A scoping review of new implementations of interprofessional bedside rounding models to improve teamwork, care, and outcomes in hospitals

ABSTRACT

Poor communication within healthcare teams occurs commonly, contributing to inefficiency, medical errors, conflict, and other adverse outcomes. Interprofessional bedside rounds (IBR) are a promising model that brings two or more health professions together with patients and families as part of a consistent, team-based routine to share information and collaboratively arrive at a daily plan of care. The purpose of this systematic scoping review was to investigate the breadth and quality of IBR literature to identify and describe gaps and opportunities for future research. We followed an adapted Arksey and O’Malley Framework and PRISMA scoping review guidelines. PubMed, CINAHL, PsycINFO, and Embase were systematically searched for key IBR words and concepts through June 2020. Seventy-nine articles met inclusion criteria and underwent data abstraction. Study quality was assessed using the Mixed Methods Assessment Tool. Publications in this field have increased since 2014, and the majority of studies reported positive impacts of IBR implementation across an array of team, patient, and care quality/delivery outcomes. Despite the preponderance of positive findings, great heterogeneity, and a reliance on quantitative non-randomized study designs remain in the extant research. A growing number of interventions to improve safety, quality, and care experiences in hospital settings focus on redesigning daily inpatient rounds. Limited information on IBR characteristics and implementation strategies coupled with widespread variation in terminology, study quality, and design create challenges in assessing the effectiveness of models of rounds and optimal implementation strategies. This scoping review highlights the need for additional studies of rounding models, implementation strategies, and outcomes that facilitate comparative research.

KEYWORDS:

• interprofessional bedside rounds
• structured interprofessional bedside rounds
• interprofessional collaborative practice
• patient-centered rounds
• rounding models and best practices
• patient-centered care
• hospital communication
• patient safety

Introduction

Poor communication within interprofessional healthcare teams occurs commonly, contributing to inefficiency, medical errors, conflict, and other adverse outcomes (Kohn, 2000; Manser, 2009). Policymakers have called for interventions and research to improve interprofessional collaboration in practice (Institute of Medicine, 2012, 2015; Kohn, 2000).⁻ Among promising models to improve collaboration is interprofessional bedside rounds (IBR). IBR is a rounding model that brings two or more health professions (i.e. physicians, nurses, pharmacists) together with patients and families as part of a consistent team-based routine to share information and collaboratively arrive at a daily plan of care (Ratelle et al., 2018; Reeves et al., 2017b). IBR is distinct from models that include multiple professions (i.e. medicine, nursing, pharmacy) but do not engage patients and families. This type of rounding model often occurs in a conference room and is frequently referred to as multidisciplinary rounds. IBR is also distinct from uniprofessional rounding models (often comprised of only physicians or only nurses) that engage patients and families at the bedside but do not include the larger interprofessional team. Both of these rounding models have substantial and growing bodies of research associated with them (Bhamidipati et al., 2016; Gurses & Xiao, 2006; Holodinsky et al., 2015; Mercedes et al., 2016; Walton et al., 2016; Will et al., 2019). IBR incorporates aspects of both of these approaches into one model that is both interprofessional and patient- and family-centered. By creating a framework for regular and better communication, IBR is thought to lead to improvements in team and patient outcomes. Frequently referred to as structured interprofessional bedside rounds (SIBR) or structured interdisciplinary bedside rounds (SIDR) these routines-of-care may improve communication, patient/staff satisfaction and experience, and clinical outcomes (Gonzalo et al., 2014; Lane et al., 2013; Ratelle et al., 2018; Reeves et al., 2017b). However, the emerging literature is heterogeneous in terms of how IBR is described and where studies are published. Further, optimal IBR models and best practices for implementation remain unclear.

A systematic scoping review of the literature was conducted to describe study characteristics and outcomes following new implementations of IBR to address this uncertainty. While new implementations of IBR have increased in recent years, little mapping or synthesis of this research has occurred. The purpose of this review was to investigate the breadth and quality of literature to identify and describe gaps and opportunities for future research.

This review builds on existing reviews in three key ways. First, by employing a scoping approach and including qualitative, quantitative, and mixed methods studies, we include a more comprehensive picture of the literature than other recent reviews have captured (Gonzalo et al., 2014; Lane et al., 2013; Pannick et al., 2015; Ratelle et al., 2018; Reeves et al., 2017b; Will et al., 2019). Second, by focusing specifically on IBR, we distinguish our efforts from those with a broader focus on interprofessional collaborative practice models in general (Baik et al., 2018; Donovan et al., 2018; Reeves et al., 2017a, 2017b; Weaver et al., 2014, 2013). Third, by centering our inquiry on rounding models that are both interprofessional and explicitly engage patients and families, this study distinctly complements reviews that focused only on one approach (Bhamidipati et al., 2016; Gurses & Xiao, 2006; Holodinsky et al., 2015; Mercedes et al., 2016; Walton et al., 2016; Will et al., 2019). Our working hypothesis is that combining these two approaches into one rounding model that is both interprofessional and patient- and family-centered holds greater potential to improve communication, care, and outcomes than either model does alone.

Methods

This systematic scoping review was developed and conducted following the adapted five-stage Arksey & O’Malley Framework (Arksey & O’Malley, 2005; Daudt et al., 2013; Levac et al., 2010; Peters et al., 2017). Reporting guidelines by PRISMA for Scoping Reviews were used to guide the manuscript’s development (Tricco et al., 2018). A review protocol is available upon request. This scoping review was not registered as, at the time of writing, Prospero did not accept registration of scoping reviews.

Formulating the question

Our team included collaborators from five institutions that either have or plan to implement an IBR model in one or more inpatient hospital units. The following three overarching research questions, which align with three of the six purposes that Munn et al. (2018) outline for a scoping review, were addressed

1. How and where is research on new implementations of IBR being conducted?

2. What types of evidence (i.e. study designs, outcomes) describing new implementations of IBR are available?

3. What knowledge gaps exist in the field of IBR research?

Identifying relevant studies: data sources and search strategy

PubMed, CINAHL, PsycINFO, and Embase were searched by a health sciences librarian (FC) in consultation with the first author (EAB) for the concepts of patient care teams, rounds, inpatient hospitals, and at the bedside or in patients’ rooms. Additionally, the term “structured interprofessional bedside rounds” and its possible synonyms were searched as phrases. The search was performed in July 2018 and repeated in January 2019 and July 2020 to complete searching from the inception of the above databases through the end of June 2020. Unique references cited in six systematic reviews were included (Bhamidipati et al., 2016; Cypress, 2012; Gurses & Xiao, 2006; Lane et al., 2013; Ratelle et al., 2018; Walton et al., 2016). Records were de-duplicated with EndNote X9 (EndNote, n.d.) then uploaded into Rayyan (Doha, Qatar; Ouzzani et al., 2016). See Appendix I for detailed search strategies.

