Institutional resuscitation protocols: do they affect cardiopulmonary resuscitation outcomes? A 6-year study in a single tertiary-care centre

Society for Simulation in Healthcare Guidelines for Simulation Training

BACKGROUND

Simulation has become a staple in the training of healthcare professionals with accumulating evidence on its effectiveness. However, guidelines for optimal methods of simulation training do not currently exist.

METHODS

Systematic reviews of the literature on 16 identified key questions were conducted and expert panel consensus recommendations determined using the Grading of Recommendations Assessment, Development, and Evaluation (GRADE) methodology.

OBJECTIVE

These evidence-based guidelines from the Society for Simulation in Healthcare intend to support healthcare professionals in decisions on the most effective methods for simulation training in healthcare.

RESULTS

Twenty recommendations on 16 questions were determined using GRADE. Four expert recommendations were also provided.

CONCLUSIONS

The first evidence-based guidelines for simulation training are provided to guide instructors and learners on the most effective use of simulation in healthcare.

Educational and Patient Care Impacts of In Situ Simulation in Healthcare: A Systematic Review

ABSTRACT

This systematic review was performed to assess the effectiveness of in situ simulation education. We searched databases including MEDLINE and Embase for studies comparing in situ simulation with other educational approaches. Two reviewers screened articles and extracted information. Sixty-two articles met inclusion criteria, of which 24 were synthesized quantitatively using random effects meta-analysis. When compared with current educational practices alone, the addition of in situ simulation to these practices was associated with small improvements in clinical outcomes, including mortality [odds ratio, 0.66; 95% confidence interval (CI), 0.55 to 0.78], care metrics (standardized mean difference, -0.34; 95% CI, -0.45 to -0.21), and nontechnical skills (standardized mean difference, -0.52; 95% CI, -0.99 to -0.05). Comparisons between in situ and traditional simulation showed mixed learner preference and knowledge improvement between groups, while technical skills showed improvement attributable to in situ simulation. In summary, available evidence suggests that adding in situ simulation to current educational practices may improve patient mortality and morbidity.

Evaluation of Simulation Outcomes

Simulation has been used in nursing education and training since Florence Nightingale's era. Over the past 20 years, simulation learning experiences (SLEs) have been used with increasing frequently to educate healthcare professionals, develop and increase the expertise of practicing professionals, and gain competency in key interprofessional skills. This chapter provides a brief overview of simulation evaluation history, beginning in the late 1990s, and the initial focus on learner self-report data. Using Kirkpatrick's Levels of Evaluation as an organizing model, four types of SLE evaluation are reviewed as well as suggestions for future research.

A review of Code Blue activations in a single Regional Australian Healthcare Service: A retrospective descriptive study of RISKMAN data

BACKGROUND

In the case of life-threatening conditions such as respiratory or cardiac arrest, or the clinical deterioration of the patient, a Code Blue activation may be instigated. A Code Blue activation involves a team of advanced trained clinicians attending the emergency needs of the patient.

AIMS AND OBJECTIVES

The aim of the study was to explore the number of cases of Code Blue activations, looking at the timing, clinical ward, diagnosis and activation criteria while noting cases where escalation from a Medical Emergency Team (MET) call occurs in one Regional Healthcare Service in Victoria, Australia, over a six-year period.

METHODS

A quantitative retrospective descriptive study of Code Blue emergencies over a six-year period from June 2010 to June 2016 was conducted. Data collected from the RISKMAN program operating at a single site was imported into SPSS (V 22) for descriptive statistical analysis. A STROBE EQUATOR checklist was used for this study (see File S1).

FINDINGS

The majority of Code Blue activations were male (59%, n = 127) and aged between 70 and 89 years of age (43%, n = 93). A Code Blue activation was more likely to occur at 08:00 hr, 14:00 hr or 22:00 hr, corresponding to the nurses' change in shift, with the majority of Code Blues (27.8%, n = 60) occurring in the emergency department. Cardiac arrest was the main activation criterion with 54.6% (n = 118) cases followed by respiratory arrest (14%, n = 32). Interestingly, 20% (n = 45) of the Code Blue activations were upgraded from a Medical Emergency Team (MET) call.

CONCLUSION

This project has produced several interesting findings surrounding Code Blue activations at one regional healthcare service which are not present in existing literature and is worthwhile for further investigation.

RELEVANCE TO CLINICAL PRACTICE

Understanding Code Blue activation criteria, common timings (month, time of day) and patient demographics ensures clinicians can remain vigilant in watching for the signs of patient deterioration and improve staff preparedness Code Blue events.

In situ simulation and its effects on patient outcomes: a systematic review

Background

The use of in situ simulation has previously been shown to increase confidence, teamwork and practical skills of trained professionals. However, a direct benefit to patient outcomes has not been sufficiently explored. This review focuses on the effect of in situ simulation training in a hospital setting on morbidity or mortality.

Methods

A combined search was conducted in PUBMED, OVID, WEB OF SCIENCE, CINAHL, SCOPUS and EMBASE. 478 studies were screened with nine articles published between 2011 and 2017 meeting the inclusion criteria for analysis.

Results

This review selected eight prospective studies and one prospective-retrospective study. Three studies isolated in situ simulation as an experimental variable while the remaining studies implemented in situ programmes as a component of larger quality improvement initiatives. Seven studies demonstrated a significant improvement in morbidity and/or mortality outcomes following integrated in situ simulation training.

Conclusion

Existing literature, albeit limited, demonstrates that in situ training improves patient outcomes either in isolation or within a larger quality improvement programme. However, existing evidence contains difficulties such as isolating the impact of in situ training from various potential confounding factors and potential for publication bias.