Prehospital to emergency department handoff: can team-based reporting improve markers of clinical efficiency in an adult emergency department?

Abstract

Interdisciplinary communication is a critical component of quality patient care. On emergency medical services (EMS) arrival to the emergency department (ED), the pre-existing opportunity-based reporting (OBR) handoff paradigm may result in disjointed, repetitive and incomplete transition of patient care to the ED, adversely impacting patient care. This quality improvement study was conducted at a tertiary care, academic university hospital ED and evaluated the impact of team-based reporting (TBR) during EMS patient handoff in the ED on several markers of clinical efficiency (CE). The standard OBR handoff protocol was compared with the TBR protocol, which brings the patient’s ED care team to bedside shortly after patient arrival, allowing EMS to give a single, synchronous handoff. The use of TBR during prehospital-ED handoffs was associated with statistically and clinically significant improvement across multiple CE quality indicators. A team-based handoff strategy is a low-cost policy intervention that provides meaningful improvements related to CE and quality care.

WHAT IS ALREADY KNOWN ON THIS TOPIC

• The existing literature on interdisciplinary rounds is heavily centred around inpatient settings and largely focuses on inpatient quality metrics, such as inpatient length of stay and rate of adverse events. Conversely, the use of interdisciplinary communication models within the emergency department has not been well studied.

WHAT THIS STUDY ADDS

• This prospective study demonstrates strong evidence for implementing a team-based reporting model between emergency medical services and emergency department staff to improve various markers of clinical efficiency, such as time-to-labs ordered, time-to-labs collected, time-to-labs resulted and time-to-patient disposition. It also highlights the degree to which communication strategies can help or hinder delivery of clinical care.

HOW THIS STUDY MIGHT AFFECT RESEARCH, PRACTICE OR POLICY

• This study represents a low-cost policy intervention that has a strong potential to meaningfully improve multiple markers of clinical efficiency related to patient safety and quality.

Introduction

The fast-paced, dynamic nature of the emergency department (ED) requires accurate communication of pertinent patient information and careful coordination of all team members to deliver high-quality care, maintain patient satisfaction and prevent inappropriate treatments, adverse events and increased costs. In particular, the initial handoff from prehospital emergency medical services (EMS) staff to hospital ED staff is particularly susceptible to information loss and could benefit from evidence-based communication strategies.

In September 2017, the Joint Commission published recommendations for improving handoff communication, which included sharing and receiving information in a team-based manner, using closed-loop communication and creating a standardised tool for handoffs.¹ Previously described standardised handoff tools for EMS-ED handoff include the ISBAR (Identification, Situation, Background, Assessment, Recommendation) and MIST (Mechanism, Injuries, Signs/Symptoms, Treatment) templates, which effectively communicate prehospital information to ED staff.^{2 3} Furthermore, staff surveys found that standardised handoff tools increased clarification of prehospital care and the events surrounding patient presentations.^{2 3}

Despite the proven benefits of a systematic handoff paradigm, the implementation of standardised communication strategies across health systems is often inconsistent.³ Without standardised communication protocols, it is common for EMS to give reports to each member of the care team separately. A study by Dawson et al found that 91% of paramedics gave reports at least twice, negatively impacting EMS’s ability to provide a clear and consistent history of present illness to the ED staff; this was shown to disproportionately affect non-trauma patients.^{4 5}

Fragmented, disjointed or duplicated information provided during EMS-ED handoffs can lead to omission of critical information and an incomplete understanding of the patient’s disease process, potentially delaying or adversely impacting care.⁴ A study analysing high-efficiency practices of resident physicians in an academic ED found seven behaviours associated with increased efficiency, one of which included taking initial patient history with the nurse present.⁶ Termed team-based reporting (TBR), this method allows all healthcare members and the patient to be present when important information is being conveyed and medical management decisions are being made. In this model, EMS gives a synchronous report to the entire medical team—physician, nurses, advanced practice providers and support staff. This allows all pertinent information to be communicated contemporaneously, along with the discussion of initial orders (eg, labs, imaging, etc), procedures and protocols, the development of a shared mental framework for patient care and the optimisation of staff communication and workflow.⁶ In fact, prior implementation of TBR at an academic ED demonstrated improvements in departmental efficiency and resident education, as measured by door-to-physician time, average patient length of stay and left-without-being-seen rate.⁷

