Effectiveness of Pictographs to Prevent Wrong-Patient Errors in the NICU

象形文字可有效防止 NICU 中错误的患者错误

基本信息

项目摘要

Wrong-patient errors pose a serious threat to patient safety, and newborns in the neonatal intensive care unit (NICU) are at greatest risk. Half of infants in the NICU on any given day are estimated to be at risk of a wrong-patient error as a result of having similar identifiers. A major contributing factor is the use of temporary, nondistinct first names, e.g., Babyboy/Babygirl, that are assigned to newborns at birth and remain unchanged throughout their hospital stay. Use of a distinct newborn naming convention that incorporated the mother’s first name (e.g., Wendysgirl) reduced the risk of wrong-patient orders in the NICU by 36%. However, the distinct naming convention conferred benefit only for singletons—multiple births remained at high risk as a result of siblings sharing the same name distinguished by a single character (e.g., 1Wendysgirl, 2Wendysgirl). Displaying patient photographs in electronic health records (EHRs) is a promising strategy to improve patient identification. However, photographs are unlikely to be an effective identifier in the NICU where an additional identifier is urgently needed. In place of patient photographs, we propose BabySAFE Pictographs as a “photo equivalent” for newborns in the NICU. Pictographs consist of three elements: 1) a pictorial image of a readily identifiable, distinctive, and easy-to-remember object; 2) the infant’s given name; and 3) a color- coded border indicating the infant’s sex. Pictographs will be displayed at the bedside and in the EHR to serve as a visual cue when providers place orders. Parents will select a Pictograph for their infants for the duration of their hospital stay, with no two infants having the same Pictograph at the same time in the same NICU. We propose conducting a cluster randomized controlled trial to assess the effectiveness of Pictographs for reducing wrong-patient orders in the NICU. We will use the automated Wrong-Patient Retract-and-Reorder measure, developed and validated by the Principal Investigator of this proposal, as the primary outcome measure. Our main hypothesis is that Pictographs will reduce the frequency of wrong-patient orders in the NICU, including among siblings of multiple births. We propose the following specific aims: Aim 1: To conduct a multi-site, cluster randomized controlled trial to compare the frequency of wrong- patient orders in the NICU between providers randomized to view verification screens with versus without BabySAFE Pictographs, as identified by the Wrong-Patient Retract-and-Reorder measure. Aim 2: To conduct subgroup analyses of the effectiveness of BabySAFE Pictographs for reducing the frequency of wrong-patient orders among siblings of multiple births in the NICU. Aim 3: To conduct a qualitative evaluation to examine the perceptions and experiences of healthcare providers and parents about BabySAFE Pictographs as an additional identifier for newborns in the NICU. This proposal addresses research gaps identified by the National Institute of Child Health and Human Development, which seeks projects to develop novel and improved methods of neonatal patient identification.
错--病人差错对病人安全构成严重威胁,新生儿重症监护室的新生儿 新生儿重症监护室(NICU)的风险最大。据估计,在任何一天,新生儿重症监护室(NICU)中的一半婴儿都有 由于具有相似的标识符而导致的错误患者错误。一个主要因素是使用 临时的、无区别的名字,例如,男婴/女婴,出生时分配给新生儿, 在住院期间保持不变。使用独特的新生儿命名惯例,其中纳入了 母亲的名字(例如,Wendysgirl)将NICU中错误患者订单的风险降低了36%。然而,在这方面, 不同的命名惯例只对独生子女有利,多胞胎仍然是高风险, 兄弟姐妹共享由单个字符区分的相同名称的结果(例如,1Wendysgirl,2Wendysgirl). 在电子健康记录(EHR)中保存患者照片是一种有前途的改善策略。 病人身份然而,照片不太可能是NICU中的有效标识符, 迫切需要额外的标识符。我们建议使用婴儿安全象形图代替患者照片 作为新生儿重症监护室新生儿的“照片等价物”。象形文字由三个要素组成:1)一个图形图像, 一个容易识别的,独特的,容易记住的物体; 2)婴儿的名字; 3)颜色- 显示婴儿性别的编码边框象形文字将显示在床边和电子健康记录中, 作为供应商下订单时的视觉提示。父母将为他们的婴儿选择一个象形文字, 他们的住院时间,没有两个婴儿在同一时间在同一个NICU有相同的象形图。 我们建议进行一项随机对照试验,以评估象形文字的有效性 减少新生儿重症监护室的错误医嘱我们将使用自动错误患者撤回和重新排序 由本提案的主要研究者制定和验证的措施,作为主要结局 measure.我们的主要假设是,象形文字将减少频率错误的病人订单, 新生儿重症监护室,包括多胞胎兄弟姐妹之间。我们提出以下具体目标: 目的1:进行一项多中心、整群随机对照试验,以比较 在NICU中,提供者之间的患者订单被随机化,以查看验证屏幕, 婴儿安全象形图,如错误患者撤回和重新排序措施所识别。 目的2:对BabySAFE Pictographs用于降低婴儿死亡率的有效性进行亚组分析。 新生儿重症监护室中多胞胎兄弟姐妹的错误医嘱频率。 目标3:进行定性评估,以检查医疗保健的看法和经验 婴儿安全象形图作为新生儿重症监护室新生儿的额外标识符。 该提案解决了国家儿童健康和人类健康研究所确定的研究差距, 发展,寻求项目,开发新的和改进的方法,新生儿病人识别。

