Optimising trauma team performance

Optimising trauma team performance

S38 Abstracts Trauma Melbourne 2009 / Injury 41S (2010) S27–S48 changes, no differences in macrophage numbers were found in the lesion site of MCP-1...

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S38

Abstracts Trauma Melbourne 2009 / Injury 41S (2010) S27–S48

changes, no differences in macrophage numbers were found in the lesion site of MCP-1−/− mice at times of maximal infiltration (4 or 7 days). However by 14 and 28 days, there was a significant reduction in the spread of macrophages in MCP-1−/− brains (50%, p < 0.05; n = 6–7), which corresponded to reduced lesion volume and neuronal loss (p < 0.05). MCP-1’s receptor CCR2 was expressed in injured cortex by a subset of F4/80 + macrophages. Astrocyte activation was attenuated in MCP-1−/− compared to wildtype controls, particularly in the dorsolateral thalamus (p < 0.05). No differences between the strains were detected in the number of dying cells at any time. Functionally, MCP-1−/− mice demonstrated a significantly improved recovery in both the NSS and ledged beam walk test compared to wildtype mice from 10 to 28 days post-CHI (2-way ANOVA, p < 0.05; n = 8–9). Conclusions: This study indicates that MCP-1 may be detrimental to long-term recovery, and contribute to the exacerbation of secondary damage following CHI. Strategies to therapeutically inhibit this chemokine may thus be of benefit to TBI patients. Acknowledgements: Supported by the Victorian Neurotrauma Initiative (VNI), Australian Government (Australian Postgraduate Award for B. Semple), and the Transport Accident Commission (TAC).

generation was significantly increased compared to HCs in order to accelerate. Postural instability, measured by lateral centre of mass displacement, and base of support was significantly increased but did not deteriorate with increasing gait speed. Conclusions: The primary cause of reduced gait speed following TBI seems to be reduced ankle power generation for push off. Reduced distal power generation was partially compensated for proximally with increased hip power generation. Postural instability, as measured by lateral COM displacement, whilst present in this population, was unchanged at faster speeds and did not seem to be the primary reason for reduced gait speed. These findings suggest that, despite the presence of postural instability, people with TBI appear unable to increase ankle plantarflexor muscle activity effectively for faster gait speeds when compared with HCs. Acknowledgements: This project was supported by the Victorian Neurotrauma Initiative.

References 1. 2. 3. 4.

Basford, et al. Arch Phys Med Rehabil 2003;84(3):343–9. Chou, et al. Gait Posture 2004;20(3):245–54. Kaufman, et al. Med Eng Phys 2006;28(3):234–9. McFadyen, et al. J Head Trauma Rehabil 2003;18(6):512–25.

doi:10.1016/j.injury.2010.01.044 doi:10.1016/j.injury.2010.01.045 ORAL ORAL FREE PAPER 2-2 FREE PAPER 2-3 Reduced ankle power generation rather than postural instability leads to slow gait following TBI

Optimising trauma team performance

G. Williams 1,2,∗ , M.E. Morris 2 , A. Schache 3 , P. McCrory 4

S. Jeffcott 1,∗ , N. Cameron 1,4

1

Physiotherapy Department, Epworth Hospital, Melbourne, Victoria, Australia 2 Melbourne School of Health Sciences, The University of Melbourne, Melbourne, Victoria, Australia 3 Department of Engineering, The University of Melbourne, Melbourne, Victoria, Australia 4 Centre for Health Exercise and Sports Medicine, The University of Melbourne, Melbourne, Victoria, Australia Introduction: Reduced gait speed is common following TBI and may restrict participation in employment, social, leisure and sporting activities. Several studies have found that people with TBI display increased medio-lateral movement in their centre of mass (COM) whilst walking.1–3 It has been hypothesized that reduced gait speed following TBI is a consequence of increased caution caused by reduced balance or postural control.4 Objectives: The aim of this study was to identify the reasons why people with TBI walk at a reduced gait speed. Methods: A sample of 55 TBI participants receiving therapy for gait disorders was recruited. 3D motion analysis of self-selected and maximum safe walking speed was conducted. The average spatio-temporal and kinetic data from 5 trials for each condition was analysed. A comparison group of 10 healthy controls (HCs) performed gait trials matched to the mean self-selected TBI gait speed and at their maximum walking speed. Results: TBI participants walked at a reduced gait speed when compared to age appropriate norms. When matched to HCs for speed, TBI participants had reduced ankle power generation at push-off, and an associated increased hip flexor and extensor power generation. The majority of TBI participants had equivalent ability to accelerate to faster gait speeds, but used an alternative method to HCs. Ankle power generation was significantly reduced, as was the ability to increase hip extensor power generation. Hip flexor power

Farrow 2 , S.

