• Media type: E-Article
  • Title: Operations management of outpatient chemotherapy process : an optimization-oriented comprehensive review
  • Contributor: Hadid, Majed [VerfasserIn]; Elomri, Adel [VerfasserIn]; El Mekkawy, Tarek [VerfasserIn]; Jouini, Oualid [VerfasserIn]; Kerbache, Laoucine [VerfasserIn]; Hamad, Anas [VerfasserIn]
  • imprint: 2022
  • Published in: Operations research perspectives ; 9(2022), Artikel-ID 100214, Seite 1-29
  • Language: English
  • DOI: 10.1016/j.orp.2021.100214
  • Identifier:
  • Keywords: Outpatient ; Chemotherapy ; Process ; Cancer ; Oncology ; Hematology ; Healthcare ; Patient pathways ; Operations management ; Operations research ; Optimization models ; Content analysis ; Social network analysis ; Aufsatz in Zeitschrift
  • Origination:
  • Footnote:
  • Description: orldwide, chemotherapy centers that provide outpatient services face significant challenges owing to increased demand and limited resources. Therefore, outpatient chemotherapy process (OCP) optimization has attracted the attention of operations management scholars. This review seeks to provide a comprehensive analysis of existing quantitative optimization-oriented research that addresses OCP problems and identifies departure points for future research. Various scientific databases were searched to collect the maximum number of OCP optimization-oriented publications. Bibliometric data mining tools were used to provide descriptive analyses of the publications. The OCP optimization-oriented research framework was obtained through social network analysis of the formulation narratives of the models. Content analysis was performed to classify the literature based on several optimization-oriented perspectives. From 1500 publications, 45 studies were screened and included in the review. The current literature lacks a holistic solution to OCP challenges, as most publications are pure optimization studies that consider narrow scopes and idealized problems. This review proposes future research opportunities based on the gaps discovered, which may lead to more insightful results for real-life OCP problems.
  • Access State: Open Access
  • Rights information: Attribution - Non Commercial - No Derivs (CC BY-NC-ND)