Effectiveness of modified Manchester triage flow model regarding patients’ waiting time

Mehwish Shaheen, Muhammad Afzal, Madiha Mukhtar. Effectiveness of modified Manchester triage flow model regarding patients’ waiting time. Cardiometry; Issue No. 29; November 2023; p. 99-102; DOI: 10.18137/cardiometry.2023.29.99102; Available from:

Clinicians use the Manchester Triage System, a clinical risk management tool, to properly manage pa- tient flow when clinical need exceeds capacity(Singh & Awasthi, 2022). A group of emergency nurses and doctors from the general, paediatric, and ophthalmology emergency departments in Manchester established the Manchester Triage Group in November 1994 (Cicolo, Nishi, & Peres, 2020). A growing number of patients, ranging from those with mild illnesses and injuries to those with serious trauma and life-threatening disorders, visit emergency rooms every day. Patients must be seen according to clinical priority rather than attendance order in order to protect patient safety (Pryce, Unwin, Kinsman, & McCann, 2021). The Manchester Triage System is used to maintain a consistent method of prioritising and assessing patients, allowing for thorough audits and improved patient safety. Globally, emergency departments (EDs) are seeing increased challenges due to an increase in patients and an inability to build capacity to keep up with demand. In the backdrop, hospital resources are being squeezed. Consequently, ED overcrowding has spread globally and become a common problem (Zachariasse et al., 2021). One of the most popular triage systems in Europe is the Manchester Triage System, which prioritises patients in the ED according to five levels: level 1 (red), immediate;

Patient flow describes how patients travel around healthcare facilities. It involves the necessary medical care, physical resources, and internal mechanisms to move patients from the point of admission to the point of discharge while maintaining quality and patient/ provider satisfaction (Tlapa et al., 2020). The major facility for urgent medical difficulties is a hospital emergency department (ED), which is a complex system with erratic demands. The patient waiting time in the ED is impacted by overcrowding, the patient flow paradigm, and the lack of resources(Lindner & Woitok, 2021). At this study, we’ll evaluate the performance of patient flow model services in a Lahore, Pakistan emergency department at a Bahria International Hospital. In order to assess the average total patient waiting time, it is important to maximise the human and material resources needed (Aburayya, Alshurideh, Albqaeen, Alawadhi, & Ayadeh, 2020).Patients must spend an excessive amount of time in the ED because of the constant flow of patients and packed waiting ar-eas(Frank & Elmqvist, 2020). Reducing the amount of time patients spend in the ED and resulting decrease 100 | Cardiometry | Issue 29. November 2023

Study Design

Quasi Experimental study design

Study Period

01 August 2023 to 30 September 2023

Sample Size

Methodology

All the information was provided via the hospital’s electronic medical record and patient monitoring system, which was utilised in the ED from 01 August 2023 to 30 September 2023. Each patient’s stay duration, wait time (from the time of registration to the beginning of nurse preparation), and process time (from the time a nurse allocated a new patient to a box to the time this patient was sent home or moved to an observation unit) were meticulously documented. The crucial variable was the median process time, which was independently determined for patients discharged straight from the ED and those transferred to the observation unit. As auxiliary variables, the median length of stay and median waiting time were also assessed. These included the daily left without being seen (LWBS) rate, the daily 72-h revisit rate, and the daily ED mortality rate. These variables could have unanticipated effects on the standard of care patients get. Finally, the interpretation of the data for the waiting time at the emergency department may be complicated by the following potential confounders:

Results

Analyzing Between waiting time in different stages all Emergency patients: Contrasting the pre and post-intervention data.

When evaluating all emergency arrivals regardless of their ESI levels, several observations were made post-intervention. The mean waiting time to reach the information desk after arrival decreased to 9 minutes from its previous duration of 12 minutes, yet the median time increased by 1 minute. Notably, there was a substantial reduction in standard deviation from 13 minutes pre-intervention to 5 minutes post-interven-

		Group		P-value
		Pre-intervention (n=41)	Post-intervention (n=41)
Waiting Time of Arrival to Information Desk	Mean ± SD	00:12 ± 00:13	00:09 ± 00:05	0.246
	Median(Q1 – Q3)	00:09(00:06 - 00:13)	00:10(00:05 - 00:13)	0.816
Waiting Time between Arrival and Triage	Mean ± SD	00:21 ± 00:16	00:18 ± 00:09	0.320
	Median(Q1 – Q3)	00:18(00:12 - 00:20)	00:18(00:10 - 00:25)	0.940
Waiting Time from Arrival to Transfer	Mean ± SD	00:26 ± 00:15	00:30 ± 00:27	0.437
	Median(Q 1 – Q 3 )	00:25(00:15 - 00:30)	00:25(00:15 - 00:38)	0.590
Total waiting time in Emergency Department	Mean ± SD	04:16 ± 02:42	02:59 ± 01:54	0.016
	Median(Q 1 – Q 3 )	04:00(03:00 - 04:40)	02:45(02:05 - 03:15)	<0.001

tion; however, this difference remained statistically insignificant with p-values >0.05.

