Objective: The objective of this study was to examine primary factors that may predict patients' failure to show at initial physical therapist evaluation in an orthopedic and sports outpatient setting.
Methods: A retrospective analysis of patients' demographic data for physical therapist evaluations between January 2013 and April 2015 was performed. A binary logistic regression model was used to evaluate the odds of a no-show at evaluation. Demographic variables of age, employment status, days waited for the appointment, payer source, and distance traveled to the clinic were analyzed. Independent variables were considered significant if the 95% CIs of the odds ratios (ORs) did not include 1.0.
Results: A total of 6971 patients were included in the final analysis, with 10% (n = 698) of the scheduled patients having a no-show event for their initial evaluation. The following factors increased the odds of patients having a no-show event: days to appointment (OR = 1.058; 95% CI = 1.042-1.074), unemployment status (OR = 1.96; 95% CI = 1.41-2.73), unknown employment status (OR = 3.22; 95% CI = 1.12-8.69), Medicaid insurance (OR = 4.87; 95% CI = 3.43-6.93), Medicare insurance (OR = 2.22; 95% CI = 1.10-4.49), unknown payer source (OR = 262.84; 95% CI = 188.72-366.08), and distance traveled 8 or more kilometers (OR = 1.31; 95% CI = 1.01-1.70). Female sex (OR = 0.73; 95% CI = 0.57-0.95) and age 40 years or older (OR = 0.44; 95% CI = 0.33-0.60) decreased the odds of a no-show event.
Conclusions: Results from this study indicate there may be some demographic factors that are predictive of patients failing to attend their first physical therapist visit.
Impact: Understanding the predictive factors and identifying potential opportunities for improvements in scheduling processes might help decrease the number of patients failing to show for their initial physical therapy appointment, with the ultimate goal of positively influencing patient outcomes.
Keywords: Attendance; Employment; Health Insurance; Medicaid; Medicare; No-Show; Patient Characteristics; Time to Appointment; Workers’ Compensation.
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