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Title Supporting the Classification of Patients in Public Hospitals in Chile by Designing, Deploying and Validating a System based on Natural Language Processing
Authors Fabian Villena, Jorge Pérez, René Lagos, Jocelyn Dunstan
Publication date July 2021
Abstract Background.
In Chile, a patient needing a specialty consultation or surgery has to first
be referred by a general practitioner, then placed on a waiting list. The
Explicit Health Guarantees (GES in Spanish) ensures, by law, the maximum
time to solve 85 health problems. Usually, a health professional manually
verifies if each referral, written in natural language, corresponds or not
to a GES-covered disease. An error in this classification is catastrophic
for patients, as it puts them on a non-prioritized waiting list,
characterized by prolonged waiting times.
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Methods.
To support the manual process, we developed and deployed a system that
automatically classifies referrals as GES-covered or not using historical
data. Our system is based on word embeddings specially trained for clinical
text produced in Chile. We used a vector representation of the reason for
referral and patient's age as features for training machine learning models
using human-labeled historical data. We constructed a ground truth dataset
combining classifications made by three healthcare experts, which was used
to validate our results.
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Results.
The best performing model over ground truth reached an AUC score of 0.94,
with a weighted F1-score of 0.85 (0.87 in precision and 0.86 in recall).
During seven months of continuous and voluntary use, the system has amended
87 patient misclassifications.
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Conclusion.
This system is a result of a collaboration between technical and clinical
experts, and the design of the classifier was custom-tailored for a
hospital's clinical workflow, which encouraged the voluntary use of the
platform. Our solution can be easily expanded across other hospitals since
the registry is uniform in Chile.
Pages 1-11
Volume 208
Journal name BMC Medical Informatics and Decision Making
Publisher Springer Nature Switzerland AG (Cham, Switzerland)
Reference URL View reference page