医疗资源利用
包含败血症路径干预前后患者的死亡率、住院天数和医疗费用等临床表格数据。
基本信息
资源简介
医疗资源利用
【数据集背景】
本数据集源站标题为《Healthcare utilisation.》。源站首次发布：2023-05-19。
【数据内容】
源站原始描述：With global estimates of 15 million cases of sepsis annually, together with a 24% in-hospital mortality rate, this condition comes at a high cost to both the patient and to the health services delivering care. This translational research determined the cost-effectiveness of state-wide implementation of a whole of hospital Sepsis Pathway in reducing mortality and/or hospital admission costs from a healthcare sector perspective, and report the cost of implementation over 12-months. A non-randomise…
【数据结构与技术规格】
文件数 1 个，合计 9.73 KB。Table 4.xls：application/vnd.ms-excel，9.73 KB。数据集 DOI：10.1371/journal.pgph.0000687.t004。
【主题与分类】
源站学科分类：Medicine、Sociology、Biological Sciences not elsewhere classified、Science Policy。主题标签：victoria &# 8217、translational research determined、public health services、provide hospital care、nurse led model、hospital admission costs、healthcare sector perspective、comprising 23 hospitals、hospital mortality rate、state &# 8217。
【适用方向】
结构化表格数据可直接用于统计建模、特征工程与队列分析。
【获取与许可】
源站页面：https://plos.figshare.com/articles/dataset/Healthcare_utilisation_/22965579
使用许可：CC BY 4.0（https://creativecommons.org/licenses/by/4.0/）。
规范引用：Brusco, Natasha K.; Sykes, Kelly; Cheng, Allen C.; Radia-George, Camilla; Travis, Douglas; Sullivan, Natalie; et al. (2023). Healthcare utilisation.. PLOS Global Public Health. Dataset
【使用注意】
· 源站最后修改于 2023-06-02，引用时请注意版本时效。
下载信息
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使用方式
数据集获取（Figshare）
- 源站标题：Healthcare utilisation.
- DOI：10.1371/journal.pgph.0000687.t004
- 发布日期：2023-05-19
- 文件数：1 个
- 文件总体积：9.73 KB
- 源站页面：https://plos.figshare.com/articles/dataset/Healthcare_utilisation_/22965579
命令行下载
curl -L -o "Table 4.xls" "https://ndownloader.figshare.com/files/40707801"
文件清单
Table 4.xls（9.73 KB）
文件总体积 9.73 KB（源站 API 实测）。
数据说明
With global estimates of 15 million cases of sepsis annually, together with a 24% in-hospital mortality rate, this condition comes at a high cost to both the patient and to the health services delivering care. This translational research determined the cost-effectiveness of state-wide implementation of a whole of hospital Sepsis Pathway in reducing mortality and/or hospital admission costs from a healthcare sector perspective, and report the cost of implementation over 12-months. A non-randomised stepped wedge cluster implementation study design was used to implement an existing Sepsis Pathway (“Think sepsis. Act fast”) across 10 of Victoria’s public health services, comprising 23 hospitals, which provide hospital care to 63% of the State’s population, or 15% of the Australian population. The pathway utilised a nurse led model with early warning and severity criteria, and actions to be initiated within 60 minutes of sepsis recognition. Pathway elements included oxygen administration; blood cultures (x2); venous blood lactate; fluid resuscitation; intravenous antibiotics, and increased monitoring. At baseline there were 876 participants (392 female (44.7%), mean 68.4 years); and during the intervention, there were 1,476 participants (684 female (46.3%), mean 66.8 years). Mortality significantly reduced from 11.4% (100/876) at baseline to 5.8% (85/1,476) during implementation (p>0.001). Respectively, at baseline and intervention the average length of stay was 9.1 (SD 10.3) and 6.2 (SD 7.9) days, and cost was $AUD22,107 (SD $26,937) and $14,203 (SD $17,611) per patient, with a significant 2.9 day reduction in length of stay (-2.9; 95%CI -3.7 to -2.2, p<0.01) and $7,904 reduction in cost (-$7,904; 95%CI -$9,707 to -$6,100, p<0.01). The Sepsis Pathway was a dominant cost-effective intervention due to reduced cost and reduced mortality. Cost of implementation was $1,845,230. In conclusion, a well-resourced state-wide Sepsis Pathway implementation initiative can save lives and dramatically reduce the health service cost per admission.
许可
CC BY 4.0
引用
学术使用请引用 DOI 10.1371/journal.pgph.0000687.t004（source: https://plos.figshare.com/articles/dataset/Healthcare_utilisation_/22965579）。
数据缺失？
依托陕西、四川两大基地，我们与超过十家三甲医院建立直接合作关系，覆盖合规授权、采集治理、专业标注、数据交付的全流程，为AI医疗团队提供即拿即用的高质量临床数据。
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