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Improving clinical reasoning and communication during handover: An intervention study of the BRIEF-C tool
  1. Ghazwan Altabbaa1,
  2. Tanya Nathalie Beran2,
  3. Marcia Clark3,
  4. Elizabeth Oddone Paolucci2,3
  1. 1Department of Medicine, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada
  2. 2Community Health Sciences, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada
  3. 3Department of Surgery, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada
  1. Correspondence to Dr Ghazwan Altabbaa; galtabba{at}


Background Existing handover communication tools often lack a clear theoretical foundation, have limited psychometric evidence, and overlook effective communication strategies for enhancing diagnostic reasoning. This oversight becomes critical as communication breakdowns during handovers have been implicated in poor patient care. To address these issues, we developed a structured communication tool: Background, Responsible diagnosis, Included differential diagnosis, Excluded differential diagnosis, Follow-up, and Communication (BRIEF-C). It is informed by cognitive bias theory, shows evidence of reliability and validity of its scores, and includes strategies for actively sending and receiving information in medical handovers.

Design A pre–test post-test intervention study.

Setting Inpatient internal medicine and orthopaedic surgery units at one tertiary care hospital.

Intervention The BRIEF-C tool was presented to internal medicine and orthopaedic surgery faculty and residents who participated in an in-person educational session, followed by a 2-week period where they practised using it with feedback.

Measurements Clinical handovers were audiorecorded over 1 week for the pre- and again for the post-periods, then transcribed for analysis. Two faculty raters from internal medicine and orthopaedic surgery scored the transcripts of handovers using the BRIEF-C framework. The two raters were blinded to the time periods.

Results A principal component analysis identified two subscales on the BRIEF-C: diagnostic clinical reasoning and communication, with high interitem consistency (Cronbach’s alpha of 0.82 and 0.99, respectively). One sample t-test indicated significant improvement in diagnostic clinical reasoning (pre-test: M=0.97, SD=0.50; post-test: M=1.31, SD=0.64; t(64)=4.26, p<0.05, medium to large Cohen’s d=0.63) and communication (pre-test: M=0.02, SD=0.16; post-test: M=0.48, SD=0.83); t(64)=4.52, p<0.05, large Cohen’s d=0.83).

Conclusion This study demonstrates evidence supporting the reliability and validity of scores on the BRIEF-C as good indicators of diagnostic clinical reasoning and communication shared during handovers.

  • Communication
  • Patient safety
  • Quality improvement
  • Transitions in care

Data availability statement

Data are available on reasonable request.

This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See:

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  • Miscommunication is known to occur during handovers but improves when a tool is used to structure the information shared. Most structured communication tools during handover are atheoretical, omit communication strategies, have limited evidence of validity and reliability, and have been tested only in simulated environments.


  • The BRIEF-C (Background, Responsible diagnosis, Included differential diagnosis, Excluded differential diagnosis, Follow-up, Communication) tool was developed based on cognitive bias theory, addresses communication strategies, has strong emerging psychometric evidence, and improves communication during handover in a clinical environment, potentially contributing to improved patient care and safety.


  • Our study can guide further research into optimising handover processes, promoting patient safety, and improving healthcare team collaboration. In practice, healthcare professionals can use the BRIEF-C to enhance communication during handovers, potentially reducing errors and improving patient outcomes. Policy-wise, this study emphasises the importance of standardised handover tools and practices, which could lead to implementing guidelines and protocols that prioritise effective communication in healthcare settings.


Transition periods along the continuum of clinical care are recognised for their inherent vulnerability and high risk to patient outcomes.1–3 Clinical handover (also known as handover or handoffs) involves transferring ‘professional responsibility and accountability for some or all aspects of care for a patient, or group of patients, to another person or professional group on a temporary or permanent basis’.4 One estimate of handovers in Australian hospitals was reported at over 7 million annually.5 Despite their frequency and necessity, the quality of clinical handovers remains a concern. For instance, in a survey of junior doctors in the UK, 32% reported that the handover process was poor, 50% adequate, 17% good, and only 1% stated that it was excellent, with only 6% receiving written handovers.6 More recently, a survey of resident trainees in the USA indicated that 15% of adverse events, errors, or near misses could be attributed to poor handoffs (compared with 19% for long work hours, 20% for limited supervision, 5% for caring for other patients, 12% for caring for their own patients, and 57% for other reasons).7

