Use case:
Observational study

Our client needed to fill in a Case Report Form with 70 variables from 2 pathologies, covering at least 5.000 patients from 8 hospitals.

Need

  • Accessing and reading clinical records requires the patient’s informed consent.

  • Manual collection of information bears enormous costs and does not allow to collect the millions of clinical records available.

  • Only between 15-25% of all information contained in hospitals is structured. The rest, is in plain text.

Solution

Data extraction, using Natural Language Processing

Implemented simultaneously in all 10 hospitals participating in the study.

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1

Electronic Health Records (EHR) Text Based

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2

Structred Database through NLP Coded.

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3

Extraction of variables.

Result
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  • A queries was run upon 10 hospitals at the same time, after authorization from hospital.

  • Complete dataset with anonymized information per patient and variables needed for the study is obtained.

  • Statistical analysis carried out by using this dataset.

Benefits

High-quality observational study, with less effort and time.

150 times more data points

Than the ones that would be found with the current methodology.

Data obtained in 10% of time

Saving up valuable time and resources.

Quality assurance

Dataset went through three independent QA filters, ensuring data excellence.

Access to the entire dataset

Instead of access to plain reports, avoiding “back box” logics.

Detailed infographic

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