ANALYSIS ON PATIENT WAITING TIME IN EMERGENCY INSTALLATION: A CASE STUDY OF JKL HOSPITAL - Siddiq Purwongemboro, Muhammad
The Healthcare Industry can be considered to be one of the most complex industries. In a healthcare delivery system, patients are typically the customers and hospitals are the service facilities. Among the departments in a hospital, the Emergency Installation can be considered to be an integral part, due to ppatients would reflect the quality of the hospital based on their experience in the emergency installation. Due to the number of patients with different priorities, the emergency installation is susceptible to waiting time. Based this consideration, this research would follow the treatment process in the emergency installation of JKL Hospital. There is evidence that suggest as much as 66% of patient that needs hospitalization would need to wait for more than 6 hours in JKL Hospital’s emergency installation before they can be transported to the Inpatient Ward. Analyzing the emergency treatment process, it is found that there are three process groups that greatly contributed to patient waiting time in JKL Hospital, which is the "Patient In-Depth Examination" process, the "Inpatient Therapy Prescription" process, and the "Inpatient Bed Confirmation" process. The delay in these three groups would result in longer patient waiting time. The root cause of the delay in the process would then be analyzed using Current Reality Tree (CRT) method. The result of the CRT suggests there are six root causes, in which three root causes is selected to be addressed: 1) the availability of machine for conducting lab test, 2) the absence of clinical pathway/practice guideline for common emergency cases, and 3) the delay in patient transportation to the inpatient ward due to Bedside Shift Report still done manually. Using the result of the root cause analysis as the basis, the solution for these issues is then formulated. Three solutions are formulated, which is: Solution 1) Increasing additional operable testing machine, Solution 2) Digitalization of the Bedside Shift Report process, and Solution 3) Utilizing Machine Learning Model to develop the clinical pathway/practice guide. Because each of these solutions refers to a different issue, several combinations of these solutions have been devised. Using Analytical Hierarchy Process (AHP) technique with four criteria of desired solution, which is Cost, Difficulty, Effectiveness, and Maintenance, it is found that the optimal result based in these criterias would be the combination of Solution 1) and Solution 2). The implications of the selected solution are then presented, along with the implementation plan of the solution.