Connor Matthew J, Connor Michael J
iAbetics Inc., Menlo Park, California, USA.
J Diabetes Sci Technol. 2010 Sep 1;4(5):1276-83. doi: 10.1177/193229681000400530.
Advances in information technology offer new avenues for assembling data about diet and care regimens of diabetes patients "in the field." This creates a challenge for their doctors and the diabetes care community--how to organize and use new data to produce better long-term outcomes for diabetes patients.
iAbetics approaches the challenge as a quality management problem, drawing on total quality concepts, which in turn are grounded in application of the scientific method. We frame the diabetes patient's quality-of-care problem as an ongoing scientific investigation aimed at quantifying and predicting relationships between specific care-management actions and their outcomes for individual patients in their ordinary course of life.
Framing diabetes quality-of-care management as a scientific investigation leads to a seven-step model termed "adaptive empirical iteration." Adaptive empirical iteration is a deliberate process to perfect the patient's choices, decisions, and actions in routine situations that make up most day-to-day life and to systematically adapt across differences in individual patients and/or changes in their physiology, diet, or environment. The architecture incorporates care-protocol management and version control, structured formats for data collection using mobile smart phones, statistical analysis on secure Web sites, tools for comparing alternative protocols, choice architecture technology to improve patient decisions, and information sharing for doctor review.
Adaptive empirical iteration is a foundation for information architecture designed to systematically improve quality-of-care provided to diabetes patients who act as their own day-to-day care provider under supervision and with support from their doctor. The approach defines "must-have" capabilities for systems using new information technology to improve long-term outcomes for diabetes patients.
信息技术的进步为在“实地”收集糖尿病患者的饮食和护理方案数据提供了新途径。这给他们的医生和糖尿病护理界带来了一项挑战——如何整理和利用新数据，为糖尿病患者带来更好的长期治疗效果。
iAbetics将这一挑战视为质量管理问题，借鉴全面质量管理概念，而全面质量管理概念又基于科学方法的应用。我们将糖尿病患者的护理质量问题构建为一项持续的科学研究，旨在量化和预测特定护理管理行动与其在日常生活中的个体患者结局之间的关系。
将糖尿病护理质量管理构建为科学研究，会引出一个名为“适应性实证迭代”的七步模型。适应性实证迭代是一个深思熟虑的过程，用于完善患者在构成大部分日常生活的常规情况下的选择、决策和行动，并针对个体患者的差异和/或其生理、饮食或环境的变化进行系统调整。该架构包括护理协议管理和版本控制、使用移动智能手机进行数据收集的结构化格式、在安全网站上进行统计分析、比较替代协议的工具、改善患者决策的选择架构技术以及供医生审查的信息共享。
适应性实证迭代是信息架构的基础，旨在系统地提高为在医生监督和支持下自行担任日常护理提供者的糖尿病患者提供的护理质量。该方法定义了使用新信息技术改善糖尿病患者长期治疗效果的系统的“必备”功能。
