基于全美大型数据库分析：揭示哮喘患者急性发作去急诊的关键因素
2025/09/22
摘要
目的： 哮喘急性发作可导致患者在无预约的情况下前往急诊科（ED）。本研究通过检查“我们所有人”研究计划数据集（All of Us database ），分析了哮喘患者中与非计划性ED就诊相关的因素。
方法： 使用“我们所有人”数据库（2018—2024年）进行了一项回顾性队列研究。利用电子健康记录（EHR）根据医生报告的哮喘诊断来识别哮喘患者。根据研究期间内的ED就诊频率将患者分为三组：普通哮喘患者（无ED就诊）、单次ED就诊哮喘患者（一次就诊）和频繁ED就诊哮喘患者（超过一次就诊）。利用Python和R进行多项逻辑回归分析，以检查人口统计学因素、社会决定因素、医疗保健可及性、邻里条件和合并症。
结果： 该研究从总共409,420名参与者中纳入了47,227名哮喘患者。研究包括33,046名（70.0%）无ED就诊记录的普通哮喘患者，4,779名（10.1%）有一次报告就诊的单次ED就诊哮喘患者，以及9,402名（19.9%）有两次或以上ED就诊的频繁ED就诊哮喘患者。与频繁ED就诊显著相关的因素包括年收入低于10,000美元（OR = 1.42; 95% CI [1.25-1.61]）、黑人/非洲裔人种（OR = 2.08; 95% CI [1.61-2.68]）、胸痛（OR = 2.31; 95% CI [2.16-2.48]）、高血压（OR = 1.19; 95% CI [1.11-1.28]）、呼吸道感染（OR = 1.60; 95% CI [1.50-1.71]）、焦虑（OR = 1.17; 95% CI [1.08-1.28]）、居住地附近有废弃建筑（OR = 1.20; 95% CI [1.14-1.26]）和感知白天邻里不安全（OR = 1.07; 95% CI [1.02-1.13]）。保护性因素包括较高收入（>200,000美元/年，OR = 0.55; 95% CI [0.42-0.70]）、医疗保险覆盖（OR = 0.65; 95% CI [0.58-0.71]）、年龄较大（每年OR = 0.99; 95% CI [0.99-0.99]）和男性（OR = 0.86; 95% CI [0.81-0.92]）。女性患者和较年轻年龄与ED就诊可能性增加相关。
结论与提示： 哮喘患者非计划性ED就诊的频率受到社会决定因素（包括种族、社会经济地位、邻里因素和特定合并症）的显著影响。这项研究告诉我们一个核心真相：哮喘患者是否去急诊，并不仅仅取决于肺部本身的问题，更是一个被社会、经济、环境和心理健康状况共同决定的“完美风暴”。这项研究就像一幅地图，为我们指明了哪些群体和哪些因素最需要帮助。医生、政策制定者和社区工作者可以据此合作，为高风险群体提供更有针对性的支持——例如，加强社区建设、提供心理服务支持、改善医保覆盖——从而最终减少哮喘急诊的发生。
关键词： 急性护理利用；我们所有人研究计划；哮喘；慢性呼吸系统疾病；合并症；急诊科就诊；流行病学；健康数据分析；医疗保健可及性；医疗保健差异；医疗保健利用模式；逻辑回归；患者结局；人口健康；预测建模；风险因素；健康的社会决定因素；社会经济地位；非计划性医疗访问。
Abstract
Objectives: Asthma exacerbations can cause patients to visit the emergency department (ED) without prior appointments. This study analyzed factors associated with unscheduled ED visits among asthma patients by examining the All of Us Research Program dataset.
Methods: We conducted a retrospective cohort study using the All of Us database (2018-2024). Electronic health records (EHR) were utilized to identify asthma patients based on physician-reported asthma diagnoses. Patients were divided into three groups based on ED visit frequency during the study period: General Asthma Patients (no ED visits), Single ED Visit Asthma Patients (one visit), and Frequent ED Visit Asthma Patients (more than one visit). Python and R were utilized to perform a multinomial logistic regression analysis in order to examine demographic factors, social determinants, healthcare accessibility, neighborhood conditions and comorbidities.
