ASERVICE-TIMEPREDICTIONMODELINSIMULATIONOFQUEUING ANALYSIS FOR DECISION SUPPORT IN HEALTHCARE

Authors

  • Quraishah,NasserYahya Z, AlGirad,SalemAliH, Almuneef,MohammedAliS, AlDaghman,HussainAbdulhadi, Alsulaiman,JaberMutarid, AlQirad,HashilAliH, AlGaraishah,ZaidYahiaZ, Albakri,MohammadAbduallah, AlMutaredMohammedHadi S,

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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Published

2023-10-21

How to Cite

Quraishah,NasserYahya Z, AlGirad,SalemAliH, Almuneef,MohammedAliS, AlDaghman,HussainAbdulhadi, Alsulaiman,JaberMutarid, AlQirad,HashilAliH, AlGaraishah,ZaidYahiaZ, Albakri,MohammadAbduallah, AlMutaredMohammedHadi S,. (2023). ASERVICE-TIMEPREDICTIONMODELINSIMULATIONOFQUEUING ANALYSIS FOR DECISION SUPPORT IN HEALTHCARE. Chelonian Research Foundation, 18(1), 311–336. Retrieved from https://acgpublishing.com/index.php/CCB/article/view/236

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