This was a prospective randomized case–control study (CHIPS, checklist in prehospital settings, German Clinical Trials Register Study ID 00005156). We used the reproducible setting of a full-scale medical simulation. The simulations took place at the Human Simulation Center (HSC) of the University Hospital Munich’s Institute for Emergency Medicine and Medical Management.

The study participants were professional EMS providers who had completed training according to federal regulations and an active assignment with an EMS. The study participants were recruited from all 26 ambulance service areas in the state of Bavaria (Germany). Each study scenario was performed by a team of four participants typical of the German prehospital setting (two paramedics representing ambulances of type C [Mobile Intensive Care Unit, Rettungswagen], one pre-hospital emergency physician and one paramedic together representing a typical German physician staffed emergency unit [NEF]).

Figure 1 shows the chronological sequence of data acquisition in the CHIPS study.

Flow chart of data collection in the CHIPS study. EMS: emergency medical services, HSC: Human Simulation Center, CHIPS: Checklist in prehospital settings, ROSC: Return of spontaneous circulation, BLS: Basic Life Support, NEF: Notarzteinsatzfahrzeug (emergency vehicle)

The ethics committee of the Faculty of Medicine of the Ludwig-Maximilians-Universität in Munich (ID 475-12) and the University of Witten/Herdecke, Germany approved the study (ID 12/2020). All participants provided written informed consent before participation.

The scenario took place inside a standard ambulance vehicle (Typ C) mock-up at HSC. Participants were asked to perform cardiopulmonary resuscitation on an adult high-fidelity patient simulator (SimMan 3G, Laerdal Medical AS; Stavanger, Norway). It was reported that he suffered from witnessed cardiac arrest with ventricular fibrillation (see scenario script in supplements). At the time of the study, the 2010 ERC guidelines were well established (01/13 to 06/14). ROSC established following the third defibrillation. After ROSC occurred the prehospital emergency physician arrived on scene with a third paramedic.

Before the start of the scenario, an HSC instructor provided a standardized introduction to the patient simulator, simulation environment, and equipment. Teams used an automated external defibrillator in the semi-automatic mode (LIFEPAK 15 defibrillator, Physio-Control; Redmond, WA, USA). The device was adjusted to cprMAX mode, a technology intended to minimize hands-off times while charging. The team indicated that they used this configuration in daily routines.

The checklist used in the scenario transferred the guideline statements of the ERC Consensus 2010 on the management of patients with ROSC into the structure of the well-established, prehospital ‘ABCDE’ mnemonic, which should enable priority-oriented care of emergency. The five sections are organized according to the ‘treat first what kills first’ principle. The sections are: ‘Airway’ (A), with four items; ‘Breathing’ (B), with four items; ‘Circulation’ (C), with seven items; ‘Disability’ (D), with six items; and ‘Exposure’ (E), with four items (Fig. 2). The graphical representation of the checklist was prepared following the recommendations for the design of medical checklists formulated by Verdaasdonk et al. [20]. The checklist was recommended to start with a standardized team timeout according to Rall et al. [25] For the teams in the intervention group (INT), the checklist was released by announcement via speaker after the teams verbalized the ROSC situation (Fig. 1 Flow Chart CHIPS-Study). Individual time periods of checklist use in the intervention scenario were measured and summed up (checklist use duration). The teams received no instructions on how to use the checklist. Style of checklist use and other findings concerning the checklist were also recorded as additional findings.

Checklist based on ABCDE mnemonic. A: Airway, B: Breathing, C: Circulation, D: Disability

To allow assessment of guideline adherence, we created the so-called Performance Score (PS) as an evaluation measure. This score evaluates the completeness and prehospital relevance of guideline recommendations for ROSC therapy based on an expert consensus (medical directors of the emergency medical services of the state of Bavaria). Therefore, a numerical value was assigned to each of 25 guideline statement in order to represent the level of obligation defined by the expert consensus. Statements termed with ‘may’ got one point, ‘should’ statements correspond to two points and ‘must’ is equal to 3 points. The individual guideline recommendation was multiplied by this numerical value and weighted accordingly.

A maximum PS of 62 points could be achieved, since the experts evaluated 18 guideline statements (GS) with three points, three GS with one point and three GS with zero points. The target temperature management (TTM), which was recommended for the first time in the guideline consensus in 2010, was the only item to receive a value of 5, as it was intended to serve as a surrogate parameter for the speed of knowledge transfer from the guideline to practical clinical application.

To ensure study continuation on time, an indefinite observation period could not be realized for ROSC therapy section. After the call-out of ROSC, each scenario was continued for 10 min according to protocol. During this time, the patient remained unconscious.

To assess time management and effective use of procedure time, the number of processed items per minute of observation was measured (items/min).

To assess the degree of organization of the work process, compliance with the defined sequence of actions specified by the checklist was examined. Each item was assigned a fixed place according to the ‘ABCDE’ mnemonic as it was indicated by the checklist. The score is the sum of the deviations from the fixed order divided by the number of items performed.

We captured the following data: (a) continuous A/V recordings of the simulation scenario from different viewing angles and (b) real-time vital sign data from the patient’s monitor using the picture-in-picture technology. The participants also completed a standardized questionnaire with demographic data (before scenario) and rated the significance of the simulation scenario for their daily practice (right after scenario). The raw video data of 2 scenarios were damaged and could not be evaluated. The corresponding pre- and post-questionnaires of these scenarios could not be removed due to anonymization.

Statistical analyses were performed using SPSS statistical software (version 27; IBM Inc., Armonk, NY, USA), and Microsoft Excel and Office 365 (Microsoft, Redmond, WA, USA) were used. Data are expressed as absolute and relative values or means ± standard deviations (SD). In case of skew distributed data, the median (interquartile range) was used instead of the mean.

Effect sizes were determined by calculating Cohen’s d, with a Cohen’s d of 0.2, 0.5, and 0.8 indicating small, medium, and large effects, respectively.

The t-test was applied to show the mean differences between the two groups. The correlation determination of the variables was calculated using the determination of Pearson correlation. The level of significance was defined at p < 0.05.