Use case:
Patient Registry
Our client sponsorizes a health-related information registry on patients with a diagnosis for a rare disease. Information comes from different hospitals and is identifiable by a very limited list of healthcare professionals. They faced the following challenges..
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Manual information introduction limits the amount of patients that can be introduced in the Registry.
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Lack of time of professionals to review patient lists and enter information manually.
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Ensuring that the registry would have continuity even after introduction of the first patients.
Quadrant
Processing of all medical records, including text notes
Electronic Health Records (EHR) Text Based
Natural Language Processing identifies all clinical concepts.
Structured Database through NLP Coded.
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Recurring queries are run upon a structured database, that was build with information collected with NLP and included all variables.
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Out of the entire patient dataset, the ones that comply with criteria are automatically selected.
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Doctors receive an alarm and decide if patients are incorporated to registry.
Set up and update of patient registry.
20 sites engaged.
Summing up a total of 170 patients
Better healthcare delivery.
By detailed insights of patients symptoms and other variables.
Automatic database update.
Include all the new patients, automatically.
Real World Data.
Exact data, obtained from the entire population.