Introduction

High quality mechanical ventilation care, such as the Awakening, Breathing, Coordination, Delirium and Early Mobility (ABCDE) bundle, has been associated with lower mortality for critically ill adults [1–3]. However, efforts to improve ABCDE delivery have been variably successful [4]. A study conducted in 2015–2017 in 68 intensive care units (ICUs) across the United States found ABCDE performance was only 4%; after receiving an intervention to improve ABCDE, performance only increased to 12% [4]. Recent data suggests that ABCDE delivery is much lower as a result of the COVID-19 pandemic [5, 6], suggesting opportunity for improvement.

Delivery of the ABCDE bundle is a complex team practice [7], with data suggesting that the nurse, physician, and respiratory therapist are the clinicians involved [8]. Delivering ABCDE involves clinicians coordinating interdependent tasks like awakening the patient, coordinating extubation, assessing for delirium and encouraging mobility [9]. As such, ABCDE involves communication, coordination, and interaction among the interprofessional team [7, 10, 11], which are also foundational processes for effective teamwork [12]. Indeed, prior work has found that interactions among team members are integral to teamwork [13] and improved patient outcomes [14, 15]. Despite this recognition, there is limited empirical evidence about team member interactions when delivering ABCDE to each patient, each shift [16]. By examining interactions among the team members who deliver ABCDE, we can identify areas for possible intervention that have not been studied before, as a way to improve ABCDE delivery and teamwork.

Building off standard network science approaches that survey individuals to identify who interacts with whom (e.g., to whom they provide and receive information [17–19], we conducted a longitudinal prospective shift-level survey of ICU clinicians caring for mechanically ventilated adults in 2 ICUs. The purpose of this study was to determine the number and types of individuals (i.e., clinicians and family members) interacting in the care of mechanically ventilated patients (i.e., ABCDE bundle) each shift, as reported by the patient’s assigned physician, nurse, and respiratory therapist (RT), in ICUs. The goal is to inform interventions to improve the interprofessional team’s ability to deliver ABCDE to each patient, each shift.

Methods

Data analysis

We analyzed clincians’ survey responses at the patient-shift level (i.e., a clinician’s response to a survey about a specific patient during a specific shift); we used quantitative cross-sectional analyses for the full sample, and stratified by the type of reporting clinician (physician, nurse, RT) and by shift (day versus night). We calculated our response rate (total number of completed and returned surveys divided by the number of all surveys possible) and then calculated descriptive statistics for the full sample. We also calculated descriptive statistics by day versus night shift using numbers/percentages for dichotomous variables (e.g., a clinician checked/ did not check interacting with the bedside nurse) and means/ranges for count variables (e.g., how many individuals does a clinician report interacting with over the patient’s care)]. The results are presented in Table 1.

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Table 1. Descriptive statistics of the sample.

https://doi.org/10.1371/journal.pone.0298586.t001

We examined the interprofessional pattern of interactions. We categorized survey responses by the type of interactions reported: 1) ‘attending physician’, ‘resident physician’, ‘fellow’ and ‘intern’ were categorized as physicians, 2) ‘bedside nurse’, ‘charge nurse’, ‘nurse manager’, and ‘other nurse’ were categorized as nurses, and 3) ‘respiratory therapist’ was left as its own category, RTs. We then calculated 3x3 interprofessional interaction matrixes showing the frequencies of each type of interprofessional interactions (physician, nurse, RT) for each type of reporting clinician (physician, nurse, RT). The matrixes were calculated for the full sample and by day versus night shift and tested for statistical differences between day and night shift interactions (see Table 2).

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Table 2. Distribution of clinician interactions by clinician type, day, and night shift.

https://doi.org/10.1371/journal.pone.0298586.t002

Lastly, we created frequency distributions for interactions with each type of individual in the set of all individuals involved in a patient’s care during a shift (all physicians, nurses, RTs, other clinicians, and family members). We created three frequency distributions, one for each type of reporting clinician (physician, nurse, RT). The histograms for the full sample are presented in Figs 1–3; similar histograms for day versus night shift analyses are presented in S1–S3 Figs.

