Objective COVID-19 has widely affected delivery of health care. In response, telerehabilitation (TR) has emerged as alternative care model. Aims were: (1) describe baseline patient characteristics and available unadjusted outcomes for episodes of care administered during COVID-19 using TR vs. traditional in-person care, (2) describe TR frequency levels by condition and telecommunication modes. Methods A descriptive retrospective observational design was used to report patient variables and outcomes including physical function, number of visits, and patient satisfaction, by TR frequency (few, most, or all visits) and telecommunication modes. Standardized differences were used to compare baseline characteristics between episodes with and without TR. Results Sample consisted of 222,680 patients [59% female; mean age (SD) = 55(18)]. Overall TR rate was 6% decreasing from 10% to 5% between 2nd and 3rd quarters of 2020. Outcome measures were available for 90% to 100% of episodes. Thirty-seven percent of clinicians administered care via TR. Patients treated using TR compared to in-person care were more likely to be younger, and live in large metropolitan areas. From those with TR, 55%, 20%, and 25% had TR during few, most, or all visits, respectively. TR care was administered equally across orthopedic body parts, with lower use for non-orthopedic conditions such as stroke, edema, and vestibular dysfunction. TR was primarily administered using synchronous (video or audio) modes. The rate of patients reported being very satisfied with their treatment results was 3% higher for no TR compared to TR. Conclusions These results provide new knowledge about to whom and how TR is being administered during the pandemic in outpatient rehabilitation practices throughout the USA. The database assessed was found to be suitable for conducting studies on associations between TR and diverse outcome measures, controlling for a comprehensive set of patient characteristics, to advance best TR care models, and promote high quality care. Impact This study provided detailed and robust descriptive information using an existing national patient database containing patient health and demographic characteristics, outcome measures, and TR administration data. Findings support the feasibility to conduct future studies on associations between TR care and patient outcomes, adjusting for a wide range of patient characteristics and clinical setting factors that may be associated with the probability of receiving TR. Finding of limited and decreasing use of TR over the study period calls for studies aimed to better understand facilitators and inhibitors of TR use by rehabilitation therapists during everyday practice to promote its use when clinically appropriate.

Background The impact of risk adjustment on clinic quality ranking for patients treated in physical therapy outpatient clinics is unknown. Objectives To compare clinic ranking, based on unadjusted versus risk-adjusted outcomes for patients with low back pain (LBP) who are treated in physical therapy outpatient clinics. Methods This retrospective cohort study involved a secondary analysis of data from adult patients with LBP treated in outpatient physical therapy clinics from 2014 to 2016. Patients with complete outcomes data at admission and discharge were included to develop the risk-adjustment model. Clinics with complete outcomes data for at least 50% of patients and at least 10 complete episodes of care per clinician per year were included for ranking assessment. The R shrinkage and predictive ratio were used to assess overfitting. Agreement between unadjusted and adjusted rankings was assessed with percentile ranking by deciles or 3 distinct quality ranks based on uncertainty assessment. Results The primary sample included 414 125 patients (mean ± SD age, 57 ± 17 years; 60% women) treated by 12 569 clinicians from 3048 clinics from all US states; 82% of patients from 2107 clinics were included in the ranking assessment. The R shrinkage was less than 1%, with a predictive ratio of 1. Risk adjustment impacted ranking for 70% or 31% of clinics, based on deciles or 3 distinct quality levels, respectively. Conclusion Important changes in ranking were found after adjusting for basic patient characteristics of those admitted to physical therapy for treatment of LBP. Risk-adjustment profiling is necessary to more accurately reflect quality of care when treating patients with LBP. Level of Evidence Therapy, level 2b. J Orthop Sports Phys Ther 2018;48(8):637-648. Epub 22 May 2018. doi:10.2519/jospt.2018.7981.

Chronic wounds have risen to epidemic proportions in the United States and can have an emotional, physical, and financial toll on patients. By leveraging data within the electronic health record (EHR), machine learning models offer the opportunity to facilitate earlier identification of wounds at risk of not healing or healing after an abnormally long time, which may improve treatment decisions and patient outcomes. Machine learning models in this study were built to predict chronic wound healing time. ApproachMachine learning models were developed using EHR data to predict patients at risk of having wounds not heal within 4, 8, and 12 weeks from the start of treatment. The models were trained on three data sets of 1,220,576 wounds, including 187 covariates describing patient demographics, comorbidities, and wound characteristics.

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Objective Research supports the relevance of the therapeutic alliance (TA) between patients and physical therapists on outcomes, but the impact of TA during routine physical therapist practice has not been quantified. The primary objective of this study was to examine the relationship between TA assessed during a physical therapy episode of care for patients with low back pain (LBP) and functional outcome at the conclusion of care. Secondary objective was to examine psychometric properties of the Working Alliance—Short Revised (WAI-SR) form, a patient-reported TA measure. Methods This study was a retrospective analysis of prospectively collected data from 676 patients (mean age = 55.6 y [SD = 16.1]; 55.9% female) receiving physical therapy for LBP in 45 outpatient clinics from one health system in the United States. Participating clinics routinely collect patient-reported data at initial, interim, and final visits. The Lumbar Computer-Adapted Test (LCAT) was used to evaluate functional outcome. The TA was assessed from the patient’s perspective at interim assessments using the WAI-SR, bivariate correlations were examined, and regression models were examined if interim WAI-SR scores explained outcome variance beyond a previously validated multivariate prediction model. Internal consistency and ceiling effects for the WAI-SR were examined. Results Interim WAI-SR scores were not correlated with patient characteristics or initial LCAT, but they were correlated with final LCAT and LCAT change from initial to final assessment. WAI-SR total score (adjusted R2 = 0.36, P < .001), and task (adjusted R2 = 0.38, P < .001) and goal subscales (adjusted R2 = 0.35, P < .001) explained additional variance in outcome beyond the base model (adjusted R2 = 0.33, P < .001). Internal consistency was higher for WAI-SR total score (α = 0.88) than for subscales (α = 0.76–0.82). Substantial ceiling effects were observed for all WAI-SR scores (27.2%—63.6%). Conclusion Findings support the importance of TA in physical therapist practice. Measurement challenges were identified, most notably ceiling effects. Impact This study supports the impact of the patient-physical therapist alliance on functional outcome. Results extend similar findings from controlled studies into a typical physical therapist practice setting. Better understanding of the role of contextual factors including the therapeutic alliance might be key to improving the magnitude of treatment effect for discrete physical therapist interventions and enhancing clinical outcomes of physical therapy episodes of care.