Data Mining approach to understanding heart failure.
Research type
Research Study
Full title
A data mining approach to understanding heart failure: Retrospective and real time analysis of Northern Ireland heart failure databases to enhance patient outcomes.
IRAS ID
270258
Contact name
Raymond Bond
Contact email
Sponsor organisation
Southern Health and Social Care Trust
Duration of Study in the UK
3 years, 0 months, 1 days
Research summary
Heart failure is a very common illness; there are nearly 900,000 people living with this illness in the UK. This disease is one of the main causes for hospital admissions in patients with heart problems.
Nowadays there are many treatments available for patients with heart failure. Some patients can be prescribed very effective pills, others can be given a special pacemaker or even more specialised electronic devices that can support the pumping function of the heart. Despite this, patients with heart failure are still facing problems with access to the best treatments without delays.
Heart Failure is a serious and deadly condition. We decided to look more closely at each patient’s journey from the point at which they receive the diagnosis to the moment when they receive the ideal treatment.
Aim: Our aim is to discover new knowledge and understanding about heart failure care in Northern Ireland. We want to use this knowledge to improve the quality of each patient’s life.
Methods: We will use statistical and mathematical analysis to understand the data (information) collected by hospitals on patients with heart failure. Once we analyse all of the information, we will find the weak links in the patient’s journey from getting a diagnosis of heart failure to receiving the best treatment.
Outcome: Once we know the weak links in patient care, we will use this information to plan better care for patients that could be used in the near future by doctors and nurses. Our results will help doctors and nurses make better decisions in treating patients and for monitoring the patients’ journey.REC name
HSC REC A
REC reference
20/NI/0013
Date of REC Opinion
24 Jan 2020
REC opinion
Favourable Opinion