Results: The research included 47, 227 asthma patients from a total participant pool of 409,420 individuals. The study included 33,046 (70.0 %) General Asthma Patients with no ED visit record, 4779 (10.1 %) Single ED Visit Asthma Patients with a single reported visit and 9402 (19.9 %) Frequent ED Visit Asthma Patients with two or more ED visits. Factors significantly associated with frequent ED visits included income less than $10,000/year (OR = 1.42; 95 % CI [1.25-1.61]), Black/African American race (OR = 2.08; 95 % CI [1.61-2.68]), chest pain (OR = 2.31; 95 % CI [2.16-2.48]), hypertension (OR = 1.19; 95 % CI [1.11-1.28]), respiratory tract infections (OR = 1.60; 95 % CI [1.50-1.71]), anxiety (OR = 1.17; 95 % CI [1.08-1.28]), living near abandoned buildings (OR = 1.20; 95 % CI [1.14-1.26]), and perceived daytime neighborhood unsafety (OR = 1.07; 95 % CI [1.02-1.13]). Protective factors included higher income (>$200,000/year, OR = 0.55; 95 % CI [0.42-0.70]), insurance coverage (OR = 0.65; 95 % CI [0.58-0.71]), older age (OR per year = 0.99; 95 % CI [0.99-0.99]), and male sex (OR = 0.86; 95 % CI [0.81-0.92]). Female patients and younger age were associated with increased likelihood of ED visits.
Conclusions: The frequency of unscheduled ED visits for asthma patients was significantly influenced by social determinants which include race, socioeconomic status, neighborhood factors, and specific comorbidities. Understanding these disparities can aid in the improvement of asthma management and the development of targeted interventions to address these critical factors.
Keywords: Acute care utilization; All of us research program; Asthma; Chronic respiratory disease; Comorbidities; Emergency department visits; Epidemiology; Health data analytics; Healthcare access; Healthcare disparities; Healthcare utilization patterns; Logistic regression; Patient outcomes; Population health; Predictive modeling; Risk factors; Social determinants of health; Socioeconomic status; Unscheduled healthcare visits.
目的： 哮喘急性发作可导致患者在无预约的情况下前往急诊科（ED）。本研究通过检查“我们所有人”研究计划数据集（All of Us database ），分析了哮喘患者中与非计划性ED就诊相关的因素。
方法： 使用“我们所有人”数据库（2018—2024年）进行了一项回顾性队列研究。利用电子健康记录（EHR）根据医生报告的哮喘诊断来识别哮喘患者。根据研究期间内的ED就诊频率将患者分为三组：普通哮喘患者（无ED就诊）、单次ED就诊哮喘患者（一次就诊）和频繁ED就诊哮喘患者（超过一次就诊）。利用Python和R进行多项逻辑回归分析，以检查人口统计学因素、社会决定因素、医疗保健可及性、邻里条件和合并症。
结果： 该研究从总共409,420名参与者中纳入了47,227名哮喘患者。研究包括33,046名（70.0%）无ED就诊记录的普通哮喘患者，4,779名（10.1%）有一次报告就诊的单次ED就诊哮喘患者，以及9,402名（19.9%）有两次或以上ED就诊的频繁ED就诊哮喘患者。与频繁ED就诊显著相关的因素包括年收入低于10,000美元（OR = 1.42; 95% CI [1.25-1.61]）、黑人/非洲裔人种（OR = 2.08; 95% CI [1.61-2.68]）、胸痛（OR = 2.31; 95% CI [2.16-2.48]）、高血压（OR = 1.19; 95% CI [1.11-1.28]）、呼吸道感染（OR = 1.60; 95% CI [1.50-1.71]）、焦虑（OR = 1.17; 95% CI [1.08-1.28]）、居住地附近有废弃建筑（OR = 1.20; 95% CI [1.14-1.26]）和感知白天邻里不安全（OR = 1.07; 95% CI [1.02-1.13]）。保护性因素包括较高收入（>200,000美元/年，OR = 0.55; 95% CI [0.42-0.70]）、医疗保险覆盖（OR = 0.65; 95% CI [0.58-0.71]）、年龄较大（每年OR = 0.99; 95% CI [0.99-0.99]）和男性（OR = 0.86; 95% CI [0.81-0.92]）。女性患者和较年轻年龄与ED就诊可能性增加相关。
结论与提示： 哮喘患者非计划性ED就诊的频率受到社会决定因素（包括种族、社会经济地位、邻里因素和特定合并症）的显著影响。这项研究告诉我们一个核心真相：哮喘患者是否去急诊，并不仅仅取决于肺部本身的问题，更是一个被社会、经济、环境和心理健康状况共同决定的“完美风暴”。这项研究就像一幅地图，为我们指明了哪些群体和哪些因素最需要帮助。医生、政策制定者和社区工作者可以据此合作，为高风险群体提供更有针对性的支持——例如，加强社区建设、提供心理服务支持、改善医保覆盖——从而最终减少哮喘急诊的发生。
关键词： 急性护理利用；我们所有人研究计划；哮喘；慢性呼吸系统疾病；合并症；急诊科就诊；流行病学；健康数据分析；医疗保健可及性；医疗保健差异；医疗保健利用模式；逻辑回归；患者结局；人口健康；预测建模；风险因素；健康的社会决定因素；社会经济地位；非计划性医疗访问。
