Phansalkar Shobha, Her Qoua L, Tucker Alisha D, Filiz Esen, Schnipper Jeffrey, Getty George, Bates David W
Shobha Phansalkar, B.S.Pharm., Ph.D., is Instructor in Medicine, Division of General Medicine, Brigham and Women's Hospital, Boston, MA, and Instructor in Medicine, Harvard Medical School, Boston. Qoua L. Her, Pharm.D., M.S., is Pharmacy Informatics and Outcomes Research Fellow, Massachusetts College of Pharmacy and Health Sciences University, Division of General Internal Medicine and Primary Care, Brigham and Women's Hospital. Alisha D. Tucker, B.S., is Project Coordinator, Partners HealthCare System, Clinical Informatics Research and Development, Wellesley Gateway, Wellesley, MA. Esen Filiz, M.Sc., is Junior Business Analyst, Vita-Systems GmbH, Mannheim, Germany. Jeffrey Schnipper, M.D., M.P.H., is Associate Professor of Medicine, Harvard Medical School, and Associate Physician, Division of General Internal Medicine and Primary Care, Brigham and Women's Hospital. George Getty, B.S., is Software Engineer II, Partners HealthCare, Clinical Informatics Research and Development, Wellesley Gateway. David W. Bates, M.D., M.Sc., is Senior Vice President for Quality and Safety and Chief Quality Officer, Division of General Internal Medicine and Primary Care, Brigham and Women's Hospital.
Am J Health Syst Pharm. 2015 Feb 1;72(3):212-7. doi: 10.2146/ajhp140082.
The potential value of adding pharmacy claims data to the medication history in the electronic health record (EHR) to improve the accuracy of medication reconciliation was studied.
Three medication history sources were used for this evaluation: a gold-standard preadmission medication list (PAML) created by reviewing all available medication history information, an EHR-generated PAML, and pharmacy claims data. The study population consisted of patients from the Partners Medication Reconciliation Study with medication history information available from all three medication history sources. The aggregated medication list from each medication history source was compared with the gold-standard PAML to identify and categorize missing medications, additional medications, and discrepancies in the various attributes of a medication order, including dose, route, and frequency. McNemar's test was used to compare paired proportions of medication entries across each source to the gold-standard PAMLs.
Fifteen patients had medication histories in all three medication history sources. Medication entries across all three sources included 169 from the gold- standard PAMLs, 158 from the EHR-PAMLs, and 351 from pharmacy claims data. The EHR-PAMLs and pharmacy claims data correctly reflected 52.1% and 43.2% of the gold-standard PAMLs, respectively. Combining the EHR-PAMLs and pharmacy claims resulted in 69.2% of the gold-standard PAMLs correctly reflected (p < 0.0001). Combining these two data sources increased the accuracy of medication history by 17.1%.
Combining the EHR-PAML and pharmacy claims data resulted in a significant increase in the number of medications correctly reflected in the gold-standard PAML compared with the EHR-PAML or claims data separately.
研究在电子健康记录（EHR）中添加药房索赔数据到用药史以提高用药核对准确性的潜在价值。
本评估使用了三种用药史来源：通过审查所有可用用药史信息创建的金标准入院前用药清单（PAML）、EHR生成的PAML以及药房索赔数据。研究人群包括来自伙伴用药核对研究且可从所有三种用药史来源获取用药史信息的患者。将每个用药史来源的汇总用药清单与金标准PAML进行比较，以识别和分类遗漏的药物、额外的药物以及用药医嘱各种属性（包括剂量、途径和频率）中的差异。使用McNemar检验比较每个来源与金标准PAML的配对用药记录比例。
15名患者在所有三种用药史来源中都有用药史。所有三个来源的用药记录包括金标准PAML中的169条、EHR - PAML中的158条以及药房索赔数据中的351条。EHR - PAML和药房索赔数据分别正确反映了金标准PAML的52.1%和43.2%。将EHR - PAML和药房索赔数据相结合，69.2%的金标准PAML得到了正确反映（p < 0.0001）。将这两个数据源相结合使用药史的准确性提高了17.1%。
与单独使用EHR - PAML或索赔数据相比，将EHR - PAML和药房索赔数据相结合可显著增加金标准PAML中正确反映的药物数量。
