Clinical decision support systems are software tools that help clinicians to make medical decisions. However, their acceptance by clinicians is usually rather low. A known problem is that they often require clinicians to manually enter lots of patient data, which is long and tedious. Existing solutions, such as the automatic data extraction from electronic health record, are not fully satisfying, because of low data quality and availability. In practice, many systems still include long questionnaire for data entry. In this paper, we propose an original solution to simplify patient data entry, using an adaptive questionnaire, i.e. a questionnaire that evolves during user interaction, showing or hiding questions dynamically. Considering a rule-based decision support systems, we designed methods for translating the system's clinical rules into display rules that determine the items to show in the questionnaire, and methods for determining the optimal order of priority among the items in the questionnaire. We applied this approach to a decision support system implementing STOPP/START v2, a guideline for managing polypharmacy. We show that it permits reducing by about two thirds the number of clinical conditions displayed in the questionnaire. Presented to clinicians during focus group sessions, the adaptive questionnaire was found "pretty easy to use". In the future, this approach could be applied to other guidelines, and adapted for data entry by patients.

翻译：临床决策支持系统是帮助临床医生做出医疗决策的软件工具。然而，临床医生对其接受度通常较低。一个已知问题是，这些系统常要求临床医生手动输入大量患者数据，过程冗长且繁琐。现有解决方案，如从电子健康记录中自动提取数据，因数据质量和可用性不足而未完全令人满意。实践中，许多系统仍包含用于数据输入的长问卷。本文提出一种创新解决方案，利用适应性问卷简化患者数据输入，即一种在用户交互过程中动态显示或隐藏问题的问卷。针对基于规则的决策支持系统，我们设计了将系统临床规则转化为决定问卷中显示项目的显示规则的方法，以及确定问卷项目间最优优先级顺序的方法。我们将该方法应用于实施STOPP/START v2（一项管理多重用药的指南）的决策支持系统。研究表明，该方法可将问卷中显示的临床条件数量减少约三分之二。在焦点小组会议上向临床医生展示时，该适应性问卷被认为“相当易用”。未来，该方法可应用于其他指南，并适应由患者进行数据输入的场景。