（南方医科大学南方医院 汤亦心 赵海金）
（Rodriguez D,et al.Factors associated with acute unscheduled care visits for asthma in the all of US dataset.Am J Emerg Med 2025 Sep 2:98:276-282.）
（Rodriguez D,et al.Factors associated with acute unscheduled care visits for asthma in the all of US dataset.Am J Emerg Med 2025 Sep 2:98:276-282.）
Abstract
Objectives: Asthma exacerbations can cause patients to visit the emergency department (ED) without prior appointments. This study analyzed factors associated with unscheduled ED visits among asthma patients by examining the All of Us Research Program dataset.
Methods: We conducted a retrospective cohort study using the All of Us database (2018-2024). Electronic health records (EHR) were utilized to identify asthma patients based on physician-reported asthma diagnoses. Patients were divided into three groups based on ED visit frequency during the study period: General Asthma Patients (no ED visits), Single ED Visit Asthma Patients (one visit), and Frequent ED Visit Asthma Patients (more than one visit). Python and R were utilized to perform a multinomial logistic regression analysis in order to examine demographic factors, social determinants, healthcare accessibility, neighborhood conditions and comorbidities.
Results: The research included 47, 227 asthma patients from a total participant pool of 409,420 individuals. The study included 33,046 (70.0 %) General Asthma Patients with no ED visit record, 4779 (10.1 %) Single ED Visit Asthma Patients with a single reported visit and 9402 (19.9 %) Frequent ED Visit Asthma Patients with two or more ED visits. Factors significantly associated with frequent ED visits included income less than $10,000/year (OR = 1.42; 95 % CI [1.25-1.61]), Black/African American race (OR = 2.08; 95 % CI [1.61-2.68]), chest pain (OR = 2.31; 95 % CI [2.16-2.48]), hypertension (OR = 1.19; 95 % CI [1.11-1.28]), respiratory tract infections (OR = 1.60; 95 % CI [1.50-1.71]), anxiety (OR = 1.17; 95 % CI [1.08-1.28]), living near abandoned buildings (OR = 1.20; 95 % CI [1.14-1.26]), and perceived daytime neighborhood unsafety (OR = 1.07; 95 % CI [1.02-1.13]). Protective factors included higher income (>$200,000/year, OR = 0.55; 95 % CI [0.42-0.70]), insurance coverage (OR = 0.65; 95 % CI [0.58-0.71]), older age (OR per year = 0.99; 95 % CI [0.99-0.99]), and male sex (OR = 0.86; 95 % CI [0.81-0.92]). Female patients and younger age were associated with increased likelihood of ED visits.
Conclusions: The frequency of unscheduled ED visits for asthma patients was significantly influenced by social determinants which include race, socioeconomic status, neighborhood factors, and specific comorbidities. Understanding these disparities can aid in the improvement of asthma management and the development of targeted interventions to address these critical factors.
Keywords: Acute care utilization; All of us research program; Asthma; Chronic respiratory disease; Comorbidities; Emergency department visits; Epidemiology; Health data analytics; Healthcare access; Healthcare disparities; Healthcare utilization patterns; Logistic regression; Patient outcomes; Population health; Predictive modeling; Risk factors; Social determinants of health; Socioeconomic status; Unscheduled healthcare visits.
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