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Simulation in Healthcare: The Journal of the Society for Simulation in Healthcare:
doi: 10.1097/SIH.0b013e3181a46aa1
Empirical Investigations

Perception of Realism During Mock Resuscitations by Pediatric Housestaff: The Impact of Simulated Physical Features

Donoghue, Aaron J. MD, MSCE; Durbin, Dennis R. MD, MSCE; Nadel, Frances M. MD, MSCE; Stryjewski, Glenn R. MD; Kost, Suzanne I. MD; Nadkarni, Vinay M. MD, MS

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Author Information

From the Division of Emergency Medicine (A.J.D, D.R.D., F.M.N.), Division of Critical Care Medicine (A.J.D., V.M.N.), Children's Hospital of Philadelphia, Pennsylvania; Division of Critical Care Medicine (G.R.S.), and Division of Emergency Medicine (S.I.K.), A. I. DuPont Hospital for Children, Wilmington, Delaware.

Supported by the Laerdal Foundation for Acute Medicine grant.

Reprints: Aaron Donoghue, MD, MSCE, Divisions of Emergency Medicine and Critical Care Medicine, The Children's Hospital of Philadelphia, Room AS24, 34th Street and Civic Center Boulevard, Philadelphia, PA 19104 (e-mail: donoghue@email.chop.edu).

The authors declare no conflict of interest.

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Abstract

Introduction: Physical signs that can be seen, heard, and felt are one of the cardinal features that convey realism in patient simulations. In critically ill children, physical signs are relied on for clinical management despite their subjective nature. Current technology is limited in its ability to effectively simulate some of these subjective signs; at the same time, data supporting the educational benefit of simulated physical features as a distinct entity are lacking. We surveyed pediatric housestaff as to the realism of scenarios with and without simulated physical signs.

Methods: Residents at three children's hospitals underwent a before-and-after assessment of performance in mock resuscitations requiring Pediatric Advanced Life Support (PALS), with a didactic review of PALS as the intervention between the assessments. Each subject was randomized to a simulator with physical features either activated (simulator group) or deactivated (mannequin group). Subjects were surveyed as to the realism of the scenarios. Univariate analysis of responses was done between groups. Subjects in the high-fidelity group were surveyed as to the relative importance of specific physical features in enhancing realism.

Results: Fifty-one subjects completed all surveys. Subjects in the high-fidelity group rated all scenarios more highly than low-fidelity subjects; the difference achieved statistical significance in scenarios featuring a patient in asystole or pulseless ventricular tachycardia (P < 0.04 for both comparisons). Chest wall motion and palpable pulses were rated most highly among physical features in contributing to realism.

Conclusions: PALS scenarios were rated as highly realistic by pediatric residents. Slight differences existed between subjects exposed to simulated physical features and those not exposed to them; these differences were most pronounced in scenarios involving pulselessness. Specific physical features were rated as more important than others by subjects. Data from these surveys may be informative in designing future simulation technology.

Among the many advantages of high-fidelity patient, simulation is the availability of physical signs as features to be programmed into clinical scenarios. These signs can include audible sounds, such as vocal sounds; auscultatable sounds, such as lung, heart, and bowel sounds; observable signs, such as chest wall movement, cyanosis, and seizure activity; and palpable signs, such as peripheral and central pulses. An optimal simulation milieu uses these signs in combination with real-time vital sign monitoring and allows learners to take cues toward decision making by physically examining the simulator directly, as opposed to being verbally prompted by a facilitator as to the patient's physical findings. However, published data to date have not clearly supported the concept that simulated physical features, as distinct from other elements of a simulation experience, are of particular educational benefit.

In the critically ill child, physical signs are of particular importance in clinical decision making, because objective vital sign changes indicative of clinical deterioration, such as hypoxia and hypotension, are frequently late findings in the setting of critically worsening respiratory or circulatory insufficiency.1 Other important physical signs of respiratory and circulatory failure, such as pallor, mottling, capillary refill, mental status alteration, and gasping or agonal respirations, are not as appreciable in currently available patient simulators. A simulation experience for the pediatric trainee which effectively conveys the state of critical respiratory or circulatory insufficiency is desirable, but it is unclear what contribution simulated physical features would make separate from other elements of a simulated clinical milieu.

