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肺癌多学科团队会议中数据反馈的临床影响:一项混合方法研究。

Clinical impact of data feedback at lung cancer multidisciplinary team meetings: A mixed methods study.

作者信息

Stone Emily, Rankin Nicole M, Vinod Shalini K, Nagarajah Mohan, Donnelly Candice, Currow David C, Fong Kwun M, Phillips Jane L, Shaw Tim

机构信息

Department of Thoracic Medicine, St Vincent's Hospital Sydney, Kinghorn Cancer Centre, University of Sydney, Sydney, New South Wales, Australia.

Research in Implementation Science and e-Health (RISe), Faculty of Health Sciences, University of Sydney, Sydney, New South Wales, Australia.

出版信息

Asia Pac J Clin Oncol. 2020 Feb;16(1):45-55. doi: 10.1111/ajco.13278. Epub 2019 Nov 12.

Abstract

AIM

Multidisciplinary team (MDT) meetings can facilitate optimal lung cancer care, yet details of structured data collection and feedback remain sparse. This study aimed to investigate data collection and the impact of feedback to lung cancer MDTs.

METHODS

A mixed-methods study using pre and post-test surveys, semistructured interviews, and observation to evaluate data collection and response to modeled data feedback in three Australian lung cancer MDTs at different locations and development stage (site A: outer metropolitan, established; site B, outer metropolitan, new; and site C, inner metropolitan, established).

RESULTS

MDT attendees (range 13-25) discussed 5-8 cases per meeting. All sites collected data prospectively (80% prepopulated) into local oncology medical information systems. The pretest survey had 17 respondents in total (88% clinicians). At sites A and C, 100% of respondents noted regular data audits, occasional at site B. Regular audit data included number of cases, stage, final diagnosis, and time to diagnosis and treatment. The post-test survey had 25 respondents in total, all clinicians. The majority (88-96%) of respondents found modeled data easy to interpret, relevant to clinical practice and the MDT, and welcomed future regular data presentations (as rated on a 5-point Likert scale mean weighted average 4.5 where > 4 demonstrates agreement). Semistructured interviews identified five major themes for MDTs: current practice, attitudes, enablers, barriers, and benefits for the MDT.

CONCLUSIONS

MDT teams exhibited positive responses to modeled data feedback. Key characteristics of MDT data were identified and may assist with future team research and development.

摘要

目的

多学科团队(MDT)会议有助于优化肺癌护理,但结构化数据收集和反馈的细节仍然较少。本研究旨在调查肺癌MDT的数据收集情况以及反馈的影响。

方法

采用混合方法研究,通过前后测试调查、半结构化访谈和观察,评估三个位于不同地点和发展阶段的澳大利亚肺癌MDT(地点A:大都市外围,已成熟;地点B:大都市外围,新建;地点C:大都市中心,已成熟)的数据收集情况以及对模拟数据反馈的反应。

结果

MDT参会人员(范围为13 - 25人)每次会议讨论5 - 8个病例。所有地点均前瞻性地(80%为预填充)将数据收集到当地肿瘤医学信息系统中。预测试调查共有17名受访者(88%为临床医生)。在地点A和C,100%的受访者指出有定期数据审核,地点B为偶尔审核。定期审核数据包括病例数、分期、最终诊断以及诊断和治疗时间。后测试调查共有25名受访者,均为临床医生。大多数(88% - 96%)受访者认为模拟数据易于解读、与临床实践和MDT相关,并欢迎未来定期进行数据展示(在5分李克特量表上评分,平均加权平均值为4.5,> 4表示同意)。半结构化访谈确定了MDT的五个主要主题:当前实践、态度、促进因素、障碍以及MDT的益处。

结论

MDT团队对模拟数据反馈表现出积极反应。确定了MDT数据的关键特征,这可能有助于未来团队的研究与发展。

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