Boken presenterer en helhetlig strategi for hvordan myndigheter, helsepersonell, industri og forbrukere kan redusere medisinske feil.

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To Err Is Human Building a Safer Health System

In 1974 an article appeared in Science magazine with the dry-sounding title “Judgment Under Uncertainty: Heuristics and Biases” by a pair of psychologists who were not well known outside their discipline of decision theory. In it Amos Tversky and Daniel Kahneman introduced the world to Prospect Theory, which mapped out how humans actually behave when faced with decisions about gains and losses, in contrast to how economists assumed that people behave. Prospect Theory turned Economics on its head by demonstrating through a series of ingenious experiments that people are much more concerned with losses than they are with gains, and that framing a choice from one perspective or the other will result in decisions that are exactly the opposite of each other, even if the outcomes are monetarily the same. Prospect Theory led cognitive psychology in a new direction that began to uncover other human biases in thinking that are probably not learned but are part of our brain’s wiring.

Thinking fast and slow.

The power of feedback.

SUMMARY Review date: 1969 to 2003, 34 years. Background and context: Simulations are now in widespread use in medical education and medical personnel evaluation. Outcomes research on the use and effectiveness of simulation technology in medical education is scattered, inconsistent and varies widely in methodological rigor and substantive focus. Objectives: Review and synthesize existing evidence in educational science that addresses the question, ‘What are the features and uses of high-fidelity medical simulations that lead to most effective learning?’. Search strategy: The search covered five literature databases (ERIC, MEDLINE, PsycINFO, Web of Science and Timelit) and employed 91 single search terms and concepts and their Boolean combinations. Hand searching, Internet searches and attention to the ‘grey literature’ were also used. The aim was to perform the most thorough literature search possible of peer-reviewed publications and reports in the unpublished literature that have been judged for academic quality. Inclusion and exclusion criteria: Four screening criteria were used to reduce the initial pool of 670 journal articles to a focused set of 109 studies: (a) elimination of review articles in favor of empirical studies; (b) use of a simulator as an educational assessment or intervention with learner outcomes measured quantitatively; (c) comparative research, either experimental or quasi-experimental; and (d) research that involves simulation as an educational intervention. Data extraction: Data were extracted systematically from the 109 eligible journal articles by independent coders. Each coder used a standardized data extraction protocol. Data synthesis: Qualitative data synthesis and tabular presentation of research methods and outcomes were used. Heterogeneity of research designs, educational interventions, outcome measures and timeframe precluded data synthesis using meta-analysis. Headline results: Coding accuracy for features of the journal articles is high. The extant quality of the published research is generally weak. The weight of the best available evidence suggests that high-fidelity medical simulations facilitate learning under the right conditions. These include the following:

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Features and uses of high-fidelity medical simulations that lead to effective learning: a BEME systematic review

Social Psychology of Organizations

The global myocardial extraction of lactate was measured in 13 halothane anesthetized dogs to assess the effect of electric countershock applied directly to the heart. Seven animals received two countershocks of 30 delivered joules each, while six animals were not shocked but were atrially paced to a rate of 190-200, both with and without occlusion of the vena cava to produce a mean arterial pressure of 40-50 mmHg. All animals had substantially positive lactate extraction in the baseline state (36 +/- 10% for countershock group vs. 41 +/- 3% for pacing group). Myocardial lactate extraction reached a markedly negative nadir 2.5 min after countershock (-19 +/- 15%), but returned toward normal by 6 min (10 +/- 6%). Lactate extraction was not significantly changed from baseline in the pacing group. The relationship between changes in regional myocardial blood flow (radiolabeled microspheres) and post-countershock myocardial damage (technetium pyrophosphate uptake) was assessed in six dogs shocked as above. Mean myocardial blood flow was increased minimally immediately after countershock (0.78 +/- 0.08 ml X min-1 X g-1 vs. 1.16 +/- 0.3), but there was no difference in blood flow between damaged and undamaged tissue at either time point. The epicardial-to-endocardial ratio of blood flow was unchanged after countershock (0.97 +/- 0.05 vs. 0.99 +/- 0.08). There was no relationship between myocardial damage and either the absolute amount of blood flow after countershock (r = -0.03) or the change in blood flow compared with the pre-shock period (r = 0.01).(ABSTRACT TRUNCATED AT 250 WORDS)

Internal countershock produces myocardial damage and lactate production without myocardial ischemia in anesthetized dogs.