Study selection

Two reviewers performed blinded title and abstract reviews using Rayyan, a web-based app for reviews (Ouzzani et al., 2016). Articles selected for full-text review were organized in REDCap (Nashville, TN) and screened by the lead author and one of 10 other review team members (see Appendix II in Supplementary Materials). At both steps, differences in determination were resolved through discussion and consensus with other reviewers. Studies were included if they were:

(1) published in English,

(2) focused on new IBR implementations,

(3) included patients or family members in rounds,

(4) reported a quantitative, qualitative, or mixed methods study design, and

(5) published in a peer review journal.

Studies were excluded if:

(1) rounds were exclusively educational, or

(2) the described interprofessional intervention was not about rounds.

Data abstraction

Data abstraction took place in two parts using online tools in a REDCap platform. First, the study quality was assessed using the Mixed Methods Assessment Tool (MMAT; Harris et al., 2009), a widely used and validated tool for critical appraisal of the methodological quality of studies divided into five categories: qualitative, randomized controlled, non-randomized, quantitative descriptive, and mixed methods (Hong et al., 2018). Answers to all MMAT questions are categorical with yes, no, or cannot tell options. The sum of “yes” items provides an overall quality score. Four researchers worked in pairs to independently evaluate the study quality of included articles using the MMAT. Any disagreements within the determination of the review pairs were reviewed and resolved by the lead author.

Nine members of our interprofessional research team abstracted article characteristics using a standardized Data Abstraction Tool (see Appendix III in Supplementary Materials). To mitigate bias and error, the lead author cross-checked a sample of abstractions (more than 25% of included articles; Mathes et al., 2017).

Descriptive statistics of abstracted data were performed with STATA SE14 (College Station, TX; StataCorp, 2017) and Microsoft Excel 2019 (Redmond, WA; Microsoft Excel Online, n.d.). Short answer fields were analyzed thematically (Attride-Stirling, 2001).

Results

The initial search yielded 1,105 unique articles (Figure 1). After the title/abstract review, 643 articles were retrieved, and 79 fulfilled inclusion criteria of being both interprofessional (having two or more professions involved) and intentionally engaged with patients and/or family members. Reasons for exclusion are listed in Figure 1; for example, rounds were not interprofessional or were purely educational. The professions most frequently described as being involved in IBR were attending physicians (n = 69, 87.3%), bedside nurses (n = 66, 83.5%), and physicians in training (n = 48, 60.8%). Pharmacists (n = 32, 40.5%), advanced practice providers (n = 27, 34.2%), and social workers (n = 22, 27.9%) were also frequent participants in IBR. In the majority of studies (n = 43, 54.4%) the previous rounding model was not sufficiently described to be able to determine where it occurred prior to the shift to IBR. When described, the most common prior locations included conference rooms or team rooms (n = 10, 12.7%), hallways (n = 9, 11.4%), or in-room but uniprofessional (n = 9, 11.4%).

Question 1: When, where, and how is research on new implementations of IBR being conducted?

Figure 1. PRISMA Diagram of studies in the selection process.

Publication trends

The number of studies describing new implementations of IBR has increased in recent years (see Appendix IV in Supplementary Materials). While the earliest article meeting inclusion criteria was published in 1988, four or fewer articles were published each year between 1988 and 2013. Starting in 2014, five or more articles were published each year. In 2018, 13 (16.5%) of the 79 articles were published, and as of June 30, 2020, five additional articles had been published. Details of included articles can be found in chronological order in Table 1. Appendix V in Supplementary Materials provides a summary table of study characteristics.

Table 1. Abbreviated details of each of the included studies in chronological order (1988-June 30, 2020).

