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Healthcare Digitalization and Pay-For-Performance Incentives in Smart Hospital Project Financing

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  • معلومة اضافية
    • بيانات النشر:
      MDPI, 2020.
    • الموضوع:
      2020
    • نبذة مختصرة :
      This study aims to explore the impact of healthcare digitalization on smart hospital project financing (PF) fostered by pay-for-performance (P4P) incentives. Digital platforms are a technology-enabled business model that facilitates exchanges between interacting agents. They represent a bridging link among disconnected nodes, improving the scalable value of networks. Application to healthcare public&ndash
      private partnerships (PPPs) is significant due to the consistency of digital platforms with health issues and the complexity of the stakeholder&rsquo
      s interaction. In infrastructural PPPs, public and private players cooperate, usually following PF patterns. This relationship is complemented by digitized supply chains and is increasingly patient-centric. This paper reviews the literature, analyzes some supply chain bottlenecks, addresses solutions concerning the networking effects of platforms to improve PPP interactions, and investigates the cost&ndash
      benefit analysis of digital health with an empirical case. Whereas diagnostic or infrastructural technology is an expensive investment with long-term payback, leapfrogging digital applications reduce contingent costs. &ldquo
      Digital&rdquo
      savings can be shared by key stakeholders with P4P schemes, incentivizing value co-creation patterns. Efficient sharing may apply network theory to a comprehensive PPP ecosystem where stakeholding nodes are digitally connected. This innovative approach improves stakeholder relationships, which are re-engineered around digital platforms that enhance patient-centered satisfaction and sustainability. Digital technologies are useful even for infectious disease surveillance, like that of the coronavirus pandemic, for supporting massive healthcare intervention, decongesting hospitals, and providing timely big data.
    • File Description:
      application/pdf
    • ISSN:
      1660-4601
      1661-7827
    • Rights:
      OPEN
    • الرقم المعرف:
      edsair.doi.dedup.....eb780cdaafeff4a2c997e44352ed69d4