Inaccuracies Exist in Trauma Registry Data Regarding Shooting Intent for Pediatric Firearm Injuries.

BACKGROUND: Institutional trauma registries, which contribute data to the National Trauma Data Bank, are a fundamental resource for trauma research, though may have significant deficits in data accuracy. We hypothesize that inaccuracies in shooting intent exist at institutional registries of pediatric trauma centers. METHODS: Pediatric firearm injuries (ages 0-17 years) in a single county between 2018 and 2020 were identified from three Level I trauma centers. Demographics and Ecodes were extracted from each registry and shooting intent was compared to retrospective review of the hospital records, including bystander as a category. RESULTS: Of 410 pediatric firearm injuries included, the majority were male (84%), non-Hispanic Black (45%) or Hispanic White (40%), and 15-17 years old (69%). Compared to final reviewer designations, the trauma registry's assault category showed high sensitivity (88.5%), but low specificity (67%), and only 78% accuracy. The trauma registry's accidental category was less sensitive (88%) but more specific (88%), with an accuracy of 88%. The most specific and accurate intention category was intentional self-harm, which had 79% sensitivity, 99.5% specificity, and 99% accuracy. Bystander shootings were most commonly categorized as assault (75%), followed by accidental (18%). CONCLUSION: Significant inaccuracies in coding of pediatric firearm shooting intent exist in trauma registries. Additionally, there is no Ecode for bystander shootings, which overestimates other intent categories. Our study highlights the importance of improving the accuracy of firearm injury data collection to provide a better understanding of firearm injuries at a national level to inform targeted prevention efforts specific to shooting types. LEVEL OF EVIDENCE: III.

Spine injuries among severely injured trauma patients: A retrospective single-center cohort study.

BACKGROUNDS AND AIMS: We aimed to determine the incidence and severity of spine injuries among severely injured trauma patients (Injury Severity Score (ISS)/New Injury Severity Score (NISS) > 15) treated in a single tertiary trauma center over 15 years. We also wanted to compare the demographics between patients with and without spine injuries and to determine the mortality of spine-injury patients. METHODS: Data from the years 2006-2020 from the Helsinki Trauma Registry (HTR), a local trauma registry of the trauma unit of the Helsinki University Hospital (HUH), were reviewed. We divided patients into two groups, namely those with traumatic spine injury (TSI) and those without traumatic spine injury (N-TSI). TSI patients were further subdivided into groups according to the level of injury (cervical, thoracolumbar, or multilevel) and the presence of neurological symptoms. RESULTS: We included 2529 patients: 1336 (53%) had a TSI and 1193 (47%) had N-TSI. TSI patients were injured more frequently by a high-fall mechanism (37% vs 21%, p < 0.001). Among TSI patients, 38% of high-fall injuries were self-inflicted. High falls, young age, and female gender were overrepresented in spine-injury patients with a self-inflicted injury mechanism. Cervical spine-injury patients were mostly elderly persons injured by a low-energy mechanism. CONCLUSIONS: Unlike other severely injured trauma patients, severely injured trauma patients with spine injuries are more frequently injured by a high-fall mechanism and self-injury.

October 7th Mass Casualty Attack in Israel: Injury Profiles of Hospitalized Casualties.

Background: On Saturday, October 7th, approximately 3000 Hamas-led terrorists infiltrated Israel's southern border and attacked civilians and soldiers. Terrorists murdered close to 1200 people, abducted hundreds, and injured thousands. This surprise attack involved an unprecedented number of casualties. This article describes the injuries and outcomes of the hospitalized casualties. Methods: Hospitalized trauma casualties with an injury date of October 7 to 8, 2023, and with ICD9 E-codes E979 and E990 through E999, were extracted from the Israel National Trauma Registry. Demographic, injury, and hospital resource-use data were analyzed. Results: A total of 630 hospitalized casualties (277 civilians and 353 soldiers) suffered from gunshot wounds (90%), explosion-related wounds (19%), and multiple injury mechanisms (16%). The median age for civilians was 33 years (ages <1-88) and 21 years for soldiers. The most frequently injured body regions were lower (49%) and upper (42%) extremities, abdominal (28%), and thoracic (23%) injuries. Four hundred thirty-one (68%) patients underwent surgery, of which 240 within 12 hours. Over half of the severe and critical (Injury Severity Score 16+) casualties were discharged to a rehabilitation center. In-hospital mortality rate was 2.5%. Conclusion: Israel's hospitals faced many challenges following the mega mass casualty incident, including the absorption, diagnosis, treatment, and rehabilitation of a massive number of casualties. Hospitals needed to immediately repurpose to provide additional imaging equipment and operating rooms. Additionally, the huge demand for rehabilitation resources necessitated immediate reorganization and transformation of existing medical facilities to accommodate the many casualties requiring rehabilitation. The injury details and outcomes from this mega mass casualty incident provide important information for planning and preparedness at local, regional, and national levels.