To measure and track clinical efficiency (CE) in an ED, surrogate markers that are clinically relevant and consistently measurable are frequently used as quality indicators. Quality indicators are standardised, evidence-based measures of healthcare quality that are often pulled from existing hospital administrative data to measure and track clinical performance and outcomes and to establish benchmarks.⁸ For example, by using time-to-point of care testing (POCT) as a surrogate marker for time-to-first treatment, one can trace trends between treatment efficiency and patient outcomes. One study by Baumer-Mouradian et al modelled how decreased time-to-laboratory results for patients with diabetic ketoacidosis correlated with faster medical decision-making and decreased ED length of stay (206 min vs 186 min).⁹ In sepsis, decreased laboratory result times through POCT were associated with improved sepsis bundle compliance, reduced mortality, higher employee engagement and cost savings.¹⁰ Although these examples pertain to specific diagnoses, they demonstrate how time-to-first labs is an appropriate initial indicator for patient care and outcomes.

In this study, we implemented TBR and closed-loop communication during EMS-ED handoffs in a large, urban, academic ED. We then used several surrogate markers to evaluate changes in CE. Based on prior studies examining markers of CE in the ED, we selected a 15% reduction in key quality indicators as an a priori threshold demonstrating improved CE.^{11 12}

Methods

Study setting

The study was performed at an urban, tertiary care, academic university hospital adult ED. The native, pre-existing EMS-ED handoff process was an asynchronous opportunity-based reporting (OBR) model (figure 1A), where nurses take EMS report as they are available. EMS is not required to provide handoff to providers; therefore, providers may not receive handoff prior to EMS departure. Providers seeking additional prehospital information are compelled to discuss with the nurse regarding prehospital events. Similar to most American academic EDs, non-critically ill patients are usually first evaluated by resident physicians prior to subsequent attending evaluation.

Figure 1. Flow chart representation of asynchronous opportunity-based reporting (OBR) handoff (A, control) versus synchronous team-based reporting (TBR) handoff (B, intervention) which results in a shared framework for patient care.

Study design

We performed a prospective quality improvement project (QIP) using a Plan-Do-Study-Act (PDSA) model from 1 August 2022 to 1 June 2023. The study includes six cycles, each consisting of 2 weeks of control followed by 2 weeks of intervention. The control group consisted of patients who were transferred using the pre-existing OBR paradigm (figure 1A). In contrast, the intervention group used synchronous TBR (figure 1B) for patient handoff, where EMS gives report to the entire ED care team contemporaneously, allowing development of a shared mental model. In this TBR model, once the patient is assigned a room, the primary nurse calls the medical team alerting them of the patient’s arrival. The care team arrives at the bedside within 5 min before EMS begins the report. During this handoff process, the resident physician and primary nurse receive report from EMS together, the team discusses the initial care plan and the ancillary staff performs tasks such as placing the patient on the monitor, inserting intravenous catheters, drawing labs and obtaining ECGs.

The inclusion criteria included patients who arrived via EMS to the ED between 07:00 and 19:00 hours, were immediately roomed in a treatment area designated for medically complex, non-traumatically injured patients and subsequently had a complete blood count (CBC) ordered, drawn and resulted. CBC was picked as the serum lab of choice, as it is the most routinely ordered lab in the ED. For the first three cycles, we included only patients seen by a third year (ie, postgraduate year 3 (PGY-3)) resident physician. For the second three cycles, we expanded to include patients seen by a second year (ie, PGY-2) resident physician. The resident and nursing composition varied for each cycle depending on the rotation schedule.

Exclusion criteria included patients seen by non-PGY-3 or non-PGY-2 providers (eg, PGY-1 residents, off-service residents or advanced practice providers), patients who came in as an ‘alert’ (eg, trauma alert, stroke alert, ST-elevation myocardial infarction alert, sepsis alert) and patients initially seen and evaluated at our affiliated free-standing EDs and subsequently transferred to the main ED via EMS for a higher echelon of care.

To minimise Hawthorne effect, the control cycles were randomly initiated throughout the year, so the ED staff had no pre-emptive warning when they were being observed. With each successive intervention cycle, implemented changes included a combination of: (1) varying the resident and nursing cohort composition for each cycle, (2) expanding the number and types of residents and nurses for each cycle, (3) identifying performance outliers and providing targeted feedback and (4) recognising and correcting poor TBR adoption.

Based on power calculations conducted during study design, we needed 55 patients in each cohort to demonstrate statistical significance. Therefore, for the study population, the control cohort consisted of a convenience sample of 248 randomly selected patients who met inclusion criteria in the control group. The intervention group consisted of all patients who met inclusion criteria and for whom patient care was transferred using the TBR method during the intervention cycles of the study.

