The power of using outcome measures (OM) and selected assessment tools extends beyond simple documentation to the ability for treatment prescription.
This presentation will focus on the use of selected standardized outcome measures that can identify physical limitations and the subsequent prescription of a targeted exercises for prosthetic training of people with lower limb loss.
Presenters will discuss the importance of pre-prosthetic training and what patient characteristics may be employed to predict candidacy for prosthetic fitting and successful ambulation with a prosthesis.
Once a person is walking with a prosthesis specific performance-based and patient-report OMs (Amputee Mobility Predictor (AMP), Functional Lower-limb Amputee Gait (FLAG) assessment, Prosthetic Lower-limb Users Survey-Mobility (PLUS-M), Activity Balance-specific Confidence (ABC) scale) may be administered to identify physical limitations, gait deviations and/or patient concerns that can be barriers to prosthetic success. Every OM item or task is correlated to a systematic treatment approach that can modify movement patterns to improve function and reduce or eliminate each gait deviation. Each exercise can be modified to accommodate the patients’ improvement or decline. The specific treatment recommendations for each associated gait deviation will be presented with the best-known evidence to support the rational for why each exercise can be effective.
A systematic progression of assessment and the specific exercises designed to enhance prosthetic use and improve a patient’s functional capabilities during prosthetic gait will be the common thread throughout the presentation.
Finally, how OMs can objectively document the change over time to demonstrate prosthetic value will be discussed.
Statement of the objective / learning objectives
Upon completion of this presentation attendees will be able to apply throughout prosthetic gait training rehabilitation process a standardized approach for treatment prescription with the use of selected outcome measures.
