自杀死亡前一年的医疗保健利用率:一个多项式方法
Austin Porter1,2, Katy Allison3, Srinivasa B Gokarakonda4
1Fay W. Boozman College of Public Health, Department of Health Policy and Management, University of Arkansas for Medical Sciences, Little Rock, AR, 72205, USA. Austin.Porter@arkansas.gov.
The journal of behavioral health services & research
|November 3, 2025
概括
通过了解那些死于自杀的人的医疗保健机会,可以改善自杀预防工作. 年轻的成年人和男性使用心理健康服务的频率较低,这凸显了针对性干预的需要.
科学领域:
- 公共卫生 公共卫生
- 流行病学 流行病学
- 医疗保健服务研究 医疗服务研究
背景情况:
- 预防自杀是一个关键的公共卫生问题,初级保健机构提供了关键的干预机会.
- 许多有自杀风险的人不寻求必要的治疗,强调需要了解医疗保健利用模式.
- 检查自杀者在获得医疗保健方面的人口差异可以为有针对性的公共卫生战略提供信息.
研究的目的:
- 分析成年自杀者在医疗保健利用中的人口差异.
- 确定在死亡前一年获得精神卫生服务,非精神卫生服务和不使用医疗保健的模式.
主要方法:
- 利用了来自阿肯色州全付款人索赔数据库 (2013-2021) 的数据,与自杀死者的重要记录联系在一起.
- 将医疗保健的利用分为精神卫生保健,非精神卫生保健和没有获得的护理.
- 采用多项物流回归来确定医疗保健利用的预测因素,包括年龄,性别,种族,教育程度,婚姻状况和农村地区.
主要成果:
- 在1678名自杀死者中,38.9%获得了心理健康护理,23.5%获得了非心理健康护理,37.5%没有获得任何护理.
- 较年轻的死者 (18-44岁) 与老年人 (65岁以上) 相比,获得精神和非精神健康服务的可能性明显低.
- 男人比女性更少获得心理健康服务,而非裔美国人使用非心理健康服务的比例更高.
结论:
- 自杀者中医疗保健使用模式因人口因素而有很大差异.
- 需要有针对性的干预措施来解决年轻人和男性医疗保健机会较低的问题.
- 加强定期寻求医疗保健的行为,特别是在压力期间,对于预防自杀的努力至关重要.
相关概念视频
Actuarial Approach
283
The actuarial approach, a statistical method originally developed for life insurance risk assessment, is widely used to calculate survival rates in clinical and population studies. This method accounts for participants lost to follow-up or those who die from causes unrelated to the study, ensuring a more accurate representation of survival probabilities.
Consider the example of a high-risk surgical procedure with significant early-stage mortality. A two-year clinical study is conducted,...
Consider the example of a high-risk surgical procedure with significant early-stage mortality. A two-year clinical study is conducted,...
283
Kaplan-Meier Approach
549
The Kaplan-Meier estimator is a non-parametric method used to estimate the survival function from time-to-event data. In medical research, it is frequently employed to measure the proportion of patients surviving for a certain period after treatment. This estimator is fundamental in analyzing time-to-event data, making it indispensable in clinical trials, epidemiological studies, and reliability engineering. By estimating survival probabilities, researchers can evaluate treatment effectiveness,...
549
Comparing the Survival Analysis of Two or More Groups
548
Survival analysis is a cornerstone of medical research, used to evaluate the time until an event of interest occurs, such as death, disease recurrence, or recovery. Unlike standard statistical methods, survival analysis is particularly adept at handling censored data—instances where the event has not occurred for some participants by the end of the study or remains unobserved. To address these unique challenges, specialized techniques like the Kaplan-Meier estimator, log-rank test, and...
548
Life Tables
488
A life table is a statistical tool that summarizes the mortality and survival patterns of a population, providing detailed insights into the likelihood of survival or death across different age intervals within a cohort. By organizing data on survival probabilities and mortality rates, life tables offer a clear snapshot of population dynamics over time. They are extensively used in demography, public health, actuarial science, and ecology to analyze life expectancy, design health interventions,...
488
Assumptions of Survival Analysis
388
Survival models analyze the time until one or more events occur, such as death in biological organisms or failure in mechanical systems. These models are widely used across fields like medicine, biology, engineering, and public health to study time-to-event phenomena. To ensure accurate results, survival analysis relies on key assumptions and careful study design.
388
Introduction To Survival Analysis
735
Survival analysis is a statistical method used to study time-to-event data, where the "event" might represent outcomes like death, disease relapse, system failure, or recovery. A unique feature of survival data is censoring, which occurs when the event of interest has not been observed for some individuals during the study period. This requires specialized techniques to handle incomplete data effectively.
The primary goal of survival analysis is to estimate survival time—the time...
The primary goal of survival analysis is to estimate survival time—the time...
735