Patient and public involvement

Our quality improvement study was developed and executed entirely by the research team without prior or direct input or feedback from the general public or patient representatives. Both patients and the public were not involved in study design, execution or dissemination of this QIP.

Staff education and recruitment

ED staff education for TBR took place at the end of the first control cycle through multiple modalities; these included an instructional video, an email with a template and a live demonstration of the mechanics and logistics of the TBR model. Staff inclusion was voluntary. Residents belonged to the emergency medicine residency PGY-2 and PGY-3 classes. The nursing staff was selected from ED nurses with greater than 6 months of clinical experience. A designated nursing leader and resident physician leader were selected from the quality improvement team and helped support their respective disciplines, educate staff, answer questions and ensure understanding of the process. A total of 15 residents and 15 nurses participated in the study.

Data acquisition and analysis

We performed a manual chart review of patient charts after each cycle. Collected data included handoff method (ie, TBR vs OBR), the time the patient was roomed (designated t₀), along with the major outcomes of interest—the surrogates for CE—which included t₀-to-provider assigned, t₀-to-CBC ordered, t₀-to-CBC collected, t₀-to-CBC resulted, t₀-to-ED disposition and t₀-to-ED departure. Each marker of CE was a continuous variable (time measured in minutes). We did not control for covariates such as age, sex, race, comorbidities or insurance status. Data were recorded using a secure Research Entry Data Capture database.

By designating the time a patient was roomed as t₀, we performed basic descriptive statistics to calculate mean times for t₀-to-provider assigned, t₀-to-CBC ordered, t₀-to-CBC collected, t₀-to-CBC resulted, t₀-to-ED disposition and t₀-to-ED departure for each cycle and handoff methodology. The average duration between lab collection and lab result should not vary based on handoff methodology (ie, the average difference between CBC collected and CBC resulted should have an average difference of 0 when comparing OBR vs TBR). Therefore, to account for variations in lab processing times, we applied the equation ([TBR+lab correction]/OBR)−1. Welch’s t-test was used to compare the means of each CE marker subgroup with statistical significance set at p<0.05. Furthermore, effect size was calculated using Cohen’s d for each CE subgroup. Microsoft Excel was used for all statistical analyses.

Results

Our study included a total of six cycles and 307 participants. The total number of participants who met inclusion criteria for the OBR control group was 248 patients (average of 41 participants per cycle) and 59 patients (average of 10 participants per cycle) for the TBR intervention group (online supplemental table 1).

Table 1 compares OBR and TBR methodologies by presenting the absolute and relative differences for all CE markers across all cycles. The mean difference for each CE marker between OBR and TBR groups for each cycle is reported in table 2. Supporting control charts for each CE marker are presented in figure 2. Compared with the asynchronous OBR method, the synchronous TBR method was associated with a 79% reduction in time (19 min to 4 min; p=0.065; d=0.17) for a physician to be assigned after a patient was roomed. The TBR method was associated with decreases in time-to-CBC ordered (67% reduction; p=0.011; d=0.25), time-to-CBC collection (38% reduction; p<0.0001; d=0.57), time-to-CBC result (22% reduction; p=0.0001; d=0.50) and time-to-ED disposition (16% reduction; p=0.022; d=0.29). Time-to-ED departure (ie, discharged, admitted, transferred) decreased by 3% (p=0.71; d=0.05). Box and whisker plots comparing CE markers based on handoff method are presented in online supplemental figure 1; each CE marker demonstrates a relatively normal distribution with mean decrease in time between OBR and TBR across all measures. The relative and absolute reductions of the aggregated mean CE markers are presented in figure 3 and online supplemental figure 2, respectively.

Table 1. Aggregate results for all clinical efficiency indices for all PDSA cycles, reported as means (in minutes).

CE marker	OBR mean time, min (95% CI)	TBR mean time, min (95% CI)	Absolute mean difference, min (OBR to TBR)	Relative % difference (OBR to TBR)	P value	Cohen’s d
t0-to-MD assigned	19 (3 to 36)	4 (3 to 6)	−15	−79	0.065	0.17
t0-to-CBC ordered	44 (23 to 65)	15 (12 to 18)	−29	−67	0.011	0.25
t0-to-CBC collected	50 (44 to 55)	31 (26 to 36)	−19	−38	<0.0001	0.57
t0-to-CBC resulted	87 (82 to 93)	68 (61 to 76)	−19	−22	0.0001	0.50
t0-to-patient disposition	338 (310 to 365)	283 (245 to 320)	−55	−16	0.022	0.29
t0-to-ED departure	541 (500 to 581)	525 (451 to 598)	−16	−3	0.71	0.05

CBC, complete blood count; CE, clinical efficiency; ED, emergency department; MD, medical doctor; OBR, opportunity-based reporting; PDSA, Plan-Do-Study-Act; t₀, time when patient is roomed; TBR, team-based reporting.

