Year: 2017
Type: article
Abstract: Will big data lead to big improvements in cardiovascular care? A 36-year-old woman presents with dyspnoea and dizziness. The clinician orders blood tests, an echocardiogram, an electrocardiogram, and documents the history in the electronic health record. A computer algorithm finds the patient’s prior test results, her genetic profile and demographic characteristics, and links in her wearable biosensor data. The algorithm creates a unique phenotype by processing all of the data sources, compares it with one million other patients, and suggests to the provider that the patient has hypertrophic cardiomyopathy, with an 83% predicted probability of sudden cardiac death in the next 10 years. The information supports an accurate and efficient diagnosis and provides individualized risk to inform shared decision making for a potential implantable cardioverter defibrillator (ICD). This scenario illustrates the promise of big data for cardiovascular clinicians—an automated system combining seemingly disparate data from various sources to provide decision support for diagnosis and treatment, as well as individualized, high-accuracy predictive analytics. How realistic is this future?
Source: European Heart Journal
Authors: Rashmee U. Shah, John S. Rumsfeld
Language: English
Subfield: Health Information Management
Field: Health Professions
Domain: Health Sciences
Open Access status: bronze
OpenAlex ID: W2668931987