First Author (Year) Article Title	Study Design (MMAT Categories) (Quantitative Non-Randomized = QNR)	MMAT Score % Yes (0–100)	Key Characteristics: Non-U.S. Setting; Pediatric Funding sources credited in publication (* if no funding credited)	Types of Outcomes Reported (Team = T; Patient = P; Findings: positive = +; neutral = n; negative = -; uncertain = ?)
Lewis et al. (1988)⸺Patient, parent, and physician perspectives on pediatric oncology rounds	QNR	80	Pediatric; Funding: Institutional	T: + P: +
Wright et al. (1996)⸺The communication gap in the ICU – a possible solution	Not Categorized	N/A	UK*	T: +, n, -
M. P. Young et al. (1998)⸺The impact of a multidisciplinary approach on caring for ventilator-dependent patients	QNR	60	*	T: n P: +, n
Scarsi et al. (2002)⸺Pharmacist participation in medical rounds reduces medication errors	QNR	80	*	T: + P: +
Treacy et al. (2002)⸺Impact of a multidisciplinary team approach upon patency rates of arteriovenous fistulae	QNR	40	Australia*	P: +
Uhlig et al. (2002)⸺System innovation: Concord Hospital	Not Categorized	N/A	*	T: + P: +
Dodek and Raboud (2003)⸺Explicit approach to rounds in an ICU improves communication and satisfaction of providers	QNR	80	Canada*	T: +
Dutton et al. (2003)⸺Daily multidisciplinary rounds shorten length of stay for trauma patients	QNR	80	*	P: +, n
Kucukarslan et al. (2003)⸺Pharmacists on rounding teams reduce preventable adverse drug events in hospital general medicine units	QNR	100	*	P: +
Schiller and Anderson (2003)⸺Family as a member of the trauma rounds: A strategy for maximized communication	Quantitative Descriptive	40	Pediatric (also Adult)*	T: +, n P: +
Fertleman et al. (2005)⸺Improving medication management for patients: the effect of a pharmacist on post-admission ward rounds	QNR	80	UK*	T: + P: +
Monaghan et al. (2005)⸺Improving patient and carer communication, multidisciplinary team working and goal-setting in stroke rehabilitation	QNR	80	UK; Funding: Institutional	T: +
Moroney and Knowles (2006)⸺Innovation and teamwork: introducing multidisciplinary team ward rounds	Not Categorized	N/A	UK*	T: +, - P: +
Bonello et al. (2008)⸺An intensive care unit quality improvement collaborative in nine department of veterans affairs hospitals: reducing ventilator associated pneumonia and catheter-related bloodstream infection rates	QNR	60	Funding: VA Midwest health care network (QI strategic priority)	P: +, n
Latta et al. (2008)⸺Parental responses to involvement in rounds on a pediatric inpatient unit at a teaching hospital: A qualitative study	Qualitative	100	Pediatric*	T: + P: +
Cameron et al. (2009)⸺Parental presence on pediatric intensive care unit rounds	Mixed Methods	80	Pediatric*	T: +, n, - P: +, n, -
Makowsky et al. (2009)⸺Capturing outcomes of clinical activities performed by a rounding pharmacist practicing in team environment	Quantitative Randomized Controlled Trial	80	Canada; Funding:Pharmaceutical, Institutional	P: +, ?
Rosen et al. (2009)⸺Family-centered multidisciplinary rounds enhance the team approach in pediatrics	QNR	60	Pediatric*	T: +
Jacobowski et al. (2010)⸺Communication in critical care: Family rounds in the intensive care unit	QNR	100	Funding: NIH, VA, Foundation, Institutional	T: n P: +, n
Rappaport et al. (2010)⸺Implementing family-centered rounds: pediatric residents’ perceptions	Quantitative Descriptive	80	Pediatric*	T: + P: +
Timmel et al. (2010)⸺Impact of the comprehensive unit-based safety program (CUSP) on safety culture in a surgical inpatient unit	QNR	60	*	T: +
Voos et al. (2011)⸺Effects of implementing family-centered rounds (FCRs) in a neonatal intensive care unit (NICU)	QNR	60	Pediatric*	T: + P: +, n
Ladak et al. (2013)⸺Family-centered rounds in Pakistani pediatric intensive care settings: Non-randomized pre- and post- study design	QNR	80	Pakistan; Pediatric; Funding: Institutional	T: +, n, - P: +
Licata et al. (2013)⸺A foundation for patient safety: Phase I implementation of interdisciplinary bedside rounds in the pediatric intensive care unit	QNR	0	Pediatric*	T: +
Roussel et al. (2013)⸺Improving recovery time following heart transplantation: the role of the multidisciplinary health care team	Not Categorized	N/A	*	P: +
Saint et al. (2013)⸺An academic hospitalist model to improve healthcare worker communication and learner education: results from a quasi-experimental study at a Veterans Affairs Medical Center	Mixed Methods	100	Funding: VA	T: + P: +
Oshimura et al. (2014)⸺Family-centered rounding: Can it impact the time of discharge and time of completion of studies at an academic children’s hospital?	QNR	40	Pediatric*	P: +
Palokas et al. (2015)⸺An interactive evaluation of patient/family centered rounds on pediatric inpatient units	Not Categorized	N/A	Pediatric*	T: + P: +
Seigel et al. (2014)⸺Successful implementation of standardized multidisciplinary bedside rounds, including daily goals, in a pediatric ICU	Not Categorized	N/A	Pediatric*	T: +
U. Sharma and Klocke (2014)⸺Attitudes of nursing staff toward interprofessional in-patient-centered rounding	QNR	0	*	T: + P: +
Southwick et al. (2014)⸺Applying athletic principles to medical rounds to improve teaching and patient care	QNR	80	*	T: + P: +, n
Wrobleski et al. (2014)⸺Discharge planning rounds to the bedside: A patient- and family-centered approach	QNR	80	Funding: Institutional	T: + P: +
Berkwitt and Grossman (2015)⸺A qualitative analysis of pediatric patient attitudes regarding family-centered rounds	Qualitative	100	Pediatric*	P: +, n, -
Gausvik et al. (2015)⸺Structured nursing communication on interdisciplinary acute care teams improves perceptions of safety, efficiency, understanding of care plan and teamwork as well as job satisfaction	QNR	60	*	T: +
Shaughnessy and Jackson (2015)⸺Introduction of a new ward round approach in a cardiothoracic critical care unit	Mixed Methods	80	UK*	T: +, n P: n
Stein et al. (2015)⸺Reorganizing a hospital ward as an accountable care unit	Not Categorized	N/A	Funding: HRSA	P: +
Tripathi et al. (2015)⸺Implementation of patient-centered bedside rounds in the pediatric intensive care unit	QNR	40	Pediatric*	T: + P: n
Allen et al. (2017)⸺A novel method of optimizing patient- and family-centered care in the ICU	QNR	40	*	T: + P: +
Braus et al. (2016)⸺Prospective study of a proactive palliative care rounding intervention in a medical ICU	QNR	100	Funding: NIH, Foundation	T: +, n P: +, n
Gustafson et al. (2016)⸺Effect of parent presence during multidisciplinary rounds on NICU-related parental stress	QNR	80	Pediatric*	T: + P: +
Henkin et al. (2016)⸺Improving nurse-physician teamwork through interprofessional bedside rounding	QNR	40	*	T: +
Justice et al. (2016)⸺Improving communication during cardiac ICU multidisciplinary rounds through visual display of patient daily goals	QNR	80	Pediatric; Funding: Pharmaceutical	T: + P: +
Okere et al. (2016)⸺Comparison of a pharmacist-hospitalist collaborative model of inpatient care with multidisciplinary rounds in achieving quality measures	QNR	80	Funding: Foundation	P: +, n
O’Leary et al. (2016)⸺Effect of patient-centered bedside rounds on hospitalized patients’ decision control, activation and satisfaction with care	Quantitative Randomized Controlled Trial	40	Funding: Foundation	T: +, n P: n
Young et al. (2018)⸺Impact of altered medication administration time on interdisciplinary bedside rounds on academic medical ward	QNR	40	*	T: +, n, - P: +
Dunn et al. (2017)⸺The impact of bedside interdisciplinary rounds on length of stay and complications	QNR	80	Funding: Foundation	T: + P: +, n
Hendricks et al. (2017)⸺Facilitators and barriers for interprofessional rounding	Qualitative	100	Funding: HRSA	T: +, n, -
Huang et al. (2017)⸺All together now: Impact of a regionalization and bedside rounding initiative on the efficiency and inclusiveness of clinical rounds	QNR	100	Funding:Pharmaceutical, Institutional	T: +
Huynh et al. (2017)⸺Structured interdisciplinary bedside rounds do not reduce length of hospital stay and 28-day re-admission rate among older people hospitalized with acute illness: an Australian study	QNR	100	Australia*	P: n
Luthy et al. (2017)⸺Bedside or not bedside: Evaluation of patient satisfaction in intensive medical rehabilitation wards	QNR	100	Switzerland*	P: +
McGrath et al. (2017)⸺Evaluating the quality improvement impact of the Global Tracheostomy Collaborative in four diverse NHS hospitals	QNR	60	UK; Funding: Foundation	T: + P: +
Monash et al. (2017)⸺Standardized attending rounds to improve the patient experience: A pragmatic cluster randomized trial	Quantitative Randomized Controlled Trial	100	Funding: NIH	T: + P: +
Thorne et al. (2017)⸺Co-producing interprofessional round work: designing spaces for patient partnership	Qualitative	100	Sweden*	T: +, n, - P: +, n, -
Abu-Rish Blakeney et al. (2018)⸺Purposeful interprofessional team intervention improves relational coordination among advanced heart failure care teams	QNR	80	Funding: HRSA, NIH	T: +
Baik and Zierler (2018)⸺RN job satisfaction and retention after an interprofessional team intervention	QNR	60	Funding: Foundation	T: +
Basic et al. (2018)⸺Structured interdisciplinary bedside rounds, in-hospital deaths, and new nursing home placements among older inpatients	QNR	100	Australia*	P: n, ?
Cao et al. (2018)⸺Patient-centered structured interdisciplinary rounds in the medical ICU	QNR	80	*	T: + P: n
Chow et al. (2018)⸺Structured interdisciplinary bedside rounds in an Australian tertiary hospital emergency department: patient satisfaction and staff perspectives	QNR	40	Australia*	T: +, n, - P: +
Clay-Williams et al. (2018)⸺Improving teamwork and patient outcomes with daily structured interdisciplinary bedside rounds: a multimethod evaluation	Mixed Methods	100	Australia; Funding: Foundation	T: +, n, - P: +, n
Cody et al. (2018)⸺Making a connection: Family experiences with bedside rounds in the intensive care unit	Qualitative	100	*	P: +, n, -
Khan et al. (2018)⸺Patient safety after implementation of a coproduced family centered communication programme: multicenter before and after intervention study	QNR	100	Canada (& U.S.) study sites; Pediatric Funding: PCORI, AHRQ	T: + P: +
Li et al. (2018)⸺Interprofessional Teamwork Innovation Model (ITIM) to promote communication and patient-centered, coordinated care	QNR	60	*	T: + P: +, n
Malec et al. (2018)⸺The care team visit: Approaching interdisciplinary rounds with renewed focus	Not Categorized	N/A	*	T: + P: n, -
Mork et al. (2018)⸺Using Kotter’s Change Framework to implement and sustain multiple complementary ICU initiatives	Not Categorized	N/A	*	T: +
Vega et al. (2018)⸺Quality improvement bedside rounding audits enhance protein provision for pediatric patients receiving continuous renal replacement therapy	QNR	40	Pediatric*	P: +
Wickersham et al. (2018)⸺Novel use of communication technology to improve nurse-physician communication, teamwork, and care coordination during bedside rounds	QNR	60	*	T: +, n
Bekmezian et al. (2019)⸺Keeping time: implementing appointment-based family-centered rounds	QNR	40	*	P: +, –
Gormley et al. (2019)⸺Impact of nurse-led interprofessional rounding on patient experience	Not categorized	N/A	Funding: HRSA	T: +, n
Ha et al. (2019)⸺A multidisciplinary approach to incorporate bedside nurses into antimicrobial stewardship and infection prevention	QNR	40	*	T: +
Lopez et al. (2019)⸺Impacting satisfaction, learning, and efficiency through structured interdisciplinary rounding in a pediatric intensive care unit: A quality improvement project	QNR	60	Funding: Institutional	T: + P: +, n
Opper et al. (2019)⸺Effects of implementing a health team communication redesign on hospital readmissions within 30 days	QNR	20	Funding: Foundation	T: n P: +
Akuamoah-Boateng et al. (2019)⸺RAMPED UP: The development and testing of an interprofessional collaboration model	QNR	80	*	T: + P: +, n
Austin et al. (2020)⸺Evaluation of a nurse practitioner-led project to improve communication and collaboration in the acute care setting	QNR	20	*	T: + P: +
Barcellos and Chatkin (2020)⸺Impact of a multidisciplinary checklist on the duration of invasive mechanical ventilation of length of stay	QNR	80	Brazil*	T: + P: +
Chava et al. (2019)⸺Multidisciplinary rounds in prevention of 30-day readmissions and decreasing length of stay in heart failure patients	QNR	40	*	P: +
Clarke et al. (2020)⸺Antimicrobial stewardship in spinal cord injury: A multidisciplinary approach	QNR	80	Australia*	P: +
Kang et al. (2020)⸺State anxiety, uncertainty in illness, and needs of family members of critically ill patients and their experiences with family-centered multidisciplinary rounds: A mixed methods study	Mixed Methods	60	South Korea; Funding: Foundation	P: +
Redley et al. (2020)⸺Mixed methods quality evaluation of structured interprofessional medical ward rounds	Mixed Methods	0	Australia*	T: +, n, -
Sunkara et al. (2020)⸺Impact of structured interdisciplinary bedside rounding on patient outcomes at a large academic medical center	QNR	80	Funding: HRSA	P: +, n

