Team performance in resuscitation teams: Comparison and critique of two recently developed scoring tools

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Abstract

Background and aim Following high profile errors resulting in patient harm and attracting negative publicity, the healthcare sector has begun to focus on training non-technical teamworking skills as one way of reducing the rate of adverse events. Within the area of resuscitation, two tools have been developed recently aiming to assess these skills – TEAM and OSCAR. The aims of the study reported here were: 1. To determine the inter-rater reliability of the tools in assessing performance within the context of resuscitation. 2. To correlate scores of the same resuscitation teams episodes using both tools, thereby determining their concurrent validity within the context of resuscitation. 3. To carry out a critique of both tools and establish how best each one may be utilised. Methods The study consisted of two phases – reliability assessment; and content comparison, and correlation. Assessments were made by two resuscitation experts, who watched 24 pre-recorded resuscitation simulations, and independently rated team behaviours using both tools. The tools were critically appraised, and correlation between overall score surrogates was assessed. Results Both OSCAR and TEAM achieved high levels of inter-rater reliability (in the form of adequate intra-class coefficients) and minor significant differences between Wilcoxon tests. Comparison of the scores from both tools demonstrated a high degree of correlation (and hence concurrent validity). Finally, critique of each tool highlighted differences in length and complexity. Conclusion Both OSCAR and TEAM can be used to assess resuscitation teams in a simulated environment, with the tools correlating well with one another. We envisage a role for both tools – with TEAM giving a quick, global assessment of the team, but OSCAR enabling more detailed breakdown of the assessment, facilitating feedback, and identifying areas of weakness for future training.

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Measuring agreement in method comparison studies.

Elliot Bland, Michael Altman (1999)

Agreement between two methods of clinical measurement can be quantified using the differences between observations made using the two methods on the same subjects. The 95% limits of agreement, estimated by mean difference +/- 1.96 standard deviation of the differences, provide an interval within which 95% of differences between measurements by the two methods are expected to lie. We describe how graphical methods can be used to investigate the assumptions of the method and we also give confidence intervals. We extend the basic approach to data where there is a relationship between difference and magnitude, both with a simple logarithmic transformation approach and a new, more general, regression approach. We discuss the importance of the repeatability of each method separately and compare an estimate of this to the limits of agreement. We extend the limits of agreement approach to data with repeated measurements, proposing new estimates for equal numbers of replicates by each method on each subject, for unequal numbers of replicates, and for replicated data collected in pairs, where the underlying value of the quantity being measured is changing. Finally, we describe a nonparametric approach to comparing methods.

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The Critical Care Safety Study: The incidence and nature of adverse events and serious medical errors in intensive care.

Jeffrey M Rothschild, Christopher Landrigan, John Cronin … (2005)

Critically ill patients require high-intensity care and may be at especially high risk of iatrogenic injury because they are severely ill. We sought to study the incidence and nature of adverse events and serious errors in the critical care setting. We conducted a prospective 1-year observational study. Incidents were collected with use of a multifaceted approach including direct continuous observation. Two physicians independently assessed incident type, severity, and preventability as well as systems-related and individual performance failures. Academic, tertiary-care urban hospital. Medical intensive care unit and coronary care unit patients. None. The primary outcomes of interest were the incidence and rates of adverse events and serious errors per 1000 patient-days. A total of 391 patients with 420 unit admissions were studied during 1490 patient-days. We found 120 adverse events in 79 patients (20.2%), including 66 (55%) nonpreventable and 54 (45%) preventable adverse events as well as 223 serious errors. The rates per 1000 patient-days for all adverse events, preventable adverse events, and serious errors were 80.5, 36.2, and 149.7, respectively. Among adverse events, 13% (16/120) were life-threatening or fatal; and among serious errors, 11% (24/223) were potentially life-threatening. Most serious medical errors occurred during the ordering or execution of treatments, especially medications (61%; 170/277). Performance level failures were most commonly slips and lapses (53%; 148/277), rather than rule-based or knowledge-based mistakes. Adverse events and serious errors involving critically ill patients were common and often potentially life-threatening. Although many types of errors were identified, failure to carry out intended treatment correctly was the leading category.