Reproducible Coding of Admission Complaints in Pediatric Rehabilitation: A Dictionary-Based Study

Background: Family-reported complaints at admission shape rehabilitation planning, but they are usually stored as free text and are rarely analyzed. Methods: We analyzed the admission complaint text of 318 children admitted to a national pediatric rehabilitation center in one admission course (22 August–8 September 2025), written in Russian in discharge summaries. We coded the text into ten complaint categories with a rule-based dictionary, compared the coding with hand coding of 209 children by a single clinician (including a test set of 40 children not used to build the dictionary), compared the categories by diagnosis group with permutation tests, and explored complaint profiles with non-negative matrix factorization of lemmatized text. Results: On the test set the dictionary agreed with the clinician’s hand coding on 98.3% of category decisions (95% CI 97.0 to 99.5%). Speech and language complaints were most frequent (73%), followed by motor (59%) and social and behavioral (36%) complaints. Motor complaints were recorded in 98% of children with cerebral palsy, and 61% of these children also had speech or language complaints. Categories differed by diagnosis (all q<0.05 except learning and memory), but motor complaints were also frequent in Down syndrome and other diagnoses. Three complaint profiles were found. Conclusions: Family-reported complaints in routine records can be coded reproducibly, and speech and language concerns were frequent in children admitted for motor disorders. Agreement was measured against a single clinician and may overestimate agreement with other clinicians.

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Journal
Epidemiology and Health Data Insights
Published
2026-10-26
DOI
https://doi.org/10.63946/ehdi/19672
Primary Topic
Medical Coding and Health Information
Type
article
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article

Reproducible Coding of Admission Complaints in Pediatric Rehabilitation: A Dictionary-Based Study

Syed Gufran Sadiq Zaidi, Saule Karibzhanova
Epidemiology and Health Data Insights
Medical Coding and Health Information
article

Reproducible Coding of Admission Complaints in Pediatric Rehabilitation: A Dictionary-Based Study

Syed Gufran Sadiq Zaidi, Saule Karibzhanova
article en

Abstract

Background: Family-reported complaints at admission shape rehabilitation planning, but they are usually stored as free text and are rarely analyzed. Methods: We analyzed the admission complaint text of 318 children admitted to a national pediatric rehabilitation center in one admission course (22 August–8 September 2025), written in Russian in discharge summaries. We coded the text into ten complaint categories with a rule-based dictionary, compared the coding with hand coding of 209 children by a single clinician (including a test set of 40 children not used to build the dictionary), compared the categories by diagnosis group with permutation tests, and explored complaint profiles with non-negative matrix factorization of lemmatized text. Results: On the test set the dictionary agreed with the clinician’s hand coding on 98.3% of category decisions (95% CI 97.0 to 99.5%). Speech and language complaints were most frequent (73%), followed by motor (59%) and social and behavioral (36%) complaints. Motor complaints were recorded in 98% of children with cerebral palsy, and 61% of these children also had speech or language complaints. Categories differed by diagnosis (all q<0.05 except learning and memory), but motor complaints were also frequent in Down syndrome and other diagnoses. Three complaint profiles were found. Conclusions: Family-reported complaints in routine records can be coded reproducibly, and speech and language concerns were frequent in children admitted for motor disorders. Agreement was measured against a single clinician and may overestimate agreement with other clinicians.

Epidemiology and Health Data InsightsVol. 2(5)
Nazarbayev University (KZ)
Openalex Percentile: Top 8%
Medical Coding and Health Information
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Reproducible Coding of Admission Complaints in Pediatric Rehabilitation: A Dictionary-Based Study — Syed Gufran Sadiq Zaidi, Saule Karibzhanova · Epidemiology and Health Data Insights (2026) | TGRS Research Map | TGRS