We designed a set of survey instruments for pediatric residents undergoing a simulation-enhanced Pediatric Advanced Life Support (PALS) training session to determine how specific simulated physical signs were perceived in their realism and contribution to the simulated patient learning experience. Data for this study were collected in the context of a larger randomized trial examining the effect of high-fidelity simulation on cognitive performance of pediatric housestaff during mock resuscitations.2

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METHODS

Residents at three tertiary children's hospitals were invited to participate. All three hospitals obtained local institutional review board's approval for the conduct of the study. Eligible participants were pediatric housestaff at level of postgraduate year 1 or 2 during the time period May 2006–January 2007. All residents approached for the study must have completed at least 5 months but no more than 14 months of residency training. Baseline data collected on each participant included their prior participation in resuscitations, their clinical procedural experience, and their experience with mock code exercises in the past (with or without simulators). After written informed consent, participants were randomized within study site and postgraduate level to either the simulator group (SIM) or the mannequin group (MAN). Neither investigators nor subjects were blinded to group assignment.

Each study session was divided into three phases (Fig. 1). The first phase (PRE phase) consisted of four case scenarios designed to require the performance of cognitive tasks pertinent to clinical assessment and intervention according to different PALS algorithms. The second phase consisted of a one-on-one review with a single investigator (AJD) of PALS algorithms, with subjects allowed to ask questions. The third phase (POST phase) consisted of two additional scenarios designed to require the same set of tasks as the PRE phase scenarios but in an altered clinical context so as to maintain the perception of “new” cases. All sessions at all three sites were run on an infant patient simulator (SimBaby, Laerdal) and were facilitated by the same investigator (AJD) to assure uniformity of the educational experience.

Figure 1
Figure 1
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For the intervention (SIM) group, all three study phases were conducted using a high-fidelity infant patient simulator (SimBaby, Laerdal) connected to an air compressor and with audio speakers enabled, which provided physical signs that were visible (chest wall movement, cyanosis), audible (vocal sounds), auscultatable (breath sounds, heart sounds), or palpable (central and peripheral pulses). For the control (MAN) group, the simulator was disconnected from the air compressor and the audio speakers were silenced, thus rendering the simulator equivalent to a standard mannequin. The scenarios are summarized in Figure 2 along with a description of the physical features employed in them for the SIM group.

Figure 2
Figure 2
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Figure 2
Figure 2
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Figure 2
Figure 2
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For all study participants in both groups, scenarios were run using the simulator software and vital signs waveforms (when obtained correctly by participants) were displayed in real time on a cardiorespiratory monitor interface. All study sessions for both groups were run in an identical setting (the same intensive care unit treatment room), with an identical resuscitation cart and equipment available. Each case was introduced by a standardized audio recording.

After the completion of all three phases, participants completed brief survey instruments. In survey 1, all participants in both groups were asked to rate the realism of each scenario in the PRE and POST phases on a 5-point Likert scale. In survey 2, participants from the SIM group only were asked to rate on a 5-point Likert scale the impact of each simulated physical sign on the realism of the scenarios (Fig. 3).

Figure 3
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Descriptive statistics with regard to survey responses were performed across both groups. Univariate comparison between SIM and MAN groups with respect to responses on Survey 1 was done by Wilcoxon rank sum testing. Responses to Survey 2 were summarized descriptively. All statistical analyses were performed using STATA version 8.0.

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RESULTS

Fifty-one subjects completed all three study phases (SIM: n = 25; MAN: n = 26). Baseline data with respect to mock code and simulation experience, as well as experience with actual resuscitations, are shown in Table 1. Nonparametric univariate analysis of these data yielded no significant differences between the two groups.

Table 1
Table 1
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Results of survey 1 are shown in Table 2. All scenarios were rated as highly realistic by both groups; the mean score was higher in the SIM group than the MAN group for all six scenarios. The difference achieved statistical significance for the PRE phase asystole (P = 0.036) and POST phase asystole/dysrhythmia (P = 0.038) scenarios; differences between the groups with regard to rating the other scenarios were not significant.

Table 2
Table 2
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Results from survey 2 are shown graphically in Figure 4. Physical features dependent on auscultation (breath sounds, heart sounds) were ranked as somewhat less contributory to the realism of the scenarios, with heart sounds having the lowest mean ranking overall (mean 2.83 ± 1.3). Chest wall movement (mean 4.48 ± 0.6) and pulses (mean 4.52, ± 0.7) were most highly rated.

