Vasek J, Delitto A; Department of Physical Therapy, University of Pittsburgh, Pittsburgh, PA, USA.

PURPOSE: The purpose of this study was to assess the ability of an algorithm to allow physical therapy students come to common conclusions as a physical therapist that has experience in prescribing wheelchairs. BACKGROUND: An algorithm was developed by a physical therapist who provides input to a multi-disciplinary rehabilitation seating clinic to assist those with minimal experience in prescribing wheeled mobility devices find a suitable match between the client’s needs and the equipment features. The algorithm was pilot studied and revised. If this device is found useful, it may potentially be utilized as a training tool in the education of students and entry-level clinicians with minimal exposure in the evaluation of wheeled mobility devices. SUBJECTS: Fifteen patients with a need for a manual wheeled mobility devices where selected for this study. These patients were referred to the physical therapy department at the Pittsburgh Veterans Affairs Healthcare System by standard referral sources located within the Healthcare System. 15 entry-level physical therapy students in various stages of their education from the University of Pittsburgh volunteered to act as the inexperienced clinicians. The therapist who developed the algorithm served as the expert clinician. METHODS: Prior to participation in this study the students were provided a copy of the algorithm and specific instructions to follow in making each determination. The students were allowed at least 24 hours to review the materials. Prior to the evaluation the expert clinician demonstrated the correct technique for the linear measurements and addressed any further questions the students had. During the examination the students utilized an assessment form that served as a condensed version of the previously issued instructions. The student performed the evaluation in the presence of the expert clinician but was not allowed to consult the therapist. Once the student selected a wheelchair to prescribe, the clinician proceeded with his portion of the evaluation and ascertained any further information he felt was necessary before deciding on a final wheeled mobility device. ANALYSIS: Analysis was performed utilizing the kappa statistic. The final prescription selections and each determination in the algorithm were analyzed for level of agreement. RESULTS: The two examiners recommended the same wheelchair for 11 of the 15 subjects. This provided a kappa coefficient of 0.61. Kappa coefficients for each determination in the algorithm will also be presented. CONCLUSIONS: The kappa statistic represents the chance corrected agreement between raters; a score of 0.61 represents a substantial level of agreement. FUNDING SOURCE: None.

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