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.
Authors
- Syed Gufran Sadiq Zaidi (ORCID: https://orcid.org/0009-0009-1468-2018)
- Saule Karibzhanova (ORCID: https://orcid.org/0009-0004-4850-8193)
Institutions
- Nazarbayev University (KZ)
Publication Details
- 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
- Field-Weighted Citation Impact
- 0.00