Introduction
The urgent care clinic at an academic dental hospital plays a critical role in meeting the healthcare needs of the local population. An evaluation was conducted to determine factors that affect the effective delivery of services at this institution. The evaluation revealed that one of the major concerns was the queuing system. It was evident that patients spent a lot of time in the queues before accessing the services they need. Magauran, Shankar, and Kahn (2016) argue that the traditional queuing system is no longer appropriate in a modern hospital. The evaluation revealed that time is wasted by patients who do not understand the right queues based on the service they need. They spend time in the wrong queues only to be redirected by the staff. The evaluation also revealed that this problem was affecting the staff. At the reception, there were nurses who had to guide patients based on the services they needed. The task was demanding, and some patients felt uncomfortable explaining their problems to them. It was clear that an automated queuing system was necessary to improve service delivery.
The Significance of Healthcare Evaluation
The healthcare system in the United Arab Emirates and many other regional countries is going through a transformation. As new technologies emerge, stakeholders in this sector try to come up with a means of enhancing the quality of services offered to patients. According to the Health Foundation (2015), healthcare evaluation has become one of the critical activities meant to improve service delivery in hospitals. It is necessary to conduct regular evaluations to understand the current issues faced by patients and medical practitioners and ways of addressing them. The regular evaluation helps in maintaining consistent improvement of service delivery. Every time an evaluation is conducted, a new issue of concern will be identified (Frye & Hemmer, 2012). The evaluation will define the issue, analyze it, and propose ways of addressing it to improve patients’ experience.
Recent healthcare evaluation conducted in this country shows that one of the issues which are affecting patients’ experience in these institutions is the time they have to wait before they can be served. According to Adibi (2015), patients who visit public healthcare institutions are often forced to wait for up to 3 hours before they can access the services they need (Graban, 2016). One of the reasons that cause delays in service delivery is the poor queue management systems used at these institutions. The traditional queuing system has become ineffective when handling a large number of patients (Barnsteiner, Disch, & Walton, 2014). It is also open to abuse. Individuals who have friends or family members working at these hospitals rarely queue a fact, which causes frustration to the other patients. It is one of the reasons why this project focused on solving the problem.
Objective #1
It is critical to evaluate the primary objectives of this project to understand what is to be achieved. The following is the first objective that had to be realized.
By 20th February 2018, there will be a decrease in waiting time from 180 minutes to 60 minutes with the queue system for the morning session
It is evident that the project has set out an ambitious plan for reducing the waiting time for patients by two thirds. Instead of waiting for three hours before getting the services that they need, these patients will only have to wait for one hour. This objective seeks to encourage patients to visit hospitals to seek early intervention for their medical problems because accessibility will be improved. They will be assured of having improved services within the shortest time possible.
Method of Evaluation Employed
It was necessary to identify an evaluation method that would help in outlining issues of interest and how they can be addressed effectively through this project. CIPP (context, input, process, and product) was considered the most appropriate method for the evaluation of issues affecting the organization. According to Haider (2015), CIPP model helps in linking evaluation with decision-making processes by providing a rational basis for the actions of the project manager. It is necessary to analyze what each of the four areas of focus in this model emphasizes when using the framework.
Context
The first area of focus is the context where the project management team has to define issues that have to be addressed. It requires the team to assess the goals that are to be achieved and priorities that have to be observed. In this case, the context of this project is to address the problem of the long time that patients have to wait in queues before they can get the services they need at various healthcare institutions in the country. The proposed solution will help in enhancing service delivery in hospitals.
Input
The next step that should be considered when using this model is the definition of tasks that should be addressed. In this case, it was established that it would be necessary to develop a better queue management system. The team will be interested in determining how this should be done. Achieving the set goals will require some resources. The new system will be based on emerging techniques in the field of information technology (Fleisher, 2013). The hospital will need a new computer system with a large database and a queuing machine that will be issuing the tickets. It may be necessary to have an officer who may help patients to pick the right ticket based on the nature of the service needed at the hospital.
