The Completeness of the Operating Room Data.

IF 1.8 4区 医学 Q3 COMPUTER SCIENCE, INFORMATION SYSTEMS Methods of Information in Medicine Pub Date : 2024-09-01 Epub Date: 2025-03-26 DOI:10.1055/a-2566-7958
Päivi Nurmela, Minna Mykkänen, Ulla-Mari Kinnunen
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Abstract

In the operating theater, a large collection of data are collected at each surgical visit. Some of these data are patient information, some is related to resource management, which is linked to hospital finances. Poor quality data lead to poor decisions, impacting patient safety and the continuity of care.The study aimed at evaluating the completeness of the data documented within surgical operations. Based on the results, the goal is to improve data quality and to identify improvement ideas of data management.The study was a quantitative evaluation of 33,684 surgical visits, focusing on data omissions. The organization identified 58 operating room data variables related to visits, procedures, resources, and personnel. Data completeness was evaluated for 36 variables, excluding 47 visits that were missing the "Complete" flag. Data preprocessing was done using Python and Pandas, with pseudonymization of personnel names. Data were analyzed using the R programming language. Data omissions were coded as "1" for missing values and "0" for others. Summary variables were created to indicate the number of personnel and procedure and data omissions per visit.The average completeness of the operating room data was 98%, which is considered excellent. However, seven variables-the start and end date and time of anesthesia, the type of treatment, personnel group, and assistant information-had completeness below the 95% target level. A total of 34% of the surgical visits contained at least one data omission. In the yearly comparison, the completeness values of variables were statistically significantly higher in 2022 compared with 2023.By ensuring existing quality assurance practices, verifying internal data maintenance and verifying and standardizing documenting practices the organization can achieve net benefits through improved data completeness, thus enhancing patient records, financial information, and management. Improved data quality will also benefit national and international registers.

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手术室数据的完整性。
在手术室,每次就诊都会收集大量的数据。其中一些数据是患者信息,一些是与资源管理相关的,这与医院财务有关。低质量的数据导致糟糕的决策,影响患者安全和护理的连续性。本研究旨在评估外科手术中记录的数据的完整性,并根据结果提高数据质量,确定数据管理改进思路。方法对33,684例外科就诊进行定量评价,重点分析数据遗漏。该组织确定了58个手术室数据变量,涉及访问、程序、资源和人员。对36个变量的数据完整性进行了评估,排除了47个缺少“完整”标志的访问。数据预处理使用Python和Pandas完成,并对人员姓名进行了假名化处理。数据分析使用R编程语言完成。数据遗漏用“1”表示缺失值,用“0”表示其他值。创建了摘要变量来表示人员和程序的数量,以及每次访问的数据遗漏。结果手术室资料的平均完整性为98%,为优等。然而,麻醉开始和结束日期和时间、治疗类型、人员分组和辅助信息等7个变量的完整性低于95%的目标水平。34%的外科就诊至少有一个数据遗漏。在年度比较中,变量的完备性值在2022年明显高于2023年。结论通过确保现有的质量保证实践,验证内部数据维护,验证和标准化文档实践,组织可以通过提高数据完整性,增强患者记录,财务信息和管理来实现净效益。数据质量的提高也将使国家和国际登记处受益。关键词:数据,患者数据,质量,卫生信息系统,手术室。
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来源期刊
Methods of Information in Medicine
Methods of Information in Medicine 医学-计算机:信息系统
CiteScore
3.70
自引率
11.80%
发文量
33
审稿时长
6-12 weeks
期刊介绍: Good medicine and good healthcare demand good information. Since the journal''s founding in 1962, Methods of Information in Medicine has stressed the methodology and scientific fundamentals of organizing, representing and analyzing data, information and knowledge in biomedicine and health care. Covering publications in the fields of biomedical and health informatics, medical biometry, and epidemiology, the journal publishes original papers, reviews, reports, opinion papers, editorials, and letters to the editor. From time to time, the journal publishes articles on particular focus themes as part of a journal''s issue.
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