Faculty of Health and Medical Sciences, University of Surrey, Guildford, UK.
Department of Psychology, University of Bournemouth, Bournemouth, UK.
BMC Med Inform Decis Mak. 2020 Feb 19;20(1):34. doi: 10.1186/s12911-020-1027-1.
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.
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.
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.
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.
尽管已有证据和理论进步解释了人类在不确定情况下的判断，但移动医疗（mHealth）临床决策支持系统（CDSS）的发展并未将决策心理学明确应用于用户需求研究。我们报告了一种用户需求方法，用于开发一种基于移动医疗的帕金森病（PD）CDSS 原型，该原型在关于专家决策和不确定性下判断的心理学文献基础上进行了理论研究。
在开发基于无线技术的 PD_Manager 之前，在 4 个欧洲国家（希腊、意大利、斯洛文尼亚、英国）进行了一系列用户需求研究。研究 1 通过对处方医生进行结构化访谈（N=47），进行了层次任务分析（HTA），包括对拟议的 CDSS 相关的用户需求、认知需求和感知风险/收益（伦理考虑）进行了分析。研究 2 根据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 是对处方医生（N=18）基于自我报告症状数据、设备生成症状数据或两者组合改变治疗意愿的意愿进行了病例研究。
研究 1 表明系统开发应摆脱“运动”和“非运动”症状评估的传统孤立模式，并建议根据基于目标的领域呈现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）。研究 2 的计算建模推断出在对不同问题进行判断时不同因素组合的情况。研究 3 表明，医生在改变患者病情的自我报告和可穿戴设备信息时，改变护理计划的可能性是相等的。
基于我们的方法，我们可以制定以下 mHealth 设计原则：1）使临床医生、患者和护理人员能够共同做出决策；2）灵活性考虑临床医生之间的诊断和治疗差异；3）从多个来源监测信息整合。我们的方法强调了医患关系在临床决策中的核心重要性，以及理论建模而非算法（技术）建模在人类判断中的相关性。