Marshall 3 , M.

Fitzgerald 4 , P.

1 NHMRC CRE in Patient Safety, Department Epidemiology and Preventive Medicine, Monash University, Melbourne, Victoria, Australia 2 Melbourne Health, Royal Melbourne Hospital, Melbourne, Victoria, Australia 3 Southern Health Simulation and Skills Centre, Monash Medical Centre, Clayton, Victoria, Australia 4 Emergency and Trauma Centre, Alfred Hospital, Melbourne, Victoria, Australia

Objectives: The patient safety literature is littered with accounts of poor team performance leading to adverse events. This is especially true in trauma setting where up to a third of deaths are reported as preventable and many are attributed to non-optimal communication and coordination.2 Trauma provides a ripe research arena but involves unique challenges, including: (1) The time critical nature of trauma management; (2) the need for multiple tasks to occur simultaneously; (3) the higher acuity of patients; (4) the ad hoc nature of teams, and finally; (5) limitations to the resources available for trauma management. This 12-month TAC funded project investigates how trauma team communication, coordination and culture contribute to team performance in this challenging healthcare environment and how this information can be used to augment current training for trauma staff. Methods: This project took a mixed method approach. It was informed conceptually by Baker and Salas’s model,1 which describes team work as consisting of: (1) Cognitions (i.e. knowledge, the “thinking”); (2) behaviours (i.e. skills, the “doing”); (3) affects (i.e. attitudes, the “feeling”). Thus, video audit of the first 30 min of trauma resuscitations was used to examine the behaviours we can see, and individual interviews and focus groups to examine the cognition and affect that we cannot but which drive these behaviours. A total of 66 videos were coded using a structured tool from the University of Maryland and 20 frontline trauma staff,

Abstracts Trauma Melbourne 2009 / Injury 41S (2010) S27–S48

from a range of specialities and seniority, participated in a total of 7 interviews and 3 focus groups. Results: Each of the 66 videos was coded twice, reflecting the different team coordination phases of resuscitation.3 There were significant differences between the scores obtained in the leader, access and activities and communication sub-categories between what we have classified as the handover phase (from patient on table until 2 min) and the stabilisation phase (from 2 min until 13 min). The qualitative work helped to describe some of this variation in leader and team behaviour within different phases. The key aspects of team working that need to be supported, and are often not reportedly done well, are situation awareness (keeping the bigger picture), leading disparate teams (especially those including outside disciplines), appropriate levels of feedback (during the resuscitation) and debriefing (after the resuscitation). Value and effectiveness of orientation was also discussed. Conclusions: Approaching different stages of the resuscitation period may be more helpful in understanding the potential performance and training requirements needed for each distinct phase of coordination within this complex period of competing demands. We also conclude that there is value in supplementing work on observable team “skills” with work to reveal “knowledge”, i.e. cognition, and “attitudes”, i.e. affect. Those at the frontline of trauma are best placed to give insights into any deficiencies in current training, orientation and debriefing regimes. Acknowledgements: The authors would like to acknowledge Prof. Colin Mackenzie and other colleagues from the University of Maryland’s Shock Trauma Unit who were involved in the development of the team performance tool we used in this project.

References 1. Baker DP, Salas E. Principles for measuring teamwork: a summary and look toward the future. In: Brannick MT, Salas E, Prince C, editors. Assessment and measurement of team performance: theory, methods, and applications. NJ: Lawrence; 1997. p. 331–55. 2. McDermott FT, Cordner S, Tremayne AB. Road traffic fatalities in Victoria, Australia and changes to the trauma care system. Br J Surg 2001;88(8):1099–104. 3. Marshall S, Miller A, Xiao Y. Development of team coordination and performance measures in a trauma setting. In: Human factors and ergonomics society 51st annual meeting. 2007.

doi:10.1016/j.injury.2010.01.046 ORAL FREE PAPER 2-4 The reliability of patient recall of hospital readmission following orthopaedic trauma C. Gosling 1,∗ , B. Cameron 1,2,3

Gabbe 1,2 , M.

