Physical Therapy Commons^™

Am-Pac Basic Mobility Inpatient Short Form (Low Function) Psychometrics/Clinimetrics, Meghan Wonderling, David Miller, Selena Soria

UNLV Theses, Dissertations, Professional Papers, and Capstones

Objective: To determine whether the Activity Measure for Post-Acute Care® Basic Mobility Inpatient Short Form (Low Function) (6-clicks LF) has increased responsiveness for patients with lower levels of physical function compared to the Activity Measure for Post-Acute Care Basic Mobility Inpatient Short Form (6-clicks). Design: Retrospective cohort study using original scores and simulated scores for assessment of internal responsiveness of the 6-clicks LF compared to the 6-clicks. Simulated 6-clicks and 6-clicks LF scores were created as a hypothetical future AM-PAC® score. Results: We found a statistically significant difference between the 6-clicks and simulated 6-clicks, t=24.8, p < 0.00 [two-tailed]. The effect size was large (d=1.2, r=0.51).There was a statistically significant difference between the 6-clicks LF and simulated 6-clicks LF, t=19.7, p < 0.00 [two-tailed]. The effect size was medium (d=0.91, r=0.41). Finally, for patients with a 6-clicks score in the bottom five-percentile (n=27), we found a statistically significant difference between the 6-clicks and 6-clicks LF, t=11.9, p < 0.00 [two-tailed]. Conclusion: Among patients scoring less than 15, the 6-clicks LF has greater internal responsiveness than the 6-clicks and thus demonstrates that the new low-level questions in the 6-clicks LF better quantify low-level patients’ functional level. Research using non-simulated data should be completed in the future to confirm these findings.

Patient Factors And Day Of The Week Influencing Physical Therapy Non-Treatment Events In The Acute Care Setting, Daniel Goodrich, Curtis Doug Jensen

UNLV Theses, Dissertations, Professional Papers, and Capstones

Background. In acute care hospitals, scheduled physical therapy visits not resulting in treatment may increase patient length of stay and the financial burden to the hospital. Previous literature has not fully evaluated the occurrence of these events, nor have any associated factors been identified.

Objective. Measure the rate of non-treatment and determine which patient characteristics were most likely to predict a non-treatment event.

Design. Retrospective review of documentation at a suburban hospital.

Methods. Data were collected from records of 1,096 patients, totaling 6,097 scheduled sessions. The rate of non-treatment was calculated and logistic regression used to …