Skip to main content
NCBI home page
NIHPA Author Manuscripts logoLink to NIHPA Author Manuscripts
. Author manuscript; available in PMC: 2022 Jan 1.
Published in final edited form as: Health Care Manage Rev. 2021 Oct-Dec;46(4):349–357. doi: 10.1097/HMR.0000000000000288

Sustaining improvements in Relational Coordination following team training and practice change: A longitudinal analysis

Erin Abu-Rish Blakeney 1, Hebatallah Naim Ali 2, Nicole Summerside 3, Danielle C Lavallee 4, Benjamin Kragen 5, Mayumi A Willgerodt 6, Bryan J Weiner 7, Leah Spacciante 8, Brenda K Zierler 9
PMCID: PMC7775290  NIHMSID: NIHMS1625911  PMID: 32649474

Abstract

Background:

Poor communication is a leading cause of errors in health care. Structured interprofessional bedside rounds (SIBR) are a promising model to improve communication.

Purpose:

To test if an intervention to improve communication and coordination in an inpatient heart failure care unit would result in lasting change.

Methodology/Approach:

The Relational Coordination (RC) survey was administered to seven workgroups (i.e., nurses, physicians) at baseline (2015) and three subsequent years following the intervention (team training, leadership development workshops, and SIBR implementation). Descriptive analysis and mixed effects models were used to assess the impact of the intervention on improving RC.

Results:

During the study period (2015–2018), 344 participants completed the survey for an overall response rate of 53.5% (n=643). Post-intervention, the RC Index significantly increased from 3.79 to 4.08 (P<0.001) and remained significantly higher over two years with a RC Index of 4.12 and 4.04, respectively (P<0.001). The range of RC scores between and within workgroups narrowed over time with non-rotating workgroups showing the most improvements.

Conclusion:

Findings indicate that positive changes as a result of the intervention have been sustained, despite high rates of turnover among all workgroups. Notably, positive change in RC was found to be more pronounced for non-rotating workgroups compared to team members who rotate within the hospital (i.e., pharmacists who rotate to other units every month).

Practice Implications:

This intervention holds promise for teams seeking best practice models of “high reliability” care organization and delivery. Sustained changes from this intervention represent an important area of future practice-based research.

Keywords: Relational Coordination, Hospital Rounds, Interprofessional Care

Introduction

Poor communication is widely recognized as a leading cause of errors and harm in health care (Institute of Medicine, 2000; James, 2013). It is increasingly recognized as a contributor to burnout and turnover among care team members (Pastores, et al., 2019; Matheson et al., 2016; Khowaja-Punjwani, Smardo, Hendricks, & Lantos, 2017). There is a need to identify models of care that lead to and sustain improvements in team communication (Institute of Medicine, 2015). Structured interprofessional bedside rounds (SIBR) are emerging as a promising inpatient care model for effective team communication. SIBR is a team process in which different members of the health care team (including the patient and their caregiver) come together at the patient’s bedside and utilize a consistent format to collaboratively arrive at a daily plan of care (Burdick, Kara, Ebright, & Meek, 2017; Gonzalo, Wolpaw, Lehman, & Chuang, 2014).

Findings of a recent systematic scoping review have identified a sharp rise in publications about SIBR implementation and outcomes—with 16 new publications in 2018 alone (Blakeney et al, 2019). This growing body of literature associates SIBR-type models with improvements in team communication, relationships, work process efficiencies, and patient outcomes (Bhamidipati et al., 2016; Blakeney et al, 2019; O’Leary et al., 2011; Ratelle et al., 2019). However, most prior studies of SIBR implementation have been cross-sectional and short-term (within 1–2 years of the intervention). Thus, a key gap in the literature is whether these improvements are sustained over time. Our study addresses this gap by testing the hypothesis that Relational Coordination (RC) improvements following a team intervention (interprofessional team training, leadership workshops, and SIBR implementation) would result in lasting change. This manuscript presents the results of two related research questions:

  1. Did an intervention to improve team communication and coordination (i.e., as measured by a validated RC survey) in the inpatient heart failure care unit result in lasting change?

  2. Was there a differential impact on RC between rotating and non-rotating groups (i.e., nurses who consistently work in the unit as compared to pharmacists and fellows who do not)?

Theory

This study and the overall parent project were guided by the Relational Model of Organizational Change and the Institute of Medicine (IOM) Interprofessional Learning Continuum Model. The IOM Learning Continuum Model highlights the importance of continuing professional development for health professionals and teams in practice settings to bring about change and improvements in health care organization, delivery, and outcomes (Institute of Medicine, 2015). The Relational Model of Organizational Change is a conceptual framework of organizational performance and change that has been used across industries where the conduct of work is highly interdependent, uncertain, and time constrained including aviation, banking, manufacturing, and health care (Gittell, 2016; Gittell & Logan, 2015). The framework highlights relational, work processes, and structural interventions that are necessary to change RC, as measured by the corresponding validated survey (Gittell, 2016).

