Auburn University, Harrison School of Pharmacy, Department of Pharmacy Care Systems, 020 Foy Hall, Auburn, AL 36849, USA.
J Biomed Inform. 2013 Oct;46(5):795-804. doi: 10.1016/j.jbi.2013.05.006. Epub 2013 Jun 13.
Drug safety surveillance using observational data requires valid adverse event, or health outcome of interest (HOI) measurement. The objectives of this study were to develop a method to review HOI definitions in claims databases using (1) web-based digital tools to present de-identified patient data, (2) a systematic expert panel review process, and (3) a data collection process enabling analysis of concepts-of-interest that influence panelists' determination of HOI.
De-identified patient data were presented via an interactive web-based dashboard to enable case review and determine if specific HOIs were present or absent. Criteria for determining HOIs and their severity were provided to each panelist. Using a modified Delphi method, six panelist pairs independently reviewed approximately 200 cases across each of three HOIs (acute liver injury, acute kidney injury, and acute myocardial infarction) such that panelist pairs independently reviewed the same cases. Panelists completed an assessment within the dashboard for each case that included their assessment of the presence or absence of the HOI, HOI severity (if present), and data contributing to their decision. Discrepancies within panelist pairs were resolved during a consensus process.
Dashboard development was iterative, focusing on data presentation and recording panelists' assessments. Panelists reported quickly learning how to use the dashboard. The assessment module was used consistently. The dashboard was reliable, enabling an efficient review process for panelists. Modifications were made to the dashboard and review process when necessary to facilitate case review. Our methods should be applied to other health outcomes of interest to further refine the dashboard and case review process.
The expert review process was effective and was supported by the web-based dashboard. Our methods for case review and classification can be applied to future methods for case identification in observational data sources.
使用观察性数据进行药物安全性监测需要对不良事件或感兴趣的健康结局（HOI）进行有效测量。本研究的目的是开发一种使用（1）基于网络的数字工具来呈现去识别患者数据，（2）系统的专家小组审查流程，以及（3）数据分析的概念-利益相关者确定 HOI 的过程，审查索赔数据库中 HOI 定义的方法。
通过交互式基于网络的仪表板呈现去识别患者数据，以进行病例审查并确定是否存在特定的 HOI。向每位小组成员提供了确定 HOI 及其严重程度的标准。使用改良 Delphi 方法，六对小组成员独立审查了三个 HOI（急性肝损伤、急性肾损伤和急性心肌梗死）中的约 200 例病例，使得小组成员对相同的病例进行了独立审查。小组成员在仪表板中为每个病例完成评估，其中包括他们对 HOI 是否存在、HOI 严重程度（如果存在）以及对其决策有贡献的数据的评估。在共识过程中解决了小组成员之间的差异。
仪表板的开发是迭代的，重点是数据呈现和记录小组成员的评估。小组成员报告说他们很快学会了如何使用仪表板。评估模块被一致使用。仪表板是可靠的，为小组成员的审查过程提供了高效的支持。当需要时，对仪表板和审查流程进行了修改，以促进病例审查。应将我们的方法应用于其他感兴趣的健康结局，以进一步完善仪表板和病例审查流程。
专家审查过程是有效的，并得到了基于网络的仪表板的支持。我们的病例审查和分类方法可应用于未来观察性数据源中病例识别的方法。