Figure 4
Figure 4
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DISCUSSION

Our study showed that junior pediatric residents undergoing a PALS training exercise found the clinical scenarios to be highly realistic with or without the use of high-fidelity simulation of specific physical findings. SIM group subjects gave slightly higher ratings to all six scenarios, but the difference only achieved statistical significance for scenarios that included the transition from a pulsatile state to a pulseless state (or vice versa). SIM subjects also gave particularly high ratings to the presence of a pulse among the physical findings listed in survey 2. These results suggest that the presence or absence of a palpable pulse in the simulated patient is a physical finding that adds to perceived realism. Conversely, the finding of weak pulses was not as highly rated, and the scenarios where the simulated patient exhibited hypoperfusion but not pulselessness (PRE tachydysrhythmia, PRE shock, and POST respiratory/shock) were not found to have significant differences in perceived realism between SIM and MAN groups; this may suggest that qualitative differences in perfusion (as judged by pulse palpation) did not contribute as strongly to realism.

Pediatric resuscitations are uncommon occurrences, and pediatric cardiac arrests have been associated with dismal outcomes despite pediatric-specific resuscitation guidelines, which have existed for decades.3,4 The use of established certification courses (eg, PALS) has been relied on for years, despite evidence that the effect of such teaching does not lead to long-term retention of knowledge or psychomotor skill.5 A recent advisory statement from the International Liaison Committee on Resuscitation for improving education included the recommendation that “high-fidelity simulation training should increasingly supplement instructor-directed training” in advanced life support courses.6 The rarity of the actual clinical events, coupled with their “high-stakes” nature and the necessity of maintaining a baseline level of preparedness for them, make pediatric resuscitation an ideal fit with the simulation paradigm.7

Studies in pediatric simulation have shown promise in its applicability to a variety of clinical areas, including newborn resuscitation8 and trauma management,9 but have not focused specifically on the use of particular technology or the impact of specific physical features of simulation exercises to date. Halamek et al,8 in their study of a simulated neonatal resuscitation training program found that despite only 50% of respondents saying the mannequin used “provided a real-life experience,” that the overall experience was highly instructive and beneficial, driven in large part by positive responses to scenarios and debriefing techniques. Our data attempt to examine the specific contribution to realism that simulated physical features make by comparing two groups of subjects whose study sessions were otherwise identical, other than the use of physical features in one group. A modest difference seems to exist, but its significance is difficult to determine.

The fact that pulse palpation was perceived by subjects as a useful physical sign in simulated resuscitations presents a challenge. The most recent revision of American Heart Association guidelines removed the recommendation that lay rescuers perform a pulse check10 based on multiple studies demonstrating its inaccuracy when performed by laypeople and healthcare providers in both healthy volunteers11,12 and adult patients with nonpulsatile circulation during cardiopulmonary bypass.13,14 Multiple studies in healthy children have demonstrated that pulse palpation is inaccurate in the pediatric age range as well, performed either by laypeople or by healthcare personnel.15–17 A recent study by Tibballs and Russell 18 examined this phenomenon for the first time in children receiving nonpulsatile extracorporeal circulatory support and found a poor overall accuracy of 78% for pulse checks performed by healthcare personnel. Given the growing evidence of the unreliability of the pulse check, the need may be becoming clearer for another means of simulating shock and circulatory arrest, particularly if considered in light of our data demonstrating how prominently the pulse check figured into our subjects' experience.

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Limitations

Our study was conducted in junior pediatric residents, who, with very rare exception, are novices in actual resuscitation experience. Our background data for our set of subjects are in keeping with prior studies documenting the scant experience pediatric housestaff generally have with respect to actual patient resuscitations.19 Junior housestaff were judged to be the most suitable group of potential subjects for the larger study examining cognitive performance, which allowed the collection of this data.

During the study period, high-fidelity simulation for mock codes was not yet in widespread use at the centers, where the study was conducted. It is possible that the degree of perceived realism expressed by our inexperienced study subjects would not be generalizable to more senior healthcare practitioners, whose opinions regarding the realism of the simulated scenarios might be more illustrative.