Poor handovers have been linked to several detrimental outcomes, including care discontinuity, adverse events, and legal malpractice claims.8 Intriguingly, malpractice insurance data in the USA identified clinical handover as a prominent cause of claims, especially among trainees (accounting for 20% of cases).9 Given these concerns, this study seeks to enhance care transition during handovers by introducing and training the utilisation of a theoretically grounded tool named the Background, Responsible diagnosis, Included differential diagnosis, Excluded differential diagnosis, Follow-up, and Communication (BRIEF-C).

Handover tools

Several tools, such as the ISBAR (Introduction, Situation, Background, Assessment, Recommendation) and I-PASS (Illness severity, Patient information, Action list, Situational awareness and contingency plans, and Synthesis) exist to aid in organising communication during handovers.10 11 However, evidence of reliability and validity is limited, and many studies were conducted in simulated, not clinical, settings.12 13 Moreover, the development of these tools was not informed by theory. Our project is unique in that the handover tool we developed includes a structured framework intended to mitigate cognitive biases that can contribute to communication errors, an often overlooked aspect in the domain of handover communication.

Cognitive bias theory

Healthcare professionals often use heuristics or ‘shortcuts’ to formulate initial diagnoses.14 Although this approach is practical and adequate in most situations, there can be instances of failed heuristics. The failed heuristics are often seen and labelled as cognitive biases,14 which are consistent deviations in judgement due to information processing limits, decision-making shortcuts and emotional, moral or social influences.15 16 The process of diagnostic clinical reasoning and reducing diagnostic cognitive errors has been identified as one of the blind spots in patient safety and healthcare.17 In fact, cognitive errors have been demonstrated to contribute to up to 74% of system-related factors and up to 65% of diagnostic errors in Internal Medicine.18 Furthermore, Emergency Medicine is considered to be an ill-structured and chaotic environment at high risk of producing cognitive errors.19 In such conditions, the combination of poor communication strategies combined with a failed heuristic that might be carried on during the transition of care will create the perfect storm for adverse patient outcomes.

The development of the BRIEF-C was based on several premises. First, clinical handover is a high-risk, high-frequency procedure that occurs in healthcare where the majority of communication failures could be averted by using a handoff tool.20–22 Second, improving the diagnostic process has emerged as a crucial benchmark for patient safety.17 Third, the heuristics and biases research suggests that quality decision-making might be influenced by judgement blind spots.14 23 Fourth, the approach to handovers was reframed as an opportunity for enhancing diagnostic care through system and process improvements. Such interventions should address the two dimensions of the linguistic dialogue during handovers: the informational structure embedded within an active collaborative format.24 Fifth, translation of communication strategies from high-reliability organisations. Here, tailoring some of the learnt lessons (e.g., face-to-face, interactive questioning, readback, limiting interruptions, delaying the transfer of responsibility during critical actions, overhearing others’ updates)25 will support grounding in communication to establish that what has been said is understood26 and interpredictability of actions and behaviours during the joint activity of handover exchange.27

Enhancing effective transitions across the patient care continuum is expected to result in more effective and timely care, foster improved communication among diverse healthcare professionals and patients, and improve planning for discharge and follow-up care in the community. There is a need for improved tools and standardised processes to narrow, and ultimately eliminate, the gap between transmitting and receiving patient information, in addition to considering the diagnostic safety at times of handover and transition to care.28 For example, surgical residents in Canada have reported their involvement in preventable patient injuries, underlining the importance of refining communication29 while integrating the diagnostic reasoning process for reducing patient harm30 and addressing our psychological tendencies to accept diagnostic suggestions.31 32

In summary, this study examines psychometric evidence of the BRIEF-C tool that was developed based on cognitive bias theory to see if its use improves communication during handovers. The study includes residents and physicians from two diverse clinical disciplines: Internal Medicine and Orthopaedic Surgery. While diverse in context, healthcare providers in both disciplines have to communicate and make judgements under parallel conditions of clinical uncertainty.18 33 34 By focusing on Internal Medicine and Orthopaedic Surgery specialties, the study captures scenarios with potential high-stakes outcomes. This choice enhances the practical applicability of the study’s findings, as effective communication in these settings is crucial to avoid errors, ensure proper diagnosis and treatment, and ultimately enhance patient well-being.