Table 2. Absolute difference (in minutes) of average CE markers between OBR and TBR for all PDSA cycles.

Cycle (date)	CE marker	OBR mean time, min (n=22)	TBR mean time, min (n=17)	Mean time difference, min
1 (September 2022)	t0-to-MD assigned	5	4	−1
	t0-to-CBC ordered	15	12	−2
	t0-to-CBC collected	33	28	−5
	t0-to-CBC resulted	94	69	−25
	t0-to-patient disposition	385	229	−156
	t0-to-ED departure	530	432	−98
2 (October 2022)	CE marker	OBR mean time, min (n=27)	TBR mean time, min (n=7)	Mean time difference, min
	t0-to-MD assigned	12	3	−10
	t0-to-CBC ordered	36	12	−24
	t0-to-CBC collected	60	29	−30
	t0-to-CBC resulted	90	67	−23
	t0-to-patient disposition	334	330	−3
	t0-to-ED departure	477	633	156
3 (December 2022)	CE marker	OBR mean time, min (n=50)	TBR mean time, min (n=12)	Mean time difference, min
	t0-to-MD assigned	34	4	−29
	t0-to-CBC ordered	21	19	−2
	t0-to-CBC collected	48	32	−17
	t0-to-CBC resulted	80	74	−6
	t0-to-patient disposition	324	292	−32
	t0-to-ED departure	598	669	71
4 (February 2023)	CE marker	OBR mean time, min (n=52)	TBR mean time, min (n=12)	Mean time difference, min
	t0-to-MD assigned	10	6	−4
	t0-to-CBC ordered	66	16	−49
	t0-to-CBC collected	58	40	−18
	t0-to-CBC resulted	98	70	−28
	t0-to-patient disposition	305	307	2
	t0-to-ED departure	508	427	−81
5 (March 2023)	CE marker	OBR mean time, min (n=50)	TBR mean time, min (n=1)	Mean time difference, min
	t0-to-MD assigned	4	3	−1
	t0-to-CBC ordered	20	17	−3
	t0-to-CBC collected	47	24	−23
	t0-to-CBC resulted	83	105	22
	t0-to-patient disposition	354	150	−204
	t0-to-ED departure	538	494	−44
6 (May 2023)	CE marker	OBR mean time, min (n=47)	TBR mean time, min (n=10)	Mean time difference, min
	t0-to-MD assigned	42	3	−38
	t0-to-CBC ordered	87	13	−74
	t0-to-CBC collected	46	26	−20
	t0-to-CBC resulted	85	56	−29
	t0-to-patient disposition	350	312	−38
	t0-to-ED departure	561	553	−8
All	CE marker	OBR mean time, min (n=248)	TBR mean time, min (n=59)	Mean time difference, min
	t0-to-MD assigned	19	4	−15
	t0-to-CBC ordered	44	15	−29
	t0-to-CBC collected	50	31	−19
	t0-to-CBC resulted	87	68	−19
	t0-to-patient disposition	338	283	−55
	t0-to-ED departure	541	525	−16

CBC, complete blood count; CE, clinical efficiency; ED, emergency department; MD, medical doctor; OBR, opportunity-based reporting; PDSA, Plan-Do-Study-Act; t₀, time when patient is roomed; TBR, team-based reporting.

Figure 2. Control charts of mean time differences between opportunity-based reporting (OBR) and team-based reporting (TBR) cycles. CBC, complete blood count; ED, emergency department; LCL, lower control limit; MD, medical doctor; t₀, time when patient is roomed; UCL, upper control limit.

Figure 3. Mean relative per cent change in time (minutes) of CE markers between all opportunity-based reporting (OBR) and team-based reporting (TBR) cycles. CBC, complete blood count; CE, clinical efficiency; ED, emergency department; MD, medical doctor (clinician).

