Non-technical skills evaluation in the critical care air ambulance environment: introduction of an adapted rating instrument--an observational study.

BACKGROUND: In the isolated and dynamic health-care setting of critical care air ambulance transport, the quality of clinical care is strongly influenced by non-technical skills such as anticipating, recognising and understanding, decision making, and teamwork. However there are no published reports identifying or applying a non-technical skills framework specific to an intensive care air ambulance setting. The objective of this study was to adapt and evaluate a non-technical skills rating framework for the air ambulance clinical environment. METHODS: In the first phase of the project the anaesthetists' non-technical skills (ANTS) framework was adapted to the air ambulance setting, using data collected directly from clinician groups, published literature, and field observation. In the second phase experienced and inexperienced inter-hospital transport clinicians completed a simulated critical care air transport scenario, and their non-technical skills performance was independently rated by two blinded assessors. Observed and self-rated general clinical performance ratings were also collected. Rank-based statistical tests were used to examine differences in the performance of experienced and inexperienced clinicians, and relationships between different assessment approaches and assessors. RESULTS: The framework developed during phase one was referred to as an aeromedical non-technical skills framework, or AeroNOTS. During phase two 16 physicians from speciality training programmes in intensive care, emergency medicine and anaesthesia took part in the clinical simulation study. Clinicians with inter-hospital transport experience performed more highly than those without experience, according to both AeroNOTS non-technical skills ratings (p = 0.001) and general performance ratings (p = 0.003). Self-ratings did not distinguish experienced from inexperienced transport clinicians (p = 0.32) and were not strongly associated with either observed general performance (r(s) = 0.4, p = 0.11) or observed non-technical skills performance (r(s) = 0.4, p = 0.1). DISCUSSION: This study describes a framework which characterises the non-technical skills required by critical care air ambulance clinicians, and distinguishes higher and lower levels of performance. CONCLUSION: The AeroNOTS framework could be used to facilitate education and training in non-technical skills for air ambulance clinicians, and further evaluation of this rating system is merited.

Fatigue in Air Medical Clinicians Undertaking High-acuity Patient Transports.

Abstract Background. Fatigue is likely to be a significant issue for air medical transport clinicians due to the challenging nature of their work, but there is little published evidence for this. Objective. To prospectively assess the levels and patterns of fatigue in air medical transport teams and determine whether specific mission factors influenced clinician fatigue. Methods. Physicians and flight nurses from two intensive care interhospital transport teams routinely completed fatigue report forms before and after patient transport missions over a 4-month period. Data collected included subjective ratings of fatigue (Samn-Perelli and visual analog scale), mission difficulty and performance. Multivariate hierarchical logistic and linear models were used to evaluate the influence of various mission characteristics on post-mission fatigue. Results. Clinicians returned 403 fully complete fatigue report forms at an estimated overall return rate of 73%. Fatigue increased significantly over the course of missions, and on 1 of every 12 fatigue reports returned clinicians reported severe post-mission fatigue (that is, levels of 6 or 7 on the Samn-Perelli scale). Factors that impacted significantly on clinician fatigue were the pre-mission fatigue level of the clinician, night work, mission duration, and mission difficulty. Poorer self-rated performance was significantly associated with higher levels of fatigue (r = -0.4, 95% CI -0.5 to -0.3), and for the 6-month period leading up to the study clinicians reported a total of 22 occasions on which they should have declined a mission due to fatigue. Conclusions. These results suggest that clinicians undertaking interhospital transports of even moderate duration experience high levels of fatigue on a relatively frequent basis. In the unique and challenging environment of air medical transport, prior fatigue, long or difficult missions, and the disadvantageous effect of night work on normal circadian rhythms are a combination where there are minimal safety margins for clinicians' performance capacity. Fatigue prevention or fatigue resistance measures could positively affect air medical clinicians in this context.

Comparison of in-flight measures with predictions of a bio-mathematical fatigue model.

INTRODUCTION: Bio-mathematical models are increasingly used for predicting fatigue in airline operations, and have been proposed as a possible component of fatigue risk management systems (FRMS). There is a need to continue to evaluate fatigue models against data collected from crews conducting commercial flight operations. METHODS: A comparison was made between several in-flight studies of pilot fatigue, conducted over a 10-yr period on a variety of operations, and the predictions of a widely used bio-mathematical model, the System for Aircrew Fatigue Evaluation (SAFE). The in-flight studies collected a variety of subjective ratings as well as reaction time on a performance task. RESULTS: Overall correlation between observed and predicted fatigue was stronger for subjective fatigue than reaction time. More detailed analysis on selected studies shows discrepancies between predicted and observed fatigue, which may be explained by a variety of confounders. Closer analysis of the duty time, time of day, and schedule length show discrepancies of up to 15% between observed and predicted fatigue. DISCUSSION: This study provides comparison between the predictions of one bio-mathematical model, SAFE, and observed fatigue measures across a number of operations. Possible causes of discrepancies are discussed. There is potential for more comparison studies of this type with the various available models.

The occupational health and safety of flight attendants.

In order to perform safety-critical roles in emergency situations, flight attendants should meet minimum health standards and not be impaired by factors such as fatigue. In addition, the unique occupational and environmental characteristics of flight attendant employment may have consequential occupational health and safety implications, including radiation exposure, cancer, mental ill-health, musculoskeletal injury, reproductive disorders, and symptoms from cabin air contamination. The respective roles of governments and employers in managing these are controversial. A structured literature review was undertaken to identify key themes for promoting a future agenda for flight attendant health and safety. Recommendations include breast cancer health promotion, implementation of Fatigue Risk Management Systems, standardization of data collection on radiation exposure and health outcomes, and more coordinated approaches to occupational health and safety risk management. Research is ongoing into cabin air contamination incidents, cancer, and fatigue as health and safety concerns. Concerns are raised that statutory medical certification for flight attendants will not benefit either flight safety or occupational health.

