Paradigm changes for diagnosis: using big data for prediction

Clin Chem Lab Med. 2019 Feb 25;57(3):317-327. doi: 10.1515/cclm-2018-0971.

Abstract

Due to profound changes occurring in biomedical knowledge and in health systems worldwide, an entirely new health and social care scenario is emerging. Moreover, the enormous technological potential developed over the last years is increasingly influencing life sciences and driving changes toward personalized medicine and value-based healthcare. However, the current slow progression of adoption, limiting the generation of healthcare efficiencies through technological innovation, can be realistically overcome by fostering convergence between a systems medicine approach and the principles governing Integrated Care. Implicit with this strategy is the multidisciplinary active collaboration of all stakeholders involved in the change, namely: citizens, professionals with different profiles, academia, policy makers, industry and payers. The article describes the key building blocks of an open and collaborative hub currently being developed in Catalonia (Spain) aiming at generation, deployment and evaluation of a personalized medicine program addressing highly prevalent chronic conditions that often show co-occurrence, namely: cardiovascular disorders, chronic obstructive pulmonary disease, type 2 diabetes mellitus; metabolic syndrome and associated mental disturbances (anxiety-depression and altered behavioral patterns leading to unhealthy life styles).

Keywords: Integrated Care; big data; personalized medicine; systems medicine; value-based healthcare.

MeSH terms

  • Big Data*
  • Delivery of Health Care*
  • Humans
  • Precision Medicine*
  • Predictive Value of Tests
  • Spain