Predicting Pain Response to a Remote Musculoskeletal Care Program for Low Back Pain Management: Development of a Prediction Tool.

Background: Low back pain (LBP) presents with diverse manifestations, necessitating personalized treatment approaches that recognize various phenotypes within the same diagnosis, which could be achieved through precision medicine. Although prediction strategies have been explored, including those employing artificial intelligence (AI), they still lack scalability and real-time capabilities. Digital care programs (DCPs) facilitate seamless data collection through the Internet of Things and cloud storage, creating an ideal environment for developing and implementing an AI predictive tool to assist clinicians in dynamically optimizing treatment.

Exploring the Importance of Race and Gender Concordance Between Patients and Physical Therapists in Digital Rehabilitation for Musculoskeletal Conditions: Observational, Longitudinal Study.

Background: Race/ethnicity and gender concordance between patients and providers is a potential strategy to improve health care interventions. In digital health, where human interactions occur both synchronously and asynchronously, the effect of concordance between patients and providers is unknown.

Objective: This study aimed to evaluate the impact of race/ethnicity or gender concordance between patients and physical therapists (PTs) in engagement and the clinical outcomes following a digital care program (DCP) in patients with musculoskeletal (MSK) conditions.

Development of the scoliosis research society spinal deformity surgery safety checklist.

Purpose: Spine deformity surgery is a complex multi-step procedure that has a relatively high complication rate. The use of surgical safety checklists has been shown to reduce perioperative adverse events, but existing lists are varied and non-specific for spinal deformity surgery. Thus, the purpose of this study was to develop a comprehensive surgical checklist for complex spinal corrective surgery.

Applying AI to Safely and Effectively Scale Care to Address Chronic MSK Conditions.

: The rising prevalence of musculoskeletal (MSK) conditions has not been balanced by a sufficient increase in healthcare providers. Scalability challenges are being addressed through the use of artificial intelligence (AI) in some healthcare sectors, with this showing potential to also improve MSK care. Digital care programs (DCP) generate automatically collected data, thus making them ideal candidates for AI implementation into workflows, with the potential to unlock care scalability.

Recovering Work Productivity in a Population With Chronic Musculoskeletal Pain: Unveiling the Value and Cost-Savings of a Digital Care Program.

Objective: To investigate potential savings obtained from restoring productivity in employees with chronic MSK pain through a digital care program (DCP).

Methods: Secondary analysis of a prospective longitudinal study assessing cumulative savings overall or across several industry sectors by analyzing changes in Work Productivity and Activities Impairment (WPAI questionnaire).

Results: Employees from 50 U.

Digital Care Program for Urinary Incontinence in Females: A Large-Scale, Prospective, Cohort Study.

Female urinary incontinence (UI) is highly prevalent in the US (>60%). Pelvic floor muscle training (PFMT) represents first-line care for UI; however, access and adherence challenges urge new care delivery models. This prospective cohort study investigates the feasibility and safety of a remote digital care program (DCP) combining education and PFMT with real-time biofeedback with an average duration of 10 weeks.

The potential of a multimodal digital care program in addressing healthcare inequities in musculoskeletal pain management.

Digital interventions have emerged as a solution for time and geographical barriers, however, their potential to target other social determinants of health is largely unexplored. In this post-hoc analysis, we report the impact of social deprivation on engagement and clinical outcomes after a completely remote multimodal musculoskeletal (MSK) digital care program managed by a culturally-sensitive clinical team. Patients were stratified in five categories according to their social deprivation index, and cross-referenced with their race/ethnicity, rurality and distance to healthcare facilities.

Comparing Digital to Conventional Physical Therapy for Chronic Shoulder Pain: Randomized Controlled Trial.

Background: Chronic shoulder pain (CSP) is a common condition with various etiologies, including rotator cuff disorders, adhesive capsulitis, shoulder instability, and shoulder arthritis. It is associated with substantial disability and psychological distress, resulting in poor productivity and quality of life. Physical therapy constitutes the mainstay treatment for CSP, but several barriers exist in accessing care.

Managing Musculoskeletal Pain in Older Adults Through a Digital Care Solution: Secondary Analysis of a Prospective Clinical Study.

Background: Aging is closely associated with an increased prevalence of musculoskeletal conditions. Digital musculoskeletal care interventions emerged to deliver timely and proper rehabilitation; however, older adults frequently face specific barriers and concerns with digital care programs (DCPs).

Objective: This study aims to investigate whether known barriers and concerns of older adults impacted their participation in or engagement with a DCP or the observed clinical outcomes in comparison with younger individuals.

Randomized-controlled trial assessing a digital care program versus conventional physiotherapy for chronic low back pain.

Low back pain (LBP) is the world's leading cause of years lived with disability. Digital exercise-based interventions have shown great potential in the management of musculoskeletal conditions, promoting access and easing the economic burden. However, evidence of their effectiveness for chronic LBP (CLBP) management compared to in-person physiotherapy has yet to be unequivocally established.

System-wide integration of patient reported outcome measure collection through an electronic medical record system: A state-wide retrospective study.

Background And Purpose: In spine neurosurgery practice, patient-reported outcome measures (PROMs) are tools used to convey information about a patient's health experience and are an integral component of a clinician's decision-making process as they help guide treatment strategies to improve outcomes and minimize pain. Currently, there is limited research showing effective integration strategies of PROMs into electronic medical records. This study aims to provide a framework for other healthcare systems by outlining the process from start to finish in seven Hartford Healthcare Neurosurgery outpatient spine clinics throughout the state of Connecticut.

Engagement and Utilization of a Complete Remote Digital Care Program for Musculoskeletal Pain Management in Urban and Rural Areas Across the United States: Longitudinal Cohort Study.