Based on mounting evidence that better safety climate is related to lower incidence (Naveh, Katz-Navon, and Stern 2005; Hofmann and Mark 2006; Neal and Griffin 2006; Vogus and Sutcliffe 2007; Singer et al. 2008b;) and greater reporting (Cohen et al. 2004; Weingart et al. 2004; Gandhi et al. 2005;) of adverse events and to increased communication among managers and staff (Hofmann and Morgeson 1999), considerable effort among hospitals is being focused on improving safety climate. Along with hospitals' own efforts, several voluntary, collaborative initiatives that could improve safety climate (e.g., Leapfrog Group's patient safety leaps, and Institute for Healthcare Improvement's 5 Million Lives campaign) have garnered substantial participation among both public and private hospitals. “Benchmarking” of safety-climate survey results through participation in such collaborative initiatives is an effective way for hospitals to target quality improvement efforts. Benchmarking enables a hospital to compare its survey results with those of other hospitals, thereby facilitating identification of relative strength and weakness. It is being encouraged by numerous organizations. Since 2002, the Joint Commission's performance improvement standard (PI.01.01.01) has encouraged hospitals to collect data on staff perceptions of safety risks and improvement opportunities and to compare data with external sources (Joint Commission on Accreditation of Health Care Organizations 2002). The Agency for Healthcare Research and Quality (AHRQ) established the Hospital Survey on Patient Safety Culture Comparative Database for this purpose in 2006. Its 2009 database included safety-climate results from 622 hospitals (Sorra et al. 2009). Independent investigators engaged in benchmarking safety climate have also identified systematic differences in safety climate within and among hospitals, which provide clues to improving safety climate more generally (Singer et al. 2003; Thomas, Sexton, and Helmreich 2003; Makary et al. 2006; Sexton et al. 2006a, b, c; Vogus and Sutcliffe 2007; Hartmann et al. 2008; Singer et al. 2008a, 2009). Benchmarking safety-climate survey results across health care systems is difficult due to coordination challenges.

Our own effort to measure and benchmark safety climate is unique in that we used essentially the same survey instrument and sampling and administration procedures at approximately the same time in two discrete populations of hospitals in the United States: the Veterans Health Administration (VA) health care system and a national sample, excluding VA hospitals. This provided a novel opportunity to compare safety climate across two populations encompassing great diversity in both individual hospital characteristics and overall organizational structure, and potentially to identify any hospital features systematically related to safer care.

Differences in safety climate between VA and other U.S. hospitals may inherently exist because the VA is a nationally integrated network, while few U.S. hospitals come from large, integrated systems and none come from nationally integrated systems. As a system, the VA enjoys distinct advantages in broadly implementing and enforcing compliance with standardized safety activities. The VA conducts several initiatives with potential to improve safety climate. For example, the VA National Center for Patient Safety was established specifically to promote a systems approach to preventing and reducing harm to patients and to encourage hospitals to conduct root cause analyses after safety incidents (http://www.va.gov/ncps/vision.html, accessed on August 26, 2008, for NCPS).

In this paper, we examine differences in safety climate between 69 diverse U.S. hospitals and 30 VA hospitals using cross-sectional employee surveys. Given potential advantages in promoting strong safety climate in a nationally integrated network, we hypothesized that safety climate among VA hospitals would be stronger than among U.S. hospitals.

Differences in safety climate between U.S. and VA samples may arise from multiple sources. First, there may be variation between the two samples in measured characteristics associated with safety climate—for instance, one sample may contain more large hospitals than the other. The residual difference in safety climate between the two samples would be attributable to differential effects of the sample characteristics between the two health care systems (e.g., hospital size may impact VA hospitals differently than U.S. hospitals). We performed comparisons of safety climate in these two settings that allowed us to discern the relative impact of these potential sources of difference. We hypothesized that variance in observed sample characteristics would explain more of the difference in safety climate between U.S. and VA hospitals than would differential effects of sample characteristics on the two groups.

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Comparing safety climate between two populations of hospitals in the United States.

Anesthesia crisis resource management training

IntroductionThere has been interest in the use of high-fidelity medical simulation to evaluate performance. We hypothesized that technical and nontechnical performance in the simulated environment is related to other various criterion measures, providing evidence to support the validity of the score

External validation of simulation-based assessments with other performance measures of third-year anesthesiology residents.

Background: This research provides an educational perspective on simulation-based medical education by implementing both the characteristics of meaningful learning and the concepts of facilitating, training, and learning processes.Aims: This study aims to evaluate, from the perspectives of both facilitators and students, the meaningfulness of five different simulation-based courses.Methods: The courses were implemented in the spring of 2010. The data were collected from facilitators (n = 9) and students (n = 25) using group interviews (one individual interview), observations, video recordings, and pre- and post-questionnaires. The research analyzes qualitative data using the qualitative content analysis method to answer the following research question: From facilitators’ and students’ perspectives, how does the facilitating and training in simulation-based learning environments (SBLEs) foster the meaningful learning of students?Results: It seems that simulation-based learning is, at its foundation, meanin...

David M. Gaba

Papers

Internal countershock produces myocardial damage and lactate production without myocardial ischemia in anesthetized dogs.

Comparing safety climate between two populations of hospitals in the United States.

Anesthesia crisis resource management training

External validation of simulation-based assessments with other performance measures of third-year anesthesiology residents.

Towards meaningful simulation-based learning with medical students and junior physicians.