Rogers Kai J, Krasowski Matthew D
Department of Pathology, University of Iowa Hospitals and Clinics, Iowa City, IA 52242, USA.
Data Brief. 2023 Mar 1;47:109012. doi: 10.1016/j.dib.2023.109012. eCollection 2023 Apr.
Point-of-care testing is widely used in a variety of clinical settings. While this testing provides immediate and actionable clinical information, it is prone to error in both the interpretation and reporting of results. Point-of-care urinalysis presents unique opportunities for errors, ranging from variation in visual interpretation to input of results. The data included here represent the results from 63,279 urinalyses from 36,780 unique patients performed over a span of three years at an academic medical center and its associated clinics. The data include the patient age/legal sex, methodology (instrument and test strip used), and the available test results (color, clarity, glucose, bilirubin, ketones, specific gravity, blood, pH, protein, urobilinogen, nitrite, and leukocyte esterase). Additionally, we include the method of interface between the testing instrumentation and our electronic medical record (EMR). These fell into one of three broad categories: "Interfaced" (results directly transmitted from the urinalysis instrument to the EMR via specialized data interface), "Manual" (results input by selecting from a drop-down menu in the laboratory information system), and "Enter/Edit" (results typed freely into a text field in the EMR). Analysis of this data was primarily a direct comparison of detectable errors (typos, uninterpretable results, and results outside the reportable range) as a function of the method of entry into the EMR. Secondary analysis comparing the impact of restricting drop-down menu options for urine color and clarity was also performed. These data are of use to others as they are diverse in terms of the test performed and the method of interface. Others may wish to analyze these data when making decisions as to how to perform and report these tests and when estimating risks of error with various methods of data entry.
即时检验在各种临床环境中广泛应用。虽然这种检验能提供即时且可用于指导治疗的临床信息，但在结果解读和报告方面容易出错。即时尿分析存在独特的出错可能性，从视觉解读的差异到结果录入都可能出错。这里包含的数据代表了在一所学术医疗中心及其附属诊所三年期间对36,780名不同患者进行的63,279次尿分析结果。数据包括患者年龄/法定性别、方法（使用的仪器和试纸条）以及可获得的检测结果（颜色、透明度、葡萄糖、胆红素、酮体、比重、血液、pH值、蛋白质、尿胆原、亚硝酸盐和白细胞酯酶）。此外，我们还纳入了检测仪器与我们的电子病历（EMR）之间的接口方式。这些接口方式分为三大类之一：“接口连接”（结果通过专门的数据接口从尿分析仪器直接传输到EMR）、“手动”（通过在实验室信息系统的下拉菜单中选择来录入结果）和“输入/编辑”（结果自由输入到EMR的文本字段中）。对这些数据进行分析主要是直接比较可检测到的错误（拼写错误、无法解读的结果以及超出报告范围的结果）与录入EMR的方法之间的关系。还进行了二次分析，比较限制尿液颜色和透明度下拉菜单选项的影响。这些数据对其他人有用，因为它们在检测项目和接口方式方面具有多样性。其他人在决定如何进行和报告这些检测以及评估各种数据录入方法的出错风险时，可能希望分析这些数据。