Background: Musculoskeletal (MSK) conditions are the number one cause of disability worldwide. Digital care programs (DCPs) for MSK pain management have arisen as alternative care delivery models to circumvent challenges in accessibility of conventional therapy. Despite the potential of DCPs to reduce inequities in accessing care, the outcomes of such interventions in rural and urban populations have yet to be studied.

Sleep Disturbance in Musculoskeletal Conditions: Impact of a Digital Care Program.

Background: Musculoskeletal (MSK) pain is highly prevalent worldwide, resulting in significant disability, and comorbid sleep disturbances. Digital therapy for MSK pain can provide significant improvements in care access, alongside pain and disability reductions. However, studies on the effect of such programs on sleep are lacking.

Long-Term Clinical Outcomes of a Remote Digital Musculoskeletal Program: An Ad Hoc Analysis from a Longitudinal Study with a Non-Participant Comparison Group.

Digital solutions have emerged as an alternative to conventional physiotherapy, particularly for chronic musculoskeletal pain (CMP) management; however, its long-term effects remain largely unexplored. This study focuses on patients reporting CMP, assessing 1-year clinical outcomes after a multimodal digital care program (DCP) versus non-participants, who enrolled in the program but never engaged in a single exercise session or partook of the educational content made available to them. In this longitudinal study ad-hoc analysis, pain and functionality outcomes at 1-year reassessment were studied, focusing on the odds of reaching minimal clinically important difference (MCID) and, overall average reduction in both outcomes.

Impact on productivity impairment of a digital care program for chronic low back pain: A prospective longitudinal cohort study.

Background: Low back pain (LBP) is the leading cause of disability in the United States and the main reason for absenteeism. Successful management of chronic LBP (CLBP) is dependent on multimodal evidence-based interventions. Digital interventions (DI) may ease accessibility to such treatments, increasing adherence, while reducing healthcare-related costs.

Fear Avoidance Beliefs in Upper-Extremity Musculoskeletal Pain Conditions: Secondary Analysis of a Prospective Clinical Study on Digital Care Programs.

Background: Fear-avoidance beliefs (FAB) have been associated with poorer prognosis and decreased adherence to exercise-based treatments in musculoskeletal (MSK) pain. However, the impact of high FAB on adherence and outcomes in upper extremity MSK (UEMSK) pain is poorly explored, particularly through exercise-based digital care programs (DCP).

Objective: Assess the adherence levels, clinical outcomes and satisfaction in patients with UEMSK pain and elevated FAB after a fully remote multimodal DCP.

Racial and Ethnic Differences in Outcomes of a 12-Week Digital Rehabilitation Program for Musculoskeletal Pain: Prospective Longitudinal Cohort Study.

Background: Musculoskeletal (MSK) pain disproportionately affects people from different ethnic backgrounds through higher burden and less access to care. Digital care programs (DCPs) can improve access and help reduce inequities. However, the outcomes of such programs based on race and ethnicity have yet to be studied.

Digital Care Programs for Chronic Hip Pain: A Prospective Longitudinal Cohort Study.

Chronic hip pain is a cause of disability worldwide. Digital interventions (DI) may promote access while providing proper management. This single-arm interventional study assesses the clinical outcomes and engagement of a completely remote multimodal DI in patients with chronic hip pain.

Digital rehabilitation for hand and wrist pain: a single-arm prospective longitudinal cohort study.

Introduction: Wrist and hand represent the third most common body part in work-related injuries, being associated with long-term absenteeism. Telerehabilitation can promote access to treatment, patient adherence, and engagement, while reducing health care-related costs.

Objective: Report the results of a fully remote digital care program (DCP) for wrist and hand pain (WP).

An Artificial Neural Network Model for the Prediction of Perioperative Blood Transfusion in Adult Spinal Deformity Surgery.

Prediction of blood transfusion after adult spinal deformity (ASD) surgery can identify at-risk patients and potentially reduce its utilization and the complications associated with it. The use of artificial neural networks (ANNs) offers the potential for high predictive capability. A total of 1173 patients who underwent surgery for ASD were identified in the 2017-2019 NSQIP databases.

Digital Rehabilitation for Elbow Pain Musculoskeletal Conditions: A Prospective Longitudinal Cohort Study.

Elbow musculoskeletal pain (EP) is a major cause of disability. Telerehabilitation has shown great potential in mitigating musculoskeletal pain conditions, but EP is less explored. This single-arm interventional study investigates clinical outcomes and engagement levels of a completely remote multimodal digital care program (DCP) in patients with EP.

Digital Rehabilitation for Acute Low Back Pain: A Prospective Longitudinal Cohort Study.

Background: Low back pain (LBP) has a lifetime prevalence of 70-80%. Access to timely and personalized, evidence-based care is key to prevent chronic progression. Digital solutions may ease accessibility to treatment while reducing healthcare-related costs.

Impacts of Digital Care Programs for Musculoskeletal Conditions on Depression and Work Productivity: Longitudinal Cohort Study.

Background: Comorbidity between musculoskeletal (MSK) pain and depression is highly common, and is associated with a greater symptom burden and greater loss of work productivity than either condition alone. Multimodal care programs tackling both physical and mental health components may maximize productivity recovery and return to work. Digital delivery of such programs can facilitate access, ensure continuity of care, and enhance patient engagement.

The Effect of a Multidisciplinary Spine Clinic on Time to Care in Patients with Chronic Back and/or Leg Pain: A Propensity Score-Matched Analysis.

Chronic back and leg pain are leading causes of disability worldwide. The purpose of this study was to compare the care in a unidisciplinary (USC) versus multidisciplinary (MSC) spine clinic, where patients are evaluated by different specialists during the same office visit. Adult patients presenting with a chief complaint of back and/or leg pain between June 2018 and July 2019 were assessed for eligibility.