Prevalence and predictors of no-shows to physical therapy for musculoskeletal conditions

• Published in: PloS one 2021-05, Vol.16 (5), p.e0251336-e0251336
• Main Authors: Bhavsar, Nrupen A, Doerfler, Shannon M, Giczewska, Anna, Alhanti, Brooke, Lutz, Adam, Thigpen, Charles A, George, Steven Z
• Format: Article
• Language: English
• Subjects: Adolescent; Adult; Age; Aged; Aged, 80 and over; Appointments and Schedules; Biology and Life Sciences; Body Mass Index; Care and treatment; Chronic pain; Chronic Pain - physiopathology; Editing; Electronic health records; Engineering and Technology; Female; Health care; Humans; Male; Medical referrals; Medical research; Medicine; Medicine and Health Sciences; Medicine, Experimental; Methodology; Middle Aged; Musculoskeletal diseases; Musculoskeletal Pain - physiopathology; Musculoskeletal Pain - therapy; Narcotics; No-Show Patients; Occupational therapy; Opioids; Orthopedics; Pain; Patient Acceptance of Health Care; Patient compliance; Patient outcomes; Patients; People and places; Physical Sciences; Physical therapists; Physical therapy; Physical Therapy Modalities; Physical training; Prevalence; Public health; Research and Analysis Methods; Retrospective Studies; Social Sciences; Socioeconomic factors; Subgroups; Surgery; Telemedicine - methods; Therapeutics, Physiological; Therapy; United States; Workforce; Young Adult
• ISSN: 1932-6203; 1932-6203
• DOI: 10.1371/journal.pone.0251336

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. Retrospective cohort study. Commercial provider of physical therapy within the United States with 828 clinics across 26 states. 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. Prevalence of no-shows for musculoskeletal conditions and predictors of patient no-show. 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. 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.