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Validation of an ICD-9-CM-Based Monitoring Tool for Regional Trauma Systems: The PaTraME Study in Pavia Province, Italy

Title: Validation of an ICD-9-CM-Based Monitoring Tool for Regional Trauma Systems: The PaTraME Study in Pavia Province, Italy
Authors: Paola Fugazzola; Leandro Gentile; Francesco Chiarolanza; Pietro Perotti; Mario Alessiani; Federico Capra Marzani; Lorenzo Cobianchi; Simone Frassini; Federico Alberto Grassi; Catherine Klersy; Alba Muzzi; Alessandra Palo; Stefano Perlini; Maurizio Raimondi; Luca Ansaloni; on behalf of the PaTraME Study Group on behalf of the PaTraME Study Group
Source: Medical Sciences ; Volume 14 ; Issue 1 ; Pages: 13
Publisher Information: Multidisciplinary Digital Publishing Institute
Publication Year: 2025
Collection: MDPI Open Access Publishing
Subject Terms: trauma system; centralization; administrative data; TMPM-ICD9; XISS; quality monitoring
Description: Background/Objectives: Continuous trauma-system monitoring is limited by the lack of scalable, low-cost tools. The Pavia Trauma Management Epidemiology (PaTraME) project uses routinely collected ICD-9-CM discharge data (SDO) and the Trauma Mortality Probability Model (TMPM) to derive Injury Severity Score (XISS) and probability of death (TMPM-POD), creating a cost-free surveillance framework for regional trauma networks. Methods: We conducted a retrospective study of all major-trauma admissions (XISS > 15) in Pavia Province from 2014 to 2021. Anonymized SDO records were linked with emergency department flows and mortality registries. XISS and TMPM-POD were computed for each case. Case volumes, severity distributions, hub-centralization, and mortality (in-hospital, 30-day, and 180-day) were analyzed using trend and regression models (p < 0.05). Conclusions: We identified 1959 major-trauma admissions. Volumes increased up to 2019, dropped during the COVID-19 pandemic, and partially recovered in 2021 (p < 0.001). Overall, 61.5% of patients were admitted to hub centers, with an upward trend (p < 0.001). Hubs treated more severe trauma (median XISS 17 vs. 16; TMPM-POD 0.06 vs. 0.05, both p < 0.001). In-hospital mortality remained stable (8.2–11.4%, p = 0.828). TMPM-POD showed strong agreement with observed in-hospital mortality (Lin’s concordance correlation coefficient 0.81), though calibration worsened at higher risk levels. PaTraME confirms TMPM-POD as a valid mortality predictor and demonstrates a reproducible administrative-data framework for trauma surveillance. Rising hub admissions and stable mortality despite increasing complexity suggest improved system performance. Stratification of XISS and TMPM-POD between hub and spoke centers highlights peripheral hospitals managing disproportionately severe cases, informing targeted resource allocation and supporting quality improvement via automated dashboards.
Document Type: text
File Description: application/pdf
Language: English
Relation: Critical Care Medicine; https://dx.doi.org/10.3390/medsci14010013
DOI: 10.3390/medsci14010013
Availability: https://doi.org/10.3390/medsci14010013
Rights: https://creativecommons.org/licenses/by/4.0/
Accession Number: edsbas.DC62FFD6
Database: BASE