Clinical Sciences/Health Conditions
Stephen A. Ashford, PhD Rehabilitation Medicine, MSc Neurorehabilitaton Advanced Practice, BSc Physiotherapy, PGCert Education, PGCert Prescribing, PGDip Sonography
Consultant Physiotherapist and Associate Professor
London North West University Healthcare NHS Trust
London, England, United Kingdom
Jorge Jacinto, MD
head of department PMR
Centro de medicina de Reabilitação de Alcoitão
Estoril, Lisboa, Portugal
Klemens Fheodroff, MD
Professor
Gailtal-Klinik
Hermagor, Burgenland, Austria
Lynne Turner-Stokes, DM, FRCP, MBE
Professor of rehabilitation
London North West University Healthcare NHS Trust & King's College London
London, England, United Kingdom
Setting goals is integral to rehabilitation practice, particularly when managing spasticity. Using the pre-defined goal framework for spasticity management we aimed to produce a physical treatment intervention decision algorithm using goal category in the arm and the leg for people following an acquired brain injury.
Design:
Following secondary analysis and mapping of goal setting categories and treatment interventions in three spasticity intervention studies a) the Leg Activity measure study b) Ankle Contracture data set and c) the Upper Limb International Spasticity-III study (total n=1207).
A framework for treatment planning was mapped onto the goal categories of; pain, involuntary movement, contracture prevention, active function (self-performance of tasks), passive function (secondary performance of tasks or personal care).
Based on this framework and evidenced through the literature a treatment algorithm was mapped between goal categories and the physical treatments most appropriate to deliver alongside other spasticity management using botulinum toxin injection. The subsequent algorithm was incorporated into a web-based application (app).
Results:
Interventions identified per category in the arm were: Pain 302 (22%) (positioning), Involuntary Movement 166 (12%) (position, orthotics), Contracture Prevention or minimisation 139 (17%) (positioning, shoulder support and slings, orthotics – splinting to maintain muscle length, task-practice), Active Function 174 (13%) (task-practice training, orthotics), passive function 501 (37%) (positioning, shoulder-supports, orthotics).
Interventions identified per category in the leg were: Pain 117 (15%) (positioning), Involuntary Movement 10 (1%) (orthotics), Contracture Prevention 139 (17%) (positioning, orthotics, task-practice), Active Function 356 (44%) (task -practice, orthotics), passive function (orthotics, positioning) 181 (44%).
Conclusion:
The resulting algorithm incorporated into a web-based application is being tested in clinical practice for people with stroke, other brain injury and their carers. A Data Protection Impact Assessment (DPIA) has been completed in preparation for further testing of the algorithm process in a service evaluation.
