Investigation of factors from assistive technology professionals that impact timeliness of wheelchair service delivery: a cross-sectional study

Abstract

Purpose The purpose of this study was to examine factors associated with variability in time from assessment to device delivery (cycle time). Our hypothesis was that device type and type of insurance would be the strongest predictor of cycle time. Materials and methods Data were extracted from the Functional Mobility Assessment/Uniform Dataset (FMA/UDS) Registry that at the time of analysis contained a sample of 2588 people with disabilities (PWD) who were provided with a wheeled mobility device (WMD) between 21 March 2016 and 29 June 2021. To examine the effect of individual factors on the variability in cycle time, a robust linear regression analysis was conducted. Results The average national cycle time was 101.5 (SD = 59.9) d. Geographic area (Capital Metro [p < .001], Great Lakes [p = .016], and Northeast area [p < .001]), higher years since onset of disability (p < .001) and customizable devices (p = .021) were associated with higher cycle time. Non-customizable devices (p = .005), scooters (p < .001), Group 2 power wheelchairs (PWCs; p < .001), and funding source (Medicaid managed care (p < .001) and “other” (p = .028)) were associated with lower cycle time. Conclusions Longer cycle time is likely related to variations in clinical practice, insurance coverage criteria and the level of customizability of the device needed for a particular diagnosis, especially long-term disabilities. Implications for rehabilitation The national average number of days between initial evaluation and device delivery (cycle time) to deliver a wheeled mobility device (WMD) varies based on specific variables such as type of WMD, diagnosis and payer source. Geographic area, years since onset of disability, device type, primary diagnosis and funding source significantly impact cycle times. Increased complexity of the WMD, both manual and power wheelchairs (PWCs), was associated with longer cycle times. As more service delivery models emerge, specific benefits and challenges need to be reported on how they impact cycle time.