儿童养诊所错过的机会:多变量分析
Amy Ricketts1, Dana M Bakula2, Sarah Edwards3
1Remote Health Solutions, Children's Mercy Hospital, Kansas City, MO; School of Nursing and Health Sciences, University of Missouri-Kansas City, Kansas City, MO; Division of Gastroenterology, Children's Mercy Hospital, Kansas City, MO.
概括
30.2%的儿科预约没有出现,与更长的等待时间和边缘化群体有关. 减少儿科预约缺席需要解决预约时间问题,并支持弱势群体.
科学领域:
- 儿童获得医疗保健的机会.
- 医疗保健管理的管理
- 公共卫生 公共卫生
背景情况:
- 患者不参加儿科门诊就诊会破坏诊所的工作流程.
- 错过的预约限制了患者获得基本医疗保健服务的机会.
- 没有出现导致医疗保健系统的重大财务损失.
研究的目的:
- 确定儿童门诊护理中患者不出院的关键决定因素.
- 分析影响幼儿错过预约的因素.
- 为减少无人出现率和改善医疗保健准入的战略提供信息.
主要方法:
- 对487名计划在2023年1月至7月期间的儿科患者 (≤4岁) 的分析.
- 描述性人口统计分析和检查预约预约时间.
- 单变量和多变量后勤回归用于识别非出席预测因素.
主要成果:
- 错过机会的总比率为30.2% (147名患者).
- 缺席的独立决定因素包括预约领先时间,边缘化人口,药物使用和以前的缺席.
- 多变量后勤回归确定了这些变量和错过约会之间的显著关系.
结论:
- 预约预约时间是导致儿科不出院的主要可修改因素.
- 非可修改的因素突出显示了有针对性的干预措施的领域,以减少错过的预约.
- 减少未出院的策略应优先考虑改善贫困社区弱势儿科患者的治疗机会.
相关概念视频
Inflammatory Bowel Disease III: Diagnostic Studies and Management I-Nutritional Therapy
643
Various diagnostic tests are employed in the diagnostic process for Inflammatory Bowel Disease (IBD), particularly to differentiate between Crohn's disease and ulcerative colitis.
Diagnostic studies
A colonoscopy is the definitive screening test, distinguishing ulcerative colitis from other colon diseases with similar symptoms. During a colonoscopy test, inflamed mucosa with exudate ulcerations can be observed, and biopsies are taken to determine the histologic characteristics of the...
Diagnostic studies
A colonoscopy is the definitive screening test, distinguishing ulcerative colitis from other colon diseases with similar symptoms. During a colonoscopy test, inflamed mucosa with exudate ulcerations can be observed, and biopsies are taken to determine the histologic characteristics of the...
643
Bias in Epidemiological Studies
1.3K
Biases can arise at various stages of research, from study design and data collection to analysis and interpretation. Recognizing and addressing these biases is essential to ensure the validity and reliability of epidemiological findings.Broadly speaking, biases in epidemiology fall into three main categories: selection bias, information bias, and confounding. A more detailed description of possible biases is:
1.3K
Confounding in Epidemiological Studies
578
Confounding in statistical epidemiology represents a pivotal challenge, referring to the distortion in the perceived relationship between an exposure and an outcome due to the presence of a third variable, known as a confounder. This variable is associated with both the exposure and the outcome but is not a direct link in their causal chain. Its presence can lead to erroneous interpretations of the exposure's effect, either exaggerating or underestimating the true association. This...
578
Strategies for Assessing and Addressing Confounding
360
Confounding is a critical issue in epidemiological studies, often leading to misleading conclusions about associations between exposures and outcomes. It occurs when the relationship between the exposure and the outcome is mixed with the effects of other factors that influence the outcome. Given that, addressing confounding is of high importance for drawing accurate inferences in research.
Confounding can be addressed at both the design phase of a study and through analytical methods after data...
Confounding can be addressed at both the design phase of a study and through analytical methods after data...
360
Statistical Methods for Analyzing Epidemiological Data
898
Epidemiological data primarily involves information on specific populations' occurrence, distribution, and determinants of health and diseases. This data is crucial for understanding disease patterns and impacts, aiding public health decision-making and disease prevention strategies. The analysis of epidemiological data employs various statistical methods to interpret health-related data effectively. Here are some commonly used methods:
898
Model-Independent Approaches for Pharmacokinetic Data: Noncompartmental Analysis
319
Noncompartmental analyses offer an alternative method for describing drug pharmacokinetics without relying on a specific compartmental model. In this approach, the drug's pharmacokinetics are assumed to be linear, with the terminal phase log-linear. This assumption allows for simplified analysis and interpretation of the drug's behavior in the body.
One important characteristic of noncompartmental analyses is that drug exposure increases proportionally with increasing doses. This...
One important characteristic of noncompartmental analyses is that drug exposure increases proportionally with increasing doses. This...
319


