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重新开发 Predict: Breast Cancer 网站,并提出开发界面以支持决策的建议。

Redevelopment of the Predict: Breast Cancer website and recommendations for developing interfaces to support decision-making.

机构信息

Winton Centre for Risk and Evidence Communication, University of Cambridge, Cambridge, UK.

Division of Neuroscience and Experimental Psychology, University of Manchester, Manchester, UK.

出版信息

Cancer Med. 2021 Aug;10(15):5141-5153. doi: 10.1002/cam4.4072. Epub 2021 Jun 21.

Abstract

OBJECTIVES

To develop a new interface for the widely used prognostic breast cancer tool: Predict: Breast Cancer. To facilitate decision-making around post-surgery breast cancer treatments. To derive recommendations for communicating the outputs of prognostic models to patients and their clinicians.

METHOD

We employed a user-centred design process comprised of background research and iterative testing of prototypes with clinicians and patients. Methods included surveys, focus groups and usability testing.

RESULTS

The updated interface now caters to the needs of a wider audience through the addition of new visualisations, instantaneous updating of results, enhanced explanatory information and the addition of new predictors and outputs. A programme of future research was identified and is now underway, including the provision of quantitative data on the adverse effects of adjuvant breast cancer treatments. Based on our user-centred design process, we identify six recommendations for communicating the outputs of prognostic models including the need to contextualise statistics, identify and address gaps in knowledge, and the critical importance of engaging with prospective users when designing communications.

CONCLUSIONS

For prognostic algorithms to fulfil their potential to assist with decision-making they need carefully designed interfaces. User-centred design puts patients and clinicians needs at the forefront, allowing them to derive the maximum benefit from prognostic models.

摘要

目的

为广泛使用的乳腺癌预后工具 Predict: Breast Cancer 开发一个新的界面,以方便在术后乳腺癌治疗方面做出决策。为向患者及其临床医生传达预后模型的结果提出建议。

方法

我们采用了以用户为中心的设计过程,包括对临床医生和患者进行背景研究和原型迭代测试。方法包括调查、焦点小组和可用性测试。

结果

通过添加新的可视化效果、即时更新结果、增强解释性信息以及添加新的预测因子和输出,更新后的界面现在可以满足更广泛受众的需求。已经确定并正在进行未来的研究计划,包括提供有关辅助乳腺癌治疗不良影响的定量数据。基于我们的以用户为中心的设计过程,我们确定了 6 条用于传达预后模型输出的建议,包括需要使统计数据背景化、识别和解决知识差距,以及在设计沟通时与潜在用户进行接触的重要性。

结论

为了使预后算法能够充分发挥其在决策辅助方面的潜力,它们需要精心设计的界面。以用户为中心的设计将患者和临床医生的需求放在首位,使他们能够从预后模型中获得最大的收益。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0cb2/8335820/7ef23edaa45d/CAM4-10-5141-g001.jpg

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