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2011 Annual Conference

October 27–30, 2011

The Woodlands Waterway Marriott

2011 Research Poster Abstracts


Saturday, October 29, 2011 at 1:00 PM–2:00 PM CDT
Exhibit Hall
Presenter's Name - Last Name First

Szot, Lauren and Tseng, Eileen


Utilizing standardized outcome measures (OMs) is essential in assessing the effectiveness of physical therapy (PT) interventions. Despite the need for quantifying patient outcomes, use of OMs in PT practice continues to be limited.  The purpose of this project was to develop decision-making algorithms to guide physical therapists (PTs) across all settings in OM selection for balance and gait.


The target population for this project were physical therapists from acute care, inpatient rehabilitation, and outpatient rehabilitation who identified neurology as their primary area of clinical practice.


A questionnaire was developed and administered to determine factors that impact use and selection of OMs.  The questionnaire (n=28) revealed that 64% of PTs reported difficulty selecting an appropriate OM for a patient’s functional status, with time and ease of use identified as major influences on OM selection. The majority of PTs surveyed identified balance and gait (86% and 67%, respectively) as high priorities in the patient’s plan of care. A literature review of balance and gait outcome measures was performed. Once measures were identified, they were ranked based on psychometric properties and clinical utility using the StrokEDGE Taskforce rating scale.  A balance algorithm and a gait algorithm were constructed with these selected OMs based on the patient’s current functional status. To assess practical utility of the algorithms, PTs from each clinical setting (n=10) were chosen to participate in a one-month trial. 

Data Analysis

Qualitative data was collected during the algorithm trials with tracking forms and a final survey was distibuted to the physical therapists involved in the trial.  Clinicians completed a tracking form everytime they utilized either of the algorithms, documenting which algorithm was utilized, at what point in the patient's admission was the algorithm used, what barriers to use occurred, and any suggestions for revision.  The survey assessed how the algorithms may have influenced the physical therapists in their clinical practice and their perception of the clinical utility of the algorithms.


During the trial the balance algorithm and the gait algorithm were utilized 55 times and 41 times, respectively.  Time to complete the algorithms ranged from 5 seconds to 10 minutes (mean=113 seconds). Impaired cognition, medical instability, and functional inappropriateness were reported as barriers to use.  All participants agreed that both algorithms were effective in guiding their decision making in OM selection, and 94% reported increased confidence in their choices of outcome measures. Participants agreed that the balance algorithm (100%) and the gait algorithm (78%) were useful for the majority of their patients. Those who were neutral (11%) or disagreed (11%) reported limited ability to use the gait algorithm due to their patients being non-ambulatory. However, it was reported that with improvements in medical stability and function, the ability to use the gait algorithm increased.  Eighty-nine percent agreed that both algorithms prompted them to select OMs not used previously.


This preliminary trial suggests that the balance and gait outcome measure algorithms developed in this study are appropriate for patients with neurologic disorders and can guide physical therapists in their decision-making process and increase their confidence for outcome measure selection.       

Clinical Relevance

Literature indicates that PTs believe OMs assist in developing the plan of care and monitoring effectiveness of treatment; however, time constraints, lack of familiarity of measures, and difficulty with OM selection result in inconsistent use.  Decision making frameworks have been used in neurologic PT practice to guide clinical judgment. Therefore, an evidence-based, decision making algorithm will aid PTs in selection of OMs with sound psychometric properties and clinical utility. 


Catherine Lauren Szot, PT, DPT, NCS, TIRR Memorial Hermann Hospital
Jill Seale, PT, PhD, University of Texas-Medical Branch
Eileen Tseng, PT, DPT, NCS, TIRR Memorial Hermann Hospital