BACKGROUND Despite the established evidence and theoretical advances explaining human judgments under uncertainty, developments of mobile health (mHealth) Clinical Decision Support Systems (CDSS) have not explicitly applied the psychology of decision making to the study of user needs. We report on a user needs approach to develop a prototype of a mHealth CDSS for Parkinson's disease (PD), which is theoretically grounded in the psychological literature about expert decision making and judgement under uncertainty. METHODS A suite of user needs studies was conducted in 4 European countries (Greece, Italy, Slovenia, the UK) prior to the development of PD_Manager, a mHealth-based CDSS designed for Parkinson's disease, using wireless technology. Study 1 undertook Hierarchical Task Analysis (HTA) including elicitation of user needs, cognitive demands and perceived risks/benefits (ethical considerations) associated with the proposed CDSS, through structured interviews of prescribing clinicians (N = 47). Study 2 carried out computational modelling of prescribing clinicians' (N = 12) decision strategies based on social judgment theory. Study 3 was a vignette study of prescribing clinicians' (N = 18) willingness to change treatment based on either self-reported symptoms data, devices-generated symptoms data or combinations of both. RESULTS Study 1 indicated that system development should move away from the traditional silos of 'motor' and 'non-motor' symptom evaluations and suggest that presenting data on symptoms according to goal-based domains would be the most beneficial approach, the most important being patients' overall Quality of Life (QoL). The computational modelling in Study 2 extrapolated different factor combinations when making judgements about different questions. Study 3 indicated that the clinicians were equally likely to change the care plan based on information about the change in the patient's condition from the patient's self-report and the wearable devices. CONCLUSIONS Based on our approach, we could formulate the following principles of mHealth design: 1) enabling shared decision making between the clinician, patient and the carer; 2) flexibility that accounts for diagnostic and treatment variation among clinicians; 3) monitoring of information integration from multiple sources. Our approach highlighted the central importance of the patient-clinician relationship in clinical decision making and the relevance of theoretical as opposed to algorithm (technology)-based modelling of human judgment.

中文翻译：

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设计针对帕金森氏病的mHealth临床决策支持系统：一种基于理论的用户需求方法。

背景技术尽管已有证据和理论进展解释了不确定性下的人类判断，但移动健康（mHealth）临床决策支持系统（CDSS）的发展尚未将决策心理学明确地应用于用户需求的研究。我们报告了一种用户需求方法，以开发针对帕金森氏病（PD）的mHealth CDSS原型，该原型理论上基于有关不确定性下专家决策和判断的心理学文献。方法在使用无线技术开发基于mHealth的针对帕金森氏病的CDSS PD_Manager之前，在四个欧洲国家（希腊，意大利，斯洛文尼亚，英国）进行了一套用户需求研究。研究1进行了分层任务分析（HTA），包括确定用户需求，通过对处方医生进行结构化访谈，了解与拟议CDSS相关的认知需求和感知风险/利益（道德考量）（N = 47）。研究2基于社会判断理论对处方医生（N = 12）的决策策略进行了计算建模。研究3是一项小插图研究，根据临床医生自我报告的症状数据，设备产生的症状数据或两者的组合，处方了临床医生（N = 18）愿意改变治疗的意愿。结果研究1表明，系统开发应摆脱传统的“运动”和“非运动”症状评估孤岛，并建议根据目标域提供症状数据将是最有益的方法，最重要的是患者的整体生活质量（QoL）。在对不同问题做出判断时，研究2中的计算模型推断出不同的因素组合。研究3表明，根据来自患者自我报告和可穿戴设备的患者状况变化信息，临床医生同样有可能更改护理计划。结论基于我们的方法，我们可以制定以下mHealth设计原则：1）实现临床医生，患者和护理人员之间的共同决策；2）灵活性，可以解释临床医生之间的诊断和治疗差异；3）从多个来源监视信息集成。