SCIREHAB Background and Overview
Inpatient rehabilitation for spinal cord injury (SCI) has been studied largely as an undifferentiated black box. Research has not addressed which specific therapy interventions, medical procedures, patient education, counseling, or activities are effective when offered in various combinations or sequences, for specific types of patients and impairments. SCIREHAB: Improving Outcomes through Practice-Based Evidence proposes to open the black box of acute rehabilitation for individuals with SCI and create sophisticated, outcomes-based tools for clinical decision-making.
Previous research has focused on the effects of acute SCI rehabilitation interventions in the aggregate, without examining effects of specific components or of the interaction of components with individual patient characteristics. Since effects of SCI can be wide ranging, and health care resources are limited, making an optimal choice of rehabilitation interventions based on a patient’s needs has the potential to improve patient outcomes and lower health care costs significantly.
This 5-year project will use Clinical Practice Improvement (CPI) research methodology to isolate specific components of rehabilitation interventions. CPI can determine how, and to what degree, each component is associated with outcomes. CPI is an outcomes-directed, model-building process that has identified and established effective and efficient evidence-based treatment guidelines in stroke rehabilitation and other diagnostic groups and clinical settings.
CPI methodology will be used to identify specific rehabilitation interventions that are most effective for specific patient types with delineated neurological impairments. Differential effectiveness will be judged by eight primary outcomes of acute rehabilitation: (1) neurologic recovery and (2) functional independence attained during initial rehabilitation and the first year after injury; (3) discharge to home; (4) medical complications and (5) rehospitalization in the first year after injury; and (6) return to productive activity, (7) the extent of societal participation, and (8) perceived quality of life reported at the first anniversary of injury.
Treatment effects will be examined controlling for differences in patient characteristics and for severity of injury and illness. CPI methodology allows a large number of intervention-by-impairment interactions to be examined, while patient individual differences, including severity of spinal cord injury and medical complications, are controlled for. The methodology is very efficient at identifying interventions that are associated with better outcomes.
Led by the Rocky Mountain Regional Spinal Injury System (RMRSIS) at Craig Hospital, the project is a collaborative research partnership among six SCI rehabilitation facilities (including five SCI Model Systems) and the Institute for Clinical Outcomes Research (ICOR) at International Severity Information Systems (ISIS) with extensive experience applying CPI methodology. Subjects will be 1,500 patients receiving acute rehabilitation for SCI at one of the participating centers. This study will leverage the state-of-the-art treatment expertise of six geographically and demographically diverse acute rehabilitation centers.
Detailed daily documentation of interventions performed in each therapy session, medical procedures delivered (including medications and surgeries, nursing interventions, patient education, and psychosocial services) will be recorded for a patient’s entire acute rehabilitation stay. Standardized documentation to be used in all centers will be developed by clinicians from the participating facilities in ten disciplines (physical therapy, occupational therapy, speech/language therapy, respiratory therapy, therapeutic recreation, psychology, social work / rehabilitation counseling, case management /discharge planning, nursing, and physicians) in collaboration with SCI researchers and ICOR staff. It will reflect current practice and existing research while ensuring data points are optimal for statistical analyses. Data quality assurance will include systematic training for clinical staff and chart abstracters, inter-rater reliability checks, and electronic data verification.