诊断编码与危险调整的短期死亡率之间的差异关键访问和非关键访问医院
Cyrus M Kosar1,2, Lacey Loomer1,2, Kali S Thomas1,2,3
1Department of Health Services, Policy, and Practice, Brown University, Providence, Rhode Island.
JAMA
|August 5, 2020
概括
临界接入医院 (CAH) 的诊断比非CAH更少,但在考虑编码差异时,死亡率相似. 这表明在调整并发症后,CAH结果可能与非CAH结果不相差.
科学领域:
- 医疗服务研究
- 农村卫生
- 医疗保健的质量
背景情况:
- 临床医院对于农村医疗保健至关重要.
- 与非CAH相比,CAH患者的死亡率可能更高.
- 医疗保险的报销政策可能会影响CAH的诊断编码实践.
研究的目的:
- 评估CAH与非CAH风险调整后死亡率的差异.
- 评估诊断编码变化对死亡率比较的影响.
- 了解等级条件类别 (HCC) 评分如何影响风险调整.
主要方法:
- 在2007年至2017年期间对医疗保险收费受益者的连续横截面研究.
- 分析包括肺炎,心力衰竭和中风等常见疾病.
- 使用住院和出院后30天的数据评估死亡率,包括HCC调整.
主要成果:
- 这一差距在2010年以后进一步扩大.
- 考虑到高血压病的风险调整后的死亡率在CAH中较高.
- 然而,当不对住院并发症 (HCC) 进行调整时,大多数年份的CAH和非CAH死亡率没有显著差异.
结论:
- CAH报告诊断较少,可能是由于编码做法.
- 当考虑编码差异时,CAHs的短期死亡结果与非CAHs相似.
- 结果表明编码实践的差异,不一定是护理质量的差异,可能解释了一些观察到的结果差异.
相关概念视频
Comparing the Survival Analysis of Two or More Groups
464
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...
464
Assumptions of Survival Analysis
299
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.
299
Methods of Documentation VI: Case Management Model
768
The case management model is a multidisciplinary approach that involves healthcare professionals from diverse disciplines, such as physicians, nurses, therapists, social workers, and pharmacists, working collaboratively to address the various needs of patients. Each healthcare professional brings unique expertise and perspectives, contributing to a more comprehensive understanding of the patient's condition and tailoring treatment plans accordingly.
For example, a patient with a chronic...
For example, a patient with a chronic...
768
Cancer Survival Analysis
567
Cancer survival analysis focuses on quantifying and interpreting the time from a key starting point, such as diagnosis or the initiation of treatment, to a specific endpoint, such as remission or death. This analysis provides critical insights into treatment effectiveness and factors that influence patient outcomes, helping to shape clinical decisions and guide prognostic evaluations. A cornerstone of oncology research, survival analysis tackles the challenges of skewed, non-normally...
567
Hazard Ratio
453
The hazard ratio (HR) is a widely used measure in clinical trials to compare the risk of events, such as death or disease recurrence, between two groups over time. It reflects the ratio of hazard rates—the instantaneous risk of the event occurring—between a treatment group and a control group. This measure provides valuable insights into the relative effectiveness of a treatment by assessing how the risk of an event differs between the two groups.
For example, in a clinical trial...
For example, in a clinical trial...
453
Censoring Survival Data
422
Survival analysis is a statistical method used to analyze time-to-event data, often employed in fields such as medicine, engineering, and social sciences. One of the key challenges in survival analysis is dealing with incomplete data, a phenomenon known as "censoring." Censoring occurs when the event of interest (such as death, relapse, or system failure) has not occurred for some individuals by the end of the study period or is otherwise unobservable, and it might have many different...
422


