Human Cognition and the Dynamics of Failure to Rescue: The Lewis Blackman Case

Statistical Modeling and Aggregate‐Weighted Scoring Systems in Prediction of Mortality and ICU Transfer: A Systematic Review

“…Consequently, EWSs using statistical modeling can at best augment and support-but not replace-RRT rounding, physician workup, and vigilant frontline staff. However, clinicians, too, are not perfect, and the failure-to-rescue literature suggests that certain human factors are antecedents to patient crises (eg, stress and distraction, [44][45][46] judging by precedent/experience, 44,47 and innate limitations of human cognition 47 ). Because neither clinicians nor EWSs can predict deterioration perfectly, the best possible rescue response combines clinical vigilance, RRT rounding, and EWSs using statistical modeling as complementary solutions.…”

New graduate nurses’ preparation for recognition and prevention of failure to rescue: A qualitative study

“…“Development of clinical reasoning” was an important theme in the data as participants indicated it was the basis of their ability to recognise and prevent failure to rescue. Research has been conducted related to cognitive ability and how nurses use clinical reasoning to prevent patient deterioration (Acquaviva, Haskell, & Johnson, ; Liaw, Rethans, et al., ). The overarching perception of the development of clinical reasoning in this study was that it occurred after graduation.…”

“…Nursing students and new graduates on orientation should not be shielded from the most difficult patients. With the guidance and support of experienced educators and experienced preceptors, student nurses and new graduates can provide care for patients whose condition has begun to decline (Acquaviva et al., ; Clarke & Aiken, ; Fisher & King, ). Research has demonstrated that simulation is effective in preparing nurses for care of the deteriorating patient (Gordon & Buckley, ; Gibson et al., ); however, more research is needed to ascertain best practices in both nursing schools and healthcare facilities for the development of multipatient scenarios that will enhance the new graduate's ability to make safe clinical decisions when a patient is deteriorating.…”

Evaluating team decision-making as an emergent phenomenon

“…In the cases where team members had different responses—for example, one person choosing a correct answer and another person an incorrect answer—we assumed that the correct decision would prevail, but in reality an aggregate team decision may be subject to a variety of complex influences on team dynamics. Well-described biases, such as anchoring and belief perseverance , where a voiced belief by one member becoming firmly held by all, may have influenced team members and thus affected the ultimate team decision 7. Furthermore, team decision-making within clinical settings is likely to be influenced by inherent social hierarchies.…”