期刊论文详细信息
Current oncology
Identification of performance indicators across a network of clinical cancer programs
G. Bartlett1  S.R. Khare1  G. Batist2 
[1]McGill University
[2]Segal Cancer Center, Jewish General Hospital
关键词: Performance measures;    quality indicators;    health care quality assessment;    quality improvement;    quality of cancer care;   
DOI  :  10.3747/co.23.2789
学科分类:肿瘤学
来源: Multimed, Inc.
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【 摘 要 】
BackgroundCancer quality indicators have previously been described for a single tumour site or a single treatment modality, or according to distinct data sources. Our objective was to identify cancer quality indicators across all treatment modalities specific to breast, prostate, colorectal, and lung cancer. MethodsCandidate indicators for each tumour site were extracted from the relevant literature and rated in a modified Delphi approach by multidisciplinary groups of expert clinicians from 3 clinical cancer programs. All rating rounds were conducted by e-mail, except for one that was conducted as a face-to-face expert panel meeting, thus modifying the original Delphi technique. Four high-level indicators were chosen for immediate data collection. A list of confounding variables was also constructed in a separate literature review. ResultsA total of 156 candidate indicators were identified for breast cancer, 68 for colorectal cancer, 40 for lung cancer, and 43 for prostate cancer. Iterative rounds of ratings led to a final list of 20 evidence- and consensus-based indicators each for colorectal and lung cancer, and 19 each for breast and prostate cancer. Approximately 30 clinicians participated in the selection of the breast, lung, and prostate indicators; approximately 50 clinicians participated in the selection of the colorectal indicators. ConclusionsThe modified Delphi approach that incorporates an in-person meeting of expert clinicians is an effective and efficient method for performance indicator selection and offers the added benefit of optimal clinician engagement. The finalized indicator lists for each tumour site, together with salient confounding variables, can be directly adopted (or adapted) for deployment within a performance improvement program.
【 授权许可】

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