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van der Sluijs R, Fiddelers AAA, Waalwijk JF, Reitsma JB, Dirx MJ, den Hartog D, Evers SMAA, Goslings JC, Hoogeveen WM, Lansink KW, Leenen LPH, van Heijl M, Poeze M. The impact of the Trauma Triage App on pre-hospital trauma triage: design and protocol of the stepped-wedge, cluster-randomized TESLA trial. Diagn Progn Res 2020; 4:10. [PMID: 32566758 PMCID: PMC7302135 DOI: 10.1186/s41512-020-00076-1] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/07/2020] [Accepted: 04/22/2020] [Indexed: 11/23/2022] Open
Abstract
BACKGROUND Field triage of trauma patients is crucial to get the right patient to the right hospital within a particular time frame. Minimization of undertriage, overtriage, and interhospital transfer rates could substantially reduce mortality rates, life-long disabilities, and costs. Identification of patients in need of specialized trauma care is predominantly based on the judgment of Emergency Medical Services professionals and a pre-hospital triage protocol. The Trauma Triage App is a smartphone application that includes a prediction model to aid Emergency Medical Services professionals in the identification of patients in need of specialized trauma care. The aim of this trial is to assess the impact of this new digital approach to field triage on the primary endpoint undertriage. METHODS The Trauma triage using Supervised Learning Algorithms (TESLA) trial is a stepped-wedge cluster-randomized controlled trial with eight clusters defined as Emergency Medical Services regions. These clusters are an integral part of five inclusive trauma regions. Injured patients, evaluated on-scene by an Emergency Medical Services professional, suspected of moderate to severe injuries, will be assessed for eligibility. This unidirectional crossover trial will start with a baseline period in which the default pre-hospital triage protocol is used, after which all clusters gradually implement the Trauma Triage App as an add-on to the existing triage protocol. The primary endpoint is undertriage on patient and cluster level and is defined as the transportation of a severely injured patient (Injury Severity Score ≥ 16) to a lower-level trauma center. Secondary endpoints include overtriage, hospital resource use, and a cost-utility analysis. DISCUSSION The TESLA trial will assess the impact of the Trauma Triage App in clinical practice. This novel approach to field triage will give new and previously undiscovered insights into several isolated components of the diagnostic strategy to get the right trauma patient to the right hospital. The stepped-wedge design allows for within and between cluster comparisons. TRIAL REGISTRATION Netherlands Trial Register, NTR7243. Registered 30 May 2018, https://www.trialregister.nl/trial/7038.
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Affiliation(s)
- Rogier van der Sluijs
- Department of Surgery, Maastricht University Medical Center, Maastricht, The Netherlands
- Department of Surgery, Utrecht University Medical Center, Utrecht, The Netherlands
- Network Acute Care Limburg, Maastricht University Medical Center, Maastricht, The Netherlands
| | - Audrey A. A. Fiddelers
- Network Acute Care Limburg, Maastricht University Medical Center, Maastricht, The Netherlands
| | - Job F. Waalwijk
- Department of Surgery, Maastricht University Medical Center, Maastricht, The Netherlands
- Department of Surgery, Utrecht University Medical Center, Utrecht, The Netherlands
- Network Acute Care Limburg, Maastricht University Medical Center, Maastricht, The Netherlands
| | - Johannes B. Reitsma
- Department of Epidemiology, Julius Center, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Miranda J. Dirx
- Network Acute Care Limburg, Maastricht University Medical Center, Maastricht, The Netherlands
| | - Dennis den Hartog
- Department of Surgery, Erasmus Medical Center, Rotterdam, The Netherlands
| | - Silvia M. A. A. Evers
- Care and Public Health Research Institute, Maastricht University, Maastricht, The Netherlands
| | - J. Carel Goslings
- Department of Surgery, Amsterdam University Medical Center, Amsterdam, The Netherlands
- Department of Surgery, Onze Lieve Vrouwe Hospital, Amsterdam, The Netherlands
| | | | - Koen W. Lansink
- Department of Surgery, Elisabeth TweeSteden Hospital, Tilburg, The Netherlands
| | - Luke P. H. Leenen
- Department of Surgery, Utrecht University Medical Center, Utrecht, The Netherlands
| | - Mark van Heijl
- Department of Surgery, Utrecht University Medical Center, Utrecht, The Netherlands
- Department of Surgery, Diakonessenhuis Utrecht/Zeist/Doorn, Utrecht, The Netherlands
| | - Martijn Poeze
- Department of Surgery, Maastricht University Medical Center, Maastricht, The Netherlands
- Network Acute Care Limburg, Maastricht University Medical Center, Maastricht, The Netherlands
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van der Sluijs R, Debray TPA, Poeze M, Leenen LPH, van Heijl M. Development and validation of a novel prediction model to identify patients in need of specialized trauma care during field triage: design and rationale of the GOAT study. Diagn Progn Res 2019; 3:12. [PMID: 31245626 PMCID: PMC6584978 DOI: 10.1186/s41512-019-0058-5] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/04/2019] [Accepted: 04/14/2019] [Indexed: 12/13/2022] Open
Abstract
BACKGROUND Adequate field triage of trauma patients is crucial to transport patients to the right hospital. Mistriage and subsequent interhospital transfers should be minimized to reduce avoidable mortality, life-long disabilities, and costs. Availability of a prehospital triage tool may help to identify patients in need of specialized trauma care and to determine the optimal transportation destination. METHODS The GOAT (Gradient Boosted Trauma Triage) study is a prospective, multi-site, cross-sectional diagnostic study. Patients transported by at least five ground Emergency Medical Services to any receiving hospital within the Netherlands are eligible for inclusion. The reference standards for the need of specialized trauma care are an Injury Severity Score ≥ 16 and early critical resource use, which will both be assessed by trauma registrars after the final diagnosis is made. Variable selection will be based on ease of use in practice and clinical expertise. A gradient boosting decision tree algorithm will be used to develop the prediction model. Model accuracy will be assessed in terms of discrimination (c-statistic) and calibration (intercept, slope, and plot) on individual participant's data from each participating cluster (i.e., Emergency Medical Service) through internal-external cross-validation. A reference model will be externally validated on each cluster as well. The resulting model statistics will be investigated, compared, and summarized through an individual participant's data meta-analysis. DISCUSSION The GOAT study protocol describes the development of a new prediction model for identifying patients in need of specialized trauma care. The aim is to attain acceptable undertriage rates and to minimize mortality rates and life-long disabilities.
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Affiliation(s)
- Rogier van der Sluijs
- 0000 0004 0480 1382grid.412966.eDepartment of Traumatology, Maastricht University Medical Center, Maastricht, The Netherlands
- 0000000090126352grid.7692.aDepartment of Traumatology, University Medical Center Utrecht, Utrecht, The Netherlands
- Department of Surgery, Diakonessenhuis Utrecht/Zeist/Doorn, Utrecht, The Netherlands
| | - Thomas P. A. Debray
- 0000000120346234grid.5477.1Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands
- 0000000120346234grid.5477.1Cochrane Netherlands, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands
| | - Martijn Poeze
- 0000 0004 0480 1382grid.412966.eDepartment of Traumatology, Maastricht University Medical Center, Maastricht, The Netherlands
| | - Loek P. H. Leenen
- 0000000090126352grid.7692.aDepartment of Traumatology, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Mark van Heijl
- 0000000090126352grid.7692.aDepartment of Traumatology, University Medical Center Utrecht, Utrecht, The Netherlands
- Department of Surgery, Diakonessenhuis Utrecht/Zeist/Doorn, Utrecht, The Netherlands
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