Theoretical framework for tool development

To address the need for effective communication frameworks that mitigate the potential for failed heuristics at times of transition of care, a member of the research team member (GA) initiated the tool development process by designing the core clinical data items. Feedback and redesign refinement were then completed in consultation with an expert in high-reliability organisations expert (RB), who provided insights drawn from strategies in high-risk industries like aviation. The result is a clinical handover tool—the BRIEF-C (see table 1). While the research identifies a plethora of biases,15 35 the design of our handover tool focuses on three biases that seem most prevalent in our clinical experience.36 The first bias, order effect, leads to better recall of information shared at the beginning and end of a conversation, often forgetting details in the middle. The BRIEF-C addresses this bias by systematically organising clinical data flow. Each item focuses on crucial clinical data required for effective information exchange.

Table 1

BRIEF-C items

Confirmation bias, the second bias, involves seeking evidence to support a hypothesis, neglecting contradictory evidence. Our BRIEF-C tool incorporates two items: one for including and another for excluding differential diagnoses during handover. These items spotlight how discussions should include all considered possibilities and the presentation of evidence to rule-out tentative hypotheses.

The third bias, momentum bias, occurs when a diagnostic label becomes entrenched through intermediaries when it might have just started as a possibility. This bias is represented in the last two items in table 1 regarding communication where receivers of the information summarise their understanding (read back) and senders actively listen (hear back). These two actions may lead to further discussion to resolve misunderstandings, challenge assumptions and reduce diagnostic errors. Notably, BRIEF-C triggers practitioners involved in the handover to share their understanding, or mental models, identified as crucial in communication24 and often missed in other handover tools.

Examination of validity

Evidence of content validity was obtained by a literature review on common influences on decision-making in healthcare15; experience and observations from clinical simulation environments36; and three specific cognitive biases. To obtain evidence of construct validity, a principal component analysis (PCA) was conducted using varimax rotation to obtain the most interpretable factors. Prior to conducting the PCA, the suitability of the data was evaluated using Kaiser-Meyer-Olkin and Bartlett’s test of sphericity scores. For each component (or factor), items were considered based on eigenvalues greater than or equal to 1.0, while the highest factor loadings were used to determine the number and meaning of the components. Initially, the measurement included an eighth item related to the patient’s status (e.g., current vital signs). However, including this item created several split loadings, uninterpretable factors, and less explained variance than with this item excluded. Thus, this item was excluded from further analyses and a subsequent PCA iteration. A second PCA was conducted on the seven items from the BRIEF-C tool, shown in table 2. The KMO indicator was 0.74 and Bartlett’s test of sphericity was p<0.05, both suggesting an adequate degree of correlation among the tool’s items—which is an indication that the data meet the statistical assumptions for running a PCA. Across three iterations (i.e., number of attempts to obtain a solution with one or more factors), a total of two factors explained 71.72% of the variance (a large majority is considered desirable), as indicated in the table with respective factor (or correlation) loadings. This analysis revealed two factors, with the first five BRIEF-C items measuring diagnostic clinical reasoning and the last two items identifying communication. Thus, two subscales were obtained. In other words, the BRIEF-C appears to measure two types of information shared in the handover. The first is diagnostic clinical reasoning measured by the first five BRIEF-C items shown in table 2. The second type of handover information is communication, which is measured by the two BRIEF-C items of communication read and hear back.

Table 2

Factor structure of the BRIEF-C (N=144)

As shown in the second last row of the table, the consistency of the five items measuring diagnostic clinical reasoning was high (0.82) as was the consistency of the two items measuring communication (0.99). To demonstrate consistency between raters, inter-rater reliability was calculated with Cohen’s kappa. As seen in the last row, adequate to high consistency was found.


