ICD-10 code embedding for patient matching: a first step towards applications in causal inference from hospital discharge data Article Swipe
Judith A. Bouman
,
André Moser
,
Martin Wohlfender
,
Alexandra Leichtle
,
Guido Beldi
,
Olga Endrich
,
Julien Riou
,
Christian L. Althaus
·
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.1093/ajeadv/uuaf010
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.1093/ajeadv/uuaf010
We present WEMatch, a Word2vec Enhanced ICD-10 Matching algorithm, for patient matching based on ICD-10 codes and make a first step toward evaluating its potential use in causal inference contexts by comparing it to several propensity score-based patient matching approaches. We use hospital discharge data from the Insel Group in the canton of Bern, Switzerland from 2014 to 2023, including ICD-10 codes, age, sex, and BMI for 386, 842 hospitalizations. In the null effect matched cohort design, patients are matched to a randomly selected ’treatment group’ (selected from one of four selected primary ICD-10 diagnoses) using four algorithms: WEMatch and three PSM-based models. Performance is assessed by comparing the balance of key variables, hazard ratios of mortality, and length of hospital stay between the treatment and matched control groups. WEMatch and PSM methods perform similarly for three out of four tested ICD-10 codes. For one ICD-10 code, WEMatch outperforms PSM methods, because the patient population is especially diverse. This study establishes a robust framework for systematically comparing patient matching algorithms. The groundwork is set for applying WEMatch to clinically relevant questions. By distributing this as an R package, we promote its integration into clinical research, potentially supporting future causal analyses using observational data.
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- en
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- https://academic.oup.com/ajeadvances/advance-article-pdf/doi/10.1093/ajeadv/uuaf010/64337999/uuaf010.pdf
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ICD-10 code embedding for patient matching: a first step towards applications in causal inference from hospital discharge dataWork title
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enPrimary language
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2025Year of publication
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2025-09-22Full publication date if available
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Judith A. Bouman, André Moser, Martin Wohlfender, Alexandra Leichtle, Guido Beldi, Olga Endrich, Julien Riou, Christian L. AlthausList of authors in order
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https://doi.org/10.1093/ajeadv/uuaf010Publisher landing page
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hybridOpen access status per OpenAlex
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https://academic.oup.com/ajeadvances/advance-article-pdf/doi/10.1093/ajeadv/uuaf010/64337999/uuaf010.pdfDirect OA link when available
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| primary_location.pdf_url | https://academic.oup.com/ajeadvances/advance-article-pdf/doi/10.1093/ajeadv/uuaf010/64337999/uuaf010.pdf |
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| publication_date | 2025-09-22 |
| publication_year | 2025 |
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