Process
The third step provides the management with information about the success rate of the implementation of the plan. Once the new queuing system has been implemented, the team will evaluate its performance. Of interest will be to determine if the desired goal has been achieved (Modi, 2017). In this case, the team will look at the amount of time that an individual patient has to wait before getting the needed services. Cases of time wastage, customer complaints, and missed turns should be reduced as much as possible. Still (2014) advises that it may also be necessary to determine if there are conflicts of interest and staff morale that directly arises from the implementation of the problem. Budgetary problems should also be addressed.
Product
The final stage of this model is to determine if it worked. The team will measure the actual outcome against the set goals. The final stage is meant to help the top managers in making the decision about the new project. They can decide to allow the project to continue, propose means of a modification to improve the outcome, or consider discontinuing the program because of its limited relevance.
Analysis Undertaken
Using the evaluation model discussed above, it was possible to analyze various issues directly related to this project. The analysis focused on how the proposed project could help improve service delivery at the targeted hospital. The following are the primary factors that were observed when conducting the analysis:
Observational audit
According to Krueger (2014), an observational audit helps in assessing the overall performance of a project. This assessment was necessary for evaluating the performance of the new queuing system. In this case, it involved a basic analysis of the rate at which patients are served under the new system. By identifying specific patients and determining how long he or she takes before getting the needed service, it was possible to know the effectiveness of the new approach that had been employed.
Process mapping
Denton (2013) defines process mapping as “a workflow diagram to bring forth a clearer understanding of a process or series of parallel processes” (p. 53). Using this diagram, it was possible to identify how the new system brings about improved patient flow within the hospital. It made it possible to identify specific areas of improvement under the new system.
Time data before and after the implementation
The primary goal of the new system was to reduce the amount of time that patients have to wait before getting the services they need. As such, one of the most important areas of the evaluation was the determination of how the new system had addressed the issue at hand.
Lean six-sigma
Finally, the lean six-sigma was used to promote collaboration among staff members, improve performance, eliminate waste, and improve consistency when using the new system. Using this model, it was possible to identify and eliminate issues that would waste time and resources in these hospitals. For instance, it was necessary to have an officer to help patients pick the right ticket to eliminate time wastage.
Reasons Why the Method Was Chosen and the Outcome
The method was chosen because it is supported by empirical studies. Adibi (2015) argues that CIPP model has been tried and tested for its effectiveness in an organizational setting. It identifies issues that should be addressed, how they should be addressed, and strategies necessary to determine the level of success. The new method used helped to significantly reduce the waiting time for patients visiting the hospital. Figure 1 below shows how the system eliminated time wastage.
Objective #2
To decrease the number of cases “no-shows” or chances of missed turns to 25% by 20th February 2018
The second objective was to decrease cases of no-shows or missed turns among patients, especially those who are expected to come for follow-up treatments. According to Wiler, Pines, and Ward (2017), the time that patients have to wait before they can have access to services they need may discourage them from visiting hospitals. When they are convinced that the waiting time will be shortened, these patients may be motivated to follow up on their treatment as advised by their doctors.
Method of Evaluation Employed
In this project, it was necessary to identify a model that could be used to evaluate whether or not the above objective was realized when the new queue management system was embraced. The easiest method that would have been used is to check the record at the hospital to establish the percentage of patients expected to come back for check-ups who did (Wheeler, 2013). However, the team wanted a patient-centered approach in this analysis. As such, Patient-reported outcomes measures (PROMs) were considered the most appropriate method to use in determining the success of the system (Ignatavicius & Workman, 2015). The method made it possible to measure the outcome of the project both qualitatively and quantitatively. This model was used in two main stages, as discussed below.
Data captured at the queuing machine
At the queuing machine, patients are expected to pick tickets based on two factors. First, their ticket will indicate the department of the hospital they are visiting based on the nature of their medical problem. Secondly, the ticket will indicate whether they are visiting for the first time or if they are making follow-ups. The primary interest of the evaluation team will be those making revisits to the hospital for the continuation of their medication. Using advanced ticketing system, it is easy to identify the number of patients revisiting the healthcare institutions (Hall, 2016).
The analysis will involve determining the percentage of those making follow-ups when the system is just introduced and after a four-month period of its implementation. The reason why it was necessary to wait for that period is that the outcome of the new system will take time to influence decisions of patients (Honiden & Siner, 2015). Those who had undesirable experience in the past may take time before trusting the capacity of these institutions to deliver services promptly. When given time, the attitude will change as they realize that the system has reduced the waiting time. They will be more willing to revisit the hospital to make medical follow-ups as expected (Lee, Kim, & Cho, 2018). The team will compare the number of those making regular follow-ups before and after the introduction of the new system by ensuring that the machine captures the data.