We conducted an intervention pre–post-test design involving two assessment times (pre-test and post-test) within the Departments of Surgery and Internal Medicine of a large urban academic hospital in Midwestern Canada. Observations of internists and surgeons took place while they conducted handovers for current hospital patients from September 2017 to March 2018. A total of seven groups participated in the pre-test and seven in the post-test. Those groups consisted of rounding residents on the clinical services of inpatient Internal Medicine and inpatient Orthopaedic Surgery. Residents rotate monthly, and standard operation for handover consists of an in-person meeting between the night-time on-call team and the daytime incoming team. The Orthopaedic Surgery night-time on-call team is usually composed of one faculty and 1 to 2 junior and senior residents who provide a handover at 07:00 hours to 1 daytime faculty and 3 to 4 junior and senior residents. The inpatient Internal Medicine night-time on-call team is usually composed of 2 junior and one senior resident who provide a handover at 08:00 hours to 2 daytime faculty and 6 to 8 junior residents and medical students. All residents attending the handovers were the same between the pre-intervention and post-intervention weeks for each of the different monthly clinical rotations and participated in providing or receiving the handovers on different days depending on their call schedule. Each group discussed 1 to 10 clinical handovers of new admissions (Mean=3.28; SD=2.20) summing up a total of 176 patients discussed during 144 handover meetings. An a priori power calculation using G*Power V. with a conventional small effect size of 0.25, alpha of 0.05 and power of 0.85, indicates a required sample size of 146 handovers. This effect size was selected as it is similar to results obtained by Dory et al.38 It is noted that only 144 handovers were included in this study due to technical problems.


Handovers that took place during the first week of clinical rotations for Internal Medicine and Orthopaedic Surgery at a tertiary care hospital were audio recorded. They occurred during the daily in-person handovers at time of transition of care between the night-time on-call team and the daytime incoming team. The recording device was set up on the side of the room to make it less intrusive, but the research assistant was also present. After a week of pre-test data collection, an educational intervention on the use of the BRIEF-C was started. Both faculty and residents in Internal Medicine and Oorthopaedic Surgery were invited to, individually or in small groups, complete a 30-minute face-to-face PowerPoint tutorial at different times depending on availability over a 1-week period. The training presentation was developed and delivered by a research team member (GA), and it included an explanation of the BRIEF-C items along with applied examples of patient handoffs. Additional time was provided for practice applications on newly admitted patients with the on-call team. Beginning the following week, residents and faculty were encouraged to use the BRIEF-C tool, and feedback was provided by GA or rounding faculty. As a reminder, laminated and coloured cards were taped on computer screens in the meeting rooms, showing the components of the BRIEF-C tool.

In the final and fourth week of each of the monthly clinical rotations, post-test data collection was completed with audio recordings of handovers. Handovers in the fourth week were conducted by the same group of residents and medical students who were rounding in the first week of pre-data collection, and they all participated in providing or receiving handovers on different days depending on their call schedule (i.e, give a handover if part of the night-time on-call team, or receive a handover if part of the daytime patient care team alternatively on different days).

All transcripts of the audio recordings were evaluated independently by two BRIEF-C trained raters, who were blinded to the residency group (i.e., Internal Medicine or Orthopaedic Surgery), as well as time of assessment (i.e., pre-test, post-test). One rater was an internist (GA) who also developed the BRIEF-C tool and the educational module. The second rater was an orthopaedic surgeon (MC) who was trained in the use of and scoring with the BRIEF-C tool. Neither rater was aware of whether the audio recordings occurred during pre-test or post-test. Both raters participated in a practice scoring session with the tool until they achieved 90% consensus on sample audio recordings.