Abbreviations: MMAT = Mixed Methods Assessment Tool (Harris et al., 2009).

Included articles were published in over 50 journals with a wide array of foci (Appendix VI). The Journal of Hospital Medicine published the largest number of included articles (n = 6, 7.6%), followed by the Joint Commission Journal on Quality and Patient Safety (n = 5, 6.3%), and the Journal of Nursing Care Quality (n = 4, 5.1%).

Study locations

Nearly 75% of included studies took place in the United States (n = 58), followed by the United Kingdom (n = 7, 8.9%), Australia (n = 7, 8.9%), and Canada (n = 3, 3.8%). Brazil, Pakistan, South Korea, Sweden, and Switzerland each originated one study.

The majority of studies were conducted in academic medical centers (n = 64, 81.0%). One-quarter (n = 20, 25.3%) focused on IBR with pediatric patients and their families. The remainder focused on adult (n = 52, 65.8%) or older adult (age 66+) (n = 41, 51.9%) populations.

Acute care (n = 42, 56.0%) or intensive care units (n = 28, 35.4%) were the most common settings for included studies. The most frequent clinical specialties involved were general medical/surgical (n = 37, 46.8%), cardiology (n = 15, 19.0%), and surgery (n = 7, 8.9%). Three or fewer studies reported implementations in oncology, trauma, geriatric, or rehabilitation specialty areas. The remainder either did not describe a specialty area (n = 6, 7.6%) or described implementation across an entire institution (n = 2, 2.5%).

