Quantitative Benchmarks for the Healthcare Industry

The healthcare sector is characterised by a long standing data abundance but up to now, this invaluable source of data hasn't been used due to the high sensitivity of this data, aside the privacy issues in analyzing it due to the potential re-identification of patients. Despite the scarce usage, the sector sees a wide range of beneficial applications for BDA adoption both strictly related to patients (quality of care optimisation, illness/disease diagnosis and progression, etc.) but also more general ones related to regulatory intelligence (acting upon the understanding of regulation to legally treat data) and fraud prevention and detection. Within quality of care optimisation there are several different sub use cases, from availability of hospital beds, to management of treatment's slots, to resource allocation – people and technical sources). Within this context, the increased availability of data, computational resources and the current development of privacy preserving technologies, can potentially and largely improve resource usage and optimisation. As often healthcare services and structures are government owned, cost reduction was the only relevant KPI in the past, with scarce interest in increasing profits and margins, but with shrinking budgets also the potential revenue stream creation is essential to the healthcare sector. Among the most relevant use cases, and bridging use cases with KPIs, we find quality of care optimisation. This use case is largely evaluated by profit increase because the quality of care is both related to patients' satisfaction (like customer satisfaction) but also to optimisation of services and avoiding waste of important resources. In addition, the ability to predict machinery faults/maintenance helps a better management of the general infrastructure. In spending some time on the understanding of the qualitative KPIs, it is clear that there is no KPIs more relevant than the others in assessing BDTs usage, as they are all relatively relevant.