Development of a stop light tool using the bellarmine norton assessment tool (BNAT) for physical therapy referral.

e19067 Background: Individuals with cancer experience fatigue, pain and decline in function. The Bellarmine Norton Assessment Tool (BNAT) was developed to give an objective measure identifying a person’s overall functional ability through a variety of physical assessments focused on mobility and strength. The purpose of this study was to develop a referral tool to provide health care professionals an easy determinant for physical therapy referrals. The referral tool was designed as a Red, Yellow, Green light for easy interpretation and use. Methods: The BNAT is composed of 1 self-reported physical activity question and 4 objective tests: 2-Minute Step Test (2MST); 30-Second Sit-to-Stand; Timed Arm Curl; and Timed Up and Go. A previously collected data set of BNAT scores was utilized to develop the referral tool with the poorest performance corresponding to Red and the best corresponding to Green. Three variations of normative scaling examined optimal distribution for classification. The first model averaged normative data of 70-74 age group of healthy individuals. No participants in our study achieved 50% of population norms. Therefore, the Green light represented 35% of the normative values, the Yellow light ranged from 15-34% and the Red light identified < 15%. A second model used frequency histograms for each BNAT elements. Groupings were made based on the natural break of the data to depict the Red, Yellow or Green light. A third approach combined normative and frequency distribution for each element as compared to the respective BNAT scores. The outcome assigned BNAT score of 1 and 2 to Red light, 3 to Yellow light and 4 and 5 to Green light. Except for the 2MST, these models were similar for the cutoff between color categories. The third model best fit the study population with respect to the individual’s total BNAT score. Results: Of the 161 subjects, 47 subjects (29%) fell into the Red category, 81 (50%) into Yellow and 33 (21%) into Green. Using this scaling system for the total BNAT score, 13 score combinations result in Red light, 6 scores for Yellow light and 6 scores for Green light. Regardless of the model, most individuals were assigned a Yellow light. Conclusions: The literature is void of functional cut off scores and normative distributive data for the oncology population. We defined a referral tool with scaling based off normative scores and functional assessments that reflect the distribution of oncology patients. The third model may be used as a simple referral tool among multiple health care professionals aiding in a referral for physical therapy.