ASERVICE-TIMEPREDICTIONMODELINSIMULATIONOFQUEUING ANALYSIS FOR DECISION SUPPORT IN HEALTHCARE
Abstract
TheRadiologyDepartmentofahospitalinNajrancityinSaudiArabiaisseekingwaysto improve patient experienceandusecurrentresourcesmoreefficientlyastheyfacegrowingvisitsnumbersof patients. This study's identified primary key performanceindicatorsarepatient’swaitingtimeandstaff’sidletime.Theimpactonpatientwaitingtime andradiographers'idletimewereexploredinthisstudybyusingdataminingtechniquesto predict the servicetime. Thesame simulation technique is used tostudythe impact ofassigninga type of patients to a fast track, or separate unit for low- acuitypatientsintheRadiologyDepartmentusinganoperationalresearchqueue-basedMonteCarlo simulation in a spreadsheet-based decision support tool.The model combinedtheprinciplesofqueuingtheory.Inaddition,itexpandedthediscreteeventsimulationinordertoaccountforpatients'arrivaltimerateand service time. In addition, the Departmentqueuesystemwasdesignedandanalyzedbyusingthesimulationmodel.Thepredictionmodel has been deployed into thedecisionsupporttool.Developingthistoolaims toanalyzetheeffectofchangingparticularaspectsofthesystemonthetotalwaitingtime.Thesimulationin dicatesthatthemainproblemisnottheshortageofresources,butitisineffectivequeuesystemmanagement.Simulationresultsexhibitedthattheability toaccurately predict the servicetime andassignpatientstoaparticulartypeofscanningroomlikeafasttrackminimizedoverall averagewaitingtimes48.6minutesto40.4minutesinthedepartmentduringoperationhours. This modeling approach with adecision support tool could be efficiently distributed and inform healthcaredecision-makersofimplementingafasttrackorcomparablesystemonpatients'waitingtimes.
Keywords:Service-TimePrediction,SimulationofQueuingAnalysis,DecisionSupport, Healthcare.
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