RC, the construct being measured pre-post the intervention of SIBR with team training and leadership workshops, is jointly supported by communication and coordination between team members. The RC conceptual framework posits that communication can be assessed on four dimensions: frequency, timeliness, accuracy, and ability to problem-solve. Coordination is assessed on three additional dimensions of shared goals, shared knowledge, and mutual respect. Together the seven dimensions contribute to an overall measure of RC that can be mapped over a series of relationships among and between workgroups for a holistic understanding of team dynamics (Gittell, 2002). The RC conceptual framework predicts that organizational structures such as SIBR facilitate RC in as much as they are designed to cross boundaries and reduce barriers to communication by training for teamwork and through shared protocols, management roles, meetings, and information systems. (Gittell, 2002; Gittell & Douglass, 2010).

Higher levels of RC have been found to predict satisfaction of cardiovascular patients (Romanow, Rai, & Keil, 2017) and decrease hospitalization for heart failure patients (Hagigi, 2012). In health care more broadly, Gittell, Weinberg, Bennet and Miller (2008a) observed that RC decreases the cost of hospital care. Hagigi (2012) similarly observed that RC predicts lower inpatient and outpatient costs of chronic care. Regarding human capital, RC predicts work engagement, reciprocal learning, confidence in collaboration, decreases in burnout, improves job satisfaction, and overall staff productivity (Warshawsky, Havens, & Knafl, 2012; Naruse, Sakai, & Nagata, 2015; Havens, Gittell, & Vasey, 2018; Noel et al., 2013; Gittell, Weinberg, Pfefferle, & Bishop, 2008; Baik & Zierler, 2018; Gittell et al., 2008b; Havens et al., 2018).

RC has traditionally been studied cross-sectionally to test its association with these and other outcomes of interest. This project is one of nine identified studies across sectors that examines RC pre/post-intervention, and is the first to measure RC for an intervention that includes bedside rounds, representing a new direction for the construct (Gittell & Logan, 2015). For this study, RC was measured over four years (once before the intervention and three subsequent years after the intervention), making it the longest-running published study of RC.

Method

Study Context

In this study, our academic-practice partnership collaboratively adapted and implemented interprofessional team training, leadership workshops, and SIBR processes (our intervention) in an inpatient advanced heart failure setting with the goal of improving the quality and reliability of communication, relationships, and efficiencies (Martelli, Rivard, & Roberts, 2018; Abu-Rish Blakeney, et al., 2018; Willgerodt et al., 2018). Prior to SIBR implementation, coordination of care occurred through multiple steps each day including team rounds in a designated office space and/or outside of the patient room (in the hallway) followed by patient assessment at the bedside. Nurses were not formally included in these steps and patients/caregivers only in the final step. SIBR condensed rounds to occur daily at the patient bedside allowing for full team participation of the nurse, patient, and/or caregiver to develop a shared plan of care for the patient.

This study examines change in RC between and within inpatient advanced heart failure care workgroups that make up the interprofessional care team over a four-year period at a large academic medical center in the Pacific Northwest. Workgroups are here defined as members of a single profession who normally work together (i.e., nurses who work in a particular hospital unit). This study was considered IRB exempt from a human subject’s perspective.

Between the first and second years of the study an intervention consisting of interprofessional team training, leadership development workshops, and practice change intervention (SIBR) was collaboratively selected and implemented (Abu-Rish Blakeney et al., 2018; Willgerodt et al., 2018). The resulting practice change was the adaptation and implementation of SIBR. The intervention, survey methods, and initial pre/post results—demonstrating significant improvements in RC between baseline and the first follow-up year—have been described in detail elsewhere (Abu-Rish Blakeney et al., 2018).

Participants and Data Collection

Study participants included 188 unique individuals (contributing 344 total responses) over four years from seven workgroups. Each workgroup encompassed different professional roles involved in daily care of advanced heart failure patients on two hospital units (a Critical Care Unit and a Step-Down Telemetry floor) and the cardiology service that provided primary management of those patients. Workgroups included RNs from each unit as well as Social Workers, Pharmacists, Cardiology Fellows, Advanced Practice Providers (APPs; i.e., nurse practitioners and/or physician assistants), and Attending Physicians associated with the advanced heart failure service. Members of three of the included workgroups rotate on a regular basis as part of their roles (i.e., attending physicians rotate on/off the service every two weeks). The remaining workgroups do not typically rotate as part of their roles.

Individuals who completed at least one of four annual surveys between 2015–2018 comprised the sample for this study. The first survey year (2015) was considered “baseline” as data were collected prior to the implementation of the intervention. The subsequent years represent post-intervention annual follow-up data (2016, 2017, 2018). Because the focus of the study was on overall team communication and coordination, individual respondents were not required to complete more than one RC survey during the study period. Due to concerns about survey completion rate, respondent demographics were only added for the final study year.

Measures, Metrics, and Analysis

The main metric used in this study is the RC survey, which calls for participants to assess the strength of their work relationships, specifically the level of communication and coordination with other workgroups. Using a Likert scale that ranges from a low score of 1 ‘never’ to a high score of 5 ‘always’, participants assess the frequency, timeliness, and accuracy of communication and if it focuses on problem solving. Participants also evaluate levels of coordination with other workgroups by rating their shared goals, shared knowledge and mutual respect on the same 1 to 5 Likert scale. Each RC dimension is summarized using a mean score, while the total RC index is a newly generated variable of mean score for all seven dimensions.

