Quality of care metrics for patients with inborn errors of metabolism

Michael C Adams; Elizabeth R Jalazo; Clara C Hildebrandt; Jenny Wong; Stephanie J Mascaro-Deen; Jonathan S Berg

doi:10.1016/j.ymgme.2022.03.005

Quality of care metrics for patients with inborn errors of metabolism

Mol Genet Metab. 2022 May;136(1):1-3. doi: 10.1016/j.ymgme.2022.03.005. Epub 2022 Mar 15.

Authors

Michael C Adams¹, Elizabeth R Jalazo², Clara C Hildebrandt², Jenny Wong³, Stephanie J Mascaro-Deen³, Jonathan S Berg⁴

Affiliations

¹ Department of Pediatrics, Division of Pediatric Genetics and Metabolism, The University of North Carolina at Chapel Hill School of Medicine, Chapel Hill, NC 27599, USA. Electronic address: michael.adams2@unchealth.unc.edu.
² Department of Pediatrics, Division of Pediatric Genetics and Metabolism, The University of North Carolina at Chapel Hill School of Medicine, Chapel Hill, NC 27599, USA.
³ UNC Healthcare, Information Services Division, Morrisville, NC 27560, USA.
⁴ Department of Genetics, The University of North Carolina at Chapel Hill School of Medicine, Chapel Hill, NC 27599, USA.

PMID: 35314103
DOI: 10.1016/j.ymgme.2022.03.005

Abstract

Despite recent calls to action and a heavy emphasis on timeliness of care in guidelines for common inborn errors of metabolism, there is a dearth of specific measurable quality metrics for these conditions and little to no electronic decision support for their management. We have developed a novel set of process-oriented metrics based on the aforementioned guidelines that can be calculated from data already contained in most major EHRs, which we believe are responsive to the needs of the metabolism community.

Keywords: Biochemical genetics; Clinical care; Inborn errors of metabolism; Quality improvement; Quality metrics.

MeSH terms

Benchmarking
Humans
Metabolism, Inborn Errors* / diagnosis
Metabolism, Inborn Errors* / therapy