Data-driven identification of urgent surgical procedures for use in trauma outcomes measurement.

IF 2.1 Q3 CRITICAL CARE MEDICINE
Trauma Surgery & Acute Care Open Pub Date : 2025-05-21 eCollection Date: 2025-01-01 DOI:10.1136/tsaco-2025-001783
Matthew Miller, Louisa Jorm, Blanca Gallego
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引用次数: 0

Abstract

Background: No standardized list of urgent-trauma-surgery exists for analysis in injury studies. If coded by a standard classification system, such a list could facilitate the standard evaluation and comparison of trauma systems. Solving this problem using Delphi methods or expert opinion incorporating all surgical specialties would be resource-intensive. Instead, we describe a flexible data-driven method for generating a list of urgent surgical procedures from routine administrative data.

Methods: We linked perioperative and inpatient data for trauma patients with procedures booked within 24 hours of admission from a single Australian hospital (July 2018-July 2023). Surgical procedure codes were extracted where booked free-text and coded procedures matched. Procedures were labeled urgent-by-agreement if over 75% were needed within 4 hours, or urgent-by-consensus if 50-75% met this time frame with consensus below 0.7. Our method also allows adjustment for urgency time frame.

Results: Of 567 unique procedures from 6,750 total in 4,737 trauma admissions, 161 were classified as urgent-by-agreement and 6 as urgent-by-consensus. 15 surgical specialties were represented on this list.

Discussion and conclusions: Using routinely collected data, we outline a method for generating and updating urgent surgical procedure lists for trauma patients that could be applied at the institution level or across trauma networks. In addition, different urgency periods can be accommodated. Future work could look at further automating these processes by incorporating deep learning.

用于创伤结果测量的紧急外科手术的数据驱动识别。
背景:在损伤研究中,没有标准化的紧急创伤手术清单。如果用一个标准的分类系统编码,这样的清单可以促进创伤系统的标准评价和比较。使用德尔菲法或结合所有外科专科的专家意见来解决这个问题将是资源密集型的。相反,我们描述了一种灵活的数据驱动方法,用于从常规管理数据中生成紧急外科手术程序列表。方法:我们将澳大利亚一家医院(2018年7月至2023年7月)入院24小时内预约手术的创伤患者的围手术期和住院数据进行了关联。提取预定的自由文本和编码程序相匹配的手术程序代码。如果在4小时内需要超过75%的手术,则标记为紧急手术;如果50-75%的手术符合此时间框架,而共识低于0.7,则标记为紧急手术。我们的方法也允许调整紧急时间框架。结果:在4737例创伤入院的6750例中,567例独特的手术中,161例被分类为紧急协议,6例被分类为紧急共识。这份名单上有15个外科专业。讨论和结论:利用常规收集的数据,我们概述了一种生成和更新创伤患者紧急外科手术清单的方法,该方法可以在机构层面或跨创伤网络应用。此外,可以适应不同的紧急时期。未来的工作可以通过结合深度学习来进一步实现这些过程的自动化。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
3.70
自引率
5.00%
发文量
71
审稿时长
12 weeks
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