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A measure of case complexity for streamlining workflow in multidisciplinary tumor boards: Mixed methods development and early validation of the MeDiC tool.
Soukup, Tayana; Morbi, Abigail; Lamb, Benjamin W; Gandamihardja, Tasha A K; Hogben, Katy; Noyes, Katia; Skolarus, Ted A; Darzi, Ara; Sevdalis, Nick; Green, James S A.
Afiliação
  • Soukup T; Centre for Implementation Science, Health Service and Population Research Department, King's College London, London, UK.
  • Morbi A; Department of Surgery, University College London Hospitals NHS Foundation Trust, London, UK.
  • Lamb BW; Department of Surgery and Cancer, Imperial College London, London, UK.
  • Gandamihardja TAK; Department of Urology, Cambridge University Hospitals NHS Foundation Trust, Cambridge, UK.
  • Hogben K; Chelmsford Breast Unit, Broomfield Hospital, Chelmsford, UK.
  • Noyes K; Department of Surgery and Cancer, Imperial College London NHS Trust, London, UK.
  • Skolarus TA; Department of Epidemiology and Environmental Health, University of Buffalo, Buffalo, NY, USA.
  • Darzi A; Dow Division of Health Services Research, Department of Urology, University of Michigan, Center for Clinical Management Research, Veterans Affairs Ann Arbor Healthcare System, Ann Arbor, MI, USA.
  • Sevdalis N; Department of Surgery and Cancer, Imperial College London, London, UK.
  • Green JSA; Centre for Implementation Science, Health Service and Population Research Department, King's College London, London, UK.
Cancer Med ; 9(14): 5143-5154, 2020 07.
Article em En | MEDLINE | ID: mdl-32476281
BACKGROUND AND OBJECTIVE: There is increasing emphasis in cancer care globally for care to be reviewed and managed by multidisciplinary teams (ie, in tumor boards). Evidence and recommendations suggest that the complexity of each patient case needs to be considered as care is planned; however, no tool currently exists for cancer teams to do so. We report the development and early validation of such a tool. METHODS: We used a mixed-methods approach involving psychometric evaluation and expert review to develop the Measure of case-Discussion Complexity (MeDiC) between May 2014 and November 2016. The study ran in six phases and included ethnographic interviews, observations, surveys, feasibility and reliability testing, expert consensus, and multiple expert-team reviews. RESULTS: Phase-1: case complexity factors identified through literature review and expert interviews; Phase-2: 51 factors subjected to iterative review and content validation by nine cancer teams across four England Trusts with nine further items identified; Phase 3: 60 items subjected to expert review distilled to the most relevant; Phase 4: item weighing and further content validation through a national UK survey; Phases 5 and 6: excellent interassessor reliability between clinical and nonclinical observers, and adequate validity on 903 video case discussions achieved. A final set of 27 factors, measuring clinical and logistical complexities were integrated into MeDiC. CONCLUSIONS: MeDiC is an evidence-based and expert-driven tool that gauges the complexity of cancer cases. MeDiC may be used as a clinical quality assurance and screening tool for tumor board consideration through case selection and prioritization.
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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Psicometria / Garantia da Qualidade dos Cuidados de Saúde Tipo de estudo: Guideline / Prognostic_studies / Qualitative_research / Systematic_reviews Limite: Female / Humans / Male Idioma: En Revista: Cancer Med Ano de publicação: 2020 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Psicometria / Garantia da Qualidade dos Cuidados de Saúde Tipo de estudo: Guideline / Prognostic_studies / Qualitative_research / Systematic_reviews Limite: Female / Humans / Male Idioma: En Revista: Cancer Med Ano de publicação: 2020 Tipo de documento: Article