Big Data for the Sustainability of Healthcare Project Financing

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 their overall efficiency. Interactions with telemedicine or disease management and prediction are promising but are still underexploited. However, given 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 by 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.

The Impact of Big Data Analytics on Company Performance in Supply Chain Management

“…Thus, a first attempt to define BDA is based on the 3V framework: (1) weekly generated data volume greater than 300 TB classifies companies in the BDA category; (2) the velocity of data creation and transmission plays a key role in transferring data from batch processing to real-time operation; and (3) the variety of data provided to users can include, in addition to classical SQL or XML formats, digital information such as video, text, or images [7]. Starting from this attempt to define BDA within the supply chain, some specialists have presented other approaches: (1) the process of extracting and presenting supply-chain information to ensure measurement, monitoring, forecasting, and supply-chain management [31]; (2) a broad and unique view of the entire supply chain to disclose component or full production, including analyses and key performance indicators (KPIs) [32]; (3) using quantitative methods to obtain prospective information from data in order to understand in depth what is going upstream and downstream, in order to assess the operational decision-making impact of the supply chain [33]; (4) the operational leap from data response management models that can help specialists analyze larger datasets using proven analytical and mathematical techniques [34]; and (5) the combination resulting from the application of quantitative and qualitative methods to SCM theory to solve SCM problems and predict results, taking into account the quality and availability of data [35].…”

“…To understand this impact, we need to take into account the following key features: (1) the number of entities in the supply chain; (2) the diversity of entities; (3) the existing interdependence between items, products, and supply-chain partners; (4) the dynamics of the system, represented by variety; and (5) the existence of uncertainties. The great interest of specialists is shown by the empirical studies undertaken, which highlight several advantages of BDA within EMS, such as reducing operational costs, increasing customer satisfaction, and increasing SC agility [35,[54][55][56].…”

“…According to specialist studies, several constraints have been identified in the adoption/implementation of BDA in SCM: technological barriers, expertise, and investment barriers, data barriers, organizational barriers, etc. In the category of technological barriers, the following issues were identified as the basis for BDA implementation in SCM: (1) a lack of understanding of the implementation of new technologies or a lack of tools needed to implement BDA in SCM [54]; (2) a lack of infrastructure facilities [71][72][73]; (3) low acceptance, routine, and BDA assimilation by SCM organizations and partners [73,74]; and (4) data security [35,75].…”

Visitor-Sensing: Involving the Crowd in Cultural Heritage Organizations

“…Visitors who actively participate to the management of cultural heritage organizations will also be, per se, more satisfied in that they contribute to a public good, and this increased satisfaction may encourage them to further visit the museum and to engage in positive word of mouth referrals. All this will translate into greater numbers of visitors, with positive impacts on both the economic sustainability of museums, in terms of increased revenues, and their social sustainability, in terms of a wider audience reached and increased literacy of citizens, which are two crucial aspect of the sustainability tripod to which organizations are increasingly paying attention [27,[79][80][81][82][83][84][85][86][87]. The above-mentioned issues are relevant issues for both cultural heritage organizations and policymakers [28,56], thereby benefiting simultaneously the two logics which characterize hybrid organizations [55,88].…”

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

“…PPPs have become popular worldwide as a way of improving healthcare service delivery, [29,30], and are typically associated with PF [31]. Healthcare PPPs have the potential to generate several benefits, including (i) better investment decisions, (ii) more efficient infrastructure delivery, and (iii) higher quality health services.…”