Consent and patient data were managed as follows. First, the study was approved by the University of Calgary Conjoint Health Research Ethics Board (REB16-0499). Second, a research assistant (rather than a preceptor) obtained informed consent from the medical and surgical staff. Third, all participant learners were informed that their participation would not affect their rotation assessment and that they could withdraw without penalty. Fourth, the audio recordings and transcriptions of all handovers were assigned a number rather than by name, and patient data were de-identified. Fifth, the recording device was set up on the side of the room to make it less intrusive, and the research assistant monitored the device to ensure its proper use and safe keeping. Sixth, all transcripts of the audio recordings were evaluated independently by two BRIEF-C trained raters, who were blinded to the residency group (i.e., Internal Medicine or Orthopaedic Surgery), as well as the time of assessment (i.e., pre-test and post-test). Finally, the research assistant signed the health authority’s confidentiality form, which is a standard procedure for all researchers.

Intervention analysis

Descriptive statistics in the form of mean, SD, and frequency counts were used to describe the data. To determine if the BRIEF-C scores changed after the educational intervention, one-sample t-tests were conducted. Specifically, the mean of the pre-test scores served as the designated value against which to compare the post-test mean score. This test was selected because the pre-samples and post-samples were not matched.39 This test was also used to examine differences in the time required to complete handovers before and after the intervention. Furthermore, to compare differences in handover scores between surgical and internal medicine residents, an independent samples t-test was conducted. A p-value of 0.05 served as the criterion to judge statistical significance and effect sizes were reported where results were significant to provide a comprehensive understanding of the outcomes.


By using the demographic data available for the sample, we examined if the duration of handovers differed between internal medicine and surgical residents. Residents in Internal Medicine took longer (in seconds) to complete handovers (M=270.82 s, SD=253.19) than did residents in Surgery (M=208.47 s, SD=208.13), t (140)=2.06, p<0.05, Cohen’s d=0.35 (small-medium). There was no difference, however, in the duration of clinical handovers at pre-test (M=223.86 s, SD=149.47) compared with post-test (M=271.78 s, SD=207.32), t(64)=1.86, p>0.05.

Pre-test versus post-test

The scores on the BRIEF-C items are shown in table 3. An increase was observed in the number of residents who completed various types of information sharing after the educational intervention. In particular, no one was rated as completing read-back and hear-back communication strategies in the pre-test, whereas almost a quarter of participants did in post-test.

Table 3

Frequency and (percentage) of BRIEF-C handover scores

The mean of each subscale was then calculated by summing the respective items and dividing by the number of items within that subscale (five diagnostic clinical reasoning items and two communication items). These reasoning and communication variable scores were then compared between pre-test and post-test. Results showed a significant improvement from pre-measures of the diagnostic clinical reasoning items (M=0.97, SD=0.50) to post-test (M=1.31, SD=0.64), t(64)=4.26, p<0.05, Cohen’s d=0.63 (medium-large). The pre-communication scores (M=0.02, SD=0.16) also significantly improved at post-test (M=0.48, SD=0.83), t(64)=4.52, p<0.05, Cohen’s d=0.83 (large).


The results of the study indicate that there was a notable (medium to large size) improvement in the quality of communication that occurred during handovers, following the adoption of structured communication using the BRIEF-C. In addition, evidence of several types of validity and reliability was obtained.

Communication improvement may have occurred for several reasons. The structured format of the BRIEF-C outlines all the areas of pertinent patient clinical information and actions on the part of healthcare professionals. By ensuring that all areas are addressed, there is less possibility of omitting important information. Second, engaging in a standardised approach ensures critical information is consistently communicated to minimise variations in practices and improve overall continuity of care. Third, the inclusion of different opportunities for open dialogue safeguards against three common human tendencies for bias (order, confirmation, momentum), which supports the mandate for diagnostic safety and adaptive decision-making. Fourth, the BRIEF-C’s applicability across different specialties, as evident from the diverse backgrounds of experts involved, may promote interdisciplinary team collaboration and facilitate smoother transitions when patients are handed over between different healthcare teams. Our results, therefore, seem to be relevant to a variety of handover conversations. It is noted, however, that the rate of completion at post-test remained at under 50% for most of the BRIEF-C items. Thus, there is room for further improvement that can be promoted through ongoing education, practice, monitoring, and feedback.

