Predictors of Physical Therapy Non-Treatment Among Patients Scheduled for Treatment Two Times a Day in the Acute Hospital

Background and Purpose: Consistent participation in physical therapy treatment is the key to the success of any physical therapy treatment program. Scheduled therapy sessions that do not result in treatment (non-treatment) may cause longer hospital stays and/or poor outcomes. A better understanding of the factors affecting non-treatment could allow proper adjustments to prevent non-treatment by hospital administration, improve patient-therapist interaction, and may result in improved care, greater patient satisfaction, and lower healthcare costs. The purpose of this study was to investigate characteristics of patients that affect physical therapy non-treatment events for patients scheduled for therapy twice a day (BID) in an inpatient hospital setting. Subjects: The subjects for this study were all patients scheduled to receive physical therapy BID during their hospital stay. Data was collected from a 450 bed hospital located in a metropolitan area of the Southwest United States. Data from 367 patients who were scheduled for physical therapy treatment BID were collected retrospectively from the medical record during the study period. There were 168 males and 199 females. A total of 810 scheduled BID treatment sessions were analyzed. Methods: The dependent variable was a dichotomous Yes or No to indicate if treatment occurred or did not occur giving 4 possible outcomes on a day of BID scheduled therapy: yes/yes, yes/no, no/yes, and no/no. Demographic patient information such as age, gender, diagnosis, and scheduled treatment day was also given to the research team for analysis. Patient diagnoses were grouped into 1 of 13 categories: Cardiovascular, Pulmonary, Neurological, Gastrointestinal, Musculoskeletal, Cancer, Integumentary, Genitourinary/Renal, Infections Disease, Obstetrics and Gynecology (OBGYN), Neonatal intensive care unit (NICU), Endocrine, or Other/Unknown. Ages of patients ranged from newborn children seen in the NICU to 97 years of age. Scheduled treatment day included the 7 days of the week. Descriptive and interferential statistics were performed. Chi-square analyses were performed to assess which patient characteristics including treatment day, gender, and diagnosis were associated with a change in BID treatment occurrences. One-way ANOVA and post-hoc paired t-tests were utilized to compare patient age in the 4 outcome groups. Results: Gender, diagnosis, day of the week, and age all influence non-treatment occurrence in the acute care setting for patients scheduled for BID therapy (p=\u3c0.003). Among females, 84% of scheduled sessions resulted in a yes/yes combination while only 64% yes/yes occurred for males (p=\u3c0.000). No/no events are at their highest proportions on Sunday 27.8% (p=\u3c0.000) and Saturday 23.5% (p=\u3c0.002). Tuesday and Thursday had the lowest occurrence of non-treatment at 4.2% of scheduled visits (p=\u3c0.001). Musculoskeletal diagnosis has the highest yes/yes outcome (p=\u3c0.000). The average age of patients that had a no/no outcome is 55.42 years old, and the average age that had a yes/yes outcome is 63.89 years old (p=\u3c0.002). Discussion: Gender, age, diagnosis and day of the week of treatment all appear to play a role in non-treatment in the acute hospital setting. Specifically, females have a lower occurrence of no/no treatment. Patients with musculoskeletal diagnosis has the highest occurrence of yes/yes treatment. Saturday and Sunday have the highest no/no treatment occurrence and Tuesday and Thursday have the lowest occurrence of non-treatment. It may be possible for hospitals to minimize the incidence of non-treatment, allowing patients to receive the physical therapy they need. In the future, other hospitals may use this information to reduce their BID non-treatment rates. Further studies should investigate a more inclusive population of patients in both BID scheduled treatment and those scheduled for one physical therapy treatment in order to explore trends that can potentially lead to missed treatment