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Process optimization of the preoperative anesthesia clinics at ZGT Almelo and Hengelo

Odijk, R.C.A. (2012) Process optimization of the preoperative anesthesia clinics at ZGT Almelo and Hengelo.

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Abstract:In the last couple of years, Ziekenhuisgroep Twente (ZGT) successfully reduced the access times for surgical operations. This reduction in access time led to a bottleneck shift within the patient process from surgical operation to preoperative screening (POS). According to regulations [1], only people who are screened and have consent of an anesthesiologist can be operated. In some cases, patients were not screened before the surgical operation, which led to delay and occasionally to cancellation of the surgery. Currently, the access time and waiting time at the preoperative anesthesia clinic (PAC) are not in line with the objectives of the hospital. To comfort the patients, ZGT aims at screening all patients with a ‘one stop shop’ approach where possible, but still having a reasonable waiting time for their patients. However, in the current situation patients sometimes have to wait for over an hour or come back another day. The goal of this research is to come up with suggestions to increase patient satisfaction at the preoperative anesthesia clinic while not delaying the planning of surgical operations. We researched six organizational interventions to increase the one stop shop percentage, reduce the access times (at Almelo) and shorten waiting times (especially at Hengelo) by changing the number of nurses, balancing the mixture between walk-in and appointment, changing timing policies, and changing the timeslot intervals. Therefore, we start with interviewing several involved employees in order to understand the preoperative screening process. Next, we analyze data obtained through the registration software and use a random sample of the current service at the PAC to get more insight in the characteristics of the patients, patient inflow, and preoperative screening performances. With this data, several points of improvement to increase the patient satisfaction are found. These points of improvement are that in the current situation the access time at Almelo is too long, and the waiting times at both locations exceed the acceptable waiting time. We inquire literature to find whether similar problems are studied in the past and how they were handled. We found that the access and waiting times can be reduced if a right mixture between appointments and one stop shop, another timing policy, or other timeslots intervals are implemented. Several articles give suggestions how to do this. We develop a conceptual model to determine the effect of the organizational interventions. We start with describing the process steps that a patient needs to take before having consent and the different paths to take these steps. Next, we describe that these process steps are dependent on several factors, what resources are needed, how the processing times per processing step are determined, and last the decision making policies. We discuss the interventions and output parameters. We distinguished between two different levels for interventions. On the strategic level we studied the effect of changing capacity to two nurses on every day (Section 5.1). On tactical level, we studied the effect of different planning rules and different appointment intervals (Section 5.2). Intervention 2 is based on scheduling appointments on the least busy moments. Intervention 3 studies the effect of a maximum percentage of walk-in and appointments per day. Intervention 4 is a combination of intervention 2 and 3. Intervention 5 focuses on different timing policy for scheduling appointments. Intervention 6 focuses on changing the current timeslots to better match the expected consultation times. iv With this information we start to develop a simulation model of the current situation at the PAC. We use several techniques to verify that the simulation model is a good resemblance of the conceptual model and can be used to compare the effect of different interventions. We also determine whether the simulation model was a sufficient representation of the real world. We introduced several correcting factors to better match the outputs of the simulation model with the real world data. The model is a sufficient representation of the real world to determine the effect of the interventions. However, it cannot be used to provide accurate expected waiting times of the real world system. With this in mind, we used the simulation model to test and analyze the six interventions. We find that changing the number of nurses from one to two on Friday at Hengelo has a positive influence on the overall patient satisfaction. The waiting time and access time both decrease. Changing the number of nurses from three to two for every weekday at Almelo increases the waiting time for a nurse, but decreases the waiting time for an anesthesiologist. The increase for a nurse is higher than the decrease for an anesthesiologist. This intervention does not influence the total waiting time in a positive manner at Almelo, but may not have a significant influence on the patient satisfaction as long as the waiting time per care provider does not exceed the maximum acceptable waiting time. Moreover, the personnel costs will decrease significantly when staffing one nurse less. Therefore, for the interventions on a tactical level at Almelo, we simulate with two nurses Hereby, we keep in mind that the effect of having three nurses would lead to less waiting time for a nurse and more waiting time for an anesthesiologist. Additionally, when the number of nurses does influence the effect of the tactical level interventions differently, we discuss this. At Hengelo, we also continued with two nurses