A particular strength of this study was the use of this tool within a clinical setting, which represents authentic applications in patient handovers. There was no standardisation or other control of patient data. The advantage of limited standardisation is that the BRIEF-C was applied to heterogeneous presentations of clinical cases, akin to the diverse scenarios encountered in typical hospital environments.

Several factors could explain the observation that residents specialising in Internal Medicine took more time for handovers compared with their Surgical counterparts. One factor may involve the complexity of cases and information depth; Internal Medicine cases often involve complex medical histories and comorbidities. This complexity may have required more detailed communication during handovers, leading to extended discussions. Another factor may be that Internal Medicine physicians develop comprehensive treatment plans that include interdisciplinary considerations, leading to more extensive handover discussions. Moreover, we cannot disregard the possibility of communication norms, where different specialties might have varying norms for the level of detail and thoroughness expected during handovers, influencing the duration of these discussions. Interestingly, there was no difference in the duration of clinical handovers when comparing pre-test and post-test phases, suggesting that the tool does not demand additional time resources. Instead of burdening healthcare providers at times of transition of care, it seems that the tool facilitates the provision of effective communication and the process of diagnostic reasoning.

Various forms of evidence of validity and reliability converge for the BRIEF-C’s scores as an indicator of quality communication during patient handovers. In terms of content validity, diverse background experts (high-reliability organisation, Medicine, Surgery) participated in the tool evaluation. Their collective knowledge and experience enable the BRIEF-C items to assess communication during handover accurately. This diversity also broadened the scope of content validity. The BRIEF-C tool comprehensively addresses healthcare information needs across various specialties while integrating safeguards to promote effective communication and mitigate cognitive biases. Specifically, the explicit listing of the ruled-in and ruled-out diagnoses offers an opportunity to mitigate confirmation bias. At the same time, the read/hear-back communication component invites open inquiry and discussion.24 Such discussion extends beyond traditional summary statements with a focus on pinning down decision-making based on intuition, logic or both while bringing clarity to the interaction of reasoning strategies (e.g., deductive vs inductive).40 Furthermore, this read/hear-back phase is situated at a critical time during the handover dialogue where the attention of participants is heightened (order effect bias), offering a barrier to our tendency to accept offered conclusions (i.e., momentum bias) rather than refuting such confirmations.31

Factorial validity was confirmed through an analysis of the scale’s underlying factor structure, encompassing diagnostic clinical reasoning and communication factors. Both of these factors represent quality communication about a patient during handover.41 Regarding construct validity, measurement experts explain that a change in scores on the construct being measured after an intervention provides evidence that the defined factors (e.g., diagnostic clinical reasoning and communication) were represented in the scores.42 43 In the present study, the intervention’s impact on scores (i.e., BRIEF-C scores improved after participants learnt about how all the items represent quality information that needs to be shared during handover) provided evidence of construct validity.

Evidence of reliability was obtained through good inter-rater reliability between two raters from differing specialisations (Internal Medicine and Surgery). This result underscores the robust nature of the BRIEF-C tool in producing consistent ratings across healthcare professionals with distinct training and clinical backgrounds. Moreover, the raters in our study are clinicians from within the evaluated disciplines, who are experts and most experienced on the specific performance objectives that were assessed in the measure, and, thus, best suited to evaluate them. Also, high inter-item reliability for each factor indicates that each factor’s items are similarly rated. This finding suggests that all the items are measuring the construct that each factor (diagnostic reasoning and communication) represents. The consistency of ratings between raters was in the acceptable to high range, suggesting that perhaps more training on using the BRIEF-C is warranted.

The results of this study satisfy the first step in the validation pathway, offering robust evidence of validity and reliability. Future studies should examine other forms of accuracy and consistency. For example, consequential validity can be explored by measuring cognitive biases that may be reduced due to education and administration of the BRIEF-C. Also, pre-test and post-test evaluations can measure improved patient care and outcomes.