Descriptive statistics were calculated for each workgroup and response rates for each year. This was followed by the calculation of an overall RC index (including standard deviations) and each of the seven RC dimensions for the entire population, and for each workgroup for each year (Gittell, 2012). Only participants who completed all seven survey items were included in the analysis. Validity testing for the RC survey showed a Cronbach’s alpha between 0.8–0.9 for each of the four surveyed years. Due to the varying response rate of workgroups across study years, analyses corrected for survey non-responsiveness by applying proportional weights in analyzing and summarizing the results.

We first tested if there was a significant change in total RC index and the seven dimensions’ weighted scores between the baseline ‘pre-intervention’ year 2015 and subsequent ‘post intervention’ years, using Ordinary Least Square models. Next, a linear mixed effects model was utilized to analyze changes in RC and the seven dimensions as panel data. This was deemed appropriate because correlation between the error term and the regressors could not be confirmed (Haussmann test was non-significant). A dummy new variable “rotating workgroups” was created to indicate if the participant belonged to a rotating versus nonrotating ‘baseline’ workgroup. Then, controlling for the rotation in workgroups, the linear mixed effects model tested whether increases in the main outcome measure of RC were sustained over time. We then ran contrasts to see if improvements over time were sustained comparing the post-intervention assessment (year 2) to the follow-up years (years 3 and 4) separately to pre-intervention (baseline) year. This analysis allowed us to answer our secondary question of whether RC improved more among the non-rotating workgroups than for the groups that rotate as part of their role. Data was analyzed using Stata 15.1 (StataCorp, 2017).

Results

The overall response rate was 57%. Response rates were highest among smaller workgroups (Pharmacists, Social Workers, and Attending Physicians) and lowest among the Cardiology Fellows. Patterns of responsiveness were consistent across all study years. Supplemental Table 1 shows a comparison between the total number invited and those who completed the survey per workgroup for each year. Table 1 shows the demographic characteristics of the respondents who completed the fourth year (final) survey. RNs represent the largest workgroup, with over 70% of total respondents. Respondents were mostly female (79.8%); more than half (67%) were between the ages of 25–44 years old. Approximately half of the respondents worked at the study site for four years or more and were present at baseline.

Table 1.

Participant Characteristics Among Year 4 (2018) Survey Respondents

 2018 (n=84)
Profession
 Overall RN 61 72.62%
  RN_Unit 1 34 40.48%
  RN_Unit 2 27 32.14%
 Pharmacist 5 5.95%
 Social Worker 3 3.57%
 Fellow 3 3.57%
 APP 5 5.95%
 Attending Physician 7 8.33%
Age
 18–24 4 4.76%
 25–44 57 67.86%
 45–64 23 27.38%
Gender
 Male 11 13.1%
 Female 67 79.76%
 Prefer not to say 6 7.14%
Open in a new tab

Note. APP = Advanced Practice Providers (i.e., nurse practitioners and/or physician assistants); RN = Registered Nurse; SIBR = structured interprofessional bedside rounds.

At baseline, the overall RC index was 3.79 with dimensions ranging from 3.52 for timely communication to 3.99 for shared goals. Post-intervention (year 2) showed a significant increase in the overall RC index to 4.08, as well as in five of the seven RC dimensions (excluding timely communication and shared knowledge). In the third year, these two dimensions increased compared to year 2 by 0.16 (timeliness) and 0.11 (shared knowledge) and the overall RC index increased further to 4.12 to become significant. At year 4, the overall RC index decreased slightly to 4.04 but maintained the positive change compared to the baseline value (p<0.001). Four of the seven RC dimensions (accurate, problem solving communication, shared knowledge, shared goals) decreased in the fourth year—however they remained higher than baseline but without a significant difference. Table 2 summarizes the overall RC index and seven dimensions.

Table 2.

Mean Score of 7 RC Dimensions/Year by Baseline (Reference Group) (n=344)

Dimension Mean SE Coefficient (P)
Frequent Communication
 2015 3.97 0.08 Reference
 2016 4.51 0.07 0.54 ***
 2017 4.56 0.06 0.60 ***
 2018 4.46 0.08 0.49 ***
Timely Communication
 2015 3.52 0.07 Reference
 2016 3.68 0.08 0.15
 2017 3.84 0.07 0.32 ***
 2018 3.8 0.09 0.28 **
Accurate Communication
 2015 3.81 0.08 Reference
 2016 4.03 0.09 0.22 *
 2017 4.05 0.07 0.24 **
 2018 3.99 0.08 0.18
Problem-Solving Communication
 2015 3.88 0.06 Reference
 2016 4.15 0.07 0.26 ***
 2017 4.08 0.06 0.20 *
 2018 4.01 0.08 0.13
Shared Goals
 2015 3.99 0.08 Reference
 2016 4.32 0.08 0.34 ***
 2017 4.28 0.06 0.29 ***
 2018 4.18 0.09 0.20
Shared Knowledge
 2015 3.65 0.07 Reference
 2016 3.77 0.07 0.12
 2017 3.88 0.06 0.23 **
 2018 3.79 0.06 0.13
Mutual Respect
 2015 3.68 0.09 Reference
 2016 4.11 0.08 0.44 ***
 2017 4.16 0.07 0.48 ***
 2018 4.05 0.08 0.37 ***
Overall RC Index
 2015 3.79 0.05 Reference
 2016 4.08 0.06 0.29 ***
 2017 4.12 0.05 0.34 ***
 2018 4.04 0.06 0.25 ***
Open in a new tab

Note. RC = relational coordination; SE = standard error.

