While evidence-based guidelines for the management of sTBI exist, their applicability in low-resource environments is limited, as the resources required to follow guidelines are often unavailable. To address this gap, a consensus process involving clinical experts was conducted in Colombia to develop a series of management protocols to articulate treatment options for TBI specific to different levels of resources and complexity across the prehospital, emergency department (ED), neurosurgery and intensive care (ICU) phases. The set of protocols was called BOOTStraP \[Beyond One Option for Treatment of Traumatic Brain Injury: A Stratified Protocol\]. The BOOTStraP protocols are divided into four main categories, which are based on 13 recommendations from 20 clinical experts as follows: 1) management in a basic or advanced ambulance (pre-hospital setting), 2) ED care in a low or medium-high complexity institution with or without access to a CT-Scan, 3) neurosurgery department, and 4) intermediate or ICU availability. Each one is subcategorized according to the TBI severity and can be used as a guiding tool by health professionals (e.g. EMS technicians, nurses, physicians, etc.) The user can select from a menu of treatment options depending upon resource availability (medicine, equipment, clinician training, and skill) to follow best practices given the prevailing circumstances.
This is a prospective, observational, before and after study, pilot investigation of the treatment process and outcomes for patients with TBI, who are transported by any means to a medical center for treatment. Data will be collected for each patient through the four phases of prehospital, ED, neurosurgery, and ICU, or until the patient expires. Data will be abstracted from hospital medical records.
From the initiation of the "before" phase, data for each patient will be collected from the initial patient encounter to hospital discharge, for 3 months. The BOOTStraP protocol will be implemented during the month following the end of initial data collection. After implementation ("after" phase), data for each patient will be collected from initial patient encounters to hospital discharge, for 3 months. The treatment protocols to be implemented at each center are available in the open-access published paper at the NIH PMC website: (https://pmc.ncbi.nlm.nih.gov/articles/PMC7055642/).
Each day during active data collection, the Data Collector (DC) for each site arrives at the hospital, accesses the ED records, and identifies patients admitted during the previous 24 hours who may meet inclusion criteria for the study. The DC ascertains information about the potential included patients from ED records and attending caregivers, and identifies those screened and excluded, and those screened and included. Data are transcribed from ED records and caregiver interactions directly into a web-based database. The DC completes data abstraction for included patients. The DC identifies the location and status of newly included patients, and transcribes data about each patient into the database, up to and including the current status. After completing data abstraction for new patients entered within the previous 24 hours, the DC identifies the location and status of patients previously included in the study, and transcribes data about each patient into the database, up to and including the current status. Each day during active data collection, the Study Coordinator (SC) accesses the electronic records and reviews new data entries for errors and missing data. Twice monthly, the SC visits each study site, compares abstracted data with chart records, and meets with the site DC to discuss errors and missing data. The SC and DC make any revisions together, directly into the database. During these visits, the SC records narrative information about reasons for errors and missing data, what is working and not working, and the DCs' perspectives on the barriers to and facilitators of conducting the study. The SC transcribes this narrative information into a qualitative data collection/analysis database. Categorical data will be summarized as frequencies and percentages, while continuous variables will be summarized using mean, median, minimum, maximum, and 25th and 75th percentiles. We will record narrative information from personnel at each site to investigate the barriers to and facilitators of data collection and intervention implementation. These data will be entered into a qualitative data analysis instrument, and Grounded Theory will be utilized to identify common themes. Adherence will be derived by tracking if each recommended BOOTStraP resource was available (yes/no), and if yes, whether it was utilized (yes/no). The analysis of adherence will be presented by treatment phase (prehospital, emergency department, neurosurgery, and intensive care unit). The percentage of adherence to the BOOTStrap protocol will be used as a summary statistic. The study is descriptive in nature and outcome data will be summarized descriptively by phase (before and after). The analysis will explore correlations between adherence levels by phase and individual treatments on outcome data. No hypothesis will be tested. The sample size for the study was determined based on feasibility and no formal calculation of power was performed. Implementation of BOOTStraP should increase survival to hospital discharge, and improve GOS-E at discharge. We expect there will be many barriers to implementation, especially in the pre-hospital stage. We expect adherence to protocols to be modest. This study will provide the basis to plan for a larger multi-center international study.