Symptom-based categorization of in-flight passenger medical incidents.

INTRODUCTION: The majority of in-flight passenger medical events are managed by cabin crew. Our study aimed to evaluate the reliability of cabin crew reports of in-flight medical events and to develop a symptom-based categorization system. METHODS: All cabin crew in-flight passenger medical incident reports for an airline over a 9-yr period were examined retrospectively. Validation of incident descriptions were undertaken on a sample of 162 cabin crew reports where medically trained persons' reports were available for comparison using a three Round Delphi technique and testing concordance using Cohen's Kappa. A hierarchical symptom-based categorization system was designed and validated. RESULTS: The rate was 159 incidents per 106 passengers carried, or 70.4/113.3 incidents per 106 revenue passenger kilometres/miles, respectively. Concordance between cabin crew and medical reports was 96%, with a high validity rating (mean 4.6 on a 1-5 scale) and high Cohen's Kappa (0.94). The most common in-flight medical events were transient loss of consciousness (41%), nausea/vomiting/diarrhea (19.5%), and breathing difficulty (16%). DISCUSSION: Cabin crew records provide reliable data regarding in-flight passenger medical incidents, complementary to diagnosis-based systems, and allow the use of currently underutilized data. The categorization system provides a means for tracking passenger medical incidents internationally and an evidence base for cabin crew first aid training.

Automated collection of fatigue ratings at the top of descent: a practical commercial airline tool.

INTRODUCTION: There is a need to develop an efficient and accurate way of assessing pilot fatigue in commercial airline operations. We investigated the validity of an automated system to collect pilot ratings of alertness at the top of descent, comparing the data obtained with existing results from previous studies and those predicted by the validated SAFE fatigue model. METHODS: Boeing 777 pilots were prompted to enter a Samn-Perelli fatigue scale rating directly into the flight management system of the aircraft shortly prior to descent on a variety of short- and long-haul commercial flights. These data were examined to evaluate whether the patterns were in line with predicted effects of duty length, crew number, and circadian factors. We also compared the results with data from previous studies as well as SAFE model predictions for equivalent routes. RESULTS: The effects of duty length, time of day, and crew complement were in line with expected trends and with data from previous studies; the correlation with predictions from the SAFE model was high (r = 0.88). Fatigue ratings were greater on longer trips (except where mitigated by adding an extra pilot) and on overnight sectors (4.68 vs 3.77). DISCUSSION: The results suggest that the automated collection of subjective ratings is a valid way to collect data on fatigue in an airline setting. This method has potential benefits for the crew in assessing fatigue risk prior to approach, as part of a fatigue risk management system, with the possibility of wider safety benefits.

Fatigue in airline pilots after an additional day's layover period.

INTRODUCTION: We investigated the effect of an additional day's layover on reducing fatigue in two different duties: a two-pilot crew flying between Auckland and Brisbane, and a three-pilot crew flying between Auckland and Los Angeles. METHODS: Pilots completed a reaction time task, the Samn-Perelli fatigue scale, and the Karolinska Sleepiness Scale on both outward and return flights. The flights were conducted with and without a 1-d layover (Brisbane) and with a 1- or 2-d layover (Los Angeles). RESULTS: On the Brisbane route, the addition of a layover resulted in a significant reduction of fatigue, sleepiness, and reaction time. At top of descent, Samn-Perelli fatigue was reduced from over 5.0 to under 4.5. In contrast, the addition of an extra day layover in Los Angeles had no significant effect on the same measures during the return flight; on both flights Samn-Perelli fatigue was over 5.0 at top of descent. DISCUSSION: The results suggest that the addition of an extra night's layover has different effects depending on the type of operation. Layover periods need to ensure adequate opportunity to recover from any sleep deficit arising from the outbound journey, but the benefit of increased layover time may be limited if time-zone shifts cause a mismatch between local time and the circadian rhythm of sleep.

Pilot fatigue in short-haul operations: effects of number of sectors, duty length, and time of day.

INTRODUCTION: There is little research on what factors are associated with fatigue in short-haul pilots. The aim was to investigate how length of duty, number of sectors, time of day, and departure airport affect fatigue levels in short-haul operations. METHODS: Pilots completed Samn-Perelli fatigue ratings prior to descent at the end of each rostered short-haul duty over a 12-wk period. Overall, 1370 usable responses were collected (67% of rostered duties) and fatigue scores were examined in relation to the departure airport, the number of sectors flown, time, and the length of duty period. RESULTS: The most important influences on fatigue were the number of sectors and duty length. These were associated with fatigue in a linear fashion. Time of day had a weaker influence, with lower levels at midday and increased fatigue later in the day. Fatigue was also higher during duties originating from an airport where pilots needed to position the night before and spend the night in a hotel. DISCUSSION: Data from the study enabled the quantification of fatigue at this critical phase of flight in duties lasting between 2 and 12 h and finishing between 08:00 to 24:00. The data obtained may be useful for identifying factors associated with fatigue, evaluating existing fatigue models, and identifying or predicting problem duties within an airline operation. The methodology used in the study may be successfully applied to gather fatigue data in other airline operations.