Heart Failure Clinical Trial
Official title:
Heart Failure in Norway: Combining Artificial Intelligence and a Database of 15000 Patients to Understand Clinical Characteristics, Mortality and Health Care Resource Use
The prevalence of Heart failure above 70 years of age is 10% and 5 year mortality rate above
60%, higher than for cancer. The readmission rate first after hospitalisation is 44% despite
the availability of life prolonging and life quality enhancing treatment. There is a lack of
resources for adequate diagnostic workup necessary for implementing evidence-based treatment.
This projects aims at assessing the impact of guidelines based diagnostic workup and
guidelines based treatment of heart failure on mortality and readmission rates. As the
symptoms defining the degree of heart failure and the discharge medication only is available
in the electronic patient files, artificial intelligence is used to retrieve this information
to assess if treatment is according to guidelines.
The project is using first a rule based text processing approach using IBM Watson, then
advancing to a machine learning approach using readmission and mortality as endpoints.
The project has access to digitally stored echocardiographic measurements as well as digital
ECG's and lab data on 15 000 patients admitted with a diagnosis of Heart failure. If the
retrieval of symptoms and function by artificial intelligence is successful, the next step is
to assess if those benefitting the most from echocardiography can be identified using
information from the ECG's, lab data or symptoms and functional capacity as described in the
Electronic Health Records.
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