*

P<0.05

**

P<0.01

***

P<0.001.

The linear mixed effects model investigates the sustainability of the intervention on RC over the study period as well as its differential efficacy based on whether workgroup members rotate or not (Table 3). The model showed that the second year yielded a significant increase in RC index by 0.33 (SE=0.06) as well as in six of the seven dimensions. Where frequency of communication increased by the highest average of 0.51 (SE=0.1)—followed by mutual respect with 0.52 (SE=0.1) and shared goals by average 0.42 (SE=0.1)—accurate and problem-solving communication by an average increase of 0.29 (SE=0.1 and 0.09 respectively) and timely communication showed positive change of an average of 0.21 (SE=0.08) with significance. While shared knowledge did not significantly change from year 1 to year 2, it did increase significantly in year 3 with an average increase of 0.22 (SE=0.09) compared to baseline. The third year scores also showed that the intervention had a positive sustainable impact on RC index and seven dimensions. In the fourth year, the intervention sustained the positive change in RC index and five of the seven dimensions. However, accuracy of communication and shared knowledge decreased to be non-significant compared to baseline values.

Table 3.

Linear Mixed Effects Model Analyses of the Association Between Rotating Workgroups and Years on Relational Coordination (RC) Scores and the Seven RC Dimensions (n=344)

Variable Frequent Comm. Timely Comm. Accurate Comm. Problem Solving Comm. Shared Goals Shared Knowledge Mutual Respect RC
Years Est. (SE) Est.(SE) Est. (SE) Est. (SE) Est. (SE) Est. (SE) Est. (SE) Est. (SE)
2016 0.51 (0.10)*** 0.21 (0.08)** 0.29 (0.10)** 0.29 (0.09)*** 0.42 (0.10)*** 0.12 (0.09) 0.52 (0.10) *** 0.33 (0.06) ***
2017 0.60 (0.10)*** 0.35 (0.08)*** 0.28 (0.09)** 0.23 (0.08)** 0.38 (0.09)*** 0.22 (0.09) ** 0.55 (0.10) *** 0.37 (0.06) ***
2018 0.49 (0.11)*** 0.30 (0.08)*** 0.16 (0.09) 0.17 (0.08) * 0.30 (0.09)*** 0.15 (0.08) 0.42 (0.11) *** 0.28 (0.06) ***
Rotating Workgroup (RW)
Rotating 0.69 (0.11)*** 0.55 (0.12)*** 0.29 (0.14) * 0.17 (0.14) 0.37 (0.18) * 0.03 (0.16) 0.32 (0.16) * 0.35 (0.11) ***
Year # RW
2016#RW −0.51 (0.17) ** −0.26 (0.19) −0.28 (0.18) −0.39 (0.19) * −0.65 (0.25)** 0.10 (0.25) −0.37 (0.17) * −0.34 (0.15) *
2017#RW −0.34 (0.14) * −0.31 (0.17) −0.12 (0.18) −0.37 (0.19) * −0.64 (0.21) ** 0.09 (0.21) −0.39 (0.19) * −0.31 (0.13) *
2017#RW −0.30 (0.16) −0.16 (0.20) −0.02 (0.21) −0.40 (0.21) * −0.63 (0.27) * 0.01 (0.22) −0.39 (0.22) −0.26 (0.16)
Open in a new tab

Note. Comm. = communication; Est. = estimated; RC = relational coordination; SE = standard error.

*

P<0.05

**

P<0.01

***

P<0.001.

The linear mixed effects model also analyzed pre- and post-intervention differences between rotating and non-rotating workgroups. Rotating workgroups had, on average, an RC index at baseline 0.35 higher overall compared to non-rotating workgroups; and had statistically higher baseline values for five dimensions (Figure 1). Rotating workgroups did not differ in problem solving and shared knowledge dimensions compared to non-rotating workgroups. In years 2 and 3, rotating workgroups showed weaker RC index changes, represented by a negative slope, when compared to non-rotating workgroups. Also, rotating workgroups had weaker changes in three dimensions (frequent communication, problem solving, and shared goals) compared to non-rotating workgroups, moving from baseline to year 2 and year 3. This weaker negative change pattern in RC index between rotating and non-rotating workgroups diminished in the fourth year as did the other dimensions, except for problem solving and shared goals.

Figure 1.

Figure 1

Open in a new tab

Overall RC Index by workgroup over time for rotating and non-rotating workgroups

Footnote: Rotating workgroups include Attending Physicians, Cardiology Fellows, and Pharmacists. Non-rotating workgroups include RNs (both units), Advanced Practice Providers, and Social Workers.

Discussion

The purpose of this novel intervention and analysis was to examine the effect of an intervention consisting of interprofessional team training, leadership development workshops, and SIBR on communication and coordination of care over time. We found that improvements in communication and coordination (as measured by RC) had been largely maintained over the course of three annual follow-up surveys from baseline, suggesting a number of key points. First, changes stemming from providing team and leadership training and instituting SIBR have made a meaningful, positive impact on team communication and coordination in an inpatient advanced heart failure setting. Second, improvements in RC generated by SIBR implementation following the intervention are to a large extent self-reinforcing as improvements have been sustained. Third, there were differential changes in RC over time for rotating vs. non-rotating workgroups.

