TY - JOUR AU - Li, Patrick AU - Chen, Bob AU - Rhodes, Evan AU - Slagle, Jason AU - Alrifai, Mhd Wael AU - France, Daniel AU - Chen, You PY - 2021 DA - 2021/9/3 TI -通过并发电子健康记录使用衡量协作:网络分析研究JO - JMIR Med Inform SP - e28998 VL - 9is - 9kw -协作KW -电子健康记录KW -审计日志KW -卫生保健工作者KW -新生儿重症监护病房KW -网络分析KW -聚类KW -可视化KW -并发交互KW -人机交互KW -调查仪器KW -信息学框架KW -二次数据分析AB -背景:卫生保健机构内部的协作至关重要，它允许有效利用集体卫生保健工作者(HCW)的专业知识。涉及电子健康记录(EHRs)的人机交互已经变得普遍，并作为使用统计和网络分析方法量化这些合作的途径。目的:通过分析电子病历的并发使用情况来衡量医疗卫生中心的协作及其特征。方法:通过从审计日志数据中提取并发EHR使用事件，我们定义了并发会话。对于每个HCW，我们建立了一个称为并发强度的度量，即并发会话中EHR活动占所有EHR活动的比例。采用统计模型检验不同医护人员并发强度的差异。对于从入院到出院的每一次患者就诊，我们测量了所有HCWs同时使用电子病历的情况，我们称之为时间模式。再次，我们应用统计模型来检验工作日和周末之间入院、出院和住院中间天数的时间模式差异。 Network analysis was leveraged to measure collaborative relationships among HCWs. We surveyed experts to determine if they could distinguish collaborative relationships between high and low likelihood categories derived from concurrent EHR usage. Clustering was used to aggregate concurrent activities to describe concurrent sessions. We gathered 4 months of EHR audit log data from a large academic medical center’s neonatal intensive care unit (NICU) to validate the effectiveness of our framework. Results: There was a significant difference (P<.001) in the concurrent intensity (proportion of concurrent activities: ranging from mean 0.07, 95% CI 0.06-0.08, to mean 0.36, 95% CI 0.18-0.54; proportion of time spent on concurrent activities: ranging from mean 0.32, 95% CI 0.20-0.44, to mean 0.76, 95% CI 0.51-1.00) between the top 13 HCW specialties who had the largest amount of time spent in EHRs. Temporal patterns between weekday and weekend periods were significantly different on admission (number of concurrent intervals per hour: 11.60 vs 0.54; P<.001) and discharge days (4.72 vs 1.54; P<.001), but not during intermediate days of hospital stay. Neonatal nurses, fellows, frontline providers, neonatologists, consultants, respiratory therapists, and ancillary and support staff had collaborative relationships. NICU professionals could distinguish high likelihood collaborative relationships from low ones at significant rates (3.54, 95% CI 3.31-4.37 vs 2.64, 95% CI 2.46-3.29; P<.001). We identified 50 clusters of concurrent activities. Over 87% of concurrent sessions could be described by a single cluster, with the remaining 13% of sessions comprising multiple clusters. Conclusions: Leveraging concurrent EHR usage workflow through audit logs to analyze HCW collaboration may improve our understanding of collaborative patient care. HCW collaboration using EHRs could potentially influence the quality of patient care, discharge timeliness, and clinician workload, stress, or burnout. SN - 2291-9694 UR - https://medinform.www.mybigtv.com/2021/9/e28998 UR - https://doi.org/10.2196/28998 UR - http://www.ncbi.nlm.nih.gov/pubmed/34477566 DO - 10.2196/28998 ID - info:doi/10.2196/28998 ER -