UC Davis

Aim

To assess the accuracy, reliability, and discriminatory ability of a mobile app for measurement of migration percentage in hip surveillance radiographs of children with cerebral palsy (CP).

Method

The free mobile app HipScreen (www.hipscreen.org) was utilized by a diverse group of users to measure the migration percentage of 40 hips at two time points after completing an online tutorial and competency test. The mean absolute error (MAE) was calculated against the reference standard obtained on a radiology workstation. Statistical analyses included linear regression, intraclass correlation coefficient (ICC), and area under receiver-operating characteristic curve (AUC).

Results

Thirty-seven users completed the study, with 30 having a healthcare professional background, but only 15 with x-ray interpretation expertise. The overall MAE of migration percentage measurement using the HipScreen app was 5.72% (95% confidence interval [CI]: 5.38-6.06), with good reliability between time points (ICC = 0.83). With a migration percentage less than 30% considered as a positive case, the HipScreen app had a sensitivity of 94% (95% CI: 87-97), specificity of 66% (95% CI: 61-77), and an AUC of 0.92 (95% CI: 0.88-0.96).

Interpretation

Users from a broad range of backgrounds can utilize the HipScreen app to measure hip surveillance radiographs with clinically acceptable accuracy, reliability, and discriminatory ability.

What this paper adds

The HipScreen app can accurately and reliably measure migration percentage. As a screening tool, HipScreen has excellent sensitivity and discriminatory ability. A broad range of HipScreen users achieve clinically acceptable performance.