These findings are promising. In addition to the widely documented need to improve communication in healthcare, success and sustainability of change initiatives (in all fields) are known to be relatively low (Institute of Medicine, 2000; Hughes, 2011). Sustained use of the SIBR model is likely due to effectiveness of implementation strategies, prior team training and leadership development, beneficial aspects of the intervention itself (i.e., increased efficiency), as well as the readiness of the workgroups and the care team for change from previous models (Powell et al., 2019; Hendricks, LaMothe, Kara, & Miller, 2017). RC survey results make visible the positive impacts these changes had on team communication and coordination.

Additionally, RC theory suggests that a secondary outcome to structuring bedside rounds—strengthening relationships and connection between team members—also contributes to sustaining the effects of the intervention (Gittell & Logan, 2015). Gittell & Logan (2015) propose that interventions that improve RC are self-reinforcing because of their correlation with psychological safety and the ability to learn from failure: “…as positive change to RC takes hold, participants are then able to enact new structures that further reinforce and sustain RC in a kind of bootstrapping process” (page 24). Kenwood (2011) found that introducing the concept of RC increased scores over time for teams where RC was initially low, and to maintain RC for teams where RC was high. Consistent with this, in this study, we found sustained improvements in RC dimensions and in some cases continued improvement in later years despite little additional training of frontline care team members. The SIBR process is now standard practice and new team members are fitting into the process. This suggests that people who are joining the organization are also modelling the behaviors they observe and to which they are oriented. While these results are promising, slight decreases in some of the 2018 scores suggested a need for booster or onboarding training sessions for new team members, which have been initiated.

Positive, self-reinforcing team-based models of care prove critical in environments with dynamic staffing (Gittell, 2016; Pronovost et al, 2006; Martelli, Rivard, & Roberts, 2018). In this study, sustained improvements reflect promisingly on the sustainability of SIBR implementation and potential for scale-up. Findings are encouraging in relation to the IOM Learning Continuum Model, as the intervention represents an example of continuing professional development efforts reliably resulting in positive change (Institute of Medicine, 2015; Martelli, Rivard, & Roberts, 2018). Study results also add to the evidence base for the Relational Model of Organizational Change as our intervention involved structural, relational, and work process elements (Gittell, 2016). In this study, these interventions were associated with sustained positive change in RC.

A third interesting aspect of this study’s results were the differential changes in RC over time for rotating workgroups as compared to non-rotating. We found that rotating workgroups (Attending Physicians, Cardiology Fellows, Pharmacists) had higher RC scores at baseline compared to the non-rotating groups (Nurses, APPs, Social Workers). RC for the non-rotating groups increased over the course of the project compared to baseline. In comparison, rotating groups (whose RC scores were higher at baseline) experienced less pronounced increases. In the case of both Pharmacists and Cardiology Fellows, RC decreased following the intervention but still remained higher than some of the other workgroups. Ultimately, the overall team RC index increased compared to baseline and the range of workgroup-specific RC became higher and had a narrower spread over the course of this project. Additional research is needed to determine the how these differential changes are related to the rotating nature of these workgroups as opposed to organizational culture or a leveling of the communication and relationship expectations (i.e., historically based power dynamics between rotating and non-rotating groups). This would be consistent with Baik and Zierler’s (2018) nested study which found that in addition to increasing RC, the intervention (team training, leadership development, and SIBR) increased nurse job satisfaction. Alternatively, it is common to see decreases in scores with increased awareness/ knowledge of concepts following training (Kruger & Dunning, 1999).

This manuscript adds to the evidence around SIBR as an effective and sustainable model of “highly reliable” care to help establish and maintain effective patterns of interprofessional communication and relationships among inpatient care teams (Pronovost et al, 2006; Martelli, Rivard, & Roberts, 2018). Survey results and emergent themes from qualitative interviews with this same group (Willgerodt et al., 2019) suggest that this change project represents an example of real and sustained positive culture change. In addition, this manuscript describes the longest identified longitudinal analysis of RC and the first identified study that describes RC as a result of an intervention aimed at improving bedside rounds.

In this study we had the benefit of a large and expert team as well as resources to carry out a robust evaluation of the development and implementation process of SIBR. During the course of this change process there have been very few changes in leadership roles within this group. We believe that this consistency and that the positive relationships modeled by these leaders (medical director, nurse manager, lead APP) played a crucial role in the implementation and sustainment of the intervention and the associated change process. This cannot be replicated for each environment in which SIBR is implemented so it will be important to identify essential aspects of the intervention as well as implementation and sustainment strategies that can be utilized in a cost-effective and resource reasonable manner.

We see a number of important next steps in our work around SIBR as well as for the field of team-based practice transformation (also known as interprofessional collaborative practice). For example, there are numerous SIBR-type models being described in the literature, some with purposeful team training and some without (Blakeney et al, 2019). Understanding the similarities and differences among these models (i.e., approach, purpose, and implementation strategies) will clarify the mechanism of action of SIBR, identify essential program components, and inform effective implementation strategies for different environments. Additional research is needed on the perceived value of SIBR from the perspective of patients and families as well as other care team members. For example, in this study, the variation in RC scores within and between workgroups over time suggest that the intervention may have differential impacts depending on one’s role in the care team, exposure to training, and/or readiness or desire for change.

