Orrico Kathleen B
University of California, San Francisco, School of Pharmacy, USA.
J Manag Care Pharm. 2008 Sep;14(7):626-31. doi: 10.18553/jmcp.2008.14.7.626.
Accuracy and transportability of the recorded outpatient medication list are important in the continuum of patient care. Classifying discrepancies between the electronic medical record (EMR) and actual drug use by the root cause of discrepancy (either system generated or patient generated) would guide quality improvement initiatives.
To quantify and categorize the number and type of medication discrepancies that exist between the medication lists recorded in EMRs and the comprehensive medication histories obtained through telephone interviews conducted by a team of nurses providing advice to health plan members at the Palo Alto Medical Foundation in Palo Alto, California.
The study was conducted as a retrospective comparison of EMR medication lists with information obtained by patient interview. Interview data were obtained by a review of telephone calls made to a nurse advice line by health plan members seeking information about sinusitis, urinary tract infection, acute conjunctivitis, pharyngitis, emergency contraception, or mastitis. As part of the advice protocol, a medication reconciliation process was conducted between July 1 and December 31, 2006. Changes to the medication list made during the telephone visit were extracted, categorized, and evaluated by the study's principal investigator. Data extraction included the number and type of identified medication discrepancies, patient age, gender, and condition that prompted the telephone contact. A modified version of the Medication Discrepancy Tool (MDT) was used to categorize medication discrepancies as either system generated (e.g., failure of the provider to update a medication list) or patient generated (e.g., failure of the patient to report use of an over-the-counter product).
A total of 233 discrepancies were identified from 85 medication reconciliation phone visits, averaging 2.7 per medication list. The most common type of discrepancy was a medication recorded in the EMR but no longer being used by the patient (n=164, 70.4%), followed by omission from the EMR of a medication being taken by the patient (n=36, 15.5%). 79.8% (n=186) of the discrepancies were attributed to system-generated factors, whereas 20.2% (n=47) were patient generated. Approximately half (n=118, 50.6%) of the discrepancies fell into 4 broad American Hospital Formulary System therapeutic classifications: anti-infective agents (14.2%), anti-inflammatory agents (14.2%), analgesics (12.4%), and vitamins (9.9%). The most common patient-generated discrepancy was omission of a multivitamin (n=13, 27.7%), and the most common system-generated prescription drug discrepancy was expired entry for the intranasal corticosteroid mometasone furoate (n=12, 6.5%).
Discrepancies in the outpatient setting were common and predominantly system generated. The most common discrepancy was the presence in the EMR of a medication no longer being taken by the patient. Adding foreseeable end dates to prescription drug orders at computerized order entry might be considered in an effort to improve the accuracy of the outpatient medication list. Reliable systems to involve patients in routinely reconciling EMRs with actual medication use may also warrant examination. The MDT methodology served as a useful qualitative guide for evaluating discrepancies and developing targeted means for resolution.
记录的门诊用药清单的准确性和可传输性在患者连续护理中很重要。根据差异的根本原因(系统产生或患者产生)对电子病历(EMR)与实际用药情况之间的差异进行分类,将有助于指导质量改进措施。
量化并分类电子病历中记录的用药清单与通过电话访谈获得的全面用药史之间存在的用药差异的数量和类型,这些电话访谈由一组护士进行,他们为加利福尼亚州帕洛阿尔托市帕洛阿尔托医疗基金会的健康计划成员提供建议。
该研究是对电子病历用药清单与通过患者访谈获得的信息进行回顾性比较。访谈数据通过审查健康计划成员打给护士咨询热线的电话获得,这些成员寻求有关鼻窦炎、尿路感染、急性结膜炎、咽炎、紧急避孕或乳腺炎的信息。作为咨询方案的一部分,在2006年7月1日至12月31日期间进行了用药核对过程。研究的主要研究者提取、分类并评估了电话问诊期间用药清单的变化。数据提取包括已识别用药差异的数量和类型、患者年龄、性别以及促使电话联系的病情。使用改良版的用药差异工具(MDT)将用药差异分类为系统产生的(例如,提供者未更新用药清单)或患者产生的(例如,患者未报告使用非处方药产品)。
从85次用药核对电话问诊中共识别出233处差异,平均每份用药清单有2.7处差异。最常见的差异类型是电子病历中记录的药物患者不再使用(n = 164,70.4%),其次是患者正在服用的药物未记录在电子病历中(n = 36,15.5%)。79.8%(n = 186)的差异归因于系统产生的因素,而20.2%(n = 47)是患者产生的。大约一半(n = 118,50.6%)的差异属于美国医院药品 formulary 系统的4大类治疗分类:抗感染药(14.2%)、抗炎药(14.2%)、镇痛药(12.4%)和维生素(9.9%)。最常见的患者产生的差异是未服用多种维生素(n = 13,27.7%),最常见的系统产生的处方药差异是鼻用皮质类固醇糠酸莫米松的条目过期(n = 12,6.5%)。
门诊环境中的差异很常见,且主要是系统产生的。最常见的差异是电子病历中存在患者不再服用的药物。为提高门诊用药清单的准确性,可考虑在计算机化医嘱录入时为处方药订单添加可预见的截止日期。还可能需要审查让患者常规参与使电子病历与实际用药情况相核对的可靠系统。MDT方法是评估差异和制定有针对性解决方法的有用定性指南。