ID-5184 Wonca Abstracts supplement A-K 13-10-23 - Flipbook - Page 42
WONCA 2023 Supplement 1: WONCA 2023 abstracts (A–K)
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International Classification of Primary Care (ICPC-2)
and search engines: Evaluation of three algorithms for
information retrieval to aid medical coding
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Dr Vinicius Anjos De Almeida, Luis Fernandez Lopez
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Department of Legal Medicine, Bioethics, Occupational Medicine, and Physical Medicine and
Rehabilitation, Faculty of Medicine, University of São Paulo
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International classifications are a crucial tool for organising healthcare data, helping us to understand
populations both locally and globally. However, with the continuous advancement of medical
knowledge, these classifications are becoming increasingly complex. For instance, the International
Classification of Diseases, 11th edition (ICD-11), comprises 17,000 categories of disease. In contrast,
the International Classification of Primary Care, 3rd edition (ICPC-3), is more concise, with 1350 codes.
Despite this, healthcare professionals still face the challenge of correctly attributing codes to various
clinical scenarios, making tools necessary to help them find the right codes efficiently and accurately.
This research evaluates three different search engines for the ICPC-2 code, developed by the author
to tackle this issue. The search engines were created using the Python programming language and its
open source libraries, and vary in their information retrieval algorithms: BM25 ranking algorithm; vector
search powered by OpenAI embeddings; and a combination of both methods. They were all built with
the same Portuguese thesaurus for ICPC-2 codes, which maps concepts to their appropriate codes.
The search engines’ performance was evaluated and compared using their search history. The first
version became available online in August 2021, only in Portuguese. All entries were reviewed by the
author, assigned an expected ICPC-2 code using the thesaurus as a guide. The entries were then
submitted to each information retrieval algorithm to determine if the correct code was retrieved as the
first result or among the top five results. Kappa statistics were used to calculate the agreement rate with
respect to the reference.
The goal of this presentation is to present the main results and limitations of this research, discuss the
growing complexity of medical coding, explore how it can be addressed using search engines and
information retrieval algorithms and examine potential future approaches to medical coding.
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