Discussion

The existing literature related to TBR in the form of interdisciplinary rounds is heavily centred around inpatient services and assesses outcome measures such as staff perception of safety culture, patient length of stay and rate of adverse events during hospitalisation.13,15 To the authors’ best knowledge, there is no literature that evaluates the impact of TBR implementation on CE markers in an ED setting. Our study evaluated whether synchronous TBR during EMS-ED handoff was associated with improvements in markers of CE. We found that the implementation of a synchronous TBR protocol during EMS-ED handoff was associated with statistically significant improvements in most measured CE markers when compared with the control group which used an asynchronous OBR paradigm. We found greater than 15% reduction in nearly all CE markers, which was the a priori threshold for improved CE. Moreover, these improvements in CE markers persisted despite varying and expanding the nursing and resident cohort to include PGY-2 residents as well, demonstrating the broad applicability of TBR. More importantly, these improvements are also clinically significant, especially as time-to-ED disposition decreased by 55 min when using the TBR protocol. The implications of these findings are significant; improved team communication positively impacts patient care and ED throughput. Using effective communication to minimise any latency or lag between a patient being physically roomed and ultimately dispositioned is critical for optimising patient care, both for the individual patient and from a systems perspective.

We suspect time-to-ED disposition improved due to better front-end communication between physician and nursing staff once the patient arrived in the ED. When the care team was in sync, they developed a shared mental model that translated into a concerted and focused clinical inertia, allowing staff to initiate management prior to orders being placed, to anticipate subsequent steps and to pre-emptively plan for contingencies, ultimately resulting in a quicker disposition time.¹⁶ The fundamental mechanism at play is better closed-loop communication, which improves clarity of task.

Despite the clinically and statistically significant improvement observed for multiple measured CE metrics, the time-to-provider assigned and time-to-ED departure metric showed no statistically significant difference. The improvement in time-to-provider assigned (reduction from 19 min to 4 min; p=0.065; d=0.17) approaches statistical significance. This could be due to inadequate power or how the electronic medical record fits in the provider workflow. We also speculate that physicians might routinely arrive at the patient bedside on EMS arrival at baseline; put differently, physician arrival is not the rate-limiting step for downstream patient assessment and disposition. However, the implementation of a TBR paradigm permits initial communication that is essential for timely and efficient patient care. We contend that even though time-to-provider assigned did not reach statistical significance, the physicians participating in TBR were able to communicate orders and thought processes to the rest of the care team sooner, allowing the ‘dominos’ of patient care orders to be enacted. In a busy ED where physicians are bombarded with numerous distractions, the care team can carry out patient care even if the physician is delayed in inputting orders.

The limited improvement in the time-to-ED departure metric (reduction from 541 min to 525 min; p=0.71; d=0.05) likely reflects systemic issues related to ED flow, specifically ED outflow, as patient ED flow is a function of input, throughput and output factors.¹⁷ Our QIP successfully improved communication and throughput through the ED by decreasing time-to-labs ordered, time-to-labs collected, time-to-labs resulted and time-to-ED disposition. However, if systemic, hospital-wide census and outflow issues are not concomitantly addressed, patients will still not be able to depart the ED in a timely fashion, resulting in a protracted ED length of stay.

With each successive intervention cycle, we expanded and varied the resident and nursing cohort composition. The resident cohort included only PGY-3 residents initially and later was expanded to include PGY-2 residents as well. As the resident physicians rotated into and out of the ED, the cohort naturally evolved. More nursing staff were included in subsequent iterations as well. By varying the team composition, we hoped to demonstrate TBR’s sustainability over time and its reliability and effectiveness in meaningful CE changes. After each PDSA cycle, targeted feedback was provided to any performance outliers. An unanticipated challenge we experienced was poor early adoption (table 2, cycle 1), likely due to study setting and design. In the traditional OBR paradigm, nursing staff take EMS handoff with or without physicians present. After TBR was ‘implemented’ in cycle 1, it was unclear who had the responsibility of gathering the team to bedside, and the team frequently did not assemble. After this shortcoming was identified and the responsibility of TBR was placed on nursing staff, we saw an immediate improvement in CE measures.

The number of patients enrolled in the TBR arm (n=59) and OBR arm (n=248) is significantly different. This is due to a variety of factors that should not impact the observed CE marker improvements. First, this study was designed as proof of concept that TBR can effectively improve CE markers and was not designed to study its widespread implementation. Second, the large 90-bed ED is staffed by hundreds of nurses and providers who were not trained in the TBR process. Therefore, the OBR cohort was a randomised convenience sample of the native, much larger, ongoing OBR process. Finally, the TBR cohort consisted of a much smaller group of trained nurses and resident physicians. Ultimately, the difference in enrolment does not reflect poor global adoption.