Funding for IBR Research Most publications reported no research funding (n = 52, 65.8%) (Table 1). Fourteen publications (17.7%) indicated funding from one or more U.S. federal funding sources – these included: Health Resources and Services Administration (n = 5, 6.3%), National Institutes of Health (n = 4, 5.1%), Veterans Affairs (n = 3, 3.8%), Patient-Centered Outcomes Research Institute (n = 1, 1.3%), or Agency for Healthcare Research and Quality (n = 1, 1.3%). Ten studies (12.7%) credited a foundation grant while 8 (10.1%) cited institutional funding. Three studies (3.8%) reported funding from pharmaceutical companies.

Question 2: What types of evidence describing new implementations of IBR models are available?

Study designs and quality

The majority (n = 69, 87.3%) of included studies asked both clear research questions and collected appropriate data to answer those research questions (Table 2).

Table 2. Summary of Mixed Methods Appraisal Tool (MMAT) results by study design (n = 79).

Screening Questions (all study types) (n = 79) *If no or can’t tell for screening questions, study not further categorized/evaluated
	Yes	No	Can’t Tell
S1. Are there clear research questions?	69 (87.3%)	8 (10.1%)	2 (2.5%)
S2. Do the collected data allow to address the research questions?	69 (87.3%)	5 (6.3%)	5 (6.3%)
Did not meet MMAT screening criteria n = 10 (12.7%)
Qualitative n = 5 (6.3%)
Methodological quality criteria	Yes	No	Can’t Tell
1.1 Is the qualitative approach appropriate to answer the research question	5 (100%)	0 (0%)	0 (0%
1.2 Are the qualitative data collection methods adequate to address the research question?	5 (100%)	0 (0%)	0 (0%
1.3 Are the findings adequately derived from the data?	5 (100%)	0 (0%)	0 (0%
1.4. Is the interpretation of results sufficiently substantiated by data?	5 (100%)	0 (0%)	0 (0%
1.5. Is there coherence between qualitative data sources, collection, analysis and interpretation?	5 (100%)	0 (0%)	0 (0%
Quantitative randomized controlled trials n = 3 (3.8%)
2.1. Is randomization appropriately performed?	1 (33.3%)	0 (0.0%)	2 (66.7%)
2.2. Are the groups comparable at baseline?	3 (100%)	0 (0%)	0 (0%
2.3. Are there complete outcome data?	3 (100%)	0 (0%)	0 (0%
2.4. Are outcome assessors blinded to the intervention provided?	2 (66.7%)	0 (0.0%)	1 (33.3%)
2.5 Did the participants adhere to the assigned intervention?	2 (66.7%)	0 (0.0%)	1 (33.3%)
Quantitative non-randomized n = 53 (67.1%)
3.1. Are the participants representative of the target population?	45 (84.9%)	2 (3.8%)	6 (11.3%)
3.2. Are measurements appropriate regarding both the outcome and intervention (or exposure)?	47 (88.7%)	2 (3.8%)	4 (7.6%)
3.3. Are there complete outcome data?	39 (73.6%)	13 (24.5%)	1 (1.9%)
3.4. Are the confounders accounted for in the design and analysis?	17 (32.1%)	36 (67.9%)	0 (0%)
3.5. During the study period, is the intervention administered (or exposure occurred) as intended?	25 (47.2%)	1 (1.9%)	27 (50.9%)
Quantitative descriptive n = 2 (2.5%)
4.1. Is the sampling strategy relevant to address the research question?	2 (100.0%)	0 (0%)	0 (0%)
4.2. Is the sample representative of the target population?	1 (50.0%)	0 (0%)	1 (50.0%)
4.3. Are the measurements appropriate?	1 (50.0%)	1 (50.0%)	0 (0%)
4.4. Is the risk of nonresponse bias low?	2 (100.0%)	0 (0%)	0 (0%)
4.5. Is the statistical analysis appropriate to answer the research question?	2 (100.0%)	0 (0%)	0 (0%)
Mixed methods n = 6 (7.6%)
5.1. Is there an adequate rationale for using a mixed methods design to address the research question?	3 (50.0%)	3 (50.0%)	0 (0%)
5.2. Are the different components of the study effectively integrated to answer the research question?	5 (83.3%)	1 (16.7%)	0 (0%)
5.3. Are the outputs of the integration of qualitative and quantitative components adequately interpreted?	5 (83.3%)	1 (16.7%)	0 (0%)
5.4. Are divergences and inconsistencies between quantitative and qualitative results adequately addressed?	4 (66.7%)	1 (16.7%)	1 (16.7%)
5.5. Do the different components of the study adhere to the quality criteria of each tradition of the methods involved?	4 (66.7%)	2 (33.3%)	0 (0%)

The most frequently published study design was a quantitative non-randomized approach (n = 53, 67.1%). These studies used other non-randomized units or patient groups as controls or utilized a pre-test/posttest approach to measure outcomes associated with IBR implementation. The balance of studies were mixed methods (n = 6, 7.6%), qualitative (n = 5, 6.3%), randomized controlled trials (n = 3, 3.8%), or quantitative descriptive (n = 2, 2.5%). Study quality varied widely across study types (Table 2). While small in number (n = 5), qualitative studies were the most highly rated for quality and the majority focused on qualitative explorations of patient and family perspectives of IBR (Berkwitt & Grossman, 2015; Cody et al., 2018; Hendricks et al., 2017; Latta et al., 2008; Thorne et al., 2017).

Among the non-randomized studies (n = 53), the most common MMAT deficiencies noted were unaddressed confounders (i.e. disease severity of patients) and lack of intervention fidelity. Fidelity is “the degree to which an intervention is delivered as intended” (Proctor et al., 2011, p. 69). In nearly 70% of these studies (n = 36) confounders were not accounted for in the design and analysis. In over 50% of these studies (n = 28), reviewers were unable to determine whether the intervention was delivered as intended or concluded that it had not been delivered as intended (Table 2).

