How can big data help to improve chronic disease management?


How can big data help to improve chronic disease management?

29 September, 2018

Chronic diseases are the main cause of mortality and morbidity in Europe. The impact of these illnesses in healthcare is huge since strategies to manage patients often involve sending them to secondary care institutions, an increase of costs for them and an overstretched service due to the flood of visits that has effects in the quality of care.

According to the publication Health at a Glance: Europe 2016. State of Health in the EU Cycle by the OECD, cardiovascular disease, kidney disease, respiratory disease, and diabetes represent the 59 % of deaths from non-communicable diseases in Europe. For the last several years, the management of these illnesses has become an important challenge for the healthcare systems.

One of the areas of research in BigMedilytics is devoted to exploring how big data can help to solve problems in a wide spectrum of chronic diseases and conditions through the value chain and contribute to increase effectiveness and quality of interventions as well as widen possibilities to prevent diseases and its consequences.

The improvement of care in chronic conditions can contribute to reducing inefficiency and waste while patient’s risk is reduced, enhancing health-related quality of life (QOL) and cost containment. The integration of health data from the “real world” and innovative analytic procedures allow us to explore how to apply this data and quantify the beneficial impact obtained.

The five pilots included in theme 1 cover from the rising problem of clustering in chronic non-communicable disease due to the ageing process, to more specific but relevant healthcare problems. Some of these medical issues are the follow-up of patients with renal transplantation, chronic obstructive pulmonary disease, heart failure, and gestational diabetes.

In each of these conditions, the pilots will explore improvements in the stratification of patient’s risk based in large populations with multiple sources of data and/or continuous monitoring. An appropriate stratification will let the design of advanced interventions beyond current clinical practices and the validation of efficiency improvements in healthcare delivery and outcomes analysing the impact in quality care and overall costs.

As a result of big data analytics, the burden on the healthcare system related to chronic diseases will be reduced by ensuring that only critical patients are sent to secondary care whereas non-critical patients are attended to by primary care.