Additionally, it is important to come to a greater understanding of the patient outcomes that might be affected (either positively or negatively) by SIBR implementation. Multiple studies have examined patient-centered outcome measures but few have also reported on the impact on the team following SIBR implementation (Ratelle et al., 2019; Blakeney et al., 2019). Our working hypothesis of SIBR’s mechanism of action is that it helps to improve team communication and relationships thereby enhancing a team’s ability to provide highly reliable care. The gap in addressing team outcomes of SIBR implementation in much of the literature makes it challenging to rigorously determine the impact of SIBR implementation on many patient outcomes (e.g., length of stay, readmission, and satisfaction).

Limitations

Limitations encountered in this study include small numbers (by design many workgroups include fewer than five people while others include nearly 100 or more individuals). Despite these small numbers, response rates within the study population were high, providing confidence in the results for this study population. It is unclear the extent to which the described changes are sustainable through leadership changes (which will eventually occur in any environment) as well as other changes in care organization. Further, while our early changes resulted in initial improvements, in 2018 while the overall RC score remains higher than the baseline score itself, it is starting to decrease. This may indicate a need for refresher training, which we started developing and piloting in 2019.

Core functions of this model and implementation strategies also remain unclear. The intervention involved multiple components including, purposeful interprofessional team training, quarterly leadership development workshops for unit change leaders, and the introduction of SIBR. The different strategies offered opportunities for team members to build new skills for leadership, communication, relationship building, and collaboration. All aspects of this model need further study to determine the extent to which they are essential and/or scalable.

Conclusions

Health care environments are complex. Practice changes need to accommodate that complexity, yet also provide structure that can increase reliability of care within these environments to ensure that the safest, highest quality care is provided to patients and their families. Our study findings indicate sustained improvements as a result of interprofessional team training, leadership workshops, and SIBR. More pronounced positive change in RC for non-rotating workgroups as compared to team members who rotate to other areas of the hospital should be further studied. Improvements in care team communication and coordination generated by the intervention have been self-reinforcing as improvements have been sustained absent ongoing training of front-line staff and despite turnover among care team members. This study highlights the potential value of using the RC survey on an ongoing basis as both part of a complex intervention and as an evaluation tool. Findings also indicate that select RC domains may be more amenable to improvement and reinforcement with one-time team-training and/or SIBR implementation while others may need to be targeted in other ways.

Practice Implications

RC was increased and sustained through team training, leadership development workshops, and ongoing SIBR practice change. This model of intervention and care holds promise for other teams and institutions seeking best practice models for improving reliability, communication, relationships, care, and clinical outcomes in settings where team membership is dynamic. Sustained changes in RC, predicting sustained changes in patient outcomes like those observed in cross-sectional studies, represent an important area of future practice-based research.

Supplementary Material

Supplement Table 1

Acknowledgements

The authors would like to acknowledge the invaluable partnerships and collaborations with our clinical partners at the University of Washington (UW) Medical Center, the UW WWAMI Institute for Simulation in Healthcare (WISH), grant team members from the UW Schools of Nursing, Medicine, and Pharmacy, and the UW Center for Health Sciences Interprofessional Education, Research, and Practice. In particular, we wish to acknowledge the leadership and project contributions of Dr. Kevin O’Brien, Susan Pambianco, NP, and Renee Paquet, RN, MHA. We also appreciate the assistance of Erich von Abele for his professional writing services who assisted with final copyediting and formatting and Kenneth Pike from the UW School of Nursing Office of Nursing Research who provided statistical assistance.

Funding for the overall project was received from the Health Resources Services Administration (# UD7HP26909). In addition to project funding from HRSA, the lead author received funding from the NIH National Heart, Lung, and Blood Institute K12 (#5K12HL137940) as part of the UW Implementation Science Training Program which supported her time during data analysis, manuscript writing, and revision. Finally, BK and NS received support from NCATS (UL1 TR002319) during data analysis, manuscript writing, and revision.

Approval for Human Subjects Research: This study was determined to be exempt by the University of Washington Human Subjects Division.

Contributor Information

Erin Abu-Rish Blakeney, Department of Biobehavioral Nursing and Health Informatics, School of Nursing, University of Washington..

Hebatallah Naim Ali, Heller School for Social Policy and Management, Brandeis University.

Nicole Summerside, Center for Health Sciences Interprofessional Education, Research & Practice, University of Washington..

Danielle C. Lavallee, Department of Surgery, University of Washington.

Benjamin Kragen, Heller School for Social Policy and Management , Brandeis University.

Mayumi A. Willgerodt, Department of Family and Child Nursing, School of Nursing, University of Washington.

Bryan J. Weiner, Departments of Global Health and Health Services, School of Public Health, University of Washington.

Leah Spacciante, University of Washington Medical Center.

Brenda K. Zierler, Department of Biobehavioral Nursing and Health Informatics, School of Nursing, University of Washington.