Hart 2,4 , A.

Sutherland 1,2,3 , P.

1

Department of Epidemiology & Preventive Medicine, Monash University, Melbourne, Victoria, Australia 2 National Trauma Research Institute, The Alfred, Melbourne, Victoria, Australia 3 Emergency & Trauma Centre, The Alfred, Melbourne, Victoria, Australia 4 Department of Orthopaedics, The Royal Melbourne Hospital, Melbourne, Victoria, Australia Objectives: Accuracy of information recalled by patients is integral to the success of clinical outcomes registries, trials and doctor–patient interaction. Patient, interviewer and information variance can lead to information instability, especially where recall periods are greater than two months.2 Personal and environmental factors may contribute to potential recall bias.1–3 Our aim was to

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determine level of agreement, at six months, between patient recall of readmission to Victorian major trauma centres with hospital medical records. Methods: The Victorian Orthopaedic Trauma Outcomes Registry (VOTOR) captured information for all patients, over the age of 15 years, admitted to the two adult major trauma services in Victoria for management of orthopaedic and/or spinal injuries. Patients were excluded from the registry if they presented with a pathological fracture related to a metastatic disease or their orthopaedic injury was managed by another unit.4 For the current study, a random sample of 200 patients, enrolled between August 2003 and July 2006, was extracted from the registry. Retrospective comparison of patient hospital medical records to prospectively collected data about readmission, from the VOTOR data base, six months after a patients’ injury event. Demographic, injury event, diagnosis, management and in-hospital outcomes were collected from the patient’s medical record or hospital information systems. In addition, longer term outcomes, such as pain, function and healthrelated quality of life, were collected by telephone interview at six months. Results: Thirty-eight patients had a recorded readmission, with only 18 (47.7%) agreeing with the hospital medical record. A total of 87% of patients accurately recalled their readmission status at six months corresponding to a moderate agreement ( = 0.503, 95% CI: 0.347–0.670, P < 0.001) and a substantial prevalence and bias adjusted kappa (PABAK = 0.74, 95% CI: 0.647–0.833, P < 0.001). A false positive rate of 3.7% and a false negative rate of 53% were recorded for the sampled population. There were no significant differences between patients who agreed with their hospital medical record and those that did not. For patients with a hospital medical record readmission the number of readmissions (X21 = 2.17, P = 0.337), length of stay (X21 = 1.43, P = 0.232), time to readmission since injury (z = −1.328, P = 0.184) or reason for readmission (X21 = 2.97, P = 0.226) showed no association with their accuracy of recall. Conclusions: There were no personal, physical, pain or disability characteristics that influenced the ability of a patient to accurately recall information over a six-month period, although this warrants further investigation. The poor recall of readmission information after six months indicates that the reliability of this information should not be assumed when used in clinical registries, trials or doctor patient interactions. Acknowledgements: The Victorian Orthopaedic Trauma Outcomes Registry (VOTOR) is funded by TAC Health Research. Dr. Belinda Gabbe was supported by a Career Development Award from the National Health and Medical Research Council. We would also like to thank Smith & Nephew, Synthes, Stryker, De Puy & KCI Medical Australia for their support of VOTOR. References 1. Barsky AJ. Forgetting, fabricating, and telescoping: the instability of the medical history. Arch Intern Med 2002;162(9):981–4. 2. Jenkins P, Earle-Richardson G, Slingerland DT, et al. Time dependent memory decay. Am J Ind Med 2002;41(2):98–101. 3. Jordan K, Jinks C, Croft P. Health care utilization: measurement using primary care records and patient recall both showed bias. J Clin Epidemiol 2006;59(8):791–7. 4. Urquhart DM, Edwards ER, Graves SE, et al. Characterisation of orthopaedic trauma admitted to adult Level 1 Trauma Centres. Injury 2006;37:120–7.

doi:10.1016/j.injury.2010.01.047