- FutuRS, the technological subsidiary of the healthcare group, creates a decision-making support model to predict clinical worsening and act proactively.
- It is a revolutionary archetype, which "learns" as new information becomes available and will be key if new outbreaks occur.
VALENCIA, JUNE 12, 2020. Ribera Health has developed a predictive model that predicts which COVID19 patients admitted may need care in the Intensive Care Unit (ICU). The FutuRS Data Science team, the technological subsidiary of the health group, has designed a model that analyzes and processes the variables of each patient to predict their evolution in a way that assists professionals in making decisions based on objective data.
It is a revolutionary model, which "learns" as the available information evolves and which has been positively assessed by the Drug Research Ethics Committee (CEIM) of the Group's hospitals. The objective of this initiative is to make it a key tool for the last phases of de-escalation, the "new normal" and above all, in anticipation of a possible new outbreak.
Ribera Salud plans to offer this technology to the governments of the regions where it operates, both in Spain and internationally, as part of its commitment to society, to share best practices, as it already did at the seminar organized by the IFC (International Finance Corporation) of the World Bank.
Mireia Ladios, Corporate Head of Quality at Ribera Salud, assures that "the early detection of clinical worsening is a differentiating element of quality, in a highly demanding environment such as the current Coronavirus pandemic." The exhaustive control, collection and analysis of patient data is the basis for the creation of this predictive model that allows the clinician to be alerted to the patient's progress, "providing him/her the opportunity to review and adjust the therapeutic plan before the patient deteriorates further"” . Ladios explains that the predictive model has been built based on a selection of clinical variables, established by health professionals and the current medical literature on COVID, and Data Mining and Machine Learning (ML) techniques have been used for its development. To know the performance of the model, measures such as sensitivity, specificity, area under the curve or the F1 score, among others, have been used.
The technical development has been led by Francisco Aznar, Software Development Manager (FutuRS) and Adrián Belso, Data Science Lead (FutuRS); and from the research level, the participation of José Fernández de Maya, Francisco Javier Ballesta, both from the Vinalopó and Torrevieja Health Departments, and Maria José Cabañero Martinez from the Faculty of Health Sciences of the University of Alicante, who explain that this predictive model "will make it easier for the health manager to make decisions in the face of a possible demand for scarce care resources, such as ICU beds, or the distribution of workloads according to the need for care of the patients".
Since its origins, Ribera Salud has always had a very high commitment to the application of information technologies and has been a firm believer in the benefits that they bring both to our professionals and in health results for our patients. The disruption of this type of cognitive solutions provides complementary tools to our professionals to help them in highly volatile scenarios such as the covid crisis.
