Using Electronic Health Record Data to Measure Care Quality for Individuals with Multiple Chronic Medical Conditions
Using Electronic Health Record Data to Measure Care Quality for Individuals with Multiple Chronic Medical Conditions
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DOI：
10.1111/jgs.14248
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发表时间：
2016-09-01
影响因子：
6.3
通讯作者：
Zulman, Donna M.
中科院分区：
文献类型：
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作者：
Bayliss, Elizabeth A.;McQuillan, Deanna B.;Zulman, Donna M.
目的：为开发一种基于电子健康记录（EHR）的针对多种慢性病（MCCs）患者的以数据驱动的优质护理衡量标准提供信息。
设计：采用焦点小组、互动网络研讨会以及改良的德尔菲法进行定性研究。
地点：综合医疗服务体系内的研究部门。
参与者：网络研讨会和德尔菲法过程包括17名临床老年医学和初级保健、卫生政策、质量评估、卫生技术以及卫生系统运营方面的专家。焦点小组包括从65岁及以上患有三种或更多慢性疾病的个体随机样本中选取的10名年龄在70 - 87岁之间且患有三到六种慢性疾病的个体。
测量：通过网络研讨会和焦点小组，征求关于代表MCCs患者高质量护理的构想的意见。创建了一份代表这些构想的潜在衡量标准的工作清单。利用改良的德尔菲法，专家对每项可能的衡量标准的重要性以及使用EHR数据实施每项衡量标准的可行性进行评级。
结果：高优先级的构想反映的是护理过程而非结果。有可能可行测量的高优先级构想包括评估身体功能、抑郁症筛查、药物重整、年度流感疫苗接种、入院后随访以及记录预先指示。较难测量的高优先级构想包括目标设定和共同决策、识别药物相互作用、评估社会支持、与患者及时沟通以及良好客户服务的其他方面。较低优先级的领域包括疼痛评估、护理的连续性以及过度使用筛查或实验室检测。
结论：高质量的MCC护理应使用有意义的过程衡量标准而非结果来衡量。尽管目前一些护理过程可从电子数据中提取，但获取其他过程将需要调整和应用技术以鼓励全面的、以患者为中心的护理。
OBJECTIVES: To inform the development of a data-driven measure of quality care for individuals with multiple chronic conditions (MCCs) derived from an electronic health record (EHR).DESIGN: Qualitative study using focus groups, interactive webinars, and a modified Delphi process.SETTING: Research department within an integrated delivery system.PARTICIPANTS: The webinars and Delphi process included 17 experts in clinical geriatrics and primary care, health policy, quality assessment, health technology, and health system operations. The focus group included 10 individuals aged 70-87 with three to six chronic conditions selected from a random sample of individuals aged 65 and older with three or more chronic medical conditions.MEASUREMENTS: Through webinars and the focus group, input was solicited on constructs representing highquality care for individuals with MCCs. A working list was created of potential measures representing these constructs. Using a modified Delphi process, experts rated the importance of each possible measure and the feasibility of implementing each measure using EHR data.RESULTS: High-priority constructs reflected processes rather than outcomes of care. High-priority constructs that were potentially feasible to measure included assessing physical function, depression screening, medication reconciliation, annual influenza vaccination, outreach after hospital admission, and documented advance directives. High-priority constructs that were less feasible to measure included goal setting and shared decision-making, identifying drug-drug interactions, assessing social support, timely communication with patients, and other aspects of good customer service. Lower-priority domains included pain assessment, continuity of care, and overuse of screening or laboratory testing.CONCLUSION: High-quality MCC care should be measured using meaningful process measures rather than outcomes. Although some care processes are currently extractable from electronic data, capturing others will require adapting and applying technology to encourage holistic, person-centered care.