Improving post-injury follow-up survey response: incorporating automated modalities.

BACKGROUND: Incorporating post-discharge data into trauma registries would allow for better research on patient outcomes, including disparities in outcomes. This pilot study tested a follow-up data collection process to be incorporated into existing trauma care systems, prioritizing low-cost automated response modalities. METHODS: This investigation was part of a larger study that consisted of two protocols with two distinct cohorts of participants who experienced traumatic injury. Participants in both protocols were asked to provide phone, email, text, and mail contact information to complete follow-up surveys assessing patient-reported outcomes six months after injury. To increase follow-up response rates between protocol 1 and protocol 2, the study team modified the contact procedures for the protocol 2 cohort. Frequency distributions were utilized to report the frequency of follow-up response modalities and overall response rates in both protocols. RESULTS: A total of 178 individuals responded to the 6-month follow-up survey: 88 in protocol 1 and 90 in protocol 2. After implementing new follow-up contact procedures in protocol 2 that relied more heavily on the use of automated modalities (e.g., email and text messages), the response rate increased by 17.9 percentage points. The primary response modality shifted from phone (72.7%) in protocol 1 to the combination of email (47.8%) and text (14.4%) in protocol 2. CONCLUSIONS: Results from this investigation suggest that follow-up data can feasibly be collected from trauma patients. Use of automated follow-up methods holds promise to expand longitudinal data in the national trauma registry and broaden the understanding of disparities in patient experiences.

Impacting trauma care in resource-limited settings: Lessons learned from Tanzania's web-based trauma registry initiatives.

BACKGROUND: Trauma significantly impacts Tanzanian healthcare. Lacking standardized hospital-based minimal trauma data sets places further challenges for policymakers. In other resource-limited countries, implementing trauma systems and registries has reduced injury mortalities. In 2013, we introduced an electronic trauma registry, iTRAUMATM at the Tanzanian Muhimbili Orthopedic Institute (MOI) but noted several drawbacks. In 2023, we introduced a robust web-based trauma registry platform. This study assesses the feasibility and utility of implementing the platform at MOI and summarizes challenges, lessons, and results compared to existing systems. METHODS: This prospective observational study involved clinicians collecting data directly on the platform at the point-of-care, following specific training. Semi-structured interviews with local stakeholders identified challenges and areas for improvement. Data were reported from July to December 2023. RESULTS: Data from 2930 patients showed 59% of injuries were from road traffic collisions (RTCs), with 43% of patients arriving at MOI by non-ambulances. Our findings show that non-ambulance arrivals were associated with higher injury severity (p < 0.026), mortalities (p < 0.017), and delayed hospital arrival (p < 0.004), underscoring the critical role of prompt transport in trauma management. The new platform identified trauma care gaps, with a mean arrival-to-care time of 29.89 min, prompting trauma training at MOI to enhance clinician capacities. It also demonstrated superiority over existing systems by improving data completeness, timeliness, and usability. Challenges included gaining support for the platform's functionality, technology integration, and navigating administrative changes. With continued communication, stakeholder acceptance and support were achieved. CONCLUSION: The web-based platform has become MOI's standard trauma database, demonstrating its feasibility and utility. It overcame the existing challenges of data completeness, timeliness, and usability for policymaking. Positive feedback has prompted plans to expand the platform to other hospitals, benefiting clinical benchmarking and trauma preventive efforts. Ensuring sustainability requires involvement from the Ministry of Health, ongoing training, functionality enhancements, and strengthened global partnerships.

Survey of Satisfaction and Utility of an Application to Find Inconsistencies in Trauma Registry Data.

