Improving performance of the Tariff Method for assigning causes of death to verbal autopsies
Improving performance of the Tariff Method for assigning causes of death to verbal autopsies
复制标题
DOI：
10.1186/s12916-015-0527-9
复制
发表时间：
2015-12-08
期刊：
影响因子：
9.3
通讯作者：
Lopez, Alan D.
中科院分区：
文献类型：
--
作者：
Serina, Peter;Riley, Ian;Lopez, Alan D.
背景：关于人群死因分布的可靠数据是良好公共卫生实践的基础。在没有全面的死亡医学证明的情况下，收集基本死亡率数据的唯一可行方法是死因推断。关税法是由人口健康研究联盟（PHMRC）开发的，用于从VA信息中确定COD。鉴于其改善COD信息的潜力，人们有兴趣改进该方法。我们描述了进一步发展的Tariff Methods.Methods：本研究使用的数据从PHMRC和澳大利亚国家卫生与医学研究理事会（NHMRC）的研究。医院死亡的金标准临床诊断标准被指定为目标原因列表。VA收集家庭使用PHMRC死因推断工具，包括医疗保健经验（HCE）。使用经验证的PHMRC数据库对原始关税方法（关税1.0）进行了培训，其中已收集了符合黄金标准（经验证的VA）的医院记录的死亡VA。在这项研究中，关税1.0的性能进行了测试，从家庭调查（社区VA）收集的PHMRC和NHMRC研究的VA。然后，我们修正了模型，以解释先前观察到的模型偏差，并开发了关税2.0。关税2.0的性能进行了测量，在个人和人口水平上使用的验证PHMRC database.Results：中位机会校正一致性（CCC）和平均原因特异性死亡率分数（CSMF）的准确性，并为每三个模块，有和没有HCE，关税2.0执行显着优于关税1.0，特别是在儿童和新生儿。成人、儿童和新生儿HCE治疗后CSMF准确性的改善分别为2.5%、7.4%和14.9%，HCE治疗后中位CCC准确性的改善分别为6.0%、13.5%和21.2%。类似的改进水平，在分析中看到没有HCE.Conclusions：关税2.0解决了关税方法的应用程序的主要缺点，在社区环境中分析数据从VA。它提供了一个估计COD从VA具有更好的性能，在个人和人口水平比以前版本的这种方法，它是公开使用。
Background: Reliable data on the distribution of causes of death (COD) in a population are fundamental to good public health practice. In the absence of comprehensive medical certification of deaths, the only feasible way to collect essential mortality data is verbal autopsy (VA). The Tariff Method was developed by the Population Health Metrics Research Consortium (PHMRC) to ascertain COD from VA information. Given its potential for improving information about COD, there is interest in refining the method. We describe the further development of the Tariff Method.Methods: This study uses data from the PHMRC and the National Health and Medical Research Council (NHMRC) of Australia studies. Gold standard clinical diagnostic criteria for hospital deaths were specified for a target cause list. VAs were collected from families using the PHMRC verbal autopsy instrument including health care experience (HCE). The original Tariff Method (Tariff 1.0) was trained using the validated PHMRC database for which VAs had been collected for deaths with hospital records fulfilling the gold standard criteria (validated VAs). In this study, the performance of Tariff 1.0 was tested using VAs from household surveys (community VAs) collected for the PHMRC and NHMRC studies. We then corrected the model to account for the previous observed biases of the model, and Tariff 2.0 was developed. The performance of Tariff 2.0 was measured at individual and population levels using the validated PHMRC database.Results: For median chance-corrected concordance (CCC) and mean cause-specific mortality fraction (CSMF) accuracy, and for each of three modules with and without HCE, Tariff 2.0 performs significantly better than the Tariff 1.0, especially in children and neonates. Improvement in CSMF accuracy with HCE was 2.5 %, 7.4 %, and 14.9 % for adults, children, and neonates, respectively, and for median CCC with HCE it was 6.0 %, 13.5 %, and 21.2 %, respectively. Similar levels of improvement are seen in analyses without HCE.Conclusions: Tariff 2.0 addresses the main shortcomings of the application of the Tariff Method to analyze data from VAs in community settings. It provides an estimation of COD from VAs with better performance at the individual and population level than the previous version of this method, and it is publicly available for use.