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一种混合式自动病历检查、数据收集与分析系统的开发。

Development of a hybrid automated chart checking, data collection, and analysis system.

作者信息

Clouser Edward L, Chen Quan, Harrington Daniel P, Rong Yi, Buckey Courtney R

机构信息

Department of Radiation Oncology, Mayo Clinic Arizona, Phoenix, Arizona, USA.

出版信息

J Appl Clin Med Phys. 2025 Jul;26(7):e70161. doi: 10.1002/acm2.70161.

Abstract

PURPOSE

To describe the creation and clinical deployment of an integrated stand-alone hybrid automated chart review platform that is comprised of a database, oncology information system (OIS) interfaces, and a user interface (UI).

METHODS

A consensus checklist was developed to homogenize the practices of clinical physics staff and physics residents for all plan types. Critical review of the single checklist's items led to the creation of a new concept, the "plan attribute," which permits specialization of the final checklist based on the characteristics of a particular plan. Only relevant and applicable tests are automatically populated to form a plan checklist based on plan attributes. Each populated checklist in this hybrid automation platform includes elements of full automation, steps or functions that use automation to augment a human input or effort, as well as steps completed by humans. Logging and categorizing of deficiencies found during the chart check was also implemented.

RESULTS

Chart check data was analyzed for an over 4-year time span starting from the clinical deployment of the tool in October 2020. This analysis included a total of 427 073 tests spread among 7882 initial chart checks. The recorded deficiencies at three triage levels showed 7116 minor errors, 679 major errors, and 71 plan rejections. The plan rejection level is the highest chart deficiency, which required the plan to be rejected and sent back for serious remediation and/or new plan generation.

CONCLUSION

This report describes the successful development and implementation of a hybrid-automated chart checking program. The software leverages modern database and software design to improve the per case performance and experience of a multi-user group. Chart check database permits high-level review and improvement in all aspects of plan check and user performance.

摘要

目的

描述一个集成的独立混合自动化图表审查平台的创建和临床应用,该平台由数据库、肿瘤信息系统(OIS)接口和用户界面(UI)组成。

方法

制定了一份共识清单,以使临床物理工作人员和物理住院医师对所有计划类型的操作标准化。对单一清单项目的严格审查产生了一个新概念,即“计划属性”,它允许根据特定计划的特征对最终清单进行专门化。仅自动填充相关且适用的测试,以根据计划属性形成计划清单。这个混合自动化平台中的每个填充清单都包括完全自动化的元素、使用自动化来增强人工输入或工作的步骤或功能,以及由人工完成的步骤。还实施了对图表检查期间发现的缺陷进行记录和分类。

结果

从2020年10月该工具临床应用开始,对超过4年时间跨度的图表检查数据进行了分析。该分析包括总共427073次测试,分布在7882次初始图表检查中。在三个分诊级别记录的缺陷显示有7116个小错误、679个大错误和71次计划拒绝。计划拒绝级别是最高的图表缺陷级别,这要求计划被拒绝并送回进行严重整改和/或生成新计划。

结论

本报告描述了一个混合自动化图表检查程序的成功开发和实施。该软件利用现代数据库和软件设计来提高多用户组的每例性能和体验。图表检查数据库允许对计划检查和用户性能的所有方面进行高级审查和改进。

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