Institute for Health Metrics and Evaluation, University of Washington, 2301 Fifth Ave, Suite 600, Seattle, WA 98121, USA.
Popul Health Metr. 2011 Aug 4;9:27. doi: 10.1186/1478-7954-9-27.
Verbal autopsy methods are critically important for evaluating the leading causes of death in populations without adequate vital registration systems. With a myriad of analytical and data collection approaches, it is essential to create a high quality validation dataset from different populations to evaluate comparative method performance and make recommendations for future verbal autopsy implementation. This study was undertaken to compile a set of strictly defined gold standard deaths for which verbal autopsies were collected to validate the accuracy of different methods of verbal autopsy cause of death assignment.
Data collection was implemented in six sites in four countries: Andhra Pradesh, India; Bohol, Philippines; Dar es Salaam, Tanzania; Mexico City, Mexico; Pemba Island, Tanzania; and Uttar Pradesh, India. The Population Health Metrics Research Consortium (PHMRC) developed stringent diagnostic criteria including laboratory, pathology, and medical imaging findings to identify gold standard deaths in health facilities as well as an enhanced verbal autopsy instrument based on World Health Organization (WHO) standards. A cause list was constructed based on the WHO Global Burden of Disease estimates of the leading causes of death, potential to identify unique signs and symptoms, and the likely existence of sufficient medical technology to ascertain gold standard cases. Blinded verbal autopsies were collected on all gold standard deaths.
Over 12,000 verbal autopsies on deaths with gold standard diagnoses were collected (7,836 adults, 2,075 children, 1,629 neonates, and 1,002 stillbirths). Difficulties in finding sufficient cases to meet gold standard criteria as well as problems with misclassification for certain causes meant that the target list of causes for analysis was reduced to 34 for adults, 21 for children, and 10 for neonates, excluding stillbirths. To ensure strict independence for the validation of methods and assessment of comparative performance, 500 test-train datasets were created from the universe of cases, covering a range of cause-specific compositions.
This unique, robust validation dataset will allow scholars to evaluate the performance of different verbal autopsy analytic methods as well as instrument design. This dataset can be used to inform the implementation of verbal autopsies to more reliably ascertain cause of death in national health information systems.
在没有充分的生命登记系统的人群中，死因推断方法对于评估主要死因至关重要。由于有无数的分析和数据收集方法，因此必须从不同人群中创建高质量的验证数据集，以评估比较方法的性能并为未来的死因推断实施提出建议。本研究旨在汇集一组严格定义的金标准死亡案例，这些死亡案例已通过死因推断收集，以验证不同死因推断方法确定死因准确性的方法。
数据收集在四个国家的六个地点进行：印度安得拉邦、菲律宾保和岛、坦桑尼亚达累斯萨拉姆、墨西哥墨西哥城、坦桑尼亚奔巴岛和印度北方邦。人口健康指标研究联盟（PHMRC）制定了严格的诊断标准，包括实验室、病理学和医学影像学检查结果，以在医疗机构中确定金标准死亡案例，并根据世界卫生组织（WHO）标准制定了增强型死因推断工具。死因清单基于世界卫生组织全球疾病负担估计的主要死因、确定独特体征和症状的潜力以及确定金标准病例所需的充足医疗技术构建。对所有金标准死亡案例进行了盲法死因推断。
共收集了 12000 多例死因推断金标准诊断死亡案例（7836 例成人、2075 例儿童、1629 例新生儿和 1002 例死产）。由于难以找到足够的病例来满足金标准标准，以及某些死因的分类错误问题，因此用于分析的目标病因清单减少为成人 34 种、儿童 21 种和新生儿 10 种，不包括死产。为确保方法验证和比较性能评估的严格独立性，从病例总体中创建了 500 个测试训练数据集，涵盖了一系列特定病因的组成。
这个独特的、强大的验证数据集将使学者能够评估不同死因推断分析方法和工具设计的性能。该数据集可用于为死因推断的实施提供信息，以更可靠地确定国家卫生信息系统中的死因。
