Big Data for the Sustainability of Healthcare Project Financing

Roberto Moro Visconti, Donato Morea*

*Autore corrispondente per questo lavoro

Risultato della ricerca: Contributo in rivistaArticolo in rivistapeer review

Abstract

This study aims to detect if and how big data can improve the quality and timeliness of information in infrastructural healthcare Project Finance (PF) investments, making them more sustainable and increasing overall efficiency. Interactions with telemedicine or disease management and prediction are promising but still underexploited. However, given the rising health expenditure and shrinking budgets, data-driven cost-cutting is inevitably required. An interdisciplinary approach combines complementary aspects concerning big data, healthcare information technology, and PF investments. The methodology is based on a business plan of a standard healthcare Public-Private Partnership (PPP) investment, compared with a big data-driven business model that incorporates predictive analytics in different scenarios. When Public and Private Partners interact through networking big data and interoperable databases, they boost value co-creation, improving Value for Money and reducing risk. Big data can also help shortening supply chain steps, expanding economic marginality and easing the sustainable planning of smart healthcare investments. Flexibility, driven by timely big data feedbacks, contributes to reducing the intrinsic rigidity of long-termed PF healthcare investments. Healthcare is a highly networked and systemic industry that can benefit from interacting with big data that provide timely feedbacks for continuous business model re-engineering, reducing the distance between forecasts and actual occurrences. Risk shrinks and sustainability is fostered, together with the bankability of the infrastructural investment.
Lingua originaleEnglish
pagine (da-a)1-17
Numero di pagine17
RivistaSustainability
Volume11
DOI
Stato di pubblicazionePubblicato - 2019

Keywords

  • business model innovation
  • data mining
  • healthcare informatics
  • healthcare management.
  • internet of health
  • interoperability
  • networks
  • predictive analytics
  • public-private partnership
  • value chain

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