DataTools4Heart
Treatment, referral pathways and prognosis of patients with heart failure: a federated cohort study across multiple European Hospitals
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In heart failure, the patient’s heart is not able to pump blood around sufficiently, leading to symptoms such as shortness of breath and fluid retention. Patients with heart failure often also have chronic kidney disease. In this situation, it is difficult to find the best dose of medication to use, as patients are at risk of complications. It is also difficult to know which patients can be safely treated at home and which patients need to be admitted to hospital for closer monitoring.
In this study, we aim to use real word clinical data to evaluate the prescription of medication in patients with chronic kidney disease who are hospitalized with heart failure. This will lead to improved knowledge of the current implementation of clinical treatment guidelines. Secondly, we aim to develop a risk score for patients admitted with heart failure. This may help clinicians may help the clinician to decide if a patient should be admitted or managed at home, and what level of monitoring is required. The risk score could also help to predict and optimise the use of health care resources.
For these aims, we will analyse clinical data extracted from the UCLH electronic health record. Findings from these data will be combined with findings from patient data at other European hospitals, under the DataTools4Haert project (https://www.datatools4heart.eu/). This will be carried out using a federated learning approach, in which data is analysed within each hospital and the results are combined without any data leaving the individual hospital. This will allow research questions to be answered robustly using data from a large, diverse patient population whilst maintaining the security and privacy of patient data.
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Please contact any of following people for more information:
Dr Anoop Shah
Baptiste Briot-Ribeyre
View Our Synthetic Data:
The information you see here is synthetic data. It’s not real data, does not contain real patient details, and cannot be traced back to any real patients. It is only designed to look like real health records.
We created these data to show the kind of information used in a research project called DataTools4Heart: federated patient data analysis for research. This study aims to use real world clinical data to evaluate the prescription of medication in patients with chronic kidney disease who are hospitalized with heart failure. The project is led by Anoop Shah, an Associate Professor and Consultant in Clinical Pharmacology.
Because this data is randomly generated using a tool called datafaker, some parts may not make sense — for example, a birth date might appear after a death date. That’s because the columns are made separately and don’t always link together in a realistic way.
Please note that this data is part of our preliminary version of synthetic datasets. We’re actively improving our process so that over time, more datasets will be available, and the data will look more and more like real-world data, without ever containing any real patient details.
This dataset is only for demonstration and learning purposes. Any similarity to real people is purely coincidental.
How to browse our synthetic data:
1) In the embedded table above, click the ‘view’ button next to the file you’d like to look at.
2) A new window will open up to Figshare, where the file is stored. You will see a collection of tiles containing the file folder on the top half of the page, and a project description on the bottom half of the page.
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6) The files are in CSV format, which is like a simple version of an Excel spreadsheet.
Tip: Each row in the file is a ‘record’ (like a line in a spreadsheet), and each column is a type of information (like date, condition, or measurement).
