare systems remains a barrier. This issue prevented the solution from being fully digital and created a manual element of follow-up. Prospective digital solutions are being explored to improve follow-up rates of incidental findings of MH and facilitate early diagnosis of genetic kidney disease.
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