2023 ACMG Annual Clinical Genetics Meeting Digital Edition: Poster Gallery-Reducing Delays of Dextrose Administration in Patients in Acute Metabolic Crisis

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The authors of this document discuss the challenge of identifying specific patient cohorts in the electronic health record (EHR) for continuous quality improvement. They focus specifically on patients with inborn errors of metabolism (IEM), where immediate management is crucial during acute decompensation. The authors mention that modern EHRs use more specific diagnoses beyond just ICD10 codes, which is important for identifying rare diseases like metabolic disorders.<br /><br />The authors describe their patient identification method, which involved using specific problem list diagnoses in the EHR. By cross-validating these diagnoses, they were able to identify over 400 patients with inborn errors of metabolism seen by metabolic providers. <br /><br />To speed up care delivery for these patients, the authors utilized Clinical Decision Support (CDS) and consulted with the UNC Health Pharmacy Analytics and Outcomes team to develop a query of their EHR. They found that using the patient's problem list was the best method for identifying IEM patients. They also performed a manual chart review to resolve any discrepancies.<br /><br />To track quality metrics in this patient population, the authors created a "Metabolism Patient Care Dashboard." This dashboard provided an up-to-date patient list with medical record numbers, hospital admissions, dates of care, and metabolism quality of care metrics such as time-to-dextrose, time-to-first ammonia, and length of stay.<br /><br />In conclusion, the authors successfully identified over 400 patients with inborn errors of metabolism using specific problem list diagnoses in the EHR. They used this information to develop a dashboard that tracks important quality metrics for these patients. By streamlining the identification process and implementing CDS, the authors aim to reduce delays in care and improve outcomes for patients with metabolic disorders.<br /><br />References:<br />1. Adams et al. Quality of care metrics for patients with inborn errors of metabolism. Mol Genet Metab. 2022 May;136(1):1-3.<br />2. Prietsch V, Lindner M, Zschocke J, Nyhan WL, Hoffmann GF. Emergency management of inherited metabolic diseases. J Inherit Metab Dis. 2002 Nov;25(7):531-46.

Asset Subtitle

Presenting Author - Monika Williams, MD; Co-Author - Michael C. Adams, MD; Co-Author - Evan W. Colmenares, PharmD;

Meta Tag

Biochemical genetics

Databases

Metabolic Disorder

Co-Author Michael C. Adams, MD

Co-Author Evan W. Colmenares, PharmD

Presenting Author Monika Williams, MD

Keywords

electronic health record

patient cohorts

inborn errors of metabolism

specific problem list diagnoses

metabolic disorders

Clinical Decision Support

Metabolism Patient Care Dashboard

quality metrics

care delivery

streamlining