Introduction: Data quality is essential for trauma registries, but few tools have been developed to maximize it. The author's center created a new application to automatically identify >500 logic errors in registry data and produce individualized data quality reports for staff. Objective metrics indicated the application is effective, but staff perceptions were unknown. The aim of this project was to assess registry staff satisfaction with and perceived usefulness of the new application. Methods: Anonymous cross-sectional online survey with 5-point Likert scales and free-text responses. Results: Of 10 eligible staff members who use the new application, 8 responded to the survey. Confidence in data accuracy before the new application was generally low but unanimously higher after implementation (8/8; 95% CI, 5/8-8/8). Respondents found the application at least somewhat helpful overall (6/6; 95% CI, 3/6-6/6; 2 nonresponses), with 5/6 finding it very helpful. Respondents were at least somewhat satisfied with the new application (8/8; 95% CI, 5/8-8/8), with 4/8 being very satisfied. There was minimal negative feedback other than the new process being initially overwhelming. Conclusions: Respondents found the new application to be beneficial in several ways, including indirectly. Additional research is needed to be able to generalize these single center findings and determine best practices for data validation, but software-based approaches to augment more common data validation processes may be a beneficial and welcomed job aid for registry staff.

Association of trauma classifications to long-term outcome in blunt trauma patients.

PURPOSE: The impact of major trauma is long lasting. Although polytrauma patients are currently identified with the Berlin polytrauma criteria, data on long-term outcomes are not available. In this study, we evaluated the association of trauma classification with long-term outcome in blunt-trauma patients. METHODS: A trauma registry of a level I trauma centre was used for patient identification from 1.1.2006 to 31.12.2015. Patients were grouped as follows: (1) all severely injured trauma patients; (2) all severely injured polytrauma patients; 2a) severely injured patients with AIS ≥ 3 on two different body regions (Berlin-); 2b) severely injured patients with polytrauma and a physiological criterion (Berlin+); and (3) a non-polytrauma group. Kaplan-Meier survival analysis was performed to estimate differences in mortality between different groups. RESULTS: We identified 3359 trauma patients for this study. Non-polytrauma was the largest group (2380 [70.9%] patients). A total of 500 (14.9%) patients fulfilled the criteria for Berlin + definition, leaving 479 (14.3%) polytrauma patients in Berlin- group. Berlin + patients had the highest short-term mortality compared with other groups, although the difference in cumulative mortality gradually plateaued compared with the non-polytrauma patient group; at the end of the 10-year follow up, the non-polytrauma group had the greatest mortality due to the high number of patients with traumatic brain injury (TBI). CONCLUSION: Excess mortality of polytrauma patients by Berlin definition occurs in the early phase (30-day mortality) and late deaths are rare. TBI causes high early mortality followed by increased long-term mortality.

Alcohol-Intoxicated Patients With Blunt Trauma and Head Injuries Have Better Outcomes Than Sober Patients.

BACKGROUND: Although alcohol-intoxicated patients have difficulties evaluating their consciousness level and being transported prehospital, there is some evidence that the survival outcomes for alcohol-intoxicated patients with head injuries are better. The present study evaluated whether the survival and brain function outcomes in alcohol-intoxicated trauma patients with head injuries were better than those in sober patients using the Japan Trauma Data Bank (JTDB), a nationwide trauma registry in Japan. METHODS: The 17,823 patients with blunt trauma, including head injuries, who were registered in the JTDB database between January 2019 and December 2021 were retrospectively analyzed. Logistic regression analyses were performed for in-hospital survival in patients with blunt trauma, including those with head injuries, and for good brain function based on the Glasgow outcome scale (GOS) in patients with only head injuries. Survival rates by head injury score using the abbreviated injury scale (AIS) 2008 or injury severity score (ISS) categories were compared between drinking and nondrinking groups. RESULTS: Drinking significantly affected survival (odds ratio 1.800, p<0.001) and good brain function (odds ratio 1.546, p<0.001), as indicated by logistic regression analysis using head injuries alone or blunt multisite trauma (including head injuries), respectively. According to analyses by the ISS category or head AIS score, there were significant differences between the drinking and non-drinking groups in several categories (ISS 9-15, 16-24, and 25-40 and AIS 3 and 5) regarding survival rates with blunt trauma, including head injuries, or good GOS rates with head injuries alone. CONCLUSIONS: The survival rates for blunt trauma, including head injuries, and the prognosis for brain function based on the GOS were better in the drinking group than in the control group for cases with head injuries alone. A multivariate analysis also showed that alcohol consumption was significantly associated with better outcomes.

