Different scenarios/ “What if?” conditions were simulated during the operationalization of NCI OPD to facilitate decision making. In all the scenarios the focus was on improving the overall patient experience by optimally deploying and utilizing resources. The parameters include average patient waiting times, census, throughput, staff utilization parameters, utilization of screening rooms, utilization of DMG [Disease Management Group] rooms and time at which OPD finishes. The dashboards function in the software provides a real time update on these parameters and thus it is easy to obtain a longitudinal trend over period of time.
The decision points were for deployment of staff [different cadres], size of the waiting area andopening up of additional floors for patient care with focus on better patient experience. The simulation model has helped to strike a fine balance to minimize the waiting times by optimally deploying resources. The general tendency towards blanket increase in manpower could be circumvented as the models provided a real time picture of staff utilizations and staff state times. They also helped to identify the main bottlenecks in the overall process.
The process flow of patients at cancer institute is that the patient first goes to the screening room where the doctor first screens and decides if the patient has to be registered under the institute. Subsequently the patient goes to the registration counter, gets the card made and proceeds to the DMG [Disease Management Group] room where detailed evaluation is done. Subsequently the patient goes to the SWEC [Single Window Exit Counter] where fees for tests are paid, and then samples are drawn in the sample collection area by a lab technician, following which the patient leaves the OPD. [Figure 1]
The different scenarios that were modeled are as under:
The initial patient load was about 40 patients per day. The resources deployed were 2 screening rooms [with 2 doctors], 2 DMG rooms [with 2 doctors], 1 receptionist, 2 PCCs [patient Care Coordinators] and 1 lab technician. With these resources the OPD finished at 3 pm which was also what we could see on ground. [Figure 2]
The peak census at any given point of time was 25, based on which the capacity of waiting area was kept at 30 initially. This helped to provide seating for patients while they wait for consultation. We could see that utilization of DMG rooms [83.58%] and utilization of doctors in DMG rooms [83.5%] was high and was likely to become a bottleneck with any increase in workload. The staff state times also reflected the same. The utilization of receptionists however was barely around 11% which clearly indicated that there was no need to augment in near future. The average waiting time for patients was around 100 minutes towards the end of the OPD.
In the second scenario patient load was increased to 60 patients per day in the simulation model. With the same resources as in scenario 1, the OPD did not finish at 3pm. Instead 20 patients were yet to be seen with average waiting time of 115 minutes. Utilization of DMG rooms and doctors in DMG rooms was around 89%. The utilization of screening rooms and doctors there was about 83%. The average state times of the doctors and patients reflected the same. The peak census crossed 40 patients. The capacity of the waiting hall was increased to 50 which provided seating arrangements for patients waiting. The OPD got over around 5pm which was corroborated on ground. [Figure 3]
In the third scenario patient load the patient load was increased to 100 patients per day with the same resources in scenario 1 and simulation was run. The OPD did not finish at 3pm and 58 patients were still waiting to be seen at 3pm. The peak census had crossed 80 which called for more waiting area. The average wait time increased to 138 minutes. Utilization of screening rooms and doctors there had crossed 93% and utilization of DMG rooms and their doctors had crossed 91%. The staff state times reflected the same. Utilization of reception area, lab area, lab technicians, receptionists and PCCs all remained barely around 20%. [Figure 4]
In the fourth scenario the manpowerwas increased for a patient load of 100 patients per day in the simulation. Based on the staff utilization seen in scenario 3, additional 1 doctor was deployed in screening area and 2 additional doctors deployed in DMG rooms. That makes a total of 3 doctors in screening area and 4 doctors in DMG rooms. There were some improvements with average waiting time coming down to 128 minutes, with about 24 patients remaining to be seen at 3pm in the OPD waiting area.
The utilization of DMG rooms and its doctors cooled down to 81% but utilization of screening room and its doctors continued to be more than 90%. The peak census came down to little above 60 which decreased the waiting area required. The utilization of other staff increased but continued to be around 40%. [Figure 5]
In the fifth scenario an additional floor was opened to cater to the load of 100 patients per day. Based on utilization figures from scenario 4, the screening room was found to be the bottleneck. Therefore all the DMG rooms were now shifted to the first floor and capacity of screening rooms increased in ground floor. With the increased manpower and additional floor opened, the OPD finished at 2:10 pm itself with average waiting time dropping dramatically to 81 minutes. The utilization of screening room and its doctors cooled down to around 81% and that of DMG rooms and its doctors hovered around 82%.The peak census came down to a little below 60 which decreased the need for any further expansion of waiting areas. The utilization of other staff slightly increased but still didn’t mandate any further augmentation. [Figure 6]
The results are summarized in Table 1 for different scenarios.