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Fig 1. Frequency of clinician interactions as reported by physicians (n = 499).

https://doi.org/10.1371/journal.pone.0298586.g001

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Fig 2. Frequency of clinician interactions as reported by nurses (n = 523).

https://doi.org/10.1371/journal.pone.0298586.g002

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Fig 3. Frequency of clinician interactions as reported by RTs (n = 536).

https://doi.org/10.1371/journal.pone.0298586.g003

Results

We received 1558 complete surveys (499 physician surveys, 523 nurse surveys, and 536 RT surveys) from 404 clinicians who cared for 169 patients over 166 shifts for a total response rate of 65% (Table 1). We collected more surveys during the day shift than the night shift (Table 1). The number of clinicians surveyed per patient-shift varied between 1 and 4, with the majority of patient shifts (42.9%) having 2 clinicians surveyed. Physicians, nurses, and RTs were equally represented among surveyed respondents (i.e., about one-third from each clinician category).

The average number of interactions within a patient’s ICU team was 2.60 (range 0–9; Table 1). Within each team, physicians reported an average of 2.65 interactions (range 0–8), nurses reported an average of 3.33 interactions (range 0–9), and RTs reported 1.86 interactions (range 0–7). Across all shifts, the reported interactions were fewer on night shift (1.99, range 0–8) compared to day shift (3.02, range 0–9). The largest difference in interactions on night shift, compared to day shift, was reported by physicians (3.44, range 0–9 on day shift compared to 1.66, range 0–8 on night shift); RTs reported a similar number of interactions across both shifts (1.67, range 0–7 on night shift compared to 1.98, range 0–5, on day shift).

Most interactions each shift were interprofessional (Table 2). Physicians reported the highest frequency of interactions with nurses: 70.5% of physician surveys reported interacting with at least one nurse (e.g., a bedside nurse or a charge nurse), followed by other physicians (57.3% of surveys), and RTs (48.3% of surveys). Nurses also reported the highest frequency of interactions with physicians (78.8% of surveys), followed by RTs (72.7% of surveys), and other nurses (37.3% of surveys). RTs reported the highest frequency of interactions with nurses (77.8% of surveys), followed by physicians (51.9% of surveys) and other RTs (11.6%). For nearly all nurse and physician surveys, the differences between day and night shift interactions were statistically significant (Table 2).

Across all three clinician types, the bedside nurse was the most frequently reported interaction (reported in 69.9% of physician surveys and 75.9% of RT surveys) (Figs 1–3). Among physicians, interactions with the patient’s attending were reported in 35.2% of nurses surveys and 21.3% of RT surveys whereas interactions with the resident were reported in 53% of nurses surveys and 27.2% of RT surveys. Interns were reported in 41.9% of all nurses surveys whereas fellows were mentioned less frequently (22.8% for physician surveys, 20.5% for nurses surveys, 15.3% for RT surveys). Across all surveys, the least reported interactions were with nurse managers and physical therapists, and other nurses (e.g., charge nurse, clinical nurse specialist, clinical nurse leader or other staff nurse). On the day shift, cinicians reported interacting with family members although this varied by clinician (Figs 1–3): physicians reported interacting with a family member on 18.5% of day-shift surveys (S1 Fig), nurses on 24.6% of day-shift surveys (S2 Fig), and RTs on 5.3% of day-shift surveys (S3 Fig). Interactions with family members were less frequent overnight, with only 10.8% of nurse night-shift surveys (S2 Fig) and <5% of physician and RT night-shift surveys reporting such interactions (S1 and S3 Figs).

Overall, clinicians reported interacting with one fewer individual during the night shift than during the day shift (1.99 versus 3.02 individuals) (Table 1). In addition to fewer interactions with family members, attending physician interactions were less frequently reported during night shifts: only 9.2% of RT night-shift surveys and <5% of nurses and physician night-shift surveys reported interacting with the attending physician (S1–S3 Figs). Notably, 34.8% of physician surveys, 8.6% of nurses surveys, and 19.4% of RT surveys taken during the night shift reported no interactions with any individuals over the patient’s care that shift (S1–S3 Figs).

Discussion

In 2 ICUs in the Midwest, we used a network lens to identify a small number of interprofessional team member interactions each shift when delivering ABCDE. Nurses interacted most often with other clinicians and family members. While this may appear self-evident, until now, there was no empirical data demonstrating individual clinicians interactions in ABCDE for each patient, each shift. Given the importance of team interactions to effective teamwork [12], as well as the low penetrance of ABCDE implementation [4], such data, regarding who is interacting with whom for ABCDE, can be used to inform interventions, targeted at the patient-level ICU team, each shift, to improve team coordination, teamwork and ABCDE delivery. Compared to unit-level interventions to improve ABCDE which have had limited effectiveness [4], a patient-shift-level intervention approach is consistent with the actual care delivery and has the potential to lead to the consistent delivery of ABCDE for ICU patients. Specifically, our results suggest three possible approaches for designing patient-shift-level interventions to improve ABCDE–targeting the interprofessional shift-level team, focusing on the nurse, and examining how to include family members in ABCDE care.