Similarly, the mean waiting time taken to reach triage decreased by 3 minutes, accompanied by a 7 minute reduction in standard deviation, while the median waiting time remained unchanged. However, the difference in mean time was statistically insignificant, with a p-value of 0.320.

The average waiting time for transfer to respective departments increased by 4 minutes post-intervention, along with an increase in standard deviation, yet this change remained statistically insignificant. The median waiting time for transfer remained unchanged at 25 minutes, consistent with the pre-intervention duration.

The overall mean waiting time post-intervention totalled 2 hours and 59 minutes, with a standard deviation of 1 hour and 54 minutes. In contrast, pre-intervention, this mean time was 4 hours and 16 minutes, with a standard deviation of 2 hours and 42 minutes. This change in mean waiting time was deemed statistically significant, with a p-value of 0.016. Additionally, a comparison of median waiting time revealed a significant reduction by 1 hour and 15 minutes, decreasing to 2 hours and 45 minutes post-intervention, indicated by a highly significant p-value of <0.001.

Discussion

This post study shows how a patients flow model effect treatment of patients and efficient and greatly decrease the value of waiting time. This degrades the flow and quality and is removed. By further minimising the time spent waiting between phases and giving the next user in the process exactly what they need, quality and productivity increase. Staff members on the front lines are trained to spot waste and to enhance and standardise their workflow. The flow model has been tried to be implemented in the ED before, but the results weren’t always thought to be clinically relevant. Each organization’s own local environment is taken into account as generic lean principles are interpreted and modified. Organizations who have correctly applied these ideas have not only produced statistically significant outcomes, but also improvements that are pertinent to the therapeutic setting. The way this strategy was used in the current study should be highlighted because it could mean the difference between failure and success. Success depended on the dedication of the ED management team as well as the formation and empowerment of a multidisciplinary team of frontline employees. Frontline staff members were given more freedom to develop solutions to issues that led to waste, delayed flow, and poorer quality care in the ED because they have more knowledge of the systems. The new procedure was more enthusiastically adopted by the rest of the staff as a result of the bottom-up rather than top-down strategy, and successful implementation was easier to achieve. The ED executive team played two roles: they assisted in providing the means for implementation and got involved in problems that came up during analysis and implementation, serving as genuine methodology consultants. In the current study, it was also noteworthy that the availability of internal knowledge and abilities eliminated the need for an external consultant. Staff members may not accept or get accustomed to being observed or punished and may be unwilling to have outsiders meddle with their regular activities.

Conclusion

The current post study analysis how Improving patient flow within the ED is ultimately achieved by reducing the amount of waiting time patients spend in the ED, thereby reducing departmental crowding. Shorter patient journey times are associated with improved patient satisfaction and reductions in mortality and morbidity. ED effectiveness and overcrowding are not only determined by external pressure, but also by internal factors. Measurement of patient flow across ED has proved useful in detecting these factors and in being used to plan an ED reorganisation.

Recommendations

I recommend implementation of this modified patient Flow Model in Emergency Departments of Hospitals to get the standard results regarding patients waiting time. I first suggest duplicating it in another area to see if the results are consistent. The consequences of patient wait times for a Modified Triage patients’ Flow model and an ESI patient triage level might be compared, as a second suggestion.

Contributions

Mehwish Shaheen – wrote the main manuscript text, conception, design of the study, acquisition of data, manuscript review and revision, data and models’ analysis. Muhammad Afzal and Syed Naveed Tahir, – conception and design of the study, manuscript review and revision Nauman Rafi Rajput, Abida Raz-zaq, Maryam Behram, Madiha Mukhtar and Sumaira Shaheen – acquisition of data, manuscript review and revision.

Ethics approval

Approval was obtained from the ethics committee Bahria International Hospital, Lahore, Pakistan. The procedures used in this study adhere to the tenets of the Declaration of Lahore, Pakistan.

Conflict of interest

The authors have no competing interests to declare that are relevant to the content of this article.

Funding

No funding was acquired.