References

  1. Abu-Rish Blakeney E, Lavallee DC, Baik D, Pambianco S, O’Brien KD, & Zierler BK (2018). Purposeful interprofessional team intervention improves relational coordination among advanced heart failure care teams. Journal of Interprofessional Care, 0(0), 1–9. doi: 10.1080/13561820.2018.1560248 [DOI] [PMC free article] [PubMed] [Google Scholar]
  2. Baik D, & Zierler B (2018). RN job satisfaction and retention after an interprofessional team intervention. Western Journal of Nursing Research, 41(4), 615–630. doi: 10.1177/0193945918770815 [DOI] [PubMed] [Google Scholar]
  3. Bhamidipati VS, Elliott DJ, Justice EM, Belleh E, Sonnad SS, & Robinson EJ (2016). Structure and outcomes of interdisciplinary rounds in hospitalized medicine patients: A systematic review and suggested taxonomy. Journal of Hospital Medicine, 11(7), 513–523. doi: 10.1002/jhm.2575 [DOI] [PubMed] [Google Scholar]
  4. Blakeney EL, Chu F, White A, Lavallee D, Tanner E, Summerside N, Woodward K, Dang D, Weiner B (2019). Implementation of interprofessional bedside rounding models with hospitalized patients: A scoping review of quantitative and qualitative evidence. 12th Annual Conference on the Science of Dissemination and Implementation in Health. Arlington, VA. December 4–6, 2019. https://academyhealth.confex.com/academyhealth/2019di/meetingapp.cgi/Paper/34938 [Google Scholar]
  5. Burdick K, Kara A, Ebright P, & Meek J (2017). Bedside Interprofessional Rounding: The view from the patient’s Side of the Bed. Journal of Patient Experience, 4(1), 22–27. doi: 10.1177/2374373517692910 [DOI] [PMC free article] [PubMed] [Google Scholar]
  6. Gittell J (2012). Relational coordination: Guidelines for theory, measurement and analysis. Relational Coordination Research Collaborative. Boston, MA: Brandeis University. [Google Scholar]
  7. Gittell JH (2002). Coordinating mechanisms in care provider groups: Relational coordination as a mediator and input uncertainty as a moderator of performance effects. Management Science, 48(11), 1408–1426. [Google Scholar]
  8. Gittell JH (2016). Transforming relationships for high performance: The power of relational coordination. Palo Alto, CA: Stanford University Press. [Google Scholar]
  9. Gittell JH, & Logan C (2015). Outcomes and predictors of relational coordination empirical assessment of an emerging HRM theory. (Unpublished manuscript). Heller School for Social Policy and Management. Waltham, Massachusets: Brandeis University. https://rcrcconnect.org/wp-content/uploads/2016/02/Outcomes-and-Predictors-of-Relational-Coordination-8-16.pdf [Google Scholar]
  10. Gittell JH, Weinberg D, Bennett A, & Miller JA (2008a). Is the doctor in? A relational approach to job design and the coordination of work. Human Resource Management, 47(4), 729–755. [Google Scholar]
  11. Gittell JH, Weinberg DB, Pfefferle S, & Bishop C (2008b). Impact of relational coordination on job satisfaction and quality outcomes: A study of nursing homes. Human Resource Management Journal, 18(2), 154–170. [Google Scholar]
  12. Gonzalo JD, Wolpaw DR, Lehman E, & Chuang CH (2014). Patient-centered interprofessional collaborative care: factors associated with bedside interprofessional rounds. Journal of General Internal Medicine, 29(7), 1040–1047. doi: 10.1007/s11606-014-2817-x [DOI] [PMC free article] [PubMed] [Google Scholar]
  13. Hagigi F (2012). Relational coordination as a driver of cost and quality performance in chronic care. Paper presentation at the Academy Health Meetings, Orlando, FL. [Google Scholar]
  14. Havens DS, Gittell JH, & Vasey J (2018). Impact of relational coordination on nurse job satisfaction, work engagement and burnout: Achieving the quadruple aim. The Journal of Nursing Administration, 48(3), 132–140. doi: 10.1097/NNA.0000000000000587 [DOI] [PubMed] [Google Scholar]
  15. Hendricks S, LaMothe VJ, Kara A, & Miller J (2017). Facilitators and barriers for interprofessional rounding: A qualitative study. Clinical Nurse Specialist CNS, 31(4), 219–228. doi: 10.1097/NUR.0000000000000310 [DOI] [PubMed] [Google Scholar]
  16. Hughes M (2011). Do 70 per cent of all organizational change initiatives really fail? Journal of Change Management, 11(4), 451–464. doi: 10.1080/14697017.2011.630506 [DOI] [Google Scholar]
  17. Institute of Medicine. (2000). To err is human: Building a safer health system. Kohn LT, Corrigan JM, & Donaldson MS (Eds.). Institute of Medicine (US) Committee on Quality of Health Care in America. Washington, DC: National Academies Press (US). Retrieved from http://www.ncbi.nlm.nih.gov/books/NBK225182/ [PubMed] [Google Scholar]
  18. Institute of Medicine. (2015). Measuring the impact of interprofessional education on collaborative practice and patient outcomes. Washington, D.C.: National Academies Press. Retrieved from http://www.nap.edu/catalog/21726 [PubMed] [Google Scholar]
