患者输入的健康数据和定制的电子建议可提高预防保健水平。
Patient-Entered Wellness Data and Tailored Electronic Recommendations Increase Preventive Care.
作者信息
Foucher-Urcuyo Julie, Longworth David, Roizen Michael, Hu Bo, Rothberg Michael B
机构信息
From the Lerner College of Medicine (JF-U), the Wellness Institute (MR), the Department of Internal Medicine and Medicine Institute Center for Value-Based Care Research (MBR), and Quantitative Health Science (BH), Cleveland Clinic, Cleveland, Ohio; and the Division of Primary Care, Lahey Health, Burlington, MA (DL).
出版信息
J Am Board Fam Med. 2017 May-Jun;30(3):350-361. doi: 10.3122/jabfm.2017.03.160231.
PURPOSE
We investigated whether a tool using patient-entered wellness data to generate tailored electronic recommendations improved preventive care delivery.
METHODS
We conducted a mixed-methods retrospective study of primary care encounters utilizing an Integrated Wellness Tool with a matched-comparison before-and-after study design. Encounters took place at a single clinic within the Cleveland Clinic Health System. The primary outcome was preventive orders placed. Index patients were matched, based on propensity scores, with comparison patients seen in the same clinic several months earlier.
RESULTS
Five providers conducted 863 patient encounters using the tool during the study period. During encounters using the tool, providers placed more orders for smoking cessation programs (2.4 vs 0.5%, < .01), lifestyle medicine (2.4 vs 0%, < .01) and psychology (2.3 vs 1.0%, = .04) consults, online nutrition (2.4 vs 1.4%, = .04) and stress management (5.5 vs 0.9%, < .01) programs, spirometry (5.9 vs 1.7%, < .01) and polysomnography (6.3 vs 1.3%, < .01) tests, and antidepressant (7.2 vs 3.9%, = .01) and hypnotic (2.2 vs 0.7%, = .01) medications when compared with matched encounters.
CONCLUSIONS
Patients are willing to enter lifestyle data, and these data influence provider orders.
目的
我们调查了一种利用患者输入的健康数据生成个性化电子建议的工具是否能改善预防保健服务的提供。
方法
我们采用混合方法，对初级保健就诊进行回顾性研究，使用综合健康工具，并采用匹配前后对照研究设计。就诊在克利夫兰诊所医疗系统内的一家诊所进行。主要结果是开出的预防医嘱。根据倾向得分，将索引患者与几个月前在同一诊所就诊的对照患者进行匹配。
结果
在研究期间，五位提供者使用该工具进行了863次患者就诊。在使用该工具的就诊过程中，与匹配的就诊相比，提供者开出了更多的戒烟项目医嘱（2.4%对0.5%，P<0.01）、生活方式医学医嘱（2.4%对0%，P<0.01）和心理会诊医嘱（2.3%对1.0%，P=0.04）、在线营养医嘱（2.4%对1.4%，P=0.04）和压力管理项目医嘱（5.5%对0.9%，P<0.01）、肺活量测定医嘱（5.9%对1.7%，P<0.01）和多导睡眠图检查医嘱（6.3%对1.3%，P<0.01），以及抗抑郁药医嘱（7.2%对3.9%，P=0.01）和催眠药医嘱（2.2%对0.7%，P=0.01）。
结论
患者愿意输入生活方式数据，且这些数据会影响提供者的医嘱。
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