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An intelligent real-time scheduler for out-patient clinics: A multi-agent system model.

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Title: An intelligent real-time scheduler for out-patient clinics: A multi-agent system model.
Authors: Munavalli, Jyoti R1 (AUTHOR) jyothimunavalli@gmail.com, Rao, Shyam Vasudeva2 (AUTHOR), Srinivasan, Aravind3 (AUTHOR), van Merode, GG4 (AUTHOR)
Source: Health Informatics Journal. Dec2020, Vol. 26 Issue 4, p2383-2406. 24p.
Subject Terms: *Algorithms, Analysis of variance, Health care rationing, Health services administration, Outpatient services in hospitals, Interviewing, Medical appointments, Medical needs assessment, Medical informatics, Descriptive statistics
Geographic Terms: India
Abstract: Scheduling of resources and patients are crucial in outpatient clinics, particularly when the patient demand is high and patient arrivals are random. Generally, outpatient clinic systems are push systems where scheduling is based on average demand prediction and is considered for long term (monthly or bimonthly). Often, planning and actual scenario vary due to uncertainty and variability in demand and this mismatch results in prolonged waiting times and under-utilization of resources. In this article, we model an outpatient clinics as a multi-agent system and propose an intelligent real-time scheduler that schedules patients and resources based on the actual status of departments. Two algorithms are implemented: one for resource scheduling that is based on predictive demand and the other is patient scheduling which performs path optimization depending on the actual status of departments. In order to match resources with stochastic demand, a coordination mechanism is developed that reschedules the resources in the outpatient clinics in real time through auction-bidding procedures. First, a simulation study of intelligent real-time scheduler is carried out followed by implementation of the same in an outpatient clinic of Aravind Eye Hospital, Madurai, India. This hospital has huge patient demand and the patient arrivals are random. The results show that the intelligent real-time scheduler improved the performance measures like waiting time, cycle time, and utilization significantly compared to scheduling of resources and patients in isolation. By scheduling resources and patients, based on system status and demand, the outpatient clinic system becomes a pull system. This scheduler transforms outpatient clinics from open loop system to closed-loop system. [ABSTRACT FROM AUTHOR]
Copyright of Health Informatics Journal is the property of Sage Publications Inc. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Education Research Complete
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DbLabel: Education Research Complete
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PubType: Academic Journal
PubTypeId: academicJournal
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  Data: An intelligent real-time scheduler for out-patient clinics: A multi-agent system model.
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  Data: Scheduling of resources and patients are crucial in outpatient clinics, particularly when the patient demand is high and patient arrivals are random. Generally, outpatient clinic systems are push systems where scheduling is based on average demand prediction and is considered for long term (monthly or bimonthly). Often, planning and actual scenario vary due to uncertainty and variability in demand and this mismatch results in prolonged waiting times and under-utilization of resources. In this article, we model an outpatient clinics as a multi-agent system and propose an intelligent real-time scheduler that schedules patients and resources based on the actual status of departments. Two algorithms are implemented: one for resource scheduling that is based on predictive demand and the other is patient scheduling which performs path optimization depending on the actual status of departments. In order to match resources with stochastic demand, a coordination mechanism is developed that reschedules the resources in the outpatient clinics in real time through auction-bidding procedures. First, a simulation study of intelligent real-time scheduler is carried out followed by implementation of the same in an outpatient clinic of Aravind Eye Hospital, Madurai, India. This hospital has huge patient demand and the patient arrivals are random. The results show that the intelligent real-time scheduler improved the performance measures like waiting time, cycle time, and utilization significantly compared to scheduling of resources and patients in isolation. By scheduling resources and patients, based on system status and demand, the outpatient clinic system becomes a pull system. This scheduler transforms outpatient clinics from open loop system to closed-loop system. [ABSTRACT FROM AUTHOR]
– Name: AbstractSuppliedCopyright
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  Data: <i>Copyright of Health Informatics Journal is the property of Sage Publications Inc. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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RecordInfo BibRecord:
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    Identifiers:
      – Type: doi
        Value: 10.1177/1460458220905380
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      – Code: eng
        Text: English
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      Pagination:
        PageCount: 24
        StartPage: 2383
    Subjects:
      – SubjectFull: Algorithms
        Type: general
      – SubjectFull: Analysis of variance
        Type: general
      – SubjectFull: Health care rationing
        Type: general
      – SubjectFull: Health services administration
        Type: general
      – SubjectFull: Outpatient services in hospitals
        Type: general
      – SubjectFull: Interviewing
        Type: general
      – SubjectFull: Medical appointments
        Type: general
      – SubjectFull: Medical needs assessment
        Type: general
      – SubjectFull: Medical informatics
        Type: general
      – SubjectFull: Descriptive statistics
        Type: general
      – SubjectFull: India
        Type: general
    Titles:
      – TitleFull: An intelligent real-time scheduler for out-patient clinics: A multi-agent system model.
        Type: main
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            NameFull: Munavalli, Jyoti R
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            NameFull: Rao, Shyam Vasudeva
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            NameFull: Srinivasan, Aravind
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            NameFull: van Merode, GG
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          Dates:
            – D: 01
              M: 12
              Text: Dec2020
              Type: published
              Y: 2020
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              Value: 14604582
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              Value: 26
            – Type: issue
              Value: 4
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            – TitleFull: Health Informatics Journal
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