Injury severity bias in missing prehospital vital signs: Prevalence and implications for trauma registries.

BACKGROUND: Vital signs are important factors in assessing injury severity and guiding trauma resuscitation, especially among severely injured patients. Despite this, physiological data are frequently missing from trauma registries. This study aimed to evaluate the extent of missing prehospital data in a hospital-based trauma registry and to assess the associations between prehospital physiological data completeness and indicators of injury severity. METHODS: A retrospective review was conducted on all adult trauma patients brought directly to a level 1 trauma center in Toronto, Ontario by paramedics from January 1, 2015, to December 31, 2019. The proportion of missing data was evaluated for each variable and patterns of missingness were assessed. To investigate the associations between prehospital data completeness and injury severity factors, descriptive and unadjusted logistic regression analyses were performed. RESULTS: A total of 3,528 patients were included. We considered prehospital data missing if any of heart rate, systolic blood pressure, respiratory rate or oxygen saturation were incomplete. Each individual variable was missing from the registry in approximately 20 % of patients, with oxygen saturation missing most frequently (n = 831; 23.6 %). Over 25 % (n = 909) of patients were missing at least one prehospital vital sign, of which 69.1 % (n = 628) were missing all four of these variables. Patients with incomplete data were more severely injured, had higher mortality, and more frequently received lifesaving interventions such as blood transfusion and intubation. Patients were most likely to have missing prehospital physiological data if they died in the trauma bay (unadjusted OR: 9.79; 95 % CI: 6.35-15.10), did not survive to discharge (unadjusted OR: 3.55; 95 % CI: 2.76-4.55), or had a prehospital GCS less than 9 (OR: 3.24; 95 % CI: 2.59-4.06). CONCLUSION: In this single center trauma registry, key prehospital variables were frequently missing, particularly among more severely injured patients. Patients with missing data had higher mortality, more severe injury characteristics and received more life-saving interventions in the trauma bay, suggesting an injury severity bias in prehospital vital sign missingness. To ensure the validity of research based on trauma registry data, patterns of missingness must be carefully considered to ensure missing data is appropriately addressed.

Using the GAP score as a complement to the NISS score in identifying severely injured patients- A registry-based cohort study of adult trauma patients in Sweden.

BACKGROUND: New Injury Severity Score (NISS) and Glasgow Coma Scale, Age and Pressure (GAP) scoring systems have cutoffs to define severe injury and identify high-risk patients. This is important in trauma quality monitoring and improvement. The overall aim was to explore if GAP scoring system can be a complement or an alternative to the traditional NISS scoring system. METHODS: Adults exposed to trauma between 2017 and 2021 were included in the study, using data from The Swedish Trauma Registry. The performance of NISS and GAP scores in predicting mortality, and ICU admissions were assessed using the area under the receiver operator characteristics (AUROC) in all patients and in subgroups (blunt, penetrating trauma and older (≥65 years) trauma patients). Patients were classified as severely injured by NISS >15 as Severely Injured NISS (SIN) or with a high-risk for mortality, by GAP 3-18 as High Risk GAP (HRG). Undertriage was calculated based on the cutoffs HRG and SIN. RESULTS: Overall, 37,017 patients were included. The AUROC (95 % CI) for mortality using NISS was 0.84 (0.83-0.85) and for GAP 0.92 (0.91-0.93) (p-value <0.001), the AUROC (95 % CI) for ICU-admissions was 0.82 (0.82-0.83) using NISS and for GAP 0.70 (0.70-0.71) p-value <0.001, in the overall cohort. In older patients the AUROC (95 % CI) for mortality was 0.76 (0.75-0.78) using NISS and 0.79 (0.78-0.81) using GAP, p-value <0.001. Overall, 8,572 (23.2 %) and 2,908 (7.9 %) were classified as SIN and HRG, respectively, with mortality rates of 13.7 % and 34.3 %. In the HRG group low-energy falls dominated and in the SIN group most patients were exposed to MVCs. In the SIN and HRG groups the rate of Emergency Trauma Interventions according to Utstein guidelines (ETIU) and ICU admission was 14.0 vs 9.5 % and 47.0 vs 62.5 % respectively. CONCLUSION: Our findings suggest that the GAP score and its cutoff 3-18 can be used to define severe trauma as complement to NISS >15 and can be a valuable tool in trauma quality monitoring and improvement. However, both scoring systems were less accurate in predicting mortality for the older trauma patients and should be explored further.

