By 2020, heart disease and stroke will become the leading causes of death and disability worldwide, with the number of fatalities projected to increase to more than 24 million by 2030.
Common cardiovascular diseases - heart arrhythmias (primarily atrial fibrillation or AF), heart failure (HF) and acute coronary syndrome (ACS) – cause much of this disability. While major advances in the management of these diseases have been achieved, medical management of these cardiovascular patients remains challenging. Current treatment guidelines are often not followed, leaving many patients not or undertreated.
Guideline committees call for more data to inform management recommendations. Ultimately, these data should aid the development of new medications, interventions and targeted management recommendations that improve outcomes, in all patients but in particular in pertinent patient subgroups. Likewise, healthcare providers should have new and improved diagnostics to select the right course of treatment. Such data should also help delay these diseases to more advanced ages.
Although current technology has led to the collection of massive amounts of healthcare data, wide scale exploitation of these data sources has yet to be achieved. This is mainly due to obstacles in the linkage of data, which results in fragmented and isolated datasets. Disease registries capturing incident cases are rare as many patient registries are designed for healthcare administration purposes whereas information on incident cases is crucial for studies of the aetiology and for studies of baseline characterization of patients.
Powerful insights could be generated from the combination or linking of in-patient and out-patient hospital data, prescription data, sociodemographic data, clinical trial data from pharmaceutical companies and data from newer technologies and 'omic measurements under appropriate data governance respectful of privacy.Scope:
The main goal of this initiative is to improve AF, HF, and ACS patient outcomes through better access and use of data. This will require:
1.defining and prioritising relevant patient outcomes in collaboration with key healthcare system stakeholders and patients;
2.accessing and analysing relevant morbidity and mortality data from large population based healthcare databases and patient data sources;
3.collecting and analysing data from clinical studies, genotyping, protein biomarkers, advanced imaging, or quality of life information directly from patients;
4.exploring algorithms that combine traditional and newer sources of data to improve the ability to assess the risk of a patient or population for relevant cardiovascular outcomes, diagnose the subtype and biological drivers of those risks, prescribe effective treatments, and monitor for progression or regression of disease;
5.translating the insights from these analyses to disease management concepts and guidelines, and innovative drug development to improve patient outcomes.Expected Impact:
The expected impacts of the proposed project are better and safer treatment paradigms for patients with AF, HF, and ACS. This impact should be achieved by providing evidence which will make it easier for HCPs and other stakeholders to provide the right treatment to the right patient at the right time.