Scheitel Marianne R, Kessler Maya E, Shellum Jane L, Peters Steve G, Milliner Dawn S, Liu Hongfang, Komandur Elayavilli Ravikumar, Poterack Karl A, Miksch Timothy A, Boysen Jennifer, Hankey Ron A, Chaudhry Rajeev
Rajeev Chaudhry, MBBS,MPH, Associate Professor of Medicine, Division of Primary Care Internal Medicine, Knowledge and Delivery Center, Mayo Clinic, 200 First Street SW, Rochester, MN 55905, TEL: (507) 255-3956, E-mail:
Appl Clin Inform. 2017 Feb 8;8(1):124-136. doi: 10.4338/ACI-2016-07-RA-0114.
The 2013 American College of Cardiology / American Heart Association Guidelines for the Treatment of Blood Cholesterol emphasize treatment based on cardiovascular risk. But finding time in a primary care visit to manually calculate cardiovascular risk and prescribe treatment based on risk is challenging. We developed an informatics-based clinical decision support tool, MayoExpertAdvisor, to deliver automated cardiovascular risk scores and guideline-based treatment recommendations based on patient-specific data in the electronic heath record.
To assess the impact of our clinical decision support tool on the efficiency and accuracy of clinician calculation of cardiovascular risk and its effect on the delivery of guideline-consistent treatment recommendations.
Clinicians were asked to review the EHR records of selected patients. We evaluated the amount of time and the number of clicks and keystrokes needed to calculate cardiovascular risk and provide a treatment recommendation with and without our clinical decision support tool. We also compared the treatment recommendation arrived at by clinicians with and without the use of our tool to those recommended by the guidelines.
Clinicians saved 3 minutes and 38 seconds in completing both tasks with MayoExpertAdvisor, used 94 fewer clicks and 23 fewer key strokes, and improved accuracy from the baseline of 60.61% to 100% for both the risk score calculation and guideline-consistent treatment recommendation.
Informatics solution can greatly improve the efficiency and accuracy of individualized treatment recommendations and have the potential to increase guideline compliance.
2013年美国心脏病学会/美国心脏协会血脂治疗指南强调基于心血管风险的治疗。但在初级保健就诊时抽出时间手动计算心血管风险并根据风险开出处方具有挑战性。我们开发了一种基于信息学的临床决策支持工具MayoExpertAdvisor，以根据电子健康记录中的患者特定数据提供自动心血管风险评分和基于指南的治疗建议。
评估我们的临床决策支持工具对临床医生计算心血管风险的效率和准确性的影响及其对提供符合指南的治疗建议的效果。
要求临床医生查看选定患者的电子健康记录。我们评估了使用和不使用我们的临床决策支持工具计算心血管风险并提供治疗建议所需的时间、点击次数和按键次数。我们还将使用和不使用我们工具的临床医生得出的治疗建议与指南推荐的建议进行了比较。
使用MayoExpertAdvisor，临床医生在完成两项任务时节省了3分38秒，少用了94次点击和23次按键，并且将风险评分计算和符合指南的治疗建议的准确性从基线的60.61%提高到了100%。
信息学解决方案可以大大提高个性化治疗建议的效率和准确性，并有可能提高指南依从性。
