Automated Lab Test Follow-up to Reduce Medical Errors

自动化实验室测试跟进以减少医疗错误

• 批准号: 6580921
• 负责人: DAVID S GREENES
• 金额: $ 5.72万
• 依托单位: BOSTON CHILDREN'S HOSPITAL
• 依托单位国家: 美国
• 财政年份: 2002
• 资助国家: 美国
• 起止时间: 2002-09-30 至 2004-09-29
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/6580921
• 关键词: automated data processing; behavioral /social science research tag; clinical research; computer assisted diagnosis; computer program /software; computer system design /evaluation; cost effectiveness; diagnosis quality /standard; diagnostic tests; emergency health services; health care cost /financing; health care facility information system; health care service evaluation; health services research tag; human data; medical records; outcomes research; outpatient care; patient safety /medical error; telecommunications

DESCRIPTION (provided by applicant): Medical errors occur frequently when clinicians fail to respond to abnormal laboratory test results. This problem plays an especially important role in emergency departments, and other ambulatory settings because in many cases patients have been discharged by the time test results become available. An automated system to ensure follow-up for late-arriving test results may decrease rates of this type of medical error. This project will evaluate the effectiveness of a computerized system called the Automated Late-Arriving Results Monitoring System (ALARMS) in an emergency department. ALARMS gathers data from the hospital information system to generate a list of all late-arriving abnormal laboratory results. ALARMS prompts the user to respond to each result and then generates a note documenting the response, which becomes part of the medical record. The study hypothesis is that introduction of ALARMS will significantly improve rates of follow-up for late-arriving abnormal laboratory results. In the first phase, this project will evaluate the accuracy of ALARMS for identifying all late-arriving abnormal laboratory results, as compared to a manual review by researchers as the criterion standard. In the second phase, the emergency department's current rate of appropriate follow-up for late-arriving test results will be evaluated by running ALARMS in the background, with its output not yet available to clinicians. For each result identified by ALARMS, researchers will contact the patient individually to determine whether notification regarding the test result has occurred. In the third phase, ALARMS will be introduced for clinical use. Again, for each result identified by ALARMS, researchers will contact the patient to determine whether notification has occurred. The principal outcome measures will be the rate at which notification have occurred, comparing rates of medical errors (in the form of inadequate notification) before and after clinical implementation of the ALARMS system. As a secondary measure, rates of adverse events attributed to these errors will be measured as well. Finally, in the fourth phase of the study, some costs of using ALARMS, specifically, the time spent by clinicians addressing lab results that do not require follow-up, will be measured.

描述（由申请人提供）：当临床医生未能对异常实验室检测结果做出反应时，经常会发生医疗错误。 这个问题在急诊科和其他门诊环境中发挥着特别重要的作用，因为在许多情况下，患者在检测结果出来时就已经出院了。 确保对迟到的测试结果进行跟进的自动化系统可能会降低此类医疗错误的发生率。 该项目将评估急诊科中称为自动迟到结果监测系统 (ALARMS) 的计算机化系统的有效性。 警报从医院信息系统收集数据，生成所有迟到的异常实验室结果的列表。警报提示用户对每个结果做出响应，然后生成记录响应的注释，该注释将成为医疗记录的一部分。 研究假设是，引入警报将显着提高迟到的异常实验室结果的随访率。 在第一阶段，该项目将评估警报识别所有迟到的异常实验室结果的准确性，并与研究人员的手动审查作为标准进行比较。 在第二阶段，急诊科当前对迟到检测结果的适当跟进率将通过在后台运行警报来评估，其输出尚未提供给临床医生。 对于警报识别的每个结果，研究人员将单独联系患者，以确定是否已发出有关测试结果的通知。 第三阶段，ALARMS将引入临床使用。 同样，对于警报识别的每个结果，研究人员将联系患者以确定是否已发生通知。 主要结果指标是通知发生率，比较临床实施警报系统之前和之后的医疗错误率（以通知不充分的形式）。 作为次要措施，还将测量归因于这些错误的不良事件发生率。 最后，在研究的第四阶段，将测量使用警报的一些成本，特别是临床医生处理不需要后续的实验室结果所花费的时间。