Emily Stone1, Nicole Rankin2, Jane Phillips3, Kwun Fong4, David C Currow3, Alistair Miller5, Geraldine Largey6, Robert Zielinski7, Peter Flynn8, Tim Shaw9. 1. St Vincent's Hospital Thoracic Medicine and Cancer Services, Kinghorn Cancer Centre, University of Sydney, Sydney, NSW, Australia. 2. Cancer Council NSW, Cancer Research Division, University of Sydney, Sydney Catalyst Translational Cancer Research Centre, Sydney, NSW, Australia. 3. Improving Palliative, Aged and Chronic Care through Clinical Research and Translation (IMPACCT), University of Technology Sydney, Ultimo, NSW, Australia. 4. University of Queensland Thoracic Research Centre, The Prince Charles Hospital, Brisbane, QLD, Australia. 5. Monash Lung and Sleep, Monash Medical Centre, Clayton, VIC, Australia. 6. Program Manager Research and Special Projects, Southern Melbourne Integrated Cancer Services, Melbourne, VIC, Australia. 7. Central West Cancer Care Centre, Orange NSW, University of Western Sydney, Sydney, NSW, Australia. 8. Cardiothoracic Surgeon and Clinical Lead for Lung Cancer, Director Sydney West Translational Cancer Research Centre, Sydney, NSW, Australia. 9. University of Sydney, Sydney Catalyst Translational Cancer Research Centre, Sydney, NSW, Australia.
Abstract
BACKGROUND AND OBJECTIVE: 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. METHODS: 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. RESULTS: 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. CONCLUSION: 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.
BACKGROUND AND OBJECTIVE: 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. METHODS: 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. RESULTS: 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. CONCLUSION: 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.
Authors: Alice C Wismer; Milenko Rakic; Claudia E Kuehni; Manon Jaboyedoff; Fabrizio Romano; Matthias V Kopp; Julia Brandenberger; Georg Staubli; Kristina Keitel Journal: Pediatr Emerg Care Date: 2022-09-11 Impact factor: 1.602
Authors: Misa Matsuyama; Mythily Sachchithananthan; Robyn Leonard; Michael Besser; Anna K Nowak; Donna Truran; Claire M Vajdic; John R Zalcberg; Hui K Gan; Craig Gedye; Winny Varikatt; Eng-Siew Koh; Ganessan Kichenadasse; Hao-Wen Sim; Nicholas G Gottardo; Desma Spyridopoulos; Rosalind L Jeffree Journal: Neurooncol Pract Date: 2021-08-31
Authors: Janneke E W Walraven; Olga L van der Hel; J J M van der Hoeven; Valery E P P Lemmens; Rob H A Verhoeven; Ingrid M E Desar Journal: BMC Health Serv Res Date: 2022-06-27 Impact factor: 2.908