Precision Rehabilitation: Optimizing Function, Adding Value to Health Care

Objective Clinical Measurement Tools for Functional Evaluation of the Surgical Patient

Following knee surgery, clinicians have traditionally used visually rated or time-based assessments of lower extremity movement quality to measure surgical outcomes, plan rehabilitation interventions, and measure success. These methods of assessment are prone to error and do not fully capture a patient's inefficient movement patterns post surgery. Further, currently available systems which objectively measure kinematics during these tasks are expensive and unidimensional. For these reasons, recent research has called for the development of objective and low-cost precision rehabilitation tools to improve clinical measurement of movement tasks. The purpose of this article is to highlight two such tools and their applications to knee surgery. The systems highlighted within this article are the Mizzou Point-of-Care Assessment System (MPASS) and the Mizzou Knee Arthrometer Testing System (MKATS). MPASS has demonstrated high levels of agreement with the gold-standard Vicon system in measuring kinematics during sit-to-stand (R > 0.71), lateral step-down (intraclass correlation coefficient [ICC] > 0.55, apart from ankle flexion), and drop vertical jump tasks (ICC > 0.62), as well as gait (R > 0.87). MKATS has been used to quantify differences in tibiofemoral motion between groups during lateral step-down, step-up-and-over, and step-up/step-down tasks. Objective measurement of clinical tasks using portable and inexpensive instruments, such as the MPASS and MKATS, can help clinicians identify inefficient movement patterns and asymmetries which may damage and wear down supporting structures within the knee and throughout the kinetic chain causing pain and discomfort. Identifying these issues can help clinicians to plan interventions and measure their progress at a lower cost than currently available systems. The MPASS and MKATS are useful tools which have many applications to knee surgery.

Leveraging Emerging Technologies to Expand Accessibility and Improve Precision in Rehabilitation and Exercise for People with Disabilities

Physical rehabilitation and exercise training have emerged as promising solutions for improving health, restoring function, and preserving quality of life in populations that face disparate health challenges related to disability. Despite the immense potential for rehabilitation and exercise to help people with disabilities live longer, healthier, and more independent lives, people with disabilities can experience physical, psychosocial, environmental, and economic barriers that limit their ability to participate in rehabilitation, exercise, and other physical activities. Together, these barriers contribute to health inequities in people with disabilities, by disproportionately limiting their ability to participate in health-promoting physical activities, relative to people without disabilities. Therefore, there is great need for research and innovation focusing on the development of strategies to expand accessibility and promote participation in rehabilitation and exercise programs for people with disabilities. Here, we discuss how cutting-edge technologies related to telecommunications, wearables, virtual and augmented reality, artificial intelligence, and cloud computing are providing new opportunities to improve accessibility in rehabilitation and exercise for people with disabilities. In addition, we highlight new frontiers in digital health technology and emerging lines of scientific research that will shape the future of precision care strategies for people with disabilities.

ReDWINE: A clinical datamart with text analytical capabilities to facilitate rehabilitation research

Rehabilitation research focuses on determining the components of a treatment intervention, the mechanism of how these components lead to recovery and rehabilitation, and ultimately the optimal intervention strategies to maximize patients' physical, psychologic, and social functioning. Traditional randomized clinical trials that study and establish new interventions face challenges, such as high cost and time commitment. Observational studies that use existing clinical data to observe the effect of an intervention have shown several advantages over RCTs. Electronic Health Records (EHRs) have become an increasingly important resource for conducting observational studies. To support these studies, we developed a clinical research datamart, called ReDWINE (Rehabilitation Datamart With Informatics iNfrastructure for rEsearch), that transforms the rehabilitation-related EHR data collected from the UPMC health care system to the Observational Health Data Sciences and Informatics (OHDSI) Observational Medical Outcomes Partnership (OMOP) Common Data Model (CDM) to facilitate rehabilitation research. The standardized EHR data stored in ReDWINE will further reduce the time and effort required by investigators to pool, harmonize, clean, and analyze data from multiple sources, leading to more robust and comprehensive research findings. ReDWINE also includes deployment of data visualization and data analytics tools to facilitate cohort definition and clinical data analysis. These include among others the Open Health Natural Language Processing (OHNLP) toolkit, a high-throughput NLP pipeline, to provide text analytical capabilities at scale in ReDWINE. Using this comprehensive representation of patient data in ReDWINE for rehabilitation research will facilitate real-world evidence for health interventions and outcomes.