Data obtained from the patients
The second phase will be to engage these patients through a simple survey to understand factors that motivated them to make the medical follow-ups. Some patients turn up for follow-up treatments because they have no choice but to do so. Others revisit the hospital because of the belief that quality of service and the waiting time has improved. It was necessary to determine the number of patients who believe that the time they have to wait before being attended to has reduced. As Kerpchar, Protzman, and Mayzell (2015) observe, when conducting such an evaluation, one must understand that numerous factors exist which may influence patients’ decision to make follow-up visits. Factors such as reduced or eliminated costs, high-quality service, and the threat that disease poses to the patient may make them revisit the hospital as directed even if they have to spend a long time in the queues (Lu, Barrette, Noronha, Sobel, & Tobin, 2018). As such, it was necessary to engage them to be sure that one of the main reasons why they were willing to turn-up for further treatment was the improved queuing system. The information obtained from these two sources was further supported by data obtained from medical records in different departments.
Reasons Why the Method Was Chosen and the Outcome
The government of the United Arab Emirates has invested a lot in improving the quality of services in the healthcare sector (Wiger, 2018). The number of medical staff has been going up, and most hospitals have better facilities than was the case before as a way of meeting the increasing demand (Setola & Borgianni, 2016). These are factors that may prompt a patient to be regular in going for check-ups. However, the main interest in this project was to determine how the new system of queue management has helped in reducing cases of missed turns among patients (Glassman, 2017). The medical records and information from the queuing machine can help in quantitatively determining the change. However, it cannot accurately determine if the change is caused by the new system or other improvements within the facility (Han & Suneja, 2015). It is the reason why this method goes a step further to engage the patients to determine their view on this issue.
The outcome of the analysis conducted showed that there was a significant reduction in the number of patients who fail to show up for further treatment. When asked why they were keen on making follow-ups, many indicated that they were pleased with the reduced time that they have to wait before being served. Before, they had to wait for about 3 hours. The time had been reduced to 1 hour or less, which mean that they could plan their day effectively. Figure 2 below shows the significant decrease in cases of missed turns in the hospital where the new system was implemented.
It is evident from the graph above that there was more than 25% decrease in cases of missed turns registered at the hospital. It means that more patients were going for follow-up treatment than ever before after the implementation of the new system.
Dissemination Plan
It is evident that one of the main challenges that many hospitals in the country face is the number of time wastages before patients can access services they need (Parsons, 2015). It is clear from the analysis that introducing a queue management system can help in improving patient flow, especially in urgent care clinics at academic dental hospitals. It is a best practice that should be implemented in all healthcare institutions in the country. It proved successful in the academic dental clinic where it was tried, and it can work in other similar institutions. The dissemination plan at these institutions will be simple, given that the system is already tested (Graban, 2016). They will need to embrace this queue management system in its entirety, with minor adjustments based on additional services which are offered (or not offered) at the new institution. The best practice should be subject to improvement based on the emerging technologies.
Project’s Success and Impact
The new queue management system was a success in the urgent care clinic at the academic dental hospital where it was tried. It helped in improving patient flow at this hospital by decreasing the waiting time. Instead of the standard 3 hours that these patients had to wait before getting served, the new system made it possible to reduce that time to about 1 hour. This was achieved by automating the queuing system. Instead of the manual method, patients picked their tickets at the queuing machines that directed them to the right department where they should get help. It eliminated confusion and simplified the work of the staff. It improved the experience of patients, which in turn, reduced cases of missed turns. The new system had a positive impact on the organization. It registered an overall improved performance because of the change in the queuing method. The new system was also beneficial to the staff. It simplified the process of managing the flow of patients. The success of this project gave a sense of satisfaction. I was pleased to see my idea help so many people.
