Comparison of electronic growth chart software reveals clinically relevant variability hindering growth assessment: a UK study

Reena Perchard; Rebecca Moon; Justin Davies; Helen L Storr

doi:10.1530/endoabs.111.OC5.5

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Endocrine Abstracts (2025) 111 OC5.5 | DOI: 10.1530/endoabs.111.OC5.5

BSPED2025 Oral Communications Endocrine Oral Communications 1 (8 abstracts)

Comparison of electronic growth chart software reveals clinically relevant variability hindering growth assessment: a UK study

Reena Perchard ^1,2 , Rebecca Moon ^3,4 , Justin Davies ^3,5 & Helen L Storr ^6,7

Author affiliations

¹Division of Developmental Biology & Medicine, Faculty of Biology, Medicine & Health, University of Manchester, Manchester, United Kingdom; ²Paediatric Endocrinology, Royal Manchester Children’s Hospital, Manchester University NHS Foundation Trust, Manchester, United Kingdom; ³Paediatric Endocrinology, Southampton Children’s Hospital, University Hospital Southampton NHS Foundation Trust, Southampton, United Kingdom; ⁴MRC Lifecourse Epidemiology Centre, University of Southampton, Southampton, United Kingdom; ⁵Faculty of Medicine, University of Southampton, Southampton, United Kingdom; ⁶Centre for Endocrinology, William Harvey Research Institute, Queen Mary University London, Barts and the London School of Medicine, London, United Kingdom; ⁷Paediatric Endocrinology, Barts Health NHS Trust, London, United Kingdom

Background: Introduction of electronic patient records has prompted electronic growth chart software (EGCS) use for growth assessment. EGCS is recommended but there is no standardisation in clinical practice. Accuracy and consistency between EGCS are unknown.

Aim: To assess accuracy of UK EGCS packages including approaches to gestational age (GA) correction.

Methods: Of 82 participating centres, 60 (73%) used EGCS. 14 selected centres enabled investigation of 10 EGCS. For each EGCS, two centres completed standardised testing (clinical vignettes with “dummy data”), generating SDSs to analyse clinical growth management decisions. The responses informed a second-stage protocol to analyse observed discrepancies in birthweight, GA correction, height, head circumference (HC) and body mass index (BMI) SDS. Coefficient of Variation (CV) quantified consistency between centres: <5% good, 5-30% moderate and >30% poor. The proportion of EGCS-generated SDSs matching RCPCH-Application Programming Interface (API) EGCS-generated SDSs (gold standard) defined the accuracy.

Results: 10 EGCS were analysed (8 commercial, 2 in-house). Data were available for 4/10 EGCS packages from two centres and 6/10 from one. 14 centres completed the first proforma, of which 13 (including one RCPCH-API user) completed the second. For birthweight <-2SDS calculation, we observed high variability: CV 101% at 27-weeks; 7/12 RCPCH concordant), 49% at 33-weeks (6/12) and 24% at 37-weeks (6/12). GA correction methods varied widely with only 50% correcting for GA in infants born between 36-42 weeks. RCPCH-API corrected up to and beyond 18 years. For height calculations <-2 SDS at 11m, 23m and 36m for a child born at 27-weeks’ gestation, CVs were 60% (3/12), 64% (3/12) and 79% (0/12), respectively. Inconsistencies were observed at 33-weeks’ (22% (3/12), 9% (3/12) and 14% (1/12)) and 37-weeks’ gestation (8% (1/12), 6% (2/12) and 92% (1/12)). HC variability was greatest at +/-2SDS (CV 29-33%). For BMI SDS >3.5, consistency was poor (33% (10/13); range 1.3-5.2 SDS).

Conclusion: Clear inconsistencies and lack of standardisation between EGCS growth assessments exist. This impedes short stature, small-for-gestational-age and severe obesity identification, hinders clinical decision-making for referral, investigation and treatment and introduces geographical inequalities. We highlight an urgent need to develop comprehensive national standards/a position statement for EGCS packages.