Berrouiguet Sofian, Perez-Rodriguez Mercedes M, Larsen Mark, Baca-García Enrique, Courtet Philippe, Oquendo Maria
Lab-STICC, IMT Atlantique, Université Bretagne Loire, Brest, France.
Laboratoire Soins primaires, Santé publique, Registre des cancers de Bretagne Occidentale SPURBO, Equipe d'accueil 7479, Brest, France.
J Med Internet Res. 2018 Jan 3;20(1):e2. doi: 10.2196/jmir.7412.
Clinical assessment in psychiatry is commonly based on findings from brief, regularly scheduled in-person appointments. Although critically important, this approach reduces assessment to cross-sectional observations that miss essential information about disease course. The mental health provider makes all medical decisions based on this limited information. Thanks to recent technological advances such as mobile phones and other personal devices, electronic health (eHealth) data collection strategies now can provide access to real-time patient self-report data during the interval between visits. Since mobile phones are generally kept on at all times and carried everywhere, they are an ideal platform for the broad implementation of ecological momentary assessment technology. Integration of these tools into medical practice has heralded the eHealth era. Intelligent health (iHealth) further builds on and expands eHealth by adding novel built-in data analysis approaches based on (1) incorporation of new technologies into clinical practice to enhance real-time self-monitoring, (2) extension of assessment to the patient's environment including caregivers, and (3) data processing using data mining to support medical decision making and personalized medicine. This will shift mental health care from a reactive to a proactive and personalized discipline.
精神病学中的临床评估通常基于定期进行的简短面对面预约的检查结果。尽管这一方法至关重要,但它将评估简化为横断面观察,从而遗漏了有关疾病进程的重要信息。心理健康提供者基于这些有限信息做出所有医疗决策。得益于手机和其他个人设备等近期的技术进步,电子健康(eHealth)数据收集策略现在能够在就诊间隔期间获取实时患者自我报告数据。由于手机通常随时开机且随身携带,它们是广泛应用生态瞬时评估技术的理想平台。将这些工具整合到医疗实践中开创了电子健康时代。智能健康(iHealth)通过添加基于以下方面的新型内置数据分析方法,进一步发展并扩展了电子健康:(1)将新技术融入临床实践以加强实时自我监测;(2)将评估扩展至包括护理人员在内的患者环境;(3)使用数据挖掘进行数据处理以支持医疗决策和个性化医疗。这将使精神卫生保健从被动反应型转变为主动和个性化的学科。