Jason A Sharpe1, Brook I Martin2,3, Julie M Fritz1, Michael G Newman4, John Magel1, Megan E Vanneman3,5,6, Anne Thackeray1,3. 1. University of Utah, Department of Physical Therapy and Athletic Training. 2. University of Utah School of Medicine, Department of Orthopaedics. 3. University of Utah, Department of Population Health Sciences, Division of Health System Innovation and Research. 4. Data Science Services, University of Utah, Data Science Services. 5. University of Utah School of Medicine, Department of Internal Medicine, Division of Epidemiology. 6. Informatics, Decision-Enhancement and Analytic Sciences Center (IDEAS), Veterans Affairs Salt Lake City Health Care System, Informatics, Decision-Enhancement and Analytic Sciences Center (IDEAS), Salt Lake City, UT, USA.
Abstract
BACKGROUND: Musculoskeletal conditions are common and cause high levels of disability and costs. Physical therapy is recommended for many musculoskeletal conditions. Past research suggests that referral rates appear to have increased over time, but the rate of accessing a physical therapist appears unchanged. OBJECTIVE: Our retrospective cohort study describes the rate of physical therapy use after referral for a variety of musculoskeletal diagnoses while comparing users and non-users of physical therapy services after referral. METHODS: The study sample included patients in the University of Utah Health system who received care from a medical provider for a musculoskeletal condition. We included a comprehensive set of variables available in the electronic data warehouse possibly associated with attending physical therapy. Our primary analysis compared differences in patient factors between physical therapy users and non-users using Poisson regression. RESULTS: 15 877 (16%) patients had a referral to physical therapy, and 3812 (24%) of these patients accessed physical therapy after referral. Most of the factors included in the model were associated with physical therapy use except for sex and number of comorbidities. The receiver operating characteristic curve was 0.63 suggesting poor predictability of the model but it is likely related to the heterogeneity of the sample. CONCLUSIONS: We found that obesity, ethnicity, public insurance and urgent care referrals were associated with poor adherence to physical therapy referral. However, the limited predictive power of our model suggests a need for a deeper examination into factors that influence patients access to a physical therapist.
BACKGROUND: Musculoskeletal conditions are common and cause high levels of disability and costs. Physical therapy is recommended for many musculoskeletal conditions. Past research suggests that referral rates appear to have increased over time, but the rate of accessing a physical therapist appears unchanged. OBJECTIVE: Our retrospective cohort study describes the rate of physical therapy use after referral for a variety of musculoskeletal diagnoses while comparing users and non-users of physical therapy services after referral. METHODS: The study sample included patients in the University of Utah Health system who received care from a medical provider for a musculoskeletal condition. We included a comprehensive set of variables available in the electronic data warehouse possibly associated with attending physical therapy. Our primary analysis compared differences in patient factors between physical therapy users and non-users using Poisson regression. RESULTS: 15 877 (16%) patients had a referral to physical therapy, and 3812 (24%) of these patients accessed physical therapy after referral. Most of the factors included in the model were associated with physical therapy use except for sex and number of comorbidities. The receiver operating characteristic curve was 0.63 suggesting poor predictability of the model but it is likely related to the heterogeneity of the sample. CONCLUSIONS: We found that obesity, ethnicity, public insurance and urgent care referrals were associated with poor adherence to physical therapy referral. However, the limited predictive power of our model suggests a need for a deeper examination into factors that influence patients access to a physical therapist.
Authors: Rebecca Lewis; Constanza B Gómez Álvarez; Margaret Rayman; Susan Lanham-New; Anthony Woolf; Ali Mobasheri Journal: BMC Musculoskelet Disord Date: 2019-04-11 Impact factor: 2.362
Authors: Chidozie Mbada; Abraham Olawuyi; Olufemi O Oyewole; Adesola C Odole; Abiola O Ogundele; Francis Fatoye Journal: BMC Health Serv Res Date: 2019-03-14 Impact factor: 2.655
Authors: Jason A Sharpe; Anne Thackeray; Julie M Fritz; Brook I Martin; John Magel; Megan E Vanneman Journal: Musculoskelet Sci Pract Date: 2021-10-18 Impact factor: 2.520