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- Publisher Website: 10.1109/TCSS.2022.3212121
- Scopus: eid_2-s2.0-85141446866
- WOS: WOS:001123580500029
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Article: Critical Department Analysis for Large-Scale Outpatient Systems
Title | Critical Department Analysis for Large-Scale Outpatient Systems |
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Authors | |
Keywords | Bottleneck critical department demand surge (DS) healthcare large-scale systems outpatient patient satisfaction ranking simulation supply enhancement (SE) supply loss (SL) |
Issue Date | 28-Oct-2022 |
Publisher | Institute of Electrical and Electronics Engineers |
Citation | IEEE Transactions on Computational Social Systems, 2023, v. 10, n. 6, p. 3194-3203 How to Cite? |
Abstract | Abstract— Identifying critical department(s) to enhance the supply in large-scale systems is beneficial to support the system efficiency. Large-scale outpatient systems (LSOSs) are usually faced with crowdedness and, hence, require critical departmental improvement to maintain patient satisfaction under a limited budget. Besides, when demand surges (DSs) or physicians are absent [supply loss (SL)], critical department identification becomes one of the key steps to resilient clinical management. To improve the clinical services and mitigate the risk of disruptions efficiently, we conduct critical department analysis under three scenarios: one clinical improvement scenario [supply enhancement (SE)] and two clinical disruption scenarios (DS and SL). These scenarios can happen in different departments in varying time sessions (e.g., am or pm). We define the criticality of a department as the change of patient satisfaction with respect to the change of departmental supply and demand. We accordingly propose a simulation-based ranking method and implement a case study in an LSOS. The simulation results show that the criticality of the department highly depends on the time session. Surprisingly, SE may reduce patient satisfaction when the supply increases in several specific departments. Key findings and managerial insights are further discussed. |
Persistent Identifier | http://hdl.handle.net/10722/339997 |
ISSN | 2023 Impact Factor: 4.5 2023 SCImago Journal Rankings: 1.716 |
ISI Accession Number ID |
DC Field | Value | Language |
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dc.contributor.author | Zou, Chengye | - |
dc.contributor.author | Wang, Junwei | - |
dc.contributor.author | Cheng, Yao | - |
dc.date.accessioned | 2024-03-11T10:40:54Z | - |
dc.date.available | 2024-03-11T10:40:54Z | - |
dc.date.issued | 2022-10-28 | - |
dc.identifier.citation | IEEE Transactions on Computational Social Systems, 2023, v. 10, n. 6, p. 3194-3203 | - |
dc.identifier.issn | 2329-924X | - |
dc.identifier.uri | http://hdl.handle.net/10722/339997 | - |
dc.description.abstract | <p>Abstract— Identifying critical department(s) to enhance the supply in large-scale systems is beneficial to support the system efficiency. Large-scale outpatient systems (LSOSs) are usually faced with crowdedness and, hence, require critical departmental improvement to maintain patient satisfaction under a limited budget. Besides, when demand surges (DSs) or physicians are absent [supply loss (SL)], critical department identification becomes one of the key steps to resilient clinical management. To improve the clinical services and mitigate the risk of disruptions efficiently, we conduct critical department analysis under three scenarios: one clinical improvement scenario [supply enhancement (SE)] and two clinical disruption scenarios (DS and SL). These scenarios can happen in different departments in varying time sessions (e.g., am or pm). We define the criticality of a department as the change of patient satisfaction with respect to the change of departmental supply and demand. We accordingly propose a simulation-based ranking method and implement a case study in an LSOS. The simulation results show that the criticality of the department highly depends on the time session. Surprisingly, SE may reduce patient satisfaction when the supply increases in several specific departments. Key findings and managerial insights are further discussed.<br></p> | - |
dc.language | eng | - |
dc.publisher | Institute of Electrical and Electronics Engineers | - |
dc.relation.ispartof | IEEE Transactions on Computational Social Systems | - |
dc.subject | Bottleneck | - |
dc.subject | critical department | - |
dc.subject | demand surge (DS) | - |
dc.subject | healthcare | - |
dc.subject | large-scale systems | - |
dc.subject | outpatient | - |
dc.subject | patient satisfaction | - |
dc.subject | ranking | - |
dc.subject | simulation | - |
dc.subject | supply enhancement (SE) | - |
dc.subject | supply loss (SL) | - |
dc.title | Critical Department Analysis for Large-Scale Outpatient Systems | - |
dc.type | Article | - |
dc.identifier.doi | 10.1109/TCSS.2022.3212121 | - |
dc.identifier.scopus | eid_2-s2.0-85141446866 | - |
dc.identifier.volume | 10 | - |
dc.identifier.issue | 6 | - |
dc.identifier.spage | 3194 | - |
dc.identifier.epage | 3203 | - |
dc.identifier.eissn | 2329-924X | - |
dc.identifier.isi | WOS:001123580500029 | - |
dc.identifier.issnl | 2329-924X | - |