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01-12-2017 | Research | Uitgave 1/2017 Open Access

Journal of Foot and Ankle Research 1/2017

Custom-made foot orthoses: an analysis of prescription characteristics from an Australian commercial orthotic laboratory

Journal of Foot and Ankle Research > Uitgave 1/2017
Hylton B. Menz, Jamie J. Allan, Daniel R. Bonanno, Karl B. Landorf, George S. Murley
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The online version of this article (doi:10.​1186/​s13047-017-0204-7) contains supplementary material, which is available to authorized users.



Foot orthoses are widely used in the prevention and treatment of foot disorders. The aim of this study was to describe characteristics of custom-made foot orthosis prescriptions from a Australian podiatric orthotic laboratory.


One thousand consecutive foot orthosis prescription forms were obtained from a commercial prescription foot orthosis laboratory located in Melbourne, Victoria, Australia (Footwork Podiatric Laboratory). Each item from the prescription form was documented in relation to orthosis type, cast correction, arch fill technique, cast modifications, shell material, shell modifications and cover material. Cluster analysis and discriminant function analysis were applied to identify patterns in the prescription data.


Prescriptions were obtained from 178 clinical practices across Australia and Hong Kong, with patients ranging in age from 5 to 92 years. Three broad categories (‘clusters’) were observed that were indicative of increasing ‘control’ of rearfoot pronation. A combination of five variables (rearfoot cast correction, cover shape, orthosis type, forefoot cast correction and plantar fascial accommodation) was able to identify these clusters with an accuracy of 70%. Significant differences between clusters were observed in relation to age and sex of the patient and the geographic location of the prescribing clinician.


Foot orthosis prescriptions are complex, but can be broadly classified into three categories. Selection of these prescription subtypes appears to be influenced by both patient factors (age and sex) and clinician factors (clinic location).

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