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对市售推注计算器的系统性改进:一种以用户为中心的方法。

Systematic Improvement of a Bolus Calculator That Is on the Market: A User-Centric Approach.

作者信息

Eichinger Valerie, de Klepper Mirjam, Zivkovic Josip, Malenczyk Katarzyna, Theodorou Delphine, Heinemann Lutz, Silbermann Stephan

机构信息

mySugr GmbH, Vienna, Austria.

Independent UX Consultant, Vienna, Austria.

出版信息

J Diabetes Sci Technol. 2024 Jul 23:19322968241266204. doi: 10.1177/19322968241266204.

Abstract

BACKGROUND

State-of-the-art diabetes self-management includes the usage of (software) tools, such as Bolus Calculators, to support patients with their therapeutic decisions. The development of such medical devices comes with strict obligations to ensure the safety and performance for the user; however, it is also necessary to continue to evaluate such aspects after the products are introduced into the market. In addition, such aspects cannot always be sufficiently validated by clinical trials; they need real-world evaluation to systematically improve such tools while they are on the market.

METHODS

The approach described here uses innovative ways of generating user-centric evidence to improve the bolus calculator, including (1) human factor engineering, (2) analysis of glycemic real-world data, (3) patient-reported outcomes, and (4) machine-generated behavioral measurements.

RESULTS

The combination of the diverse techniques to optimize the bolus calculator triggered changes in the user experience: a significant reduction in hypoglycemic events, -0.52% (±0.05), < .01, n=3480, an increased diabetes treatment satisfaction (Diabetes Treatment Satisfaction Questionnaire [DTSQ] +9.90, < .01, n=217), as well as an increased acceptance rate of bolus calculations, +15.73 (±0.89), < .01, n=3436, were observed.

CONCLUSIONS

Altogether, human factor engineering and different forms of real-world data support fast and direct adaptations and improvements in products used for diabetes therapy.

摘要

背景

先进的糖尿病自我管理包括使用(软件)工具,如大剂量计算器,以支持患者做出治疗决策。此类医疗设备的开发伴随着确保用户安全和性能的严格义务;然而,在产品投放市场后继续评估这些方面也是必要的。此外,这些方面并非总能通过临床试验得到充分验证;它们需要进行真实世界评估,以便在产品上市期间系统地改进此类工具。

方法

本文所述方法采用创新方式生成以用户为中心的证据,以改进大剂量计算器,包括(1)人因工程学、(2)血糖真实世界数据分析、(3)患者报告结局和(4)机器生成的行为测量。

结果

多种技术相结合优化大剂量计算器引发了用户体验的变化:低血糖事件显著减少,-0.52%(±0.05),P<0.01,n=3480;糖尿病治疗满意度提高(糖尿病治疗满意度问卷[DTSQ]+9.90,P<0.01,n=217);大剂量计算的接受率提高,+15.73(±0.89),P<0.01,n=3436。

结论

总体而言,人因工程学和不同形式的真实世界数据支持对糖尿病治疗所用产品进行快速直接的调整和改进。

相似文献

3
Bolus calculators.推注计算器。
J Diabetes Sci Technol. 2014 Sep;8(5):1035-41. doi: 10.1177/1932296814532906. Epub 2014 May 19.

本文引用的文献

1
Real-World Evidence: A Primer.真实世界证据:基础篇。
Pharmaceut Med. 2023 Jan;37(1):25-36. doi: 10.1007/s40290-022-00456-6. Epub 2023 Jan 5.

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