Protocol for the Evaluation of Data-Related Processes and Challenges at Level 1-4 Trauma Centers in Arkansas: A Mixed-Methods Case Study.

Background: In the following manuscript, we describe the detailed protocol for a mixed-methods, observational case study conducted to identify and evaluate existing data-related processes and challenges currently faced by trauma centers in a rural state. The data will be utilized to assess the impact of these challenges on registry data collection. Methods: The study relies on a series of interviews and observations to collect data from trauma registry staff at level 1-4 trauma centers across the state of Arkansas. A think-aloud protocol will be used to facilitate observations to gather keystroke-level modeling data and insight into site processes and workflows for collecting and submitting data to the Arkansas Trauma Registry. Informal, semi-structured interviews will follow the observation period to assess the participant's perspective on current processes, potential barriers to data collection or submission to the registry, and recommendations for improvement. Each session will be recorded, and de-identified transcripts and session notes will be used for analysis. Keystroke level modeling data derived from observations will be extracted and analyzed quantitatively to determine time spent performing end-to-end registry-related activities. Qualitative data from interviews will be reviewed and coded by 2 independent reviewers following a thematic analysis methodology. Each set of codes will then be adjudicated by the reviewers using a consensus-driven approach to extrapolate the final set of themes. Discussion: We will utilize a mixed methods approach to understand existing processes and barriers to data collection for the Arkansas Trauma Registry. Anticipated results will provide a baseline measure of the data collection and submission processes at various trauma centers across the state. We aim to assess strengths and limitations of existing processes and identify existing barriers to interoperability. These results will provide first-hand knowledge on existing practices for the trauma registry use case and will provide quantifiable data that can be utilized in future research to measure outcomes of future process improvement efforts. The potential implications of this study can form the basis for identifying potential solutions for streamlining data collection, exchange, and utilization of trauma registry data for clinical practice, public health, and clinical and translational research.

Implementation of health-related quality of life in the German TraumaRegister DGU® - first results of a pilot study.

BACKGROUND: Approximately 30,000 people are affected by severe injuries in Germany each year. Continuous progress in prehospital and hospital care has significantly reduced the mortality of polytrauma patients. With increasing survival rates, the functional outcome, health-related quality (hrQoL) of life and ability to work are now gaining importance. Aim of the study is, the presentation of the response behavior of seriously injured patients on the one hand and the examination of the factors influencing the quality of life and ability to work 12 months after major trauma on the other hand. Building on these initial results, a standard outcome tool shall be integrated in the established TraumaRegister DGU® in the future. METHODS: In 2018, patients [Injury Severity Score (ISS) ≥ 16; age:18-75 years] underwent multicenter one-year posttraumatic follow-up in six study hospitals. In addition to assessing hrQoL by using the Short-Form Health Survey (SF-12), five additional questions (treatment satisfaction; ability to work; trauma-related medical treatment; relevant physical disability, hrQoL as compared with the prior to injury status) were applied. RESULTS: Of the 1,162 patients contacted, 594 responded and were included in the analysis. The post-injury hrQoL does not show statistically significant differences between the sexes. Regarding age, however, the younger the patient at injury, the better the SF-12 physical sum score. Furthermore, the physically perceived quality of life decreases statistically significantly in relation to the severity of the trauma as measured by the ISS, whereas the mentally perceived quality of life shows no differences in terms of injury severity. A large proportion of severely injured patients were very satisfied (42.2%) or satisfied (39.9%) with the treatment outcome. It should be emphasized that patients with a high injury severity (ISS > 50) were on average more often very satisfied with the treatment outcome (46.7%). A total of 429 patients provided information on their ability to work 12 months post-injury. Here, 194 (45.2%) patients had a full employment, and 58 (13.5%) patients were had a restricted employment. CONCLUSION: The present results show the importance of a structured assessment of the postinjury hrQoL and the ability to work after polytrauma. Further studies on the detection of influenceable risk factors on hrQoL and ability to work in the intersectoral course of treatment should follow to enable the best possible outcome of polytrauma survivors.

