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政策聚焦对关键时间敏感型疾病的影响:台湾医院急诊能力分类政策的全国性回顾性队列研究

Policy Spotlight Effects on Critical Time-Sensitive Diseases: Nationwide Retrospective Cohort Study on Taiwan's Hospital Emergency Capability Categorization Policy.

作者信息

Lin Chih-Yuan, Liu Chih-Ching, Huang Yu-Tung, Lee Yue-Chune

机构信息

Department of Neurology, Taipei City Hospital Linsen Chinese Medicine Branch, Taipei City, Taiwan.

Institute of Health and Welfare, College of Medicine, Yangming Campus, National Yang Ming Chiao Tung University, Taipei, Taiwan, Taipei City, Taiwan.

出版信息

Interact J Med Res. 2025 Mar 25;14:e54651. doi: 10.2196/54651.

DOI:10.2196/54651
PMID:40132185
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11979550/
Abstract

BACKGROUND

Taiwan's categorization of hospital emergency capability (CHEC) policy is designed to regionalize and dispatch critical patients. The policy was designed in 2009 to improve the quality of emergency care for critical time-sensitive diseases (CTSDs). The CHEC policy primarily uses time-based quality surveillance indicators.

OBJECTIVE

We aimed to investigate the impact of Taiwan's CHEC policy on CTSDs.

METHODS

Using Taiwan's 2005 Longitudinal Health Insurance Database, this nationwide retrospective cohort study examined the CHEC policy's impact from 2005 to 2011. Propensity score matching and difference-in-differences analysis within a generalized estimating equation framework were used to compare pre- and postimplementation periods. The study focused on acute ischemic stroke (AIS), ST-segment elevation myocardial infarction (STEMI), septic shock, and major trauma. AIS and STEMI cases, monitored with time-based indicators, were evaluated for adherence to diagnostic and treatment guidelines as process quality measures. Mortality and medical use served as outcome indicators. Major trauma, with evolving guidelines and no time-based monitoring, acted as a control to test for policy spotlight effects.

RESULTS

In our cohort of 9923 patients, refined through 1:1 propensity score matching, 5566 (56.09%) were male and were mostly older adults. Our analysis revealed that the CHEC policy effectively improved system efficiency and patient outcomes, resulting in significant reductions in medical orders (-7.29 items, 95% CI -10.09 to -4.48; P<.001), short-term mortality rates (-0.09%, 95% CI -0.17% to -0.02%; P=.01) and long-term mortality rates (-0.09%, 95% CI -0.15% to -0.04%; P=.001), and total medical expenses (-5328.35 points per case, 95% CI -10,387.10 to -269.60; P=.04), despite a modest increase in diagnostic fees (376.37 points, 95% CI 92.42-660.33; P=.01). The CHEC policy led to notable increases in diagnostic fees, major treatments, and medical orders for AIS and STEMI cases. For AIS cases, significant increases were observed in major treatments (β=0.77; 95% CI 0.21-1.33; P=.007) and medical orders (β=15.20; 95% CI 5.28-25.11; P=.003) compared to major trauma. In STEMI cases, diagnostic fees significantly increased (β=1983.75; 95% CI 84.28-3883.21; P=.04), while upward transfer rates significantly decreased (β=-0.59; 95% CI -1.18 to -0.001; P=.049). There were also trends toward increased major treatments (β=0.30; 95% CI -0.03 to 0.62, P=.07), medical orders (β=11.92; 95% CI -0.90 to 24.73; P=.07), and medical expenses (β=24,275.54; 95% CI -640.71 to 4,991,991.78; P=.06), although these were not statistically significant. In contrast, no significant changes were identified in process or outcome quality indicators for septic shock. These findings suggest policy spotlight effects, reflecting a greater emphasis on diseases directly prioritized under the CHEC policy.

CONCLUSIONS

The CHEC policy demonstrated the dual benefits of reducing costs and improving patient outcomes. We observed unintended consequences of policy spotlight effects, which led to a disproportionate improvement in guideline adherence and process quality for CTSDs with time-based surveillance indicators.

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6116/11979550/ce54f87b3eab/ijmr_v14i1e54651_fig1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6116/11979550/ce54f87b3eab/ijmr_v14i1e54651_fig1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6116/11979550/ce54f87b3eab/ijmr_v14i1e54651_fig1.jpg
摘要

背景

台湾医院急诊能力分类(CHEC)政策旨在对危急患者进行区域划分和调配。该政策于2009年制定,旨在提高对时间敏感型危急疾病(CTSD)的急诊护理质量。CHEC政策主要使用基于时间的质量监测指标。

目的

我们旨在调查台湾CHEC政策对CTSD的影响。

方法

利用台湾2005年纵向健康保险数据库,这项全国性回顾性队列研究考察了2005年至2011年CHEC政策的影响。在广义估计方程框架内使用倾向得分匹配和差分分析来比较实施前后的时期。该研究重点关注急性缺血性中风(AIS)、ST段抬高型心肌梗死(STEMI)、感染性休克和严重创伤。对使用基于时间指标监测的AIS和STEMI病例,作为过程质量指标评估其对诊断和治疗指南的遵循情况。死亡率和医疗使用情况作为结果指标。严重创伤,其指南不断演变且无基于时间的监测,作为对照来检验政策聚焦效应。

结果

在我们通过1:1倾向得分匹配筛选出的9923例患者队列中,5566例(56.09%)为男性,且大多为老年人。我们的分析表明,CHEC政策有效提高了系统效率和患者预后,导致医疗医嘱显著减少(-7.29项,95%置信区间-10.09至-4.48;P<.001)、短期死亡率(-0.09%,95%置信区间-0.17%至-0.02%;P=.01)和长期死亡率(-0.09%,95%置信区间-0.15%至-0.04%;P=.001),以及总医疗费用(-5328.35分/例,95%置信区间-10387.10至-269.6;P=.04),尽管诊断费用有适度增加(376.37分,95%置信区间92.42 - 660.33;P=.01)。CHEC政策导致AIS和STEMI病例的诊断费用、主要治疗和医疗医嘱显著增加。与严重创伤相比,AIS病例的主要治疗(β = 0.77;95%置信区间0.21 - 1.33;P=.007)和医疗医嘱(β = 15.20;95%置信区间5.28 - 25.11;P=.003)显著增加。在STEMI病例中,诊断费用显著增加(β = 1983.75;95%置信区间84.28 - 3883.21;P=.04),而向上转诊率显著降低(β = -0.59;95%置信区间-1.18至-0.001;P=.049)。主要治疗(β = 0.30;95%置信区间-0.03至0.62,P=.07)、医疗医嘱(β = 11.92;95%置信区间-0.90至24.73;P=.07)和医疗费用(β = 24275.54;95%置信区间-第六百四十点七一至4991991.78;P=.06)也有增加趋势,尽管这些无统计学意义。相比之下,感染性休克的过程或结果质量指标未发现显著变化。这些发现表明存在政策聚焦效应,反映出对CHEC政策直接优先考虑的疾病给予了更大关注。

结论

CHEC政策显示出降低成本和改善患者预后的双重益处。我们观察到政策聚焦效应的意外后果,即对于有基于时间监测指标的CTSD,其在遵循指南和过程质量方面有不成比例的改善。

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