One of the strengths of our study was our intention-to-treat analysis. We included all patients who were in a TBR cycle regardless of whether TBR handoff occurred. If TBR did not occur, handoff proceeded in the standard, ad hoc, disjointed manner. Therefore, the true CE improvement for TBR may be better than reported.

Relevance

The findings of our study add to the current body of literature describing the positive impact of synchronous patient handoffs on CE markers. Our data also add to this body of literature by demonstrating that interdisciplinary rounds and a shared mental model improve CE in the ED specifically. Therefore, the authors contend that interdisciplinary communication should not be limited by the four walls of the hospital; instead, it should be broadened to include all venues of medical care, including prehospital settings, such as nursing facilities to EMS handoff, family member to EMS handoff or even during transfer of care between EMS services (eg, basic life support first response to advanced life support transport agency, advanced life support to helicopter EMS, etc). Interdisciplinary communication is important for all patients, but especially important for critical patients in extremis, patients with time-sensitive conditions whose management is dependent on critical information (eg, stroke), patients who are unable to communicate, such as patients suffering from intoxication, dementia, encephalopathy, hypoglycaemia, etc, and paediatric patients. As anyone who has played the ‘telephone game’ can attest to, information is incrementally lost due to imperfect data transmission over multiple iterations, emphasising the importance of faithful and accurate patient information transfer. From the results of this study, we posit joint handoff outside the traditional brick-and-mortar hospital would incrementally improve patient care quality by mitigating information degradation.

Limitations

There are a few limitations to this study. First, the data were collected at a single large, urban, academic teaching hospital ED, which limits the generalisability to other settings, such as rural, non-academic or smaller community hospitals. This study would have to be repeated at multiple institutions to improve its generalisability. Second, although our results were statistically significant, the smaller sample size of the intervention group (TBR) included only 59 participants, as compared with 248 in the control group (OBR), which may affect the robustness and generalisability of the results. Third, as we performed six cycles throughout the year, some modified behaviours could be retained (ie, performing TBR throughout the year) or study subjects might exhibit the Hawthorne effect if they discovered they were being evaluated, potentially introducing a source of bias. If these biases were present, however, they would narrow the observed difference between the OBR and TBR groups, instead of widening the disparity. Nevertheless, we tried to minimise this bias by randomly selecting weeks for control cycles throughout the year such that these dates could not be anticipated. Despite these limitations, our findings are significant because this TBR intervention represents a very low-cost policy and procedural change that has the potential to improve multiple markers of CE. Further studies should be conducted at multiple sites to assess for generalisability, as well as the expansion of the TBR method to other areas of the ED beyond patients who arrive via EMS (ie, patients who arrive by privately owned vehicle).

The lack of patient and public involvement is a weakness of this QIP. Patient-centred outcomes such as satisfaction, adverse events, and patients’ perception of care, staff professionalism, and staff timeliness were not assessed. Along with clinical markers of performance, these are important aspects of patient-centred care and should be analysed in future studies. Similarly, soliciting feedback from providers regarding their perceptions is important as well.

The availability of ED staff to receive EMS handoff is contingent on numerous factors, including ED census, volume of EMS arrivals, presence and number of simultaneous critical patients, staff shift change, etc. Moreover, uncontrolled systemic factors such as hospital census, boarding issues or ED crowding were beyond the scope of this quality project but could influence time-to-departure metrics and overall patient flow. Although the authors believe the TBR method should be applied consistently for quality care, local ED factors can and will limit its universal application.

Finally, the subjects in the OBR and TBR groups were not propensity matched; therefore, variations in illness severity could introduce bias. This was mitigated by running multiple cycles throughout the 10-month study period.

Conclusion

The EMS-ED handoff is a critical moment in patient care where there are many opportunities for miscommunication. Currently, there is no standardised method for this interaction between ED and EMS staff at our institution. In this study, a novel synchronous TBR model was introduced as a model of communication for EMS-ED handoffs and compared against the status quo asynchronous OBR model. The results showed the TBR paradigm was associated with clinically and statistically significant improvement in multiple quality indicators of CE, particularly time-to-patient disposition. Future research with larger sample sizes and more sites will be needed to further analyse how the methods of communication between ED and EMS staff affect CE in other realms of the healthcare system.

Data availability statement

Data are available upon reasonable request.