ArticleAnnals of surgery open : perspectives of surgical history, education, and clinical approaches2025
Evaluation of an Automated Software Method Versus a Delphi Process to Translate Emergency General Surgery ICD Diagnosis Codes: Lost in Translation.
Article in Annals of surgery open : perspectives of surgical history, education, and clinical approaches, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
2 citing papers in PubMed.
- Building an emergency general surgery registry to track and benchmark outcomes.Trauma surgery & acute care open · 2026Article
- The Path Toward Harmonized Codesets for Emergency General Surgery.Annals of surgery open : perspectives of surgical history, education, and clinical approaches · 2025Article
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Authors and funding
14 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Objective: This study provides an up-to-date diagnosis framework for the study of emergency general surgery (EGS) patients. A final list of International Classification of Diseases, Tenth Revision (ICD-10) codes was the main outcome for the study. Codes were compared with the number codes generated by MapIT alone. Background: Since transition to ICD-10, a Delphi process to define EGS diagnoses, as originally described for the ICD, Ninth Revision (ICD-9) codeset, has not been performed. Automated mapping software (MapIT) has been utilized, with a few studies verifying the translation. Methods: Using previously defined ICD-9 EGS codes, MapIT was used to identify ICD-10 EGS codes. Review of adjacent codes in a Delphi process resulted in a finalized list of ICD-10 codes. Delphi and MapIT codes were quantified in the Nationwide Inpatient Sample to compare rates to the ICD-9 era. Results: MapIT identified 935 ICD-10 codes from 485 ICD-9 codes. Manual review identified an additional 1907 adjacent codes. In total, after the modified Delphi process, 1579 (55.6%) of manually and MapIT-identified codes were included in the final codeset. After initial mapping, 880 (55.7%) of the final codes did not automatically map through the software. MapIT codes resulted in a significantly decreased number of patient encounters in the Nationwide Inpatient Sample compared with Delphi codes in the ICD-10 era. Conclusions: The Delphi-created ICD-10 EGS codeset provides a more robust, accurate translation of the ICD-9 codes than MapIT software. This codeset can be used to inform EGS research to study and improve EGS patients' care.
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