Development of orthopaedic outpatient clinic scheduling information system for performance improvement

Long patients’ waiting time (PWT) and clinic overtime are common problems encountered in outpatient clinics. These usually occur in high demand clinics such as orthopaedics and cardiology. The Orthopaedic Specialist Outpatient Clinic of Hospital Serdang, Malaysia (OSOC) is facing same problems. In 2010, OSOC was successful in achieving its targeted average PWT, as prescribed in its Key Performance Index (KPI) in only three months of the year. The current study was conducted in OSOC with the aim of reducing PWT and overtime works of its staff through computer-based modelling and simulation. Problem areas requiring improvement include appointment system,resources allocation and patients flow. First, the processes in the OSOC were studied based on interviews, observation and research to ensure the system was well understood before the modelling commenced. Through this approach, the underlying causes within the system that contribute to long PWT were identified. Next, over a two-week period,data collections were performed in the clinic to obtain required data for modelling and simulation. Concurrently, additional patient data over the survey period were obtained from the OSOC. Based on these data, a computer model simulating the current operations within the OSOC, named “Current Orthopaedic Outpatient Clinic” (hereafter referred to as the “Current System”) was generated using the SIMUL8 computer software package (SIMUL8 Corporation). Validation and verification of these outputs were conducted on Current System models to ensure the integrity and accuracy of the system and its input parameters. Furthermore, baseline benchmarks on several key performance indicators were obtained. Through this process, the causes of current problems in OSOC were identified. Subsequently, a new computer simulated model, named “Improved System” was generated in which the constraints identified within the Current System have been eliminated or modified. The KPI of the Improved System was next compared with that of the Current System to determine whether the implemented changes indeed result in improvement the performance of OSOC. To this end, sensitivity analyses were carried out to determine the responsiveness of the Improved System to the changes, such as number of appointments, “no-show” rate or forced booking. Based on these simulations, these modifications would reduce the PWT significantly in the Improved System, compared with existing system. Furthermore, the entire simulated clinic sessions satisfied the criteria outlined in the clinic’s KPI. As an additional benefit,90% of the clinic sessions simulated under Improved System’s parameters greatly improved clinic end time. In the sensitivity analyses, the new model demonstrates an ability to respond differently under various input parameters. In conclusion, the results of this study demonstrate that PWT in outpatient clinic can be significantly reduced by 53.7-97% after applying the improved settings revealed by computer-assisted modelling.

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