Australian Institute of Health Innovation, Macquarie University, Sydney, NSW 2109, Australia.
J Am Med Inform Assoc. 2023 Nov 17;30(12):2086-2097. doi: 10.1093/jamia/ocad176.
This article proposes a framework to support the scientific research of standards so that they can be better measured, evaluated, and designed.
Beginning with the notion of common models, the framework describes the general standard problem-the seeming impossibility of creating a singular, persistent, and definitive standard which is not subject to change over time in an open system.
The standard problem arises from uncertainty driven by variations in operating context, standard quality, differences in implementation, and drift over time. As a result, fitting work using conformance services is needed to repair these gaps between a standard and what is required for real-world use. To guide standards design and repair, a framework for measuring performance in context is suggested, based on signal detection theory and technomarkers. Based on the type of common model in operation, different conformance strategies are identified: (1) Universal conformance (all agents access the same standard); (2) Mediated conformance (an interoperability layer supports heterogeneous agents); and (3) Localized conformance (autonomous adaptive agents manage their own needs). Conformance methods include incremental design, modular design, adaptors, and creating interactive and adaptive agents.
Machine learning should have a major role in adaptive fitting. Research to guide the choice and design of conformance services may focus on the stability and homogeneity of shared tasks, and whether common models are shared ahead of time or adjusted at task time.
This analysis conceptually decouples interoperability and standardization. While standards facilitate interoperability, interoperability is achievable without standardization.
本文提出了一个支持标准科学研究的框架，以便更好地衡量、评估和设计标准。
该框架从通用模型的概念出发，描述了一般标准问题——即在开放系统中，不可能创建一个单一的、持久的、明确的标准，并且随着时间的推移不会发生变化。
标准问题源于由操作上下文、标准质量、实现差异和随时间漂移的不确定性引起的。因此，需要使用一致性服务来适应工作，以修复标准与现实世界使用所需标准之间的差距。为了指导标准设计和修复，基于信号检测理论和技术指标，提出了一种用于在上下文中衡量性能的框架。根据操作中的通用模型类型，确定了不同的一致性策略：（1）通用一致性（所有代理访问相同的标准）；（2）中介一致性（互操作性层支持异构代理）；（3）本地化一致性（自主自适应代理管理自己的需求）。一致性方法包括增量设计、模块化设计、适配器以及创建交互和自适应代理。
机器学习应该在自适应拟合中发挥重要作用。指导一致性服务选择和设计的研究可能集中在共享任务的稳定性和同质性上，以及通用模型是提前共享还是在任务时进行调整。
该分析从概念上解耦了互操作性和标准化。虽然标准促进了互操作性，但没有标准化也可以实现互操作性。
