严重孕产妇发病率的范围审查:描述危险因素和为基于人群的监测提供信息的方法学方法。

Lisa M Korst, Kimberly D Gregory, Lisa A Nicholas, Samia Saeb, David J Reynen, Jennifer L Troyan, Naomi Greene, Moshe Fridman
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引用次数: 0

摘要

背景:目前对使用严重产妇发病率(SMM)作为产妇保健质量指标的兴趣将需要制定一种标准化方法来估计医院或区域严重产妇发病率,其中包括调整和/或对风险因素进行分层。目的:进行范围审查,以确定与交付相关的SMM风险调整的方法学考虑因素和潜在协变量。搜索方法:按照系统评价的首选报告项目和荟萃分析扩展范围评价的指导方针,对整个PubMed和EMBASE电子数据库进行系统搜索,以确定使用关键词“严重孕产妇发病率”的出版物。选择标准:纳入的研究需要以人群为基础的队列数据,并检测或调整分娩入院时发生SMM的危险因素。描述性研究和使用基于监视的数据收集方法的研究被排除在外。数据收集和分析:将信息提取到预定义的数据库中。评估了研究设计和资格、总体质量和结果、SMM定义以及患者、医院和社区层面的危险因素及其定义。主要结果:81项研究符合入选标准。由于数据源、研究设计、资格标准、SMM的定义以及风险因素的选择和定义存在很大的可变性,方法方法是异质的,研究结果不能定量地结合起来。在确定的180个潜在风险因素中,41个被归类为先前存在的疾病(例如,慢性高血压),22个被归类为产科疾病(例如,多胎妊娠),22个被归类为产时疾病(例如,分娩路线),15个被归类为非临床变量(例如,保险类型),58个被归类为医院层面变量(例如,产生量),22个被归类为社区层面变量(例如,社区贫困)。结论:制定风险调整战略,以便在医院或地区之间进行SMM比较,将需要在以下方面进行协调:a) SMM定义的标准化;B)数据来源和使用人群;c)利益风险因素的选择和定义。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

A scoping review of severe maternal morbidity: describing risk factors and methodological approaches to inform population-based surveillance.

A scoping review of severe maternal morbidity: describing risk factors and methodological approaches to inform population-based surveillance.

Background: Current interest in using severe maternal morbidity (SMM) as a quality indicator for maternal healthcare will require the development of a standardized method for estimating hospital or regional SMM rates that includes adjustment and/or stratification for risk factors.

Objective: To perform a scoping review to identify methodological considerations and potential covariates for risk adjustment for delivery-associated SMM.

Search methods: Following the guidelines for Preferred Reporting Items for Systematic Reviews and Meta-analyses Extension for Scoping Reviews, systematic searches were conducted with the entire PubMed and EMBASE electronic databases to identify publications using the key term "severe maternal morbidity."

Selection criteria: Included studies required population-based cohort data and testing or adjustment of risk factors for SMM occurring during the delivery admission. Descriptive studies and those using surveillance-based data collection methods were excluded.

Data collection and analysis: Information was extracted into a pre-defined database. Study design and eligibility, overall quality and results, SMM definitions, and patient-, hospital-, and community-level risk factors and their definitions were assessed.

Main results: Eligibility criteria were met by 81 studies. Methodological approaches were heterogeneous and study results could not be combined quantitatively because of wide variability in data sources, study designs, eligibility criteria, definitions of SMM, and risk-factor selection and definitions. Of the 180 potential risk factors identified, 41 were categorized as pre-existing conditions (e.g., chronic hypertension), 22 as obstetrical conditions (e.g., multiple gestation), 22 as intrapartum conditions (e.g., delivery route), 15 as non-clinical variables (e.g., insurance type), 58 as hospital-level variables (e.g., delivery volume), and 22 as community-level variables (e.g., neighborhood poverty).

Conclusions: The development of a risk adjustment strategy that will allow for SMM comparisons across hospitals or regions will require harmonization regarding: a) the standardization of the SMM definition; b) the data sources and population used; and c) the selection and definition of risk factors of interest.

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