Summary and Conclusion
Managing patient flow is one of the challenges that many healthcare institutions still have to deal with in the modern society. In this project, a new technology-based queue management system was developed. It was meant to reduce the waiting time and chances of missed turns in the urgent care clinic at the academic dental hospital. The outcome of the study shows that it registered impressive performance in the two areas. The time patients spent in the hospital reduced by more than half. Patients also felt the new system motivated them to make follow-ups on their medication. It also benefited the hospital and staff. It made it easy for them to attend to patients more effectively than before the implementation of the new system.
References
Adibi, S. (Ed.). (2015). Mobile health: A technology road map. Cham, Switzerland: Springer International Publishing.
Barnsteiner, J.H., Disch, J.M., & Walton, M.K. (2014). Person- and family-centered care. Indianapolis, IN: Sigma Theta Tau International.
Denton, B.T. (Ed.). (2013). Handbook of healthcare operations management: Methods and applications. New York, NY: Springer.
Fleisher, L.A. (2013). Evidence-based practice of anesthesiology (3rd ed.). Philadelphia, PA: Elsevier.
Frye, A.W., & Hemmer, P.A. (2012). Program evaluation models and related theories: AMEE guide. Medical Teacher, 34(5), 288-299. Web.
Glassman, A. (Ed.). (2017). What’s in, what’s out: Designing benefits for universal health coverage. Washington DC: Brookings Institution Press.
Graban, M. (2016). Lean hospitals: Improving quality, patient safety, and employee engagement. Boca Raton, FL: CRC Press.
Haider, A. (Ed.). (2015). Business technologies in contemporary organizations: Adoption, assimilation, and institutionalization. Hershey, PA: IGI Global.
Hall, R. (Ed.). (2016). Patient flow: Reducing delay in healthcare delivery (2nd ed.). New York, NY: Springer.
Han, D., & Suneja, A. (2015). Make your clinics flow with synchrony: A practical and innovative guide for physicians, managers, and staff. Milwaukee, WI: ASQ Quality Press.
The Health Foundation. (2015). Evaluation: What to consider, commonly asked questions about how to approach evaluation of quality improvement in health care. London, England: The Health Foundation.
Honiden, S., & Siner, J.M. (2015). Advances and challenges in critical care. Clinics in Chest Medicine, 36(3), 15-16.
Ignatavicius, D.D., & Workman, M.L. (2015). Medical-surgical nursing: Patient-centered collaborative care (8th ed.). St. Louis, MO: Elsevier.
Kerpchar, J., Protzman, C., & Mayzell, G. (2015). Leveraging lean in the emergency department: Creating a cost effective standardized, high-quality, patient-focused operation. Boca Raton, FL: CRC Press.
Krueger, J.M. (Ed.). (2014). Cases on electronic records and resource management implementation in diverse environments. Hershey, PA: IGI Global.
Lee, Y.C., Kim, S.R., & Cho, S.H. (Eds.). (2018). Severe asthma: Toward personalized patient management. Singapore, Singapore: Springer Singapore.
Lu, L.B., Barrette, E.P., Noronha, C., Sobel, H.G., & Tobin, D.G. (Eds.). (2018). Leading an academic medical practice. Cham, Switzerland: Springer.
Magauran, J.B.G., Shankar, K.N., & Kahn, J.H. (2016). Geriatric emergencies, an issue of emergency medicine clinics of North America. Philadelphia, PA: Elsevier Health Sciences.
Modi, A.J. (2017). Essentials of operations management. Mumbai, India: PHI Learning.
Parsons, L.C. (2015). Pathophysiology and care protocols for nursing management: An issue of nursing clinics, e-book. Philadelphia, PA: Elsevier Health Sciences.
Setola, N., & Borgianni, S. (2016). Designing public spaces in hospitals. New York, NY: Routledge.
Still, K.G. (2014). Introduction to crowd science. Boca Raton, FL: CRC Press.
Wheeler, D.S. (Ed.). (2013). Critical care of the pediatric patient, an issue of pediatric clinics. New York, NY: Elsevier.
Wiger, M. (2018). Logistics management operationalised in a healthcare context: Understanding care chain effectiveness through logistics management theories and systems theory. Linköping, Sweden: Linköping University Electronic Press.
Wiler, J.L., Pines, J.M., & Ward, M.J. (Eds.). (2017). Value and quality innovations in acute and emergency care. Cambridge, England: Cambridge University Press.