Influencing factors for delayed diagnosed injuries in multiple trauma patients - introducing the 'Risk for Delayed Diagnoses Score' (RIDD-Score).

PURPOSE: Delayed diagnosed injuries (DDI) in severely injured patients are an essential problem faced by emergency staff. Aim of the current study was to analyse incidence and type of DDI in a large trauma cohort. Furthermore, factors predicting DDI were investigated to create a score to identify patients at risk for DDI. METHODS: Multiply injured patients admitted between 2011 and 2020 and documented in the TraumaRegister DGU® were analysed. Primary admitted patients with severe injuries and/or intensive care who survived at least 24 h were included. The prevalence, type and severity of DDI were described. Through multivariate logistic regression analysis, risk factors for DDI were identified. Results were used to create a 'Risk for Delayed Diagnoses' (RIDD) score. RESULTS: Of 99,754 multiply injured patients, 9,175 (9.2%) had 13,226 injuries first diagnosed on ICU. Most common DDI were head injuries (35.8%), extremity injuries (33.3%) and thoracic injuries (19.7%). Patients with DDI had a higher ISS, were more frequently unconscious, in shock, required more blood transfusions, and stayed longer on ICU and in hospital. Multivariate analysis identified seven factors indicating a higher risk for DDI (OR from 1.2 to 1.9). The sum of these factors gives the RIDD score, which expresses the individual risk for a DDI ranging from 3.6% (0 points) to 24.8% (6 + points). CONCLUSION: DDI are present in a sounding number of trauma patients. The reported results highlight the importance of a highly suspicious and thorough physical examination in the trauma room. The introduced RIDD score might help to identify patients at high risk for DDI. A tertiary survey should be implemented to minimise delayed diagnosed or even missed injuries.

The role of big data management, data registries, and machine learning algorithms for optimizing safe definitive surgery in trauma: a review.

Digital data processing has revolutionized medical documentation and enabled the aggregation of patient data across hospitals. Initiatives such as those from the AO Foundation about fracture treatment (AO Sammelstudie, 1986), the Major Trauma Outcome Study (MTOS) about survival, and the Trauma Audit and Research Network (TARN) pioneered multi-hospital data collection. Large trauma registries, like the German Trauma Registry (TR-DGU) helped improve evidence levels but were still constrained by predefined data sets and limited physiological parameters. The improvement in the understanding of pathophysiological reactions substantiated that decision making about fracture care led to development of patient's tailored dynamic approaches like the Safe Definitive Surgery algorithm. In the future, artificial intelligence (AI) may provide further steps by potentially transforming fracture recognition and/or outcome prediction. The evolution towards flexible decision making and AI-driven innovations may be of further help. The current manuscript summarizes the development of big data from local databases and subsequent trauma registries to AI-based algorithms, such as Parkland Trauma Mortality Index and the IBM Watson Pathway Explorer.

Improving Post-Injury Follow-up Survey Response: Incorporating Automated Modalities.

Background: Incorporating post-discharge data into trauma registries would allow for better research on patient outcomes, including disparities in outcomes. This pilot study tested a follow-up data collection process to be incorporated into existing trauma care systems, prioritizing low-cost automated response modalities. Methods: This investigation was part of a larger study that consisted of two protocols with two distinct cohorts of participants who experienced traumatic injury. Participants in both protocols were asked to provide phone, email, text, and mail contact information to complete follow-up surveys assessing patient-reported outcomes six months after injury. To increase follow-up response rates between protocol 1 and protocol 2, the study team modified the contact procedures for the protocol 2 cohort. Frequency distributions were utilized to report the frequency of follow-up response modalities and overall response rates in both protocols. Results: A total of 178 individuals responded to the 6-month follow-up survey: 88 in protocol 1 and 90 in protocol 2. After implementing new follow-up contact procedures in protocol 2 that relied more heavily on the use of automated modalities (e.g., email and text messages), the response rate increased by 17.9 percentage points. The primary response modality shifted from phone (72.7%) in protocol 1 to the combination of email (47.8%) and text (14.4%) in protocol 2. Conclusions: Results from this investigation suggest that follow-up data can feasibly be collected from trauma patients. Use of automated follow-up methods holds promise to expand longitudinal data in the national trauma registry and broaden the understanding of disparities in patient experiences.