项目成果

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Jason Stuart Adelman其他文献

Jason Stuart Adelman的其他文献

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{{ truncateString('Jason Stuart Adelman', 18)}}的其他基金

Simulation for Attending Obstetricians to Improve Technical Skills for Managing Postpartum Hemorrhage
模拟主治产科医生提高处理产后出血的技术技能
  • 批准号:
    10650709
  • 财政年份:
    2022
  • 资助金额:
    $ 66.89万
  • 项目类别:
Simulation for Attending Obstetricians to Improve Technical Skills for Managing Postpartum Hemorrhage
模拟主治产科医生提高处理产后出血的技术技能
  • 批准号:
    10346611
  • 财政年份:
    2022
  • 资助金额:
    $ 66.89万
  • 项目类别:
Effectiveness of Pictographs to Prevent Wrong-Patient Errors in the NICU
象形文字可有效防止 NICU 中错误的患者错误
  • 批准号:
    9759951
  • 财政年份:
    2018
  • 资助金额:
    $ 66.89万
  • 项目类别:
Columbia University Patient Safety and Health Services Research Training
哥伦比亚大学患者安全与健康服务研究培训
  • 批准号:
    10187649
  • 财政年份:
    2018
  • 资助金额:
    $ 66.89万
  • 项目类别:
Patient Safety and Health Services Research Training
患者安全与健康服务研究培训
  • 批准号:
    10747777
  • 财政年份:
    2018
  • 资助金额:
    $ 66.89万
  • 项目类别:
Effectiveness of Pictographs to Prevent Wrong-Patient Errors in the NICU
象形文字可有效防止 NICU 中错误的患者错误
  • 批准号:
    10440291
  • 财政年份:
    2018
  • 资助金额:
    $ 66.89万
  • 项目类别:
Effectiveness of Pictographs to Prevent Wrong-Patient Errors in the NICU
象形文字可有效防止 NICU 中错误的患者错误
  • 批准号:
    10204069
  • 财政年份:
    2018
  • 资助金额:
    $ 66.89万
  • 项目类别:
Columbia University Patient Safety and Health Services Research Training
哥伦比亚大学患者安全与健康服务研究培训
  • 批准号:
    10407968
  • 财政年份:
    2018
  • 资助金额:
    $ 66.89万
  • 项目类别:
Providing Evidence and Developing a Toolkit to Accelerate the Adoption of Patient Photographs in Electronic Health Records
提供证据并开发工具包以加速电子健康记录中患者照片的采用
  • 批准号:
    9750084
  • 财政年份:
    2017
  • 资助金额:
    $ 66.89万
  • 项目类别:
Assess Risk of Wrong Patient Errors in an EMR that Allows Multiple Records Open
评估允许打开多条记录的 EMR 中错误患者错误的风险
  • 批准号:
    8828955
  • 财政年份:
    2014
  • 资助金额:
    $ 66.89万
  • 项目类别:

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