Team communication patterns during real and simulated trauma resuscitation—a social network analysis

Figures & data

Table 1. Characteristics of functional and divisional team structures.

Team structure characteristics
Functional team structure	Divisional team structure
Role specialisation	Cross-over competencies
Interdependence	Multi-functioning
Central coordination	Autonomous parts
Centralised communication	Decentralised coordination/communication

Table 2. Overview of the in-real-life (IRL) cases A–D and the simulated (SIM) cases 1–4.

Case	Short description
IRL A	Young male, bicycle rider without helmet, high-speed car collision, pain in back and neck, spontaneous nystagmus, stabile vital signs
IRL B	Middle-aged man, crashed on a road race bike, amnesia, suspected neurological deficits, stable vital signs
IRL C	Young adult man, knife assault, sharp thoracic laceration wound, respiratory distress
IRL D	Senior male on Warfarin treatment, four-wheel terrain motor vehicle accident, initially unconscious, amnesia, fluctuations in alertness during primary survey, open extremity fracture
SIM 1	Middle-aged woman, squeezed between the wall and an elephant at zoo, declining consciousness, pneumothorax, suspected internal bleeding
SIM 2	Middle-aged woman, self-inflicted fall accident, open bilateral femoral fractures, agitated patient with suspected vessel injury, unstable circulation
SIM 3	Young man, skiing accident, crash against a tree, fractured extremities, declining consciousness
SIM 4	Young woman, horse accident, unstable circulation, suspected pelvic fracture, and internal bleeding

Table 3. Participating team roles in the in-real-life (IRL) cases A–D and in the simulated (SIM) cases 1–4.

Team member	IRLA	IRLB	IRLC	IRLD	SIM 1	SIM 2	SIM 3	SIM 4
Examining physician	x	x	x	x	x^c	x	x	x
Team leader	x^b	x^b	x	x^c	x	x	x	x
Anaesthesiologist	x	x	x	x	x	x^d	x	x^d
Orthopaedic surgeon	x	x	x	x	x	x	x	x
Emergency room nurse	x^a	x	x	x^a	x	x	x	x
Emergency room nurse 2	x	x	x	x	x	x	x	x
Airway nurse	x	x	x	x	x	x	x	x
Patient	x	x	x	x	x	x	x	x
Anaesthesiologist 2				x	x			x
Intern	x			x		x	x
Documenting nurse		x		x		x	x	x
Coordinating nurse	x			x		x		x
Radiology nurse	x	x	x		x
Emergency room assistant nurse	x	x	x	x	x	x	X
Emergency room assistant nurse 2				x
Retrieving ambulance nurse				x
Instructor 1					x	x	x	x
Instructor 2						x	x	x
Total team members (n)	12	11	10	15	12	13	13	13

^aThe same nurse had the emergency room nurse role in both IRL A and IRL D.

^bThe same resident physician had the team leader role in both IRL A and IRL B.

^cThe same resident physician had the team leader role in IRL D and the examining physician role in SIM 1.

^dThe same resident anaesthesiologist had the anaesthesiologist role in both SIM 2 and SIM 4.

Table 4. Example of coding into a matrix for ‘all communications’.

	Anaesthesiologist	Airway nurse	Emergency physician
Anaesthesiologist		1(B)	1(E)
Airway nurse	1(C)
Emergency physician	2(A,D)	1(A)

The number is the recorded communication events for each direction, and the letter(s) following the number is/are the derived utterance from the fictive example above.

Table 5. Example of coding into a matrix for ‘individually directed communications’.

	Anaesthesiologist	Airway nurse	Emergency physician
Anaesthesiologist		1(B)	1(E)
Airway nurse	1(C)
Emergency physician	1(D)

The number is the recorded communication events for each direction, and the letter following the number is the derived utterance from the fictive example above.

