Identifying priorities in methodological research using ICD-9-ICM and ICD-10 administrative data: report from an international consortium
Identifying priorities in methodological research using ICD-9-ICM and ICD-10 administrative data: report from an international consortium
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DOI：
10.1186/1472-6963-6-77
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发表时间：
2006-06-15
影响因子：
2.8
通讯作者：
Ghali, William A.
中科院分区：
文献类型：
--
作者：
De Coster, Carolyn;Quan, Hude;Ghali, William A.
背景：卫生行政数据经常被用于卫生服务和人口健康研究。使用国际疾病分类(ICD)这一诊断编码标准系统，为使用这些数据进行比较研究提供了便利。使用数据的研究必须处理由于数据不是为研究目的而创建而产生的数据质量和有效性限制。方法：2005年6月，来自加拿大、美国、瑞士、澳大利亚、中国和英国的卫生管理数据研究人员和用户齐聚加拿大班夫，讨论和确定高优先级方法学研究领域。研究想法的产生不仅侧重于与在保健服务和人口健康研究中使用行政数据有关的事项，而且还侧重于从ICD-9过渡到ICD-10所带来的挑战。头脑风暴会议结束后，投票对建议的项目进行了排序。参与者被要求对每个项目的重要性进行评级，从1(低优先级)到10(高优先级)。结果：确定了13个潜在的研究领域，其中一些代表了准备工作，而不是研究本身。排名最靠前的三个优先事项是各国医院管理数据中数据字段的记录(平均得分8.4)，患者安全指标从ICD-9到ICD-10的转换(平均得分8.0)，以及验证医院摘要数据编码的逻辑和内部一致性的算法的开发和验证(平均得分7.0)。结论：小组讨论产生了一份关于未来卫生管理数据方法学研究的关键国际优先事项的专家意见清单。该联盟的成员欢迎参与使用卫生行政数据的研究的调查人员的联系，特别是在跨司法管辖区的合作研究或说明ICD-10应用的研究中。
Background: Health administrative data are frequently used for health services and population health research. Comparative research using these data has been facilitated by the use of a standard system for coding diagnoses, the International Classification of Diseases (ICD). Research using the data must deal with data quality and validity limitations which arise because the data are not created for research purposes. This paper presents a list of high-priority methodological areas for researchers using health administrative data.Methods: A group of researchers and users of health administrative data from Canada, the United States, Switzerland, Australia, China and the United Kingdom came together in June 2005 in Banff, Canada to discuss and identify high-priority methodological research areas. The generation of ideas for research focussed not only on matters relating to the use of administrative data in health services and population health research, but also on the challenges created in transitioning from ICD-9 to ICD-10. After the brain-storming session, voting took place to rank-order the suggested projects. Participants were asked to rate the importance of each project from 1 ( low priority) to 10 ( high priority). Average ranks were computed to prioritise the projects.Results: Thirteen potential areas of research were identified, some of which represented preparatory work rather than research per se. The three most highly ranked priorities were the documentation of data fields in each country's hospital administrative data ( average score 8.4), the translation of patient safety indicators from ICD-9 to ICD-10 ( average score 8.0), and the development and validation of algorithms to verify the logic and internal consistency of coding in hospital abstract data ( average score 7.0).Conclusion: The group discussions resulted in a list of expert views on critical international priorities for future methodological research relating to health administrative data. The consortium's members welcome contacts from investigators involved in research using health administrative data, especially in cross-jurisdictional collaborative studies or in studies that illustrate the application of ICD-10.