First, we identified that teams were comprised of 3–4 individuals, interprofessional, change from shift-to-shift, and that nurses have the most interactions. These findings empirically underscore the importance of interprofessional ICU care [28], specifically mechanical ventilation care [1, 10, 11]. These findings are novel since previous research primarily focused on everyone in the ICU as the team [16] as the primary target for ABCDE quality improvement [4], and traditionally, considered these teams to be fixed [29, 30]. Yet our data indicates a small number of team interactions with variability in the reported interactions that suggests interprofessional teams are dynamic. Together these data suggest that future work to improve ABCDE should focus on the interprofessional team present each shift for each patient as targets for improvement. An example of a patient-shift-level intervention could include a huddle with the nurse, physician, and RT assigned for each patient to discuss ABCDE. Huddles are a well-established approach that involves the team convening and discussing patient care in pre-scheduled intervals [31]; huddles have improved team communication and subsequently patient outcomes [32–34]. Because nurses had the most interactions within the team, nurse-led huddles could be particularly helpful. Indeed, a nurse-led huddle for early rehabilitation was effective in improving mobility for ICU patients [35].

Clinicians reported family member interactions in 25% of shifts (for nurses) and as low as 5% of surveys (for RTs); these percentages were also lower on night shift. While surprising in light of recent efforts to increase family member involvement in ICU care [36], our data indicate that more work is needed to incorporate family members in mechanical ventilation care. Targeting nurses, since 25% of nurse surveys reported family member interactions, may be an important first step in improving family member involvement. These data support various ongoing efforts to include family members in delirium monitoring [37, 38] and in direct patient care activities [39]. Understanding how to further engage families in critical care, specifically in ABCDE, may be necessary to improve ICU care.

Perhaps unexpectedly, 4–17% of surveys indicated no contact for ABCDE delivery that shift (more often on night shift), meaning none of the surveyed clinicians reported interacting with team members for ABCDE care. Additionally, a low percentage of nurses reported interacting with other nurses on night shift. These findings could reflect that teams may not interact as much overnight in general, there may be limited ABCDE activities overnight (e.g., no early mobility on night shift) or may reflect the protocolized nature of ABCDE delivery. While lack of interactions among the team may be surprising, protocolized care has been described as being integral to interprofessional collaboration [28], It is possible that protocolized evidence-based care has diminished the need for clinicians to interact, possibly explaining the lack of interactions. Additional research, using qualitative methods, to examine and contextualize how the team interacts and coordinates ABCDE delivery may be helpful.

Despite our study’s strengths, we acknowledge limitations. We may not have captured all interactions because we collected data only on weekdays (Monday-Friday), and because residents (not attendings) were our target respondents. Visiting hours may have differed at our two study sites resulting in varying family member interactions. Additionally, allied health presence varied in our study ICUs (i.e., physical therapists were not present on rounds); this may explain the limited interactions reported and may impact generalizability. We did not collect demographic information, aside from clinical role and site, about our study participants and we did not survey patients; these are noted limitations. We used self-reported interactions which may be subject to recall bias. Moreover, our data does not capture the quality, degree, or frequency of each interaction. However these critiques are also applicable to EHR based approaches, and likely to an even greater extent. Our study included ICUs where ABCDE care was reported as a routine part of care, thus limiting the generalizability of our findings. Finally, our study design surveyed only the nurses, physicans, and RTs, thus perceptions of other ICU clinicians (e.g., physical therapists, pharmacists) were not included; although it is important to note that these roles could be included if the nurse, physician or RT reported contact with these clinicians in our survey. Based on these limitaitons, future research should examine team interactions in a larger sample, include patients and family members as survey repsondents and focus on understanding how to improve team member interactions, ABCDE delivery and patient care considering brief shift-level interventions.

Conclusion

We empirically identified that ICU patient-shift team interactions were relatively small (3–4 interactions), fewer on night shift, dynamic and often interprofessional. Nurses had the most interactions within the teams. Interventions targeting patient, shift-level teams, focusing on nurses and exploring how to include family members, may be an important target for future work focused on improving ABCDE delivery in adult medical ICUs.

Supporting information

Acknowledgments

We thank the ICUs and participants for their participation in our study.