Table 6. Transcription details from the four real (IRL) and four simulated (SIM) cases.^a

Case	Time (min)	Nodes1 (n)	Utterances (n)	Communication events (n)	Verbal communication ‘talking to the room’ n (%)	Rate of verbal communication events (n/min)
IRL A	13	12	487	1334	94 (19.3%)	37/min
IRL B	19	11	531	1322	100 (18.8%)	28/min
IRL C	24	10	643	1122	69 (10.1%)	27/min
IRL D	11	15	953	1859	107 (11.2%)	87/min
SIM 1	20	12	600	1417	107 (17.8%)	30/min
SIM 2	7	13	284	1347	128 (45%)	41/min
SIM 3	13	13	503	1128	78 (15.5%)	39/min
SIM 4	11	13	418	1405	122 (29%)	38/min

^aNumber of team members.

Table 7. Nodes with the highest weighted point centrality scores of real (IRL A–D) and simulated cases (SIM 1–4) for individually directed and all communicative events.

Case	IRL A	IRL B	IRL C	IRL D	SIM 1	SIM 2	SIM 3	SIM 4
Highest weighted degree centrality (all/directed)	EP/A	EP/EP	EP/EP	EP/EP	EP/EP	EP/EP	EP/EP	EP/EP
Highest weighted out-degree centrality (all/directed)	EP/A	EP/EP	EP/EP	EP/EP	EP/A	EP/EP	EP/EP	EP/EP
Highest weighted in-degree centrality (all/directed)	EN2/EP	P/P	P/P	EP/EP	EP/EP	AN/M	A/EP	AN/EP

A: anaesthesiologist; AN: airway nurse; EAN: assistant nurse; EN: emergency nurse; EN2: emergency nurse 2; EP: examining physician; M: instructor 1; P: patient; TL: team leader.

‘All communication’ is the sum of individually directed communication and ‘ talking to-the-room’.

Table A1. Description of the hospitals level one trauma statistics in regards of trauma mechanisms, age groups and severity of incoming cases.

	2017 n	2018 n	2019 n	2017–2019 n (%)
Trauma cases	135	141	162	438 (100)
Gender
Female	No data	43	52
Male	No data	98	110
Trauma severity score
ISS >15	No data	25	21
NISS >15	No data	28	39
Trauma mechanism
Traffic injury	88	85	94	267 (60.1)
Knife injury	15	13	15	43 (9.8)
Gun injury	3	2	3	8 (1.8)
Fall	23	32	33	87 (19.9)
Explosion	0	1	1	2 (0.5)
Other	6	7	15	28 (6.1.
Post-ER/CT destination
Intensive care unit	35	24	29	88 (20.1)
Operation room	8	9	14	31 (7.1)
Deceased	7	8	8	23 (5.3)
Other	85	100	112	297 (67.8)

ISS: Injury Severity Score; NISS: New Injury Severity Score; ER: emergency room; CT: computed tomography.

Figure 1. Examples of social networks as examined by Leavitt (1951). Black node: team leader; Grey node: team member; Black line: communication.

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A simplified illustration of four different social networks spanning from the most centralised to the most decentralised network is shown. Each network is made up of 5–6 black and grey nodes. The first network is called ‘Wheel’—the black node is located at the centre of the network and has connections with all five grey nodes, which do not connect with one another. The second is named ‘Y’. A black node is located at the branching of the letter ‘Y’, thus having connections to three nodes, however unconnected with the lowest positioned grey node. The third is named ‘Chain’. The black node is located at the centre of a chain, and thus has connections to two adjacent nodes, but is unconnected with the other two. The fourth is named ‘circle’. It differs from the other in that no black node is present. It contains five grey nodes which are connected as a circle. All grey nodes have connections to the two nearby nodes. The wheel network is the most centralised and the circle network is the most decentralised.

Figure 2. Density is calculated as 2M/(N(N − 1)), where N = number of nodes (circles A–E in the figure) and M = number of connections between nodes.

This is an illustration of the density of two networks of the same size. There are five nodes in each network, A–E. In the first network, there are lines connecting all nodes. This represents the maximum possible connections (10) in a 5-node network, and the network has a density of 1.0. The second network has connections between A–B, A–E, B–C, B–E, B–D, and E–D. The density is hence 6/10 = 0.6.

Figure 3. Density of real (IRL A–D) and simulated (SIM 1–4) cases, using all and individually directed communication. ‘All communication’ is the sum of individually directed communication and ‘talking to-the-room’.

