The management of the Integrated Healthcare Operating Systems (IHOSs) requires more and more to improve efficiency and resilience. We conceptualize the IHOS as a supply chain made up of operating units interacting among each other to accomplish a common goal (the care), resulting from the adoption of Integrated Care Pathways (ICPs). Then, we rely on supply chain management literature to develop theoretical propositions regarding the influence of complexity dimensions on the resilience and efficiency of IHOS. We also advance the existence of a direct and moderating role of Big Data Analytics on these performance and relationships.

The effect of complexity on the resilience and efficiency of integrated healthcare systems: the moderating role of big data analytics / Zaza, V.; Bisceglie, M.; Valerio, S.; Giannoccaro, I.. - 55:10(2022), pp. 2857-2862. (Intervento presentato al convegno 10th IFAC Conference on Manufacturing Modelling, Management and Control, MIM 2022 tenutosi a fra nel 2022) [10.1016/j.ifacol.2022.10.164].

The effect of complexity on the resilience and efficiency of integrated healthcare systems: the moderating role of big data analytics

Zaza V.;Giannoccaro I.
2022-01-01

Abstract

The management of the Integrated Healthcare Operating Systems (IHOSs) requires more and more to improve efficiency and resilience. We conceptualize the IHOS as a supply chain made up of operating units interacting among each other to accomplish a common goal (the care), resulting from the adoption of Integrated Care Pathways (ICPs). Then, we rely on supply chain management literature to develop theoretical propositions regarding the influence of complexity dimensions on the resilience and efficiency of IHOS. We also advance the existence of a direct and moderating role of Big Data Analytics on these performance and relationships.
2022
10th IFAC Conference on Manufacturing Modelling, Management and Control, MIM 2022
The effect of complexity on the resilience and efficiency of integrated healthcare systems: the moderating role of big data analytics / Zaza, V.; Bisceglie, M.; Valerio, S.; Giannoccaro, I.. - 55:10(2022), pp. 2857-2862. (Intervento presentato al convegno 10th IFAC Conference on Manufacturing Modelling, Management and Control, MIM 2022 tenutosi a fra nel 2022) [10.1016/j.ifacol.2022.10.164].
File in questo prodotto:
Non ci sono file associati a questo prodotto.

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11589/252024
Citazioni
  • Scopus 0
  • ???jsp.display-item.citation.isi??? 0
social impact