Guiding theories, frameworks, and policies

Twenty-five articles (31.7%) cited a conceptual framework or theory supporting the study. The most frequently cited originated from the field of Quality Improvement (n = 9, 11.4%), including Plan-Do-Study-Act (Taylor et al., 2014), Continuous Quality Improvement (O’Donnell & Gupta, 2020), or the Quality Health Outcomes Framework (Mitchell & Lang, 2004). The next most common were six studies (7.6%) guided by a patient- and family-centered care (Davidson et al., 2017) or a shared decision-making framework (Michalsen et al., 2019), followed by five studies (6.3%) that utilized a systems framework – e.g., Toyota production systems (Rotter et al., 2019), clinical microsystems, and systems theory (Nelson et al., 2007). Finally, three studies (3.8%) referenced an interprofessional framework (Cox et al., 2016), and three studies (3.8%) referenced model of change frameworks (Bolton et al., 2021; Kotter, 2007). Additional frameworks used by individual studies include Meleis’ Transitions Theory (Meleis et al., 2000), Social-Material Practice Theory (Schatzki, 2002), AIDET format (Braverman et al., 2015), and Athletic Training Principles (Southwick et al., 2014). We found no articles citing implementation science frameworks or theories.

Nearly half of the reviewed studies (n = 33, 41.7%) referenced one or more specific organizations, policies, or practice guidelines in the framing of their study. The most commonly cited were the National Academy of Sciences’ (formerly the Institute of Medicine) (n = 9, 11.4%) statements on medical error and interprofessional care (Institute of Medicine, 2001, 2012, 2015; Kohn, 2000). This was followed by the American Academy of Pediatrics (n = 8, 10.1%) statement on patient- and family-centered rounding models as a standard of practice in inpatient pediatric care (Committee on Hospital Care and Institute for Patient- and Family-Centered Care, 2012).

Adoption/adaptation of existing IBR models

References to adoption or adaptation of a rounding model occurred in 40% of articles (n = 32). The most common approach was identifying a rounding model either from a literature review (n = 10, 10.3%) or from the 2015 study of Structured Interdisciplinary Bedside Rounds (SIBR) by Stein et al. (n = 7, 8.9%). Two studies each referenced adopting/adapting models described by Mittal (2014), O’Leary et al. (2011), and O’Leary et al. (2016)), and Gonzalo et al. (2010), Gonzalo et al. (2013, 2014a, 2014b, 2016). Two studies also described adapting models observed in other units within their hospital system (Abu-Rish Blakeney et al., 2018; Licata et al., 2013). Adoption or adaptation processes were minimally described in most studies beyond referencing these sources.

Team, patient, and care quality/delivery outcomes

Study outcomes were categorized as: (1) team outcomes, (2) patient/client outcomes, or (3) health-care quality and delivery outcomes. Educational outcomes of rounds participation among learners were also considered and are described in the next section. Over half of the included studies evaluated impacts on both team and patient outcomes (n = 41, 51.9%), 25% of studies evaluated only patient outcomes (n = 20, 25.3%), and the remaining 23% of studies evaluated only team outcomes (n = 18, 22.8%) (Table 1). Nearly 90% (n = 70, 88.6%) of studies reported one or more health-care quality and delivery outcomes as defined by the Institute of Medicine Standards of Care (Institute of Medicine, 2001). A wide range of outcomes ranging from satisfaction to maintenance of confidentiality to incidence of nosocomial infections were evaluated within these broad categories by studies with overall positive results (Table 3).

Table 3. Team, patient/client, and health-care quality and delivery outcomes reported by included studies following implementation of interprofessional bedside rounds (n = 79).

	Data collected, (n/%)			Positive (desirable change reported) (n/%)		% Positive if collected and reported	Negative (not desirable change reported) (n/%)	Outcome did not change, (n/%)		Mixed results (combination of positive, negative, no change) (n/%)
Team Outcomes
Satisfaction with change	37 (46.8)			29 (36.7)		78.4	0 (0.0)	3 (3.8)		5 (6.3)
Satisfaction with model	28 (35.4)			21 (26.6)		75.0	0 (0.0)	2 (2.5)		5 (6.3)
Rounds constructive use of time	22 (27.9)			16 (20.3)		72.7	1 (1.3)	0 (0.0)		5 (6.3)
Team Communication	34 (43.0)			29 (36.7)		85.2	0 (0.0)	2 (2.5)		3 (3.8)
Team Relationships	20 (25.3)			17(21.5)		85.0	0 (0.0)	0 (0.0)		3 (3.8)
Team Perception of Patient Centeredness of Model	23 (29.1)			16 (20.3)		69.6	0 (0.0)	2 (2.5)		5 (6.3)
High Reliability (1 did not report results)	4 (5.1)			3 (3.8)		75.0	0 (0.0)	0 (0.0)		0 (0.0)
Retention/ Turnover (2 did not report results)	5 (6.3)			2 (2.5)		40.0	0 (0.0)	1 (1.3)		0 (0.0)
Alignment with Professional Goals	3 (3.8)			1 (1.3)		33.3	0 (0.0)	0 (0.0)		2 (2.5)
Workload	11 (13.9)			6 (7.6)		54.5	0 (0.0)	0 (0.0)		5 (6.3)
Other (i.e. discussions of goals of care on rounds, number of interruptions, duration of rounds, disciplines present)	18 (22.8)			11 (13.9)		61.1	1 (1.3)	2 (2.5)		4 (5.1)
Patient/Client Outcomes
Patient Experience
Perceptions of Care Received	29 (36.7)			20 (25.3)		69.0	0 (0.0)	4 (5.1)		5 (6.3)
Overall satisfaction with rounds	24 (30.4)			17 (21.5)		70.8	0 (0.0)	5 (6.3)		2(3.8)
Experiences of families joining rounds	20 (25.3)			12 (15.2)		60.0	0 (0.0)	4 (5.1)		4 (5.1)
Maintenance of patient confidentiality	3 (3.8)			3 (3.8)		100.0	0 (0.0)	0 (0.0)		0 (0.0)
Clinical Outcomes
Length of Stay		25(31.7)	17 (21.5)		68.0		1 (1.3)		5 (6.3)		2 (2.5)
Readmissions		14 (17.7)	8 (10.1)		57.1		0 (0.0)		5 (6.3)		1 (1.3)
Incidence of Nosocomial Infections		2 (2.5)	2 (2.5)		100.0		0 (0.0)		0 (0.0)		0 (0.0)
Mortality		8 (10.8)	2 (2.5)		25.0		0 (0.0)		6(7.6)		0 (0.0)
Achievement of Clinical Performance Targets		5 (6.3)	5 (6.3)		100.0		0 (0.0)		0 (0.0)		0 (0.0)
Procedural Complications		2 (2.5)	2 (2.5)		100.0		0 (0.0)		0 (0.0)		0 (0.0)
Triggers of Harm or Actual Harm		7 (8.9)	6 (7.6)		85.7		0 (0.0)		0 (0.0)		1 (1.3)^1
Other (i.e., family stress, family knowledge of daily plan, family knows doctor, clinical deterioration, changes in medications, timing of orders /discharges)		18 (22.8)	12 (15.2)		66.7		0 (0.0)		3 (3.8)		3 (3.8)
Health Care Quality and Delivery Outcomes
Safety		17 (21.5)	15 (19.0)		88.2		0.0		1 (1.3)		1 (1.3)
Effectiveness (1 did not report results)		17 (21.5)	13 (16.5)		76.5		0.0		1 (1.3)		2 (2.5)
Patient Centeredness (4 did not report results)		32 (40.5)	19 (24.1)		59.4		1 (1.3)		5 (6.3)		3 (3.8)
Timeliness		19 (24.1)	12 (15.2)		63.2		1 (1.3)		4 (5.1)		2 (2.5)
Efficiency (1 did not report results)		31 (39.2)	21 (26.6)		67.7		1 (1.3)		2 (2.5)		6 (7.6)
Equity		3 (3.8)	0 (0.0)		0.0		0 (0.0)		1 (1.3)		2 (2.5)