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This is a bar diagram of the eight cases studied with density on the y-axis (0–1). For each case, there are two bars, where the first shows the density calculated from all communication (black) and the second from individually directed communication (grey). The cases are displayed in sequence IRL A–D followed by SIM 1–4. In all cases, the density value is higher when all communication is used. In ‘IRL C’, the difference between the bars is the lowest, and in SIM 2 the difference is the largest. The difference between the bars represents the effect of TTR on the density of the case. In order from least to highest difference are IRL C, SIM 3, IRL D, SIM 1, SIM 4, IRL B, IRL A, and SIM 2.

Figure 4. Average clustering of real (IRL A–D) and simulated (SIM 1–4) cases using all and individually directed communication. ‘All communication’ is the sum of individually directed communication and ‘talking to-the-room’.

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This is a dot plot with the eight cases studied on the X-axis, and the clustering coefficient (0–1) on the Y-axis. For each case, there are two dots, where the first (grey) shows the clustering coefficient calculated from all communication and the second (black) from individually directed communication. The distance between the dots for each case represents the effect of TTR communication on clustering coefficient. The cases are displayed in sequence IRL A–D followed by SIM 1–4. In all cases the grey dot is located at a higher level than the black dot, meaning that the clustering coefficient is higher when all communication is used for the calculation. This accounts for a lower degree of clustering in the network. The least distance between the dots is seen for SIM 3, and the greatest distance is seen for SIM 2. For the six remaining cases, the distances between the dots vary, but to a smaller degree.

Figure 5. Overall weighted centralisation comparing all and individually directed communication for real (IRL A–D) and simulated (SIM 1–4) cases. ‘All communication’ is the sum of individually directed communication and ‘talking to-the-room’.

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This is a bar diagram of the eight cases studied with overall centrality on the y-axis (0–1). For each case, there are two bars, where the first shows the overall centralisation calculated from all communication (black) and the second from individually directed communication (grey). The cases are displayed in sequence IRL A–D followed by SIM 1–4. In IRL A, IRL C, IRL D, SIM 3, and SIM 4, overall centralisation is higher when all communication is used, whereas the reverse pattern is seen for IRL B, SIM 1, and SIM 3. The difference between bar height is less for the four last cases. The figure shows that TTR communication has a centralising effect on the networks more often and to a greater extent than it has a decentralising effect.

Figure 6. The relative weighted degree centralities of different team roles of the real (IRL A–D) and simulated (SIM 1–4) cases using individually directed communication. EP: examining physician; A: anaesthesiologist; TL: team leader; EN: emergency room nurse; EN2: emergency room nurse 2; AN: airway nurse; EAN: assistant nurse; P: patient; OS: orthopaedic surgeon; DN: documenting nurse; EAN2: assistant nurse 2; XN: radiology nurse; M: instructor; A2: anaesthesiologist 2; M2: instructor 2.

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This is a dot plot with relative degree centrality on the Y-axis and the cases IRL A–D and SIM 1–4 on the x-axis. The dots for each case represent members of the team and the positions represent their relative degree centrality. The dots are labelled by team role. All cases have 1–3 team members with a high relative degree centrality (0.9–1) and an apparent distance to the next following team members of at least 0.24. The highest relative degree centrality is seen for the examining physician in IRL B-D and SIM 1–4, and the Anaesthesiologist in IRL 1. In the three cases IRL A, SIM 1, and SIM 2 more than one team member have relative degrees >0.9. These roles are Emergency physician, Anaesthesiologist, and team leader in different particular orders. The case with the greatest difference between the highest relative degree centrality team role and the next highest is sim 4. IRL B shares this feature, but the patient has the next highest relative degree centrality.

Leavitt, H.J. 1951. “Some Effects of Certain Communication Patterns on Group Performance.” Journal of Abnormal Psychology 46 (1): 38–50. doi:10.1037/h0057189.

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Data availability statement

Data sharing of original videos is not possible as they are sensitive in nature. The datasets supporting the conclusions of this article are available in this article and its Supplementary Files.