Further Psychometric Testing and Validation of the Errors of Care Omission Survey (EoCOS)

尽管大部分医疗保健是在初级保健环境中提供的，但对患者安全的研究 在初级保健方面落后于住院治疗。患者安全性问题在初级 护理，如在住院设置，但没有得到很好的研究。此外，现有的研究主要集中在错误的 委员会-做错事，如管理错误的药物-而不是错误的 遗漏-行动失败，如遗漏护理。虽然遗漏错误多于委托错误， 威胁患者安全，在文献中存在关于遗漏错误的关键空白。缺乏证据限制了 临床实践的评估和挑战管理者，政策制定者和临床医生的能力， 改变以促进患者安全。没有可靠有效的工具来衡量护理疏忽错误， 初级保健.我们正在通过文献回顾开发护理疏忽错误调查（EoCOS）， 现有工具的调查、与初级保健提供者（PCP）的访谈、内容验证和预测试 测量PCP对护理疏忽错误的感知。提出了四个领域的护理疏忽： （a）自我管理支持;（B）后续行动;（c）情绪健康;（d）护理一体化。每个EoCOS子量表 通过要求PCP在4点量表上对他们的感知进行评分的项目来测量一个域。的目的 拟议的研究是进一步评估EoCOS的心理测量特性，并完善和验证 工具.具体目标包括：（1）确定EoCOS的因子结构，并最终确定衡量EoCOS的分量表 （2）运用项目反应理论（IRT）考察EoCOS的项目绩效 3）检查每个EoCOS分量表上的项目是否通过拟合来测量预期的结构 数据来自不同的PCP，利用验证性因子分析（CFA）。横断面调查设计， 将使用在纽约州招募的PCP（医生和执业护士）样本（n= 1，328）。每个 PCP将收到一份邮寄的调查问卷，沿着附信、知情同意书和预付费的回邮信封， 将调查结果返回给研究团队。明信片提醒和第二次邮寄将进行到 提高响应率。将使用SPSS、MPlus和IRTPro软件进行数据分析。我们将随机 将样本分成两部分：一个衍生样本和一个验证样本。使用衍生样本中的数据，我们将 使用探索性因子分析建立EoCOS的因子结构，并评估其特征 使用项目反应理论模型对每个项目进行分析。使用验证示例，我们将测试 出现的因子结构与来自该样本的数据相拟合。这些分析方法将评估 EoCOS的判别性、收敛性和构造有效性，并将产生样本不变参数。 EoCOS可与不同的PCP组一起使用，以进行有意义的护理疏忽比较 跨实践和国家的错误，增加了工具的实用性。这些证据将有助于确保患者安全 初级保健系统，使护理疏忽错误可见，以便在伤害患者之前进行纠正。

Although a large proportion of healthcare care is delivered in primary care settings, research on patient safety in primary care has lagged behind that of inpatient care. Patient safety issues occur as frequently in primary care as in inpatient settings, but are not well studied. Moreover, the extant studies mainly focus on errors of commission—doing something wrong such as administering wrong medication—as opposed to errors of omission—failure of action such as missed care. Although omission errors outnumber commission errors and threaten patient safety, there is a critical gap in the literature on omission errors. This lack of evidence restricts the evaluation of clinical practice and challenges administrators', policy makers' and clinicians' abilities to make changes to promote patient safety. There are no reliable and valid tools to measure errors of care omission in primary care. We are developing the Errors of Care Omission Survey (EoCOS) through literature review, investigation of existing tools, interviews with primary care providers (PCPs), content validation, and pretesting to measure PCP perceptions of errors of care omission. Four domains underlying care omission are proposed: a) self-management support; b) follow-up; c) emotional health; and d) care integration. Each EoCOS subscale measures one domain through items asking PCPs to rate their perceptions on a 4-point scale. The purpose of the proposed study is to further evaluate the psychometric properties of the EoCOS and refine and validate the tool. Specific aims include 1) Determine the factorial structure of EoCOS and finalize the subscales measuring care omission domains; 2) Investigate performance of the items in EoCOS using Item Response Theory (IRT) models; and 3) Examine whether the items on each EoCOS subscale measure the intended construct by fitting data from different PCPs utilizing Confirmatory Factor Analysis (CFA). A cross-sectional survey design with a sample of PCPs (physicians and nurse practitioners) recruited in New York State will be used (n=1,328). Each PCP will receive a mailed survey along with cover letter, consent form, and a prepaid return envelope for returning the surveys to the research team. Post card reminders and a second mailing will be conducted to increase the response rate. SPSS, MPlus and IRTPro software will be used for data analysis. We will randomly split the sample into two: a derivation and a validation sample. Using data from the derivation sample, we will establish the factorial structure of the EoCOS using Exploratory Factor Analysis and assess the characteristics of each individual item using Item Response Theory models. Using the validation sample, we will test whether the emerged factor structure fits the data from this sample. These analytical procedures will assess the discriminant, convergent, and construct validity of the EoCOS and will produce sample invariant parameters. EoCOS may be used with various groups of PCPs for conducting meaningful comparisons of care omission errors across practices and states increasing the utility of the tool. This evidence will help create patient safety systems in primary care to make care omission errors visible so they can be corrected before harming patients.