  19. James JT (2013). A new, evidence-based estimate of patient harms associated with hospital care Journal of Patient Safety, 9(3), 122–128. doi: 10.1097/PTS.0b013e3182948a69 [DOI] [PubMed] [Google Scholar]
  20. Kenwood C (2011). Creating an integrated psychiatric rehabilitation network for those with high-level and complex needs in West Lothian: The frontline integration project. (Masters Thesis). Edinburgh Napier University: Edinburgh, Scotland. [Google Scholar]
  21. Khowaja-Punjwani S, Smardo C, Hendricks MR, & Lantos JD (2017). Physician-nurse interactions in critical care. Pediatrics, 140(3). doi: 10.1542/peds.2017-0670 [DOI] [PubMed] [Google Scholar]
  22. Kruger J, & Dunning D (1999). Unskilled and unaware of it: How difficulties in recognizing one’s own incompetence lead to inflated self-assessments. Journal of Personality and Social Psychology, 77(6), 1121–1134. doi: 10.1037/0022-3514.77.6.1121 [DOI] [PubMed] [Google Scholar]
  23. Martelli PF, Rivard PE, & Roberts KH (2018). Caveats for high reliability in healthcare. Journal of Health Organization and Management, 32(5), 674–90. doi: 10.1108/JHOM-10-2017-0286 [DOI] [PubMed] [Google Scholar]
  24. Matheson C, Robertson HD, Elliott AM, Iversen L, & Murchie P (2016). Resilience of primary healthcare professionals working in challenging environments: a focus group study. The British Journal of General Practice: The Journal of the Royal College of General Practitioners, 66(648), e507–515. doi: 10.3399/bjgp16X685285 [DOI] [PMC free article] [PubMed] [Google Scholar]
  25. Naruse T, Sakai M, & Nagata S (2016). Effects of relational coordination among colleagues and span of control on work engagement among home-visiting nurses. Japan Journal of Nursing Science,13(2), 240–246. doi: 10.1111/jjns.12107 [DOI] [PubMed] [Google Scholar]
  26. Noel P, Lanham H, Palmer R, Leykhum L, & Parchman M (2013). The importance of relational coordination and reciprocal learning for chronic illness care in primary care teams. Health Care Management Review, 38(1), 20–28. [DOI] [PMC free article] [PubMed] [Google Scholar]
  27. O’Leary KJ, Killarney A, Hansen LO, Jones S, Malladi M, Marks K, & M Shah H (2016). Effect of patient-centred bedside rounds on hospitalised patients’ decision control, activation and satisfaction with care. BMJ Quality & Safety, 25(12), 921–928. doi: 10.1136/bmjqs-2015-004561 [DOI] [PubMed] [Google Scholar]
  28. Pastores SM, Kvetan V, Coopersmith CM, Farmer JC, Sessler C, Christman JW, … Price K (2019). Workforce, workload, and burnout among intensivists and Advanced Practice Providers: A narrative review. Critical Care Medicine, 47(4), 550–557. doi: 10.1097/CCM.0000000000003637 [DOI] [PubMed] [Google Scholar]
  29. Powell BJ, Fernandez ME, Williams NJ, Aarons GA, Beidas RS, Lewis CC, … Weiner BJ (2019). Enhancing the impact of implementation strategies in healthcare: A research agenda. Frontiers in Public Health, 7, 3. doi: 10.3389/fpubh.2019.00003 [DOI] [PMC free article] [PubMed] [Google Scholar]
  30. Pronovost PJ, Berenholtz SM, Goeschel CA, Needham DM, Sexton JB, Thompson DA, … Hunt E (2006). Creating high reliability in health care organizations. Health Services Research, 41(4 Pt 2), 1599–1617. doi: 10.1111/j.1475-6773.2006.00567.x [DOI] [PMC free article] [PubMed] [Google Scholar]
  31. Ratelle JT, Sawatsky AP, Kashiwagi DT, Schouten WM, Erwin PJ, Gonzalo JD, … West CP (2019). Implementing bedside rounds to improve patient-centred outcomes: a systematic review. BMJ Quality & Safety, 28(4), 317–326. doi: 10.1136/bmjqs-2017-007778 [DOI] [PubMed] [Google Scholar]
  32. Romanow D, Rai A, & Keil M (2018). CPOE-enabled coordination: Appropriation for deep structure use and impacts on patient outcomes. MIS Quarterly, 42(1), 189–212. doi: 10.25300/MISQ/2018/13275 [DOI] [Google Scholar]
  33. StataCorp. (2017). Stata Statistical Software: Release 15. College Station, TX: StataCorp LLC. [Google Scholar]
  34. Warshawsky N, Havens DH, & Knafl G (2012). The influence of interpersonal relationships on nurse managers’ work engagement and proactive work behavior. Journal of Nursing Administration, 42(9), 418–425. [DOI] [PMC free article] [PubMed] [Google Scholar]
  35. Willgerodt MA, Abu-Rish Blakeney E, Summerside N, Vogel MT, Liner DA, & Zierler B (2019). Impact of leadership development workshops in facilitating team-based practice transformation. Journal of Interprofessional Care, 0(0), 1–11. doi: 10.1080/13561820.2019.1604496 [DOI] [PMC free article] [PubMed] [Google Scholar]

Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

Supplement Table 1
NIHMS1625911-supplement-Supplement_Table_1.docx (14.1KB, docx)

RESOURCES