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Designing a mHealth clinical decision support system for Parkinson’s disease: a theoretically grounded user needs approach

机译:设计帕金森病的MHEALTE临床决策支持系统:理论上接地的用户需求方法

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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.
机译:尽管既定的证据和理论步解释了人类判断,但在不确定性下,移动卫生(MHEALTE)临床决策支持系统(CDSS)的发展尚未明确应用于研究用户需求的决策心理学。我们报告了用户需要方法,以制定帕金森病(PD)的MEHealth CDS的原型,从理论上是关于在不确定性下专家决策和判断的心理文学中的理论上。在使用无线技术的基于MHECHTA的CDS的PD_Manager开发之前,在4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),包括用户需求诱导,认知需求和感知风险/福利(道德考虑)通过规定的临床医生的结构性访谈(n?= 47)。研究2进行了按社会判断理论的规定临床医生(N?= 12)决策策略的计算建模。研究3是规定临床医生(n?='18)愿意改变治疗的小插图研究,以根据自我报告的症状数据,设备产生的症状数据或两者的组合来改变治疗。研究1表示系统开发应远离“电机”和“非运动”症状评估的传统筒仓,并表明根据基于目标的域名提出症状数据是最有益的方法,最重要的是患者'整体生活质量(QOL)。在研究不同问题的判断时,研究2在研究中的计算建模外推不同因子组合。研究3表明,临床医生同样可能根据有关患者的自我报告和可穿戴设备的患者病情的变化的信息来改变护理计划。根据我们的方法,我们可以制定以下MHECHEATH设计原则:1)在临床医生,患者和护理人员之间实现共享决策; 2)临床医生诊断和治疗变异的灵活性; 3)监测来自多个来源的信息集成。我们的方法强调了临床决策中患者临床医生关系的核心重要性以及与算法(技术)的理论相关的相关性的人为判断的建模。

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