三份计算机化入院前用药清单中差异的患病率及临床意义
Prevalence and Clinical Significance of Discrepancies within Three Computerized Pre-Admission Medication Lists.
作者信息
Peterson Josh F, Shi Yaping, Denny Josh C, Matheny Michael E, Schildcrout Jonathan S, Waitman Lemuel R, Miller Randolph A
机构信息
Department of Biomedical Informatics, Vanderbilt University, Nashville, TN.
出版信息
AMIA Annu Symp Proc. 2010 Nov 13;2010:642-6.
Inaccurate records of pre-admission medication exposure have been identified as a major source of medication error. Authors collected records of patients' pre-admission medications: 1) the most recent outpatient medication list ("EMR"), 2) the medication list recorded by admitting providers ("H&P"), and 3) a list generated by a medication reconciliation process conducted by nursing staff ("PAML"). Forty-eight sets of pre-admission records composed of 1087 medication entries were compared to a reference standard generated by trained study staff conducting an independent interview. Sensitivity was greatest for PAML (85%), compared to EMR (76%) and H&P (76%) sources. However, positive predictive value was greatest for the H&P source at 96% vs 88% and 91% for PAML and EMR sources respectively. Potentially harmful medication discrepancies were found within all lists. The authors concluded no single list was sufficiently accurate to avoid serious medication errors.
入院前用药情况记录不准确已被确认为用药错误的主要来源。作者收集了患者入院前用药记录：1）最新的门诊用药清单（“电子病历”），2）收治医生记录的用药清单（“入院病历和体格检查”），以及3）护理人员进行用药核对过程生成的清单（“患者用药清单”）。将由48套入院前记录组成的1087条用药条目与经过培训的研究人员通过独立访谈生成的参考标准进行比较。“患者用药清单”的敏感度最高（85%），相比之下，“电子病历”（76%）和“入院病历和体格检查”（76%）来源的敏感度较低。然而，“入院病历和体格检查”来源的阳性预测值最高，为96%，而“患者用药清单”和“电子病历”来源的阳性预测值分别为88%和91%。在所有清单中均发现了潜在有害的用药差异。作者得出结论，没有一个清单足够准确，能够避免严重的用药错误。
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