Proving the Business Case for the Internet of Things

IBM uses big data to predict heart failure

Steve Rogerson
May 25, 2017
A team of scientists at IBM Research, in collaboration with scientists from California-based Sutter Health, recently completed research developing methods to help predict heart failure based on hidden clues in electronic health records (EHRs).
Over the past three years, using advances in artificial intelligence (AI), such as natural language processing, machine learning and big data analytics, the team trained models to help predict heart failure.
Today, doctors will typically document signs and symptoms of heart failure in the patient record and order diagnostic tests that help indicate the possibility that a person may experience heart failure. Despite best efforts, a patient is usually diagnosed with heart failure after an acute event that involves a hospitalisation where the disease has advanced with possibly irreversible and progressive organ damage.
The research uncovered important insights about the practical trade-offs and types of data needed to train models, and developed possible application methods that could allow future models to be more easily adopted by medical professionals. For example, the research showed that only six of the 28 original risk factors contained within the Framingham Heart Failure Signs & Symptoms (FHFSS) were consistently found to be predictors of a future diagnosis of heart failure.
In addition, other team findings showed that other data types routinely collected in EHRs – such as disease diagnoses, medication prescriptions and lab tests – when combined with FHFSS could be helpful predictors of a patient's onset of heart failure.
All three parties will continue to collaborate to improve accuracy, clinical relevance and to test models for use in clinical care. In addition, the work may have potential application to other diseases. The confluence of the availability of big data and advances in cognitive computing could have dramatic advances in earlier disease detection.
IBM Research has more than 3000 researchers in 12 labs located across six continents.
IBM and Rensselaer Polytechnic Institute have created the Center for Health Empowerment by Analytics, Learning & Semantics (Heals). Located on the Rensselaer campus, the centre is a five-year collaborative research effort aimed at researching how the application of advanced cognitive computing capabilities can help people to understand and improve their own health conditions.