Effect of Rural Trauma Team Development on the Outcomes of Motorcycle Accident-Related Injuries (Motor Registry Project): Protocol for a Multicenter Cluster Randomized Controlled Trial.

BACKGROUND: Injury is a global health concern, and injury-related mortality disproportionately impacts low- and middle-income countries (LMICs). Compelling evidence from observational studies in high-income countries shows that trauma education programs, such as the Rural Trauma Team Development Course (RTTDC), increase clinician knowledge of injury care. There is a dearth of such evidence from controlled clinical trials to demonstrate the effect of the RTTDC on process and patient outcomes in LMICs. OBJECTIVE: This multicenter cluster randomized controlled clinical trial aims to examine the impact of the RTTDC on process and patient outcomes associated with motorcycle accident-related injuries in an African low-resource setting. METHODS: This is a 2-arm, parallel, multi-period, cluster randomized, controlled, clinical trial in Uganda, where rural trauma team development training is not routinely conducted. We will recruit regional referral hospitals and include patients with motorcycle accident-related injuries, interns, medical trainees, and road traffic law enforcement professionals. The intervention group (RTTDC) and control group (standard care) will include 3 hospitals each. The primary outcomes will be the interval from the accident to hospital admission and the interval from the referral decision to hospital discharge. The secondary outcomes will be all-cause mortality and morbidity associated with neurological and orthopedic injuries at 90 days after injury. All outcomes will be measured as final values. We will compare baseline characteristics and outcomes at both individual and cluster levels between the intervention and control groups. We will use mixed effects regression models to report any absolute or relative differences along with 95% CIs. We will perform subgroup analyses to evaluate and control confounding due to injury mechanisms and injury severity. We will establish a motorcycle trauma outcome (MOTOR) registry in consultation with community traffic police. RESULTS: The trial was approved on August 27, 2019. The actual recruitment of the first patient participant began on September 01, 2019. The last follow-up was on August 27, 2023. Posttrial care, including linkage to clinical, social support, and referral services, is to be completed by November 27, 2023. Data analyses will be performed in Spring 2024, and the results are expected to be published in Autumn 2024. CONCLUSIONS: This trial will unveil how a locally contextualized rural trauma team development program impacts organizational efficiency in a continent challenged with limited infrastructure and human resources. Moreover, this trial will uncover how rural trauma team coordination impacts clinical outcomes, such as mortality and morbidity associated with neurological and orthopedic injuries, which are the key targets for strengthening trauma systems in LMICs where prehospital care is in the early stage. Our results could inform the design, implementation, and scalability of future rural trauma teams and trauma education programs in LMICs. TRIAL REGISTRATION: Pan African Clinical Trials Registry (PACTR202308851460352); https://pactr.samrc.ac.za/TrialDisplay.aspx?TrialID=25763. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/55297.

Demographic and injury trends for car crash casualties hospitalized in Level I Trauma centers over two decades: data from the National Trauma Registry.

BACKGROUND: During the past two decades, there have been many changes in automotive and medical technologies, road infrastructure, trauma systems, and demographic changes which may have influenced injury outcomes. The aim of this study was to examine injury trends among traffic casualties, specifically private car occupants, hospitalized in Level I Trauma Centers (TC). METHODS: A retrospective cohort study was performed based on data from the Israel National Trauma Registry. The data included occupants of private cars hospitalized in all six Level I TC due to a traffic collision related injury between January 1, 1998 and December 31, 2019. Demographic, injury and hospitalization characteristics and in-hospital mortality were analyzed. Chi-squared (X2) test, multivariable logistic regression models and Spearman's rank correlation were used to analyze injury data and trends. RESULTS: During the study period, 21,173 private car occupants (14,078 drivers, 4,527 front passengers, and 2,568 rear passengers) were hospitalized due to a traffic crash. The percentage of females hospitalized due to a car crash increased from 37.7% in 1998 to 53.7% in 2019. Over a twofold increase in hospitalizations among older adult drivers (ages 65+) was observed, from 6.5% in 1998 to 15.7% in 2018 and 12.6% in 2019. While no increase was observed for severe traumatic brain injury, a statistically significant increase in severe abdominal and thoracic injuries was observed among the non-Jewish population along with a constant decrease in in-hospital mortality. CONCLUSIONS: This study provides interesting findings regarding injury and demographic trends among car occupants during the past two decades. Mortality among private car occupant casualties decreased during the study period, however an increase in serious abdominal and thoracic injuries was identified. The results should be used to design and implement policies and interventions for reducing injury and disability among car occupants.

