ArticlePain medicine (Malden, Mass.)2021
Predicting Recurrent Care Seeking of Physical Therapy for Musculoskeletal Pain Conditions.
Article in Pain medicine (Malden, Mass.), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
5 citing papers in PubMed.
- Predictive factors for care intensification in a no co-pay physical therapy model for musculoskeletal pain.BMC health services research · 2026Article
- Predicting high health care use in patients with spinal disorder in secondary care: model development and validation.Pain reports · 2026Article
- Article
- Movement Clearing Screens for Military Service Member Musculoskeletal Injury Risk Identification.Journal of athletic training · 2025Article
- Electronic Health Records for Predicting Outcomes to Work-Related Musculoskeletal Disorders: A Scoping Review.Journal of occupational rehabilitation · 2024Article
Corrections and comments
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Authors and funding
7 authors.
Funding
Abstract
objectiveMusculoskeletal pain conditions are a leading cause of pain and disability internationally and a common reason to seek health care. Accurate prediction of recurrence of health care seeking due to musculoskeletal conditions could allow for better tailoring of treatment. The aim of this project was to characterize patterns of recurrent physical therapy seeking for musculoskeletal pain conditions and to develop a preliminary prediction model to identify those at increased risk of recurrent care seeking.
designRetrospective cohort.
settingAmbulatory care. SUBJECTS: Patients (n = 578,461) seeking outpatient physical therapy (United States).
methodsPotential predictor variables were extracted from the electronic medical record, and patients were placed into three different recurrent care categories. Logistic regression models were used to identify individual predictors of recurrent care seeking, and the least absolute shrinkage and selection operator (LASSO) was used to develop multivariate prediction models.
resultsThe accuracy of models for different definitions of recurrent care ranged from 0.59 to 0.64 (c-statistic), and individual predictors were identified from multivariate models. Predictors of increased risk of recurrent care included receiving workers' compensation and Medicare insurance, having comorbid arthritis, being postoperative at the time of the first episode, age range of 44-64 years, and reporting night sweats or night pain. Predictors of decreased risk of recurrent care included lumbar pain, chronic injury, neck pain, pregnancy, age range of 25-44 years, and smoking.
conclusionThis analysis identified a preliminary predictive model for recurrence of care seeking of physical therapy, but model accuracy needs to improve to better guide clinical decision-making.
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