Note. Malec et al. (2018) reported zero CAUTIs or CLABSIs during the pre-intervention period but 3 CAUTIs and 1 CLABSI by the time of the 9-month post assessment; they also report desirable changes in utilization rates of central line devices (increased) and Foley catheters (decreased).

Outcomes of rounds participation among learners

Thirteen (16.5%) of the 79 included studies considered whether participation in rounds was beneficial to learners (i.e., trainees). IBR participation was described as beneficial (n = 11, 84.6%) in the majority of studies reporting learner outcomes (Cameron et al., 2009; Cao et al., 2018; Dodek & Raboud, 2003; Khan et al., 2018; Lewis et al., 1988; Lopez et al., 2019; Rappaport et al., 2010; Saint et al., 2013; Seigel et al., 2014; Southwick et al., 2014; E. Young et al., 2018). For example, Lopez et al. (2019) surveyed resident physicians who participated in SIBR implementation and found that, in addition to shortening the length of rounds, that residents felt that “SIBR positively impacted their education, family presence positively impacted learning, and SIBR was more effective than rounds without structure (p. 4).” Two studies reported mixed findings related to participation of learners. Monash et al. (2017) found that despite their model shortening rounds on average by 8 minutes overall, trainees were less satisfied and perceived them to last longer than the previous rounding model. Bekmezian et al. (2019) described adding 5- to 10-minute-long teaching appointments into their rounding structure after concerns surfaced about teaching during their appointment-based family-centered rounds model. In the balance of the 79 included studies, learners were described as being present in 33 studies (41.8%), but learning outcomes were not described. The remaining 33 studies (41.8%) did not report having learners present.

Discussion

Rounds are a complex care routine that occurs daily for most inpatients, although formats vary widely due to overlapping or competing perspectives on the purpose of rounds (Bharwani et al., 2012; Holodinsky et al., 2015; Monash, 2017; Walton et al., 2016). Historically, rounds were uni-professional (typically medicine) and provider-centric. Increasingly, rounds have been redesigned to improve outcomes by including other professions (i.e., nursing, pharmacy) and intentional engagement with patients and families (Gonzalo et al., 2014). This combination of ubiquity and high variability is what makes rounds an opportune focus for study and improvement efforts.

This systematic scoping review identified studies reporting new IBR implementations beginning in 1988 and with increasing frequency of publications in this field since 2014. The majority of studies report positive impacts of rounding model implementation across an array of the team, patient, and care quality/delivery outcomes. Despite this growth and a preponderance of positive findings, there remains a great deal of heterogeneity and a reliance on quantitative non-randomized study and single-center designs. This makes it challenging to carry out systematic reviews or meta-analyses that would permit moving from IBR as a promising, evidence-informed care model to an evidence-based practice standard of care.

A major weakness of the existing research is a lack of explicit theory to frame why and how IBR might be expected to lead to a broad array of positive changes (Shoemaker et al., 2004). Most articles articulated a hypothesis or purpose linking improved communication between interprofessional teams and patients/families during rounds to improved patient outcomes. However, only 30% referenced a specific theory or framework that guided their study. Further, nearly half of the included studies reported on team or patient outcomes, but not both. We considered analyses examining whether patient outcomes (i.e. length of stay or readmissions) improved following IBR implementation without also incorporating assessments of team communication to have the potential for substantial confounding. Future studies should more clearly explicate the theory underlying their research and incorporate assessments of communication into analyses of patient outcomes.

A key impediment to the dissemination of successful IBR systems was a lack of specificity when reporting both pre- and post-intervention rounding models. Many articles referenced previously published IBR models, but few explicitly described the linkage between published models and the implemented model. Although we intended to abstract data about rounding model characteristics, implementation strategies, and implementation outcomes, descriptions were too sparse and varied to map these features to frameworks accurately. Even when studies included robust model details, measures of fidelity were lacking. Assessment of fidelity is essential to understanding whether findings can be attributed to a change in rounding models. However, we found that the majority of quantitative non-randomized studies did not account for confounders, and approximately 50% of these studies did not indicate if the intervention occurred as intended. Incorporating implementation science frameworks and tools in future studies would help develop a clearer picture of whether, how, and why some implementations of IBR lead to improvements in outcomes and others fail to achieve these same goals (Birken et al., 2017; Powell et al., 2019). Additional specifications would also help to clarify which elements of IBR are essential core components, and which aspects are discretionary or adaptable (Abry et al., 2015; Fixsen et al., 2009).

Additional funding is needed to close gaps in the IBR literature and to support rigorous multi-site studies with advanced study designs, such as cluster or stepped wedge randomized trials. The majority of studies included in this review did not report funding to support their implementation project, precluding costly investigations with high sample sizes, randomized designs, and rigorous monitoring of implementation fidelity. The recent surge in unfunded studies suggests that front-line care team members are open to innovation in rounding methods and hint at face validity for this type of care model. However, the current science is over-reliant on quantitative non-randomized designs. Research utilizing a variety of designs and methods, particularly qualitative, mixed methods, and RCTs would enrich and strengthen this literature.

