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Care for Walk-in : organizing a walk-in based preoperative assessment clinic in University Medical Centre Utrecht

Wolbers, Pieter (2009) Care for Walk-in : organizing a walk-in based preoperative assessment clinic in University Medical Centre Utrecht.

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Abstract:Patients that are planned for elective surgery need an individualized plan regarding their anesthesia. As part of the preoperative process, the patient is therefore assessed by an anesthetist. One of the ways to organize this assessment is by means of a Preoperative Assessment Clinic (PAC), where patients visit an anesthetist a couple of days or weeks in advance of surgery. In University Medical Centre Utrecht (UMCU), management decided that the PAC should be organized on a walk-in basis: patients should be able to visit the PAC directly after having visited the outpatient clinic. Currently, the PAC uses an appointment system so that all patients need to return to the hospital on a later day. At the same time, current waiting times are experienced to be too high. This research focuses on the organization of a walk-in based PAC that minimizes waiting times. We use various data sources to study the current design of the preoperative process and the design and performance of the PAC: 1. Data set regarding all mutations in the appointment system of both the outpatient clinics and the PAC. 2. Data set containing an overview of registrations on the surgery waiting lists. 3. Data from the information system used by the anesthetists that gives the number of registered assessments. 4. Paper records of the number of patients assessed at the PAC. 5. A time motion study performed at the PAC. 6. A patient survey for patients that visited the PAC. 7. Data regarding the number of inpatient and outpatient surgeries. The time motion study is used to quantify patient throughput at the PAC. In UMCU, patients are either assessed by an anesthesiology trained nurse or a resident. We show that the expected waiting time per provider substantially differs (22 minutes for a nurse and 38 minutes for a resident). Regarding the design and performance of the PAC we additionally conclude that: 1. 35% of all patients wait longer than 30 minutes. 2. Digitalizing the questionnaires at the clerk desk requires too much time. 3. The current design of the appointment system is not transparent due to the differentiation to specialties, user-groups, and appointment types. 2 CARE FOR WALK-IN 4. An appointment slot size of 30 minutes might not be sufficient for residents. 5. Making an ECG takes the patient 20 minutes on average; 25% of the patients need more than 25 minutes. 6. Appointments in the morning start with a delay (high provider tardiness). The results of the patient survey suggests that an average waiting time between 15 and 20 minutes is acceptable. We find that the estimation of the future number of walk-ins is complicated by the fact that the number of patients that visit the outpatient clinics heavily fluctuates per day as well as during the day. Furthermore, we have no information about the preference of the patient to visit the PAC on walk-in. We analyze five interventions that might improve waiting time: Intervention A1: An alternative schedule for TCs. Intervention A2: Excluding the ECGs. Intervention A3: Decreasing the (effective) service time at the clerk desk by 50%. Intervention A4: Decreasing the (effective) service time of residents by 50%. Intervention A5: Scheduling patients directly to providers. Based on an extensive data analysis, we derive the number of walk-ins per hour of the day. We suggest two alternative appointment systems that reserve capacity for walk-ins: one based on an appointment slot size of 30 minutes per provider, the other based on an appointment slots size of 40 minutes for residents and 30 minutes for nurses. We design a discrete-event simulation model of the PAC and use it to study the effect of various process interventions. The model also includes functionality to evaluate appointment systems under walk-in conditions. By means of the simulation model, we conclude that: 1. Excluding ECGs and balancing TCs over the day does not (greatly) improve waiting times. 2. Decreasing the processing time at the clerk desk by 50% improves the expected waiting time by 5 to 6 minutes on average. 3. Decreasing the preparation time of residents by 50% reduces the expected waiting time for a resident by 13 to 14 minutes on average. 4. Assigning patients directly to providers when scheduling appointments reduces waiting time by 2.5 to 3 minutes for nurses and 4 to 6 minutes for residents. 5. The combined effect of (2), (3), and (4) equals the sum of the individual interventions. Waiting times can be reduced by 7 to 8 minutes for nurses and 21 to 23 minutes for residents. 6. An appointment system that incorporates a 40 minute slot size for residents slightly outperforms one than incorporates 30 minutes. 7. It is essential that most appointments are scheduled in the morning and that workload is evenly balanced over the week. If these criteria are not met, the PAC risks that staff members need to work in overtime (after 4 PM). 3 8. An appointment system based on the criteria of (7) in combination with the process intervention of (5) suggest that the PAC can be successfully organized on walk-in and at the same time drastically reduce waiting times. At the time of publication of this report, implementation had not yet started. Although we believe our data analysis gives a good indication of the future number of walk-ins, possible deviations from our estimation must be addressed as soon as possible during implementation. We therefore support future implementation with a computer tool that can be used to register all walk-in patients that visit the PAC. This allows the PAC to easily evaluate the number of walk-ins per hour per day and consequently the robustness of the appointment system that has been implemented. Our research leaves an extensive database regarding the preoperative process in general and the PAC in particular. Our simulation model provides the means for management to study various process interventions. The model is suitable for modeling other (outpatient) clinics given some slight modifications.
Item Type:Essay (Master)
Clients:
University Medical Center, Utrecht
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/60433
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