Treweek Shaun
Department of Health Services Research, Directorate of Health and Social Affairs, PO Box 8054 Dep, N-0031 Oslo, Norway.
BMC Health Serv Res. 2003 Jun 6;3(1):10. doi: 10.1186/1472-6963-3-10.
Electronic medical record (EMR) systems are used for many purposes including patient care, administration, research, quality improvement and reimbursement. This study aimed to test a data extraction tool (QTools) and to provide information to support the interpretation of EMR data.
Comparison of aggregated practice data for selected EMR fields and interviews with practice staff. Practices received summaries of their data and aggregated data for other practices. Summaries were discussed in interviews.
Fourteen general practices in the Oslo area using the Winmed EMR participated. QTools ran successfully at all 14 practices. Nine practices agreed to interviews. Apart from age and sex, general patient information was poorly recorded. Face-to-face consultations account for 59% of contacts but differences in coding led to variations between practices. Psychiatric problems accounted for 13% of diagnoses, other diagnosis groups rarely accounted for more than 5%. Over 90% of diabetics and 75% of patients with heart disease were identified by diagnosis code alone.
Some variation seen in EMR data is due to differences in the way staff use their EMR. These data can support quality improvement work but this requires an awareness of how the EMR is actually used by practice staff.
电子病历（EMR）系统有多种用途，包括患者护理、管理、研究、质量改进和报销。本研究旨在测试一种数据提取工具（QTools），并提供信息以支持对电子病历数据的解读。
对选定电子病历字段的汇总实践数据进行比较，并对实践工作人员进行访谈。各医疗机构收到了其自身数据的摘要以及其他医疗机构的汇总数据。在访谈中对摘要进行了讨论。
奥斯陆地区使用Winmed电子病历的14家普通医疗机构参与了研究。QTools在所有14家医疗机构中均成功运行。9家医疗机构同意接受访谈。除年龄和性别外，一般患者信息记录不佳。面对面咨询占就诊次数的59%，但编码差异导致不同医疗机构之间存在差异。精神疾病问题占诊断的13%，其他诊断组很少超过5%。仅通过诊断代码就识别出了超过90%的糖尿病患者和75%的心脏病患者。
电子病历数据中出现的一些差异是由于工作人员使用电子病历的方式不同。这些数据可以支持质量改进工作，但这需要了解实践工作人员实际如何使用电子病历。
