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Despite the relatively low incidence of traumatic spinal cord injury (tSCI), the management and care of persons with tSCI can be resource intensive and complex, spanning multiple phases of care and disciplines. Using a simulation model built with a system level view of the healthcare system allows for prediction of the impact of interventions on patient and system outcomes from injury through to community reintegration after tSCI. As has been previously described, the Access to Care and Timing (ACT) project developed a simulation model for tSCI care using techniques from operations research. The objective of this article is to briefly describe the methodology and the application of the ACT Model, as it was used in several of the articles in this focus issue. The approaches employed in this model provide a framework to look into the complexity of interactions both within and among the different SCI programs, sites, and phases of care. [ABSTRACT FROM AUTHOR]

Neurologic impairment after spinal cord injury (SCI) is currently measured and classified by functional examination. Biological markers that objectively classify injury severity and predict outcome would greatly facilitate efforts to evaluate acute SCI therapies. The purpose of this study was to determine how well inflammatory and structural proteins within the cerebrospinal fluid (CSF) of acute traumatic SCI patients predicted American Spinal Injury Association Impairment Scale (AIS) grade conversion and motor score improvement over 6 months. Fifty acute SCI patients (29 AIS A, 9 AIS B, 12 AIS C; 32 cervical, 18 thoracic) were enrolled and CSF obtained through lumbar intrathecal catheters to analyze interleukin (IL)-6, IL-8, monocyte chemotactic protein (MCP)-1, tau, S100β, and glial fibrillary acidic protein (GFAP) at 24 h post-injury. The levels of IL-6, tau, S100β, and GFAP were significantly different between patients with baseline AIS grades of A, B, or C. The levels of all proteins (IL-6, IL-8, MCP-1, tau, S100β, and GFAP) were significantly different between those who improved an AIS grade over 6 months and those who did not improve. Linear discriminant analysis modeling was 83% accurate in predicting AIS conversion. For AIS A patients, the concentrations of proteins such as IL-6 and S100β correlated with conversion to AIS B or C. Motor score improvement also was strongly correlated with the 24-h post-injury CSF levels of all six biomarkers. The analysis of CSF can provide valuable biological information about injury severity and recovery potential after acute SCI. Such biological markers may be valuable tools for stratifying individuals in acute clinical trials where variability in spontaneous recovery requires large recruitment cohorts for sufficient power. [ABSTRACT FROM AUTHOR]

Background: A patient’s journey through the health care system is influenced by clinical and system processes across the continuum of care. Methods: To inform optimized access to care and patient flow for individuals with traumatic spinal cord injury (tSCI), we developed a simulation model that can examine the full impact of therapeutic or systems interventions across the care continuum for patients with traumatic spinal cord injuries. The objective of this paper is to describe the detailed development of this simulation model for a major trauma and a rehabilitation centre in British Columbia (BC), Canada, as part of the Access to Care and Timing (ACT) project and is referred to as the BC ACT Model V1.0. Findings: To demonstrate the utility of the simulation model in clinical and administrative decision-making we present three typical scenarios that illustrate how an investigator can track the indirect impact(s) of medical and administrative interventions, both upstream and downstream along the continuum of care. For example, the model was used to estimate the theoretical impact of a practice that reduced the incidence of pressure ulcers by 70%. This led to a decrease in acute and rehabilitation length of stay of 4 and 2 days, respectively and a decrease in bed utilization of 9% and 3% in acute and rehabilitation. Conclusion: The scenario analysis using the BC ACT Model V1.0 demonstrates the flexibility and value of the simulation model as a decision-making tool by providing estimates of the effects of different interventions and allowing them to be objectively compared. Future work will involve developing a generalizable national Canadian ACT Model to examine differences in care delivery and identify the ideal attributes of SCI care delivery. [ABSTRACT FROM AUTHOR]

AbstractInternational Classification of Diseases (ICD) codes are used to document patient morbidity in administrative databases. Although administrative data are used for research purposes, the validity of the data to accurately describe clinical diagnostic information is uncertain. We compared the clinical diagnoses for spinal cord and column injuries from a longitudinal patient registry, the Rick Hansen Spinal Cord Injury Registry (RHSCIR), to the ICD-10 spinal injury codes from the Discharge Abstract Database (DAD) at one institution. There were 603 RHSCIR participants with data describing the spinal cord injury, and 341 had data on the spinal column injury. The validity of DAD data to describe spinal injuries was evaluated using the sensitivity and positive predictive values of specific ICD-10 codes; 5.3% of the spinal column injuries and 10.9% of the spinal cord injuries documented in RHSCIR were missed in data from the DAD using ICD-10 codes. The most problematic spinal column ICD-10 code was the dislocation of the cervical vertebra (S13.1); only 14.0% of the dislocations of the cervical vertebrae in RHSCIR were correctly coded in the DAD. The most problematic spinal cord injury ICD-10 code was the incomplete lesion of the lumbar spinal cord (S34.1X); 66.7% of incomplete lesions of the lumbar spinal cord in RHSCIR were correctly coded in the DAD. The validity of DAD data to code spinal injuries is variable, and cannot be reliably used to classify all types of spinal injuries. Patient registries, such as RHSCIR, should be used if accurate detailed diagnostic data are required. [ABSTRACT FROM AUTHOR]