A proposed approach in defining population-based rates of major injury from a trauma registry dataset: delineation of hospital catchment areas (I).
A proposed approach in defining population-based rates of major injury from a trauma registry dataset: delineation of hospital catchment areas (I).
复制标题
DOI：
10.1186/1472-6963-8-80
复制
发表时间：
2008-04-10
影响因子：
2.8
通讯作者：
Trauma Audit and Research Network
中科院分区：
文献类型：
--
作者：
Alexandrescu R;O'Brien SJ;Lyons RA;Lecky FE;Trauma Audit and Research Network
确定以人口为基础的重大伤害发生率带来了方法上的挑战。我们使用来自国家创伤登记处（曼彻斯特创伤审计和研究网络（TARN））的10年（1996-2005）的出院数据来构建有效的分子和因子，以便我们可以计算未来基于人口的重大损伤率。我们检查了来自所有向TARN报告的医院的数据，以确保分子报告的连续性;患者邮政编码的完整率和明确的分母人群。我们定义了当地市场区域（>70%的患者来自与医院相同的邮政编码区）。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），评估了分子数据报告的捕获率。我们使用了一个既定的方法的基础上，病人流量划定市场领域的医院出院。然后，我们评估了潜在的竞争对手，并描述了这些分母领域。最后，我们进行了分母的敏感性分析，使用基于医院流行病学统计（HES）的患者来源矩阵，以验证我们的方法。16家医院符合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12家医院的集水区。数据质量问题包括报告病例数的波动和一些年来邮政编码填写不完整。我们发现NSRI的总体分子捕获率为83.5%。我们总共使用了40，543名住院患者来划定医院的服务区域。平均3.5个潜在的医院竞争对手和15.2个邮政编码区每个地区获得。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。大型国家创伤登记处，包括TARN，拥有确定基于人群的伤害率的合适数据。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。
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. 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. 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. 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.
登录
查看更多内容
影响因子：
3.4
作者：
Goodman, DC;Mick, SS;Carretta, HJ
通讯作者：
Carretta, HJ
影响因子：
3.7
作者：
Lyons, RA;Jones, SJ;Heaven, M
通讯作者：
Heaven, M
DOI：
10.1097/00005373-197403000-00001
发表时间：
1974-01-01
影响因子：
--
作者：
BAKER, SP;ONEILL, B;LONG, WB
通讯作者：
LONG, WB
影响因子：
--
作者：
Hippisley-Cox, J;Groom, L;Savelyich, B
通讯作者：
Savelyich, B
影响因子：
3.4
作者：
Gresenz, CR;Rogowski, J;Escarce, JJ
通讯作者：
Escarce, JJ