Nrupen A Bhavsar1, Shannon M Doerfler2, Anna Giczewska2, Brooke Alhanti2, Adam Lutz3,4, Charles A Thigpen3,4,5, Steven Z George2,6. 1. Division of General Internal Medicine, Department of Medicine, Duke University School of Medicine, Durham, NC, United Stated of America. 2. Duke Clinical Research Institute, Duke University, Durham, NC, United Stated of America. 3. ATI Physical Therapy, Greenville, SC, United Stated of America. 4. Exercise Science, Arnold School of Public Health, University of South Carolina, Columbia, SC, United Stated of America. 5. Center for Effectiveness Research in Orthopaedics, Arnold School of Public Health, University of South Carolina, Columbia, SC, United Stated of America. 6. Department of Orthopaedic Surgery, Duke University School of Medicine, Durham, NC, United Stated of America.
Abstract
OBJECTIVES: Chronic pain affects 50 million Americans and is often treated with non-pharmacologic approaches like physical therapy. Developing a no-show prediction model for individuals seeking physical therapy care for musculoskeletal conditions has several benefits including enhancement of workforce efficiency without growing the existing provider pool, delivering guideline adherent care, and identifying those that may benefit from telehealth. The objective of this paper was to quantify the national prevalence of no-shows for patients seeking physical therapy care and to identify individual and organizational factors predicting whether a patient will be a no-show when seeking physical therapy care. DESIGN: Retrospective cohort study. SETTING: Commercial provider of physical therapy within the United States with 828 clinics across 26 states. PARTICIPANTS: Adolescent and adult patients (age cutoffs: 14-117 years) seeking non-pharmacological treatment for musculoskeletal conditions from January 1, 2016, to December 31, 2017 (n = 542,685). Exclusion criteria were a primary complaint not considered an MSK condition or improbable values for height, weight, or body mass index values. The study included 444,995 individuals. PRIMARY AND SECONDARY OUTCOME MEASURES: Prevalence of no-shows for musculoskeletal conditions and predictors of patient no-show. RESULTS: In our population, 73% missed at least 1 appointment for a given physical therapy care episode. Our model had moderate discrimination for no-shows (c-statistic:0.72, all appointments; 0.73, first 7 appointments) and was well calibrated, with predicted and observed no-shows in good agreement. Variables predicting higher no-show rates included insurance type; smoking-status; higher BMI; and more prior cancellations, time between visit and scheduling date, and between current and previous visit. CONCLUSIONS: The high prevalence of no-shows when seeking care for musculoskeletal conditions from physical therapists highlights an inefficiency that, unaddressed, could limit delivery of guideline-adherent care that advocates for earlier use of non-pharmacological treatments for musculoskeletal conditions and result in missed opportunities for using telehealth to deliver physical therapy.
OBJECTIVES:Chronic pain affects 50 million Americans and is often treated with non-pharmacologic approaches like physical therapy. Developing a no-show prediction model for individuals seeking physical therapy care for musculoskeletal conditions has several benefits including enhancement of workforce efficiency without growing the existing provider pool, delivering guideline adherent care, and identifying those that may benefit from telehealth. The objective of this paper was to quantify the national prevalence of no-shows for patients seeking physical therapy care and to identify individual and organizational factors predicting whether a patient will be a no-show when seeking physical therapy care. DESIGN: Retrospective cohort study. SETTING: Commercial provider of physical therapy within the United States with 828 clinics across 26 states. PARTICIPANTS: Adolescent and adult patients (age cutoffs: 14-117 years) seeking non-pharmacological treatment for musculoskeletal conditions from January 1, 2016, to December 31, 2017 (n = 542,685). Exclusion criteria were a primary complaint not considered an MSK condition or improbable values for height, weight, or body mass index values. The study included 444,995 individuals. PRIMARY AND SECONDARY OUTCOME MEASURES: Prevalence of no-shows for musculoskeletal conditions and predictors of patient no-show. RESULTS: In our population, 73% missed at least 1 appointment for a given physical therapy care episode. Our model had moderate discrimination for no-shows (c-statistic:0.72, all appointments; 0.73, first 7 appointments) and was well calibrated, with predicted and observed no-shows in good agreement. Variables predicting higher no-show rates included insurance type; smoking-status; higher BMI; and more prior cancellations, time between visit and scheduling date, and between current and previous visit. CONCLUSIONS: The high prevalence of no-shows when seeking care for musculoskeletal conditions from physical therapists highlights an inefficiency that, unaddressed, could limit delivery of guideline-adherent care that advocates for earlier use of non-pharmacological treatments for musculoskeletal conditions and result in missed opportunities for using telehealth to deliver physical therapy.