St Vincent's Hospital Thoracic Medicine and Cancer Services, Kinghorn Cancer Centre, University of Sydney, Sydney, NSW, Australia.
Cancer Council NSW, Cancer Research Division, University of Sydney, Sydney Catalyst Translational Cancer Research Centre, Sydney, NSW, Australia.
Respirology. 2018 Oct;23(10):927-934. doi: 10.1111/resp.13307. Epub 2018 Apr 11.
While multidisciplinary team (MDT) care in lung cancer is widely practiced, there are few guidelines for MDT on best data collection strategies. MDT meetings need ready access to information for the provision of optimal treatment recommendations (the primary purpose of the meeting), audit of team performance and benchmarking. This study aimed to develop a practical data set designed for these goals through a recognized consensus process with health professionals who participate in formal MDT settings.
A modified Delphi process with three iterations (two surveys and one consensus conference) was carried out involving over 100 Australian lung cancer MDT health professionals.
In total, 122 lung cancer MDT health professionals responded to the Round 1 survey from over 350 invitees. Of the 122, 98 were available for invitation to Round 2. Of 98, 52 (53%) invitees responded to the Round 2 survey. After two rounds, 51 data elements across 8 domains (patient demographics, risk factors, biopsy data, staging, timeliness, treatment, follow-up and patient selection) achieved consensus, defined as 80% agreement. For Round 3, 33 MDT lead clinicians were invited to participate in a consensus conference. Of 33, 14 (42%) invitees distilled the 47 data elements into 23 elements across 8 domains to address the study objectives.
A practical data set for lung cancer MDT to use for optimal treatment recommendations and to evaluate team performance was developed through recognized consensus methodology. Access to streamlined, relevant and feasible data collection strategies may improve MDT decision-making, audit of team performance and facilitate benchmarking.
尽管多学科团队（MDT）在肺癌治疗中已广泛应用，但针对 MDT 最佳数据收集策略的指南却很少。MDT 会议需要随时获取信息，以便提供最佳治疗建议（会议的主要目的）、评估团队绩效和进行基准比较。本研究旨在通过与参与正式 MDT 环境的卫生专业人员进行公认的共识过程，开发一套实用的数据集，以实现这些目标。
采用三轮改良 Delphi 法（两轮问卷调查和一轮共识会议），涉及 100 多名澳大利亚肺癌 MDT 卫生专业人员。
共有 122 名肺癌 MDT 卫生专业人员对 350 多名受邀者中的第一轮调查做出了回应。在这 122 名中，有 98 名可受邀参加第二轮。在 98 名中，有 52 名（53%）受邀者对第二轮调查做出了回应。两轮过后，8 个领域（患者人口统计学、危险因素、活检数据、分期、及时性、治疗、随访和患者选择）共 51 个数据项达成共识，即 80%的参与者表示同意。对于第三轮，邀请了 33 名 MDT 首席临床医生参加共识会议。在这 33 名中，有 14 名（42%）受邀者将 47 个数据项提炼成 8 个领域的 23 个数据项，以满足研究目标。
通过公认的共识方法，开发了一套用于肺癌 MDT 的实用数据集，以实现最佳治疗建议并评估团队绩效。获得简化、相关且可行的数据收集策略可能会改善 MDT 决策、团队绩效评估并促进基准比较。