every day for the interventions on a tactical level. When analyzing the interventions on a tactical level, we keep in mind that to improve patient satisfaction, the one stop shop percentage at Almelo should increase, whereas the desired effect on the waiting times at both locations depends on the planning method. We come to the following conclusions with respect to the tactical interventions:  Intervention 2: The effect of first scheduling appointments on the least busy days and hours depends on the planning methods and timeslot interval. We find that the waiting times at Almelo increases, whereas this intervention leads to a higher one stop shop percentage and lower waiting time at Hengelo. For both locations, the access time increase, because patients are not planned on the first possible day but are planned later in the week. We conclude that the effect of this intervention is positive on the waiting times, when not too many appointments are scheduled per week and a correct timeslot interval is used. However, if the planning method is appointment based, the waiting times will increase. In both cases, the average access time will increase.  Intervention 3: The planning policy to schedule a maximum number of appointments per day affects the one stop shop percentage and waiting time at both locations. At Almelo, this leads to extra waiting time for the nurse and anesthesiologist but to a shorter average access time as well. At Hengelo, a lower one stop shop percentage leads to shorter waiting times for a nurse and anesthesia assistant, and increases the average access time. A reason for the increase in access time is that not enough timeslots are available per week. We conclude that intervention 3 has a positive influence on patient satisfaction. However other timeslot intervals and more flexibility of the system are needed to deal with the percentage of consent on time. v  Intervention 4: We analyzed the effect of combining intervention 2 and 3 and compare the results with intervention 3. We find that intervention 4 has a negative effect on the waiting times and access time at Almelo, and a positive effect at Hengelo. When we compare this intervention with intervention 3, we find that the waiting time increases in Almelo and decreases in Hengelo. A significant influence on these changes is the timeslot interval and the one stop shop percentage per day. Additionally, we find that the access times increase at both locations. A cause for this increase is that the access time is influenced by the division of the percentages per day. If there are more (sequential) days with a percentage below the average percentage, the access time will increase. We conclude that when intervention 4 is implemented and timeslots are used that fit the average consultation time, the average waiting time will decrease and the access time will increase.  Intervention 5: This intervention focuses on the timing policy. We found that a late timing policy has a negative influence on the percentage of patients with consent on time when the timing policy is later than 0.80. For timing policies between 0.35 and 0.80 there is only a slight difference in consent on time and waiting times. For earlier timing policies, the effect depends on the planning system. We conclude that changing the timing of the appointments has significant influence on the percentage of patients with consent on time, the access times, and the waiting times. Hereby, the effect depends on the planning policy. However, in general, an early timing policy leads to higher waiting times, but to lower access times as well.  Intervention 6: The final intervention on a tactical level is changing the timeslot intervals to better fit the current consultation times. At Almelo, planning more time for an ASA score 3 patient in combination with planning less time for ASA score 1 patients decreases the average waiting time. Changing the intervals at Hengelo has a negative effect on the waiting times for the nurse and anesthesiologist, which may be cause by using an appointment time which is slightly smaller than consultation times We conclude that changing the appointment interval to better fit the consultation times can improve the waiting times. However, an appointment interval that is slightly smaller than the consultation time is not improving the outcomes. An appointment interval that is equal to or slightly larger than the average consultation time is advised. When comparing the interventions, we find that in most cases is a negative correlation between the waiting and access time. Furthermore, there are several tactical interventions that improve the waiting time without influencing the access time and vice versa. Overall, the effect of the intervention differs and deciding which of these interventions is more desirable is up to the management. When implementing the interventions only some minor changes may be necessary. We recommend further research on the current discrepancies in process and policies. For example, research on the different processes depending on the ASA scores, the ECG machine at Hengelo, hiring a nurse practitioner instead of an anesthesia assistant, policy when a patient is sent for extra examination. Other recommendations are investigating the patient preferences, changing the opening hours to let more patients walk-in, and integrating an integral planning method with the policlinics. With the latter is meant that if a patient has an appointment to visit a policlinic, an appointment is immediately planned for the PAC as well.
Item Type:Essay (Master)
Clients:
Ziekenhuisgroep Twente
Faculty:BMS: Behavioural, Management and Social Sciences
Subject:85 business administration, organizational science
Programme:Industrial Engineering and Management MSc (60029)
Link to this item:http://purl.utwente.nl/essays/61702
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