Hsin Honor, Fromer Menachem, Peterson Bret, Walter Collin, Fleck Mathias, Campbell Andrew, Varghese Paul, Califf Robert
Verily Life Sciences, 269 East Grand Avenue, South San Francisco, CA 94080 USA.
Verily Life Sciences, 355 Main Street, Cambridge, MA 02142 USA.
NPJ Digit Med. 2018 Aug 22;1:37. doi: 10.1038/s41746-018-0046-0. eCollection 2018.
Psychiatry has been limited by historically rooted practices centered primarily on subjective observation. Fields such as oncology have progressed toward data-driven clinical decision-making that combines subjective clinical assessment of symptoms and preferences with biological measures such as genetics, biomarkers, imaging, and integrative physiology to derive quantitative risk scores and decision support. In contrast, psychiatry has just begun to scratch the surface of measurement-based care with validated clinical questionnaires. An opportunity exists to improve modern psychiatric care with novel data streams from digital sensors combined with clinical observation and subjective self-report. The prospect of integrating this complex information with modern computational and analytical methods could advance the field, both in research and clinical practice. Here we discuss this possibility and propose some key priorities to enable these innovations toward improving clinical outcomes in the future.
精神病学一直受到主要基于主观观察的、有着历史根源的实践的限制。肿瘤学等领域已朝着数据驱动的临床决策发展,这种决策将症状和偏好的主观临床评估与遗传学、生物标志物、影像学和综合生理学等生物学指标相结合,以得出定量风险评分并提供决策支持。相比之下,精神病学才刚刚开始通过经过验证的临床问卷触及基于测量的护理的表面。利用来自数字传感器的新数据流,结合临床观察和主观自我报告,存在改善现代精神病护理的机会。将这些复杂信息与现代计算和分析方法相结合的前景,有望在研究和临床实践两方面推动该领域的发展。在此,我们讨论这种可能性,并提出一些关键优先事项,以推动这些创新,从而在未来改善临床结果。