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CONCLUSIONS

Junior pediatric residents rated simulated PALS scenarios as highly realistic, and the use of high-fidelity simulation for physical findings resulted in greater realism in some scenarios. The varied responses of subjects to how realistic specific physical findings are on high-fidelity simulators may be of use in identifying shortcomings in current simulator features, particularly with regard to the pediatric patient and examining these phenomena further, and in a more varied group of healthcare providers may help guide the design and implementation of future simulation technology.

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REFERENCES

1.American Heart Association. Pediatric Advanced Life Support. Dallas, TX: American Heart Association; 2005.

2.Donoghue AJ, Durbin DR, Nadel FM, Stryjewski GR, Kost SI, Nadkarni VM. The effect of high-fidelity simulation on Pediatric Advanced Life Support training in pediatric housestaff: a randomized trial. Pediatr Emerg Care 2009;25:139.

3.Donoghue AJ, Nadkarni V, Berg RA, et al. Out-of-hospital pediatric cardiac arrest: an epidemiologic review and assessment of current knowledge. Ann Emerg Med 2005;46:512–522.

4.Nadkarni VM, Larkin GL, Peberdy MA, et al. First documented rhythm and clinical outcome from in-hospital cardiac arrest among children and adults. JAMA 2006;295:50–57.

5.Grant EC, Marczinski CA, Menon K. Using pediatric advanced life support in pediatric residency training: does the curriculum need resuscitation? Pediatr Crit Care Med 2007;8:433–439.

6.Chamberlain DA, Hazinski MF. Education in resuscitation: an ILCOR symposium: Utstein Abbey: Stavanger, Norway: June 22–24, 2001. Circulation 2003;108:2575–2594.

7.Fiedor ML. Pediatric simulation: a valuable tool for pediatric medical education. Crit Care Med 2004;32(suppl 2):S72–S74.

8.Halamek LP, Kaegi DM, Gaba DM, et al. Time for a new paradigm in pediatric medical education: teaching neonatal resuscitation in a simulated delivery room environment. Pediatrics 2000;106:E45.

9.Hunt EA, Hohenhaus SM, Luo X, Frush KS. Simulation of pediatric trauma stabilization in 35 North Carolina emergency departments: identification of targets for performance improvement. Pediatrics 2006;117:641–648.

10.Cummins RO, Hazinski MF. Guidelines based on fear of type II (false-negative) errors. Why we dropped the pulse check for lay rescuers. Resuscitation 2000;46:439–442.

11.Ochoa FJ, Ramalle-Gómara E, Carpintero JM, García A, Saralegui I. Competence of health professionals to check the carotid pulse. Resuscitation 1998;37:173–175.

12.Bahr J, Klingler H, Panzer W, Rode H, Kettler D. Skills of lay people in checking the carotid pulse. Resuscitation 1997;35:23–26.

13.Dick WF, Eberle B, Wisser G, Schneider T. The carotid pulse check revisited: what if there is no pulse? Crit Care Med 2000;28(suppl 11):N183–N185.

14.Eberle B, Dick WF, Schneider T, Wisser G, Doetsch S, Tzanova I. Checking the carotid pulse check: diagnostic accuracy of first responders in patients with and without a pulse. Resuscitation 1996;33:107–116.

15.Inagawa G, Morimura N, Miwa T, Okuda K, Hirata M, Hiroki K. A comparison of five techniques for detecting cardiac activity in infants. Paediatr Anaesth 2003:13:141–146.

16.Lee CJ, Bullock LJ. Determining the pulse for infant CPR: time for a change? Mil Med 1991;156:190–193.

17.Sarti A. Savron F, Casotto V, Cuttini M. Heartbeat assessment in infants: a comparison of four clinical methods. Pediatr Crit Care Med 2005;6:212–215.

18.Tibballs J, Russell P. Reliability of pulse palpation by healthcare personnel to diagnose paediatric cardiac arrest. Resuscitation 2009;80:61–64.

19.Nadel FM, Lavelle JM, Fein JA, Giardino AP, Decker JM, Durbin DR. Assessing pediatric senior residents' training in resuscitation: fund of knowledge, technical skills, and perception of confidence. Pediatr Emerg Care 2000;16:73–76.

Keywords:

Pediatrics; Simulation; Education; Resuscitation

© 2010 Lippincott Williams & Wilkins, Inc.

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