Cizik School of Nursing, The University of Texas Health Science Center Houston, Texas, USA.
McWilliams School of Biomedical Informatics, The University of Texas Health Science Center Houston, Texas, USA.
Stud Health Technol Inform. 2024 Jul 24;315:92-97. doi: 10.3233/SHTI240112.
High cholesterol levels significantly contribute to the risk of atherosclerotic cardiovascular disease (ACVD), with a notable portion of ischemic heart disease cases linked to elevated cholesterol levels. Effective graphical displays of lipid panel tests and other cardiac risk factors are crucial for quick and accurate data interpretation, enabling early intervention for individuals with hyperlipidemia. Applying design theories such as Gestalt and distributed cognitive theories is essential for creating user-centered graphical data displays in the context of cardiovascular (CV) risk factors. The proposed dashboard informed by these theories is expected to help healthcare providers better address cardiovascular disease (CVD), enhancing diagnosis, treatment, and prevention. Moreover, this approach may help alleviate clinical provider burnout, improve patient outcomes, and reduce provider stress, thus contributing to safer and more effective healthcare systems.
高胆固醇水平显著增加了动脉粥样硬化性心血管疾病（ASCVD）的风险，其中相当一部分缺血性心脏病病例与胆固醇水平升高有关。有效展示血脂谱检查和其他心脏危险因素的图形对于快速准确地解读数据至关重要，以便对高脂血症患者进行早期干预。在心血管（CV）危险因素的背景下，应用格式塔和分布式认知理论等设计理论对于创建以用户为中心的图形数据显示至关重要。基于这些理论的拟议仪表板有望帮助医疗保健提供者更好地解决心血管疾病（CVD）问题，从而改善诊断、治疗和预防效果。此外，这种方法还有助于减轻临床医生的倦怠感，改善患者的预后，并降低医生的压力，从而促进更安全、更有效的医疗保健系统。