Regarding strengths and limitations, since data were collected in a clinical environment involving residents and healthcare professionals, results may be more generalisable than if the data had been collected in a simulation environment. Indeed, if the emotions, thoughts and real system pressures/expectations that drive us to perform can only be approximated in simulation—according to its definition,44 45 then the ability to complete a study in an actual clinical environment is certainly noteworthy. However, it is important to note that the specific clinical site was not chosen randomly. It is, thus, advisable to extend the application of the BRIEF-C to various clinical settings to gather broader evidence of its generalisability. The study occurred in a busy clinical environment where healthcare providers were actively engaged in clinical duties so it was not feasible to randomly select participants or raters. Also, we were able to access a large number of handovers in a busy clinical environment, with only two handovers remaining inaccessible. The absence of a comparison group (a group that did not have the education intervention and was administered the BRIEF-C twice), means that alternative explanations for the observed improvement in the BRIEF-C scores cannot be completely ruled out. For example, it is possible that improvement was due to learning through experience gained during the month-long rotation rather than due solely to the use of the BRIEF-C. It is also possible that handover communication improved as a result of awareness of participating in a study and being audio recorded, but this explanation does not account for lower scores at pre-test than at post-test. Future studies should include data collection at 6 months to evaluate follow-up changes in handover practices and confirmation of continued use of the BRIEF-C tool. Another primary source of bias in the present study is that the education facilitator, a member of the research team, developed the education intervention and completed the BRIEF-C items at pre-test and post-test. This bias might have resulted in lower scores during the former, and higher scores during the latter administration. On the other hand, we implemented blinding strategies to ensure the education facilitator was unaware of the participant groups to help minimise conscious or subconscious influence when scoring the transcripts. Nevertheless, it is possible that the content of the clinical presentation suggested whether it was a surgical or medical patient. On the other hand, the two raters were following a standardised and objective framework with a focus on the presence or absence of clinical elements applicable in both contexts, in addition to the fact that it was not a comparison between medicine and surgery. Additionally, we applied two different randomisation orders of the pretest and post-test transcripts for both raters to reduce the likelihood of systematic bias and ensure an even distribution of potential influence across both data collection points. While these methods attempted to reduce bias, we recommend that future evaluation of this handover tool include reviewers outside of the research team.

In conclusion, our study’s results contribute to the growing evidence on effective handover practices. Our study encourages a culture of continuous improvement in handover practices. Regular use of the BRIEF-C and ongoing assessment of communication quality can drive awareness, accountability and refinement of handovers. Future direction should focus on the integration of such tools within electronic health records systems to facilitate and enhance the handover processes. It is also recommended that the BRIEF-C be studied across additional clinical roles and settings.

Data availability statement

Data are available on reasonable request.

Ethics statements

Patient consent for publication

Ethics approval

This study involves human participants and was approved by the University of Calgary Conjoint Health Research Ethics Board. Ethics ID was: REB16-0499. Participants gave informed consent to participate in the study before taking part.


The authors would like to thank Dr Robert Barrett for the consultation and feedback on the developed handover tool. He is a social scientist with a Ph.D. in conflict analysis and strategic studies, and a specialist in conflict, culture and team dynamics. He is an airline captain and an independent consultant who provided consultation for the creation of the BRIEFC from the context of best standards of communication and bias reduction in the aviation industry. He did not participate in study design, data collection, or analysis.



  • Contributors GA and EO-P designed the study. GA created the BRIEF-C tool in consultation with a high-reliability discipline expert (RB). EO-P collected the data, organised the transcription of audio recordings, and randomised the lists of coded transcripts of handovers. GA and MC collaborated in communication with faculty and residents on different clinical rotations. GA and MC completed the scoring of transcripts of the audio recording. TNB analysed the results and wrote the first draft of the manuscript. All authors approved the final manuscript. GA served as the guarantor for the overall content of this manuscript and accepts full responsibility for the work and/or the conduct of the study, had access to the data, and controlled the decision to publish.

  • Funding The Departments of Medicine and Surgery (DOM-DOS) Research Development Fund, Alberta Health Services. Office of Health and Medical Education Scholarship (OHMES) Research and Innovation Fund, Cumming School of Medicine, University of Calgary.

  • Competing interests None declared.

  • Patient and public involvement Patients and/or the public were not involved in the design, or conduct, or reporting, or dissemination plans of this research.

  • Provenance and peer review Not commissioned; externally peer reviewed.