Validity of diagnostic codes used to ascertain maternal injuries during pregnancy.

IF 5 2区医学 Q1 PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH

American journal of epidemiology Pub Date : 2025-07-08 DOI:10.1093/aje/kwaf145

Asma M Ahmed, Riyan Deria, Rosalba Barojas Chavarria, Allie Sakowicz, David Stamilio, Elizabeth T Jensen

{"title":"Validity of diagnostic codes used to ascertain maternal injuries during pregnancy.","authors":"Asma M Ahmed, Riyan Deria, Rosalba Barojas Chavarria, Allie Sakowicz, David Stamilio, Elizabeth T Jensen","doi":"10.1093/aje/kwaf145","DOIUrl":null,"url":null,"abstract":"Background: Previous research has relied on International Classification of Diseases (ICD) codes to define maternal injuries. However, the validity of these codes remains unclear. We aimed to validate ICD-10 codes used to ascertain maternal injuries using medical chart reviews as the gold standard.Methods: A retrospective cohort study of all births occurring at Atrium Health Wake Forest Baptist Medical Center in 2022-2023. We randomly selected 100 subjects with ICD-10-indicated injury and 100 subjects without indication of injury. Two independent reviewers, blinded to the ICD-10-based classification, conducted the chart review. We examined the validity of relevant injury-related codes (V00-Y38; S00-T79; O9A.2-O9A.4) and calculated positive predictive values (PPV) for different algorithms defined by varying the encounter type and the list of codes used.Results: The algorithm that included all injury-related ICD-10 codes without encounter type restrictions showed moderate PPV (71%, 95% confidence interval (CI): 61%-79%) and high negative predictive value (96% (90%-98%)). PPV was maximized when including codes V00-Y38 and restricting encounter type to inpatient or emergency department encounters (PPV 100% (93%-100%).Conclusions: This study characterizes the accuracy of ICD-10-based algorithms for ascertaining maternal injuries during pregnancy. These findings can help improve inference by providing bias parameters for future research.","PeriodicalId":7472,"journal":{"name":"American journal of epidemiology","volume":" ","pages":""},"PeriodicalIF":5.0000,"publicationDate":"2025-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"American journal of epidemiology","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1093/aje/kwaf145","RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH","Score":null,"Total":0}

引用次数: 0

Abstract

Background: Previous research has relied on International Classification of Diseases (ICD) codes to define maternal injuries. However, the validity of these codes remains unclear. We aimed to validate ICD-10 codes used to ascertain maternal injuries using medical chart reviews as the gold standard.

Methods: A retrospective cohort study of all births occurring at Atrium Health Wake Forest Baptist Medical Center in 2022-2023. We randomly selected 100 subjects with ICD-10-indicated injury and 100 subjects without indication of injury. Two independent reviewers, blinded to the ICD-10-based classification, conducted the chart review. We examined the validity of relevant injury-related codes (V00-Y38; S00-T79; O9A.2-O9A.4) and calculated positive predictive values (PPV) for different algorithms defined by varying the encounter type and the list of codes used.

Results: The algorithm that included all injury-related ICD-10 codes without encounter type restrictions showed moderate PPV (71%, 95% confidence interval (CI): 61%-79%) and high negative predictive value (96% (90%-98%)). PPV was maximized when including codes V00-Y38 and restricting encounter type to inpatient or emergency department encounters (PPV 100% (93%-100%).

Conclusions: This study characterizes the accuracy of ICD-10-based algorithms for ascertaining maternal injuries during pregnancy. These findings can help improve inference by providing bias parameters for future research.

查看原文本刊更多论文

用于确定怀孕期间产妇损伤的诊断代码的有效性。

背景：以往的研究依赖于国际疾病分类（ICD）代码来定义产妇损伤。然而，这些代码的有效性仍然不清楚。我们的目的是验证ICD-10代码用于确定产妇伤害使用医疗图表审查作为金标准。方法：对2022-2023年在Atrium Health Wake Forest Baptist Medical Center出生的所有新生儿进行回顾性队列研究。我们随机选择100例有icd -10指示损伤的受试者和100例无指示损伤的受试者。两名独立的审查员，不知道icd -10的分类，进行了图表审查。我们检验了相关伤害相关规范(V00-Y38；S00-T79;O9A.2-O9A.4)并计算出通过改变遭遇类型和所使用代码列表定义的不同算法的正预测值（PPV）。结果：该算法包括所有与伤害相关的ICD-10代码，无遭遇类型限制，PPV适中（71%，95%置信区间（CI）： 61% ~ 79%），阴性预测值较高（96%(90% ~ 98%)）。当纳入代码V00-Y38并将遭遇类型限制为住院或急诊科遭遇时，PPV达到最大（PPV 100%(93%-100%)）。结论：本研究的特点是基于icd -10算法的准确性，以确定怀孕期间的产妇损伤。这些发现可以通过为未来的研究提供偏差参数来帮助改进推理。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

求助全文

约1分钟内获得全文求助全文

来源期刊

American journal of epidemiology 医学-公共卫生、环境卫生与职业卫生

CiteScore

7.40

自引率

4.00%

发文量

221

审稿时长

3-6 weeks

期刊介绍： The American Journal of Epidemiology is the oldest and one of the premier epidemiologic journals devoted to the publication of empirical research findings, opinion pieces, and methodological developments in the field of epidemiologic research. It is a peer-reviewed journal aimed at both fellow epidemiologists and those who use epidemiologic data, including public health workers and clinicians.