Suppr超能文献

一种从创伤登记数据集定义基于人群的重伤率的提议方法:医院集水区的划定(I)。

A proposed approach in defining population-based rates of major injury from a trauma registry dataset: delineation of hospital catchment areas (I).

作者信息

Alexandrescu Roxana, O'Brien Sarah J, Lyons Ronan A, Lecky Fiona E

机构信息

Trauma Audit and Research Network, Clinical Science Building, Hope Hospital, University of Manchester, Eccles Old Road, Salford, M6 8HD, UK.

出版信息

BMC Health Serv Res. 2008 Apr 10;8:80. doi: 10.1186/1472-6963-8-80.

Abstract

BACKGROUND

Determining population-based rates for major injury poses methodological challenges. We used hospital discharge data over a 10-year period (1996-2005) from a national trauma registry, the Trauma Audit and Research Network (TARN) Manchester, to construct valid numerators and denominators so that we can calculate population-based rates of major injury in the future.

METHODS

We examined data from all hospitals reporting to TARN for continuity of numerator reporting; rates of completeness for patient postcodes, and clear denominator populations. We defined local market areas (>70% of patients originating from the same postcode district as the hospital). For relevant hospitals we assessed data quality: consistency of reporting, completeness of patient postcodes and for one selected hospital, North Staffordshire Royal Infirmary (NSRI), the capture rate of numerator data reporting. We used an established method based on patient flow to delineate market areas from hospitals discharges. We then assessed the potential competitors, and characterized these denominator areas. Finally we performed a denominator sensitivity analysis using a patient origin matrix based on Hospital Episodes Statistics (HES) to validate our approach.

RESULTS

Sixteen hospitals met the data quality and patient flow criteria for numerator and denominator data, representing 12 hospital catchment areas across England. Data quality issues included fluctuations numbers of reported cases and poor completion of postcodes for some years. We found an overall numerator capture rate of 83.5% for the NSRI. In total we used 40,543 admissions to delineate hospital catchment areas. An average of 3.5 potential hospital competitors and 15.2 postcode districts per area were obtained. The patient origin matrix for NSRI confirmed the accuracy of the denominator/hospital catchment area from the patient flow analysis.

CONCLUSION

Large national trauma registries, including TARN, hold suitable data for determining population-based injury rates. Patient postcodes from hospital discharge allow identification of denominator populations using a market area approach.

摘要

背景

确定基于人群的重伤发生率面临方法学上的挑战。我们利用了国家创伤登记处——曼彻斯特创伤审计与研究网络(TARN)——在10年期间(1996 - 2005年)的医院出院数据,构建有效的分子和分母,以便我们未来能够计算基于人群的重伤发生率。

方法

我们检查了向TARN报告数据的所有医院的数据,以确定分子报告的连续性;患者邮政编码的完整率,以及明确的分母人群。我们定义了当地市场区域(超过70%的患者来自与医院相同邮政编码区)。对于相关医院,我们评估了数据质量:报告的一致性、患者邮政编码的完整性,对于一家选定的医院——北斯塔福德郡皇家医院(NSRI),还评估了分子数据报告的捕获率。我们使用一种基于患者流量的既定方法,从医院出院数据中划定市场区域。然后我们评估了潜在的竞争对手,并对这些分母区域进行了特征描述。最后,我们使用基于医院事件统计(HES)的患者来源矩阵进行分母敏感性分析,以验证我们的方法。

结果

16家医院满足分子和分母数据的数据质量和患者流量标准,代表了英格兰的12个医院集水区。数据质量问题包括报告病例数的波动以及某些年份邮政编码填写不完整。我们发现NSRI的分子总体捕获率为83.5%。我们总共使用了40,543例入院病例来划定医院集水区。每个区域平均有3.5个潜在的医院竞争对手和15.2个邮政编码区。NSRI的患者来源矩阵证实了患者流量分析中分母/医院集水区的准确性。

结论

包括TARN在内的大型国家创伤登记处拥有用于确定基于人群的伤害发生率的合适数据。医院出院时的患者邮政编码允许使用市场区域方法识别分母人群。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6339/2365946/d1c51abfa41c/1472-6963-8-80-1.jpg

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验