NOHS participates as a partner in the CrowdHEALTH project, whose main purpose is to deliver a secure ICT platform. This platform will incorporate the collective knowledge on health care that emerges from multiple information sources in order to achieve modelling, creation and co-innovation of multi-modal health policies and to evaluateand adapt cross-domain policies.
To that end, NOHS has been a major participant in Health in All Policies, and how the use of Big Data can lead to the development of new policies. In the context of the CrowdHEALTH project, NOHS deals with how heterogeneous data sources can be exploited and collective knowledgeis gained through health records, thus facilitating new insights in healthcare. The NOHS research team analyzed inpatient and outpatient health care service data (hospitalization costs, visits to physicians, diagnostic centres, etc.) for specific non-communicable diseases (2014-2017). The results from the analysis of the NOHS dataset using Statistical as well as Machine Learning techniques were published in the special session “Statistical Applications in Health Care Services Management” in the International Symposium on Business and Industrial Statistics (ISBIS 2018) (http://conf.sta.unipi.gr/wp-content/uploads/2018/07/ISBIS2018_bookofabstracts_new.pdf). According to our study, quality, performance, expenses and fraud can be detected both with real-time monitoring and post-hoc. Furthermore, the Policy Development Toolkit (PDT),developed as part of the project,is used to calculate the most frequent diseasesand their cost, using the medical health records electronically stored in NOHS systems.
Since most public health policies focus on non-communicable diseases (NCDs), the need for recording and analyzing the cost resulting from cancer is most important,allowing selection of health practices that will bring to the community the maximum allowed benefit. Therefore, using the PDT tool developed in the context of the CrowdHEALTHproject, NOHS will aim to analyze cancer cost in order to produce data that will be utilized to foresee problems, as well as to assess future expenditure and the needs of society. Furthermore, synergies with BioAssist in the field of chronic diseases such as Chronic Obstructive Pulmonary Disease, Pulmonary Fibrosis and Hypertension are exploited.