Future studies should also address the potential for IBR models to have differential effects for different groups, including the potential to reduce inequities or disparities in inpatient hospital care. Inequities in inpatient care and outcomes are increasingly recognized (Nayfeh & Fowler, 2020). Only three studies (Braus et al., 2016; Dunn et al., 2017; Khan et al., 2018) addressed equity in their study designs or results, and those that did found a mix of positive or neutral improvements, although equity or disparities were not the primary foci of these studies. Similarly, while many articles addressed patient satisfaction or patient- and family-centeredness of rounds, the approaches used in these studies ranged widely. Examination of potential mismatches between care team perceptions of patient- and family-centeredness of IBR models and patient- and family perceptions of the same processes to improve these models would be a useful next step. Additionally, patient- and family-centered interventions may need to be developed and tested to determine the best way to orient and support patients and families’ participation in IBR.

Limitations

This review has several limitations. First, while we intentionally used broad search terms and considered a large number of articles for inclusion, the heterogeneity of terms used and the broad array of journals in which this work has been published make it likely that some studies may have been missed. Harmonization of terms for IBR models would have many benefits both in clinical practice areas and for the research literature. Second, we excluded articles that reported implementing interprofessional rounds when we were unable to determine if rounds took place at the bedside and whether patients and families were explicitly engaged. Third, we excluded published conference abstracts, and unpublished and non-peer-reviewed manuscripts. Both may contribute to underestimating the rate at which IBR models are being implemented and overestimating positive outcomes because of well-known publication bias toward positive results (H. Sharma & Verma, 2019). Additionally, as described above, we intended to examine implementation strategies and outcomes but could not due to a lack of specificity and heterogeneity in the literature. Finally, all reviewed articles predate the Covid-19 pandemic, and thus application in a pandemic situation represents an unknown and a limitation of the review.

Conclusion

This systematic scoping review investigated the current breadth and quality of literature describing new implementations of IBR that indicate substantial growth and overwhelmingly positive outcomes, albeit with gaps. To close these gaps, we encourage authors to include more detail about the IBR models they are implementing, what implementation strategies they are using, and how the new models are different from usual care prior to IBR implementation. Additionally, situating future studies within theoretical frameworks, using mixed methods approaches, and employing more rigorous study designs has the potential to greatly enhance our understanding of both how and why IBR models work. Carrying out these more complex study designs will require investment from funders to continue to build the evidence base for models of patient- and family-centered interprofessional collaborative practice.

Acknowledgments

The lead author received funding to support her time during the conceptualization, data collection, analysis and manuscript writing for this project from the NIH National Heart, Lung, and Blood Institute K12 (#5K12HL137940) as part of the UW Implementation Science Training Program and her time during manuscript revisions from a National Heart, Lung, and Blood Institute K23 (1K23HL144910-01A1). BK and NS received support from NCATS (UL1 TR002319). RS received support from the Macy Foundation.

Disclosure statement

The authors report no conflicts of interest. The authors alone are responsible for the writing and content of this article.

Supplementary material

Supplemental data for this article can be accessed on the publisher’s website.

Additional information

Funding

This work was supported by the NHLBI [1K23HL144910-01A1,5K12HL137940]; National Center for Advancing Translational Sciences [UL1 TR002319]; Macy Foundation.

Notes on contributors

Erin Abu-Rish Blakeney

Erin Abu-Rish Blakeney, PhD, MA, RN is a Research Assistant Professor at the University of Washington (UW) School of Nursing. She is also a co-lead of the Institute of Translational Health Sciences Team Science Core and affiliate faculty with the UW Center for Inteprofessional Education, Research and Practice. 

Frances Chu

Frances Chu has a Masters in Library and Information Science and works as an Adjunct Medical Librarian at Gonzaga University. She is also a PhD candidate at the University of Washington School of Nursing.

Andrew A. White

Andrew White, MD is a Professor of Medicine at the University of Washington.  He is board certified in Internal Medicine and Clinical Informatics.

G. Randy Smith

Randy Smith is an assistant professor of hospital medicine at Northwestern University Feinberg School of Medicine, and a unit medical director at Northwestern Memorial Hospital.

Kyla Woodward

Kyla Woodward is a PhD candidate at the University of Washington School of Nursing

Danielle C. Lavallee

Danielle Lavallee, PharmD, PhD is the Scientific Director for theBritish Columbia Academic Health Science Network and Affiliate Associate Professor in the Departments Health Services at theUniversity of Washington.

Rachel Marie E. Salas

Rachel Salas, MD, MEd, FAAN, FANA is a board-certified Sleep Neurologist at Johns Hopkins Medicine, Department of Neurology.

Mayumi A. Willgerodt

Mayumi Willgerodt, PhD, MPH, RN, FAAN, FNASN is Associate Professor and Vice-Chair for of Education in the Department of Child, Family, and Population Health Nursing at the University of Washington and affiliate core faculty in the Center for Health Sciences Interprofessional Education Research and Practice (CHSIE) and Leadership and Education in Adolescent Health Training Program (LEAH).

Deborah Dang

Deborah Dang recently retired from the Johns Hopkins Hospital and Health System as Director of Nursing. John Dent, MD, MS is a Professor Emeritus of Medicine at the University of Virginia Health System and a Clinical Professor of Nursing at the University of Virginia School of Nursing.

Elizabeth Ibby Tanner

Elizabeth K. Tanner, Ph.D, R.N., is a registered nurse and Professor Emeritus at Johns Hopkins School of Nursing with a joint appointment in the School of Medicine, Division of Geriatric Medicine and Gerontology. She was core faculty in the Center on Aging and Health;  principal faculty in the Center for Innovative Care in Aging and inaugural Director of the Collaborative for Interprofessional Education and Practice.

Nicole Summerside

Nicole Summerside, MHA is an affiliate instructor in the department of Biobehavorial Nursing and Health Informatics at the University of Washington School of Nursing and the Manager of Program Operations for the UW Center for Health Sciences Interprofessional Education, Research and Practice.

Brenda K. Zierler

Brenda Zierler PhD, RN, FAAN is a professor in the Department of Biobehavioral Nursing and Health Informatics at the University of Washington School of Nursing and is adjunct professor in the Department of Health Services at the University of Washington School of Public Health, and in the Departments of Surgery (Vascular Division) and Department of Biomedical Informatics and Medical Education at the University of Washington School of Medicine. She is Co-Lead of the Team Science Core for the UW Institute for Translational Health Sciences and Director of Research and Training for the Center for Health Sciences Interprofessional Education, Research and Practice.

Kevin D. O’Brien

Kevin O’Brien, MD is a Professor of Medicine at the University of Washington and Service Director for Inpatient Cardiology at the University of Washington Medical Center. 

Bryan J. Weiner

Bryan Weiner PhD, is Professor, Department of Global Health and Department of Health Systems and Population Health, at the University of Washington.