Identifying Common Data Elements to Achieve Injury-related Health Equity Across the Lifespan: A Consensus-Driven Approach.

Background: Limited availability and poor quality of data in medical records and trauma registries impede progress to achieve injury-related health equity across the lifespan. Methods: We used a Nominal Group Technique (NGT) in-person workgroup and a national web-based Delphi process to identify common data elements (CDE) that should be collected. Results: The 12 participants in the NGT workgroup and 23 participants in the national Delphi process identified 10 equity-related CDE and guiding lessons for research on collection of these data. Conclusions: These high-priority CDE define a detailed, equity-oriented approach to guide research to achieve injury-related health equity across the lifespan.

Comparison of injury severity scores derived from ICD-10-AM codes with trauma registry derived scores: A study from New Zealand.

INTRODUCTION: Various attempts at automation have been made to reduce the administrative burden of manually assigning Abbreviated Injury Severity (AIS) codes to derive Injury Severity Scores (ISS) in trauma registry data. The accuracy of the resulting measures remains unclear, especially in the New Zealand (NZ) context. The aim of this study was to compare ISS derived from hospital discharge International Classification of Diseases Australian Modification (ICD-10-AM) codes with ISS recorded in the NZ Trauma Registry (NZTR). METHODS: Individuals admitted to hospital and enrolled in the NZTR between 1 December 2016 and 30 November 2018 were included. ISS were calculated using a modified ICD to AIS mapping tool. The agreement between both methods for raw scores was assessed by the Intraclass Correlation Coefficient (ICC), and for categorical scores the Kappa and weighted Kappa index were used. Analysis was conducted by gender, age, ethnicity, and mechanism of injury. RESULTS: 3,156 patients fulfilled the inclusion criteria. The ICC for agreement between the methods was poor (0.40, 95 % CI: 0.37-0.43). The Kappa index indicated slight agreement between both methods when using a cut-off value of 12 (0.06; 95 % CI: 0.01-0.12) and 15 (0.13 6; 95 % CI: 0.09-0.17). CONCLUSION: Although the overall agreement between NZTR-ISS and ICD-ISS was slight, ICD-derived scores may be useful to describe injury patterns and for body region-specific estimations when manually coded ISS are not available.

Missing patient registrations in the Dutch National Trauma Registry of Southwest Netherlands: Prevalence and epidemiology.

INTRODUCTION: Health care patient records have been digitalised the past twenty years, and registries have been automated. Missing registrations are common, and can result in selection bias. OBJECTIVE: To assess the prevalence and characteristics of missed registrations in a Dutch regional trauma registry. METHODS: An automatically generated trauma registry export was done for ten out of eleven hospitals in trauma region Southwest Netherlands, between June 1 and August 31, 2020. Second, lists were checked for being falsely flagged as 'non-trauma'. Finally, a list was generated with trauma tick box flagged as 'trauma' but were not automatically in the export due to administrative errors. Automated and missed registration datasets were compared on patient characteristics and logistic regression models were run with random intercepts and missed registration as outcome variable on the complete dataset. RESULTS: A total of 2,230 automated registrations and 175 (7.3 %) missed registrations were included for the Dutch National Trauma Registry, ranging from 1 to 14 % between participating hospitals. Patients of the missed registration dataset had characteristics of a higher level of care, compared with patients of automated registrations. Level of trauma care (level II OR 0.464 95 % CI 0.328-0.666, p < 0.001; level III OR 0.179 95 % CI 0.092-0.325, p < 0.001), major trauma (OR 2.928 95 % CI 1.792-4.65, p < 0.001), ICU admission (OR 2.337 95 % CI 1.792-4.650, p < 0.001), and surgery (OR 1.871 95 % CI 1.371-2.570, p < 0.001) were potential predictors for missed registrations in multivariate logistic regression analysis. CONCLUSION: Missed registrations occur frequently and the rate of missed registrations differs greatly between hospitals. Automated and missed registration datasets display differences related to patients requiring more intensive care, which held for the major trauma subset. Checking for missed registrations is time consuming, automated registration lists need a human touch for validation and to be complete.