Ali Garavand, Reza Rabiei, Hassan Emami, Mehdi Pishgahi, Mojtaba Vahidi-Asl
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Data gathering was conducted using a data extraction form, and the content of selected studies was analysed with respect to key registry processes, including case finding, data gathering, data abstracting, data quality control, reporting and patient follow-up.</p><p><strong>Results: </strong>A total of 17,604 studies were identified in the search, 55 of which were relevant studies that addressed the 21 registries and were selected for the analysis. Results showed that the most common resources for case finding included admission and discharge documents, physician's reports and screening results. Patient follow-up was mainly performed through direct visits or via telephone calls. The key attributes used for checking the data quality included data accuracy, completeness and definition.</p><p><strong>Conclusion: </strong>CAD registries aim to facilitate the assessment of health services provided to patients. 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The data quality control, as a CAD registry process, requires developing standard tools and applying appropriate data quality attributes.</p><p><strong>Implications: </strong>The findings of the current study could lay the foundation for successful design and development of CAD registries based on the key registry processes for effective data management.</p>","PeriodicalId":73210,"journal":{"name":"Health information management : journal of the Health Information Management Association of Australia","volume":"51 2","pages":"63-78"},"PeriodicalIF":0.0000,"publicationDate":"2022-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1177/1833358320929366","citationCount":"10","resultStr":"{\"title\":\"The attributes of hospital-based coronary artery diseases registries with a focus on key registry processes: A systematic review.\",\"authors\":\"Ali Garavand, Reza Rabiei, Hassan Emami, Mehdi Pishgahi, Mojtaba Vahidi-Asl\",\"doi\":\"10.1177/1833358320929366\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Background: </strong>The management of data on coronary artery disease (CAD) plays a significant role in controlling the disease and reducing the mortality of patients. 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引用次数: 10
摘要
背景:冠状动脉疾病(CAD)的数据管理对控制疾病和降低患者死亡率具有重要作用。疾病登记有助于数据的管理。目的:本研究旨在确定以医院为基础的CAD登记的属性,重点关注关键登记流程。方法:在本系统综述中,我们检索了2000年至2019年在PubMed、Scopus、EMBASE和ISI Web of Knowledge中发表的研究。截至2019年11月,搜索词包括冠状动脉疾病、登记和数据管理(MeSH术语)。使用数据提取表进行数据收集,并分析选定研究的内容,包括病例发现、数据收集、数据摘要、数据质量控制、报告和患者随访。结果:在检索中共确定了17,604项研究,其中55项是涉及21个注册中心的相关研究,并被选中进行分析。结果显示,最常见的病例查找资源包括入院和出院文件、医生报告和筛查结果。患者随访主要通过直接访视或电话进行。用于检查数据质量的关键属性包括数据准确性、完整性和定义。结论:CAD登记旨在促进对提供给患者的卫生服务的评估。建立主要的注册中心程序,对发展和实施CAD注册中心至关重要。数据质量控制作为CAD注册过程,需要开发标准工具并应用适当的数据质量属性。意义:本研究的结果可以为基于有效数据管理的关键注册流程的CAD注册表的成功设计和开发奠定基础。
The attributes of hospital-based coronary artery diseases registries with a focus on key registry processes: A systematic review.
Background: The management of data on coronary artery disease (CAD) plays a significant role in controlling the disease and reducing the mortality of patients. The diseases registries facilitate the management of data.
Objective: This study aimed to identify the attributes of hospital-based CAD registries with a focus on key registry processes.
Method: In this systematic review, we searched for studies published between 2000 and 2019 in PubMed, Scopus, EMBASE and ISI Web of Knowledge. The search terms included coronary artery disease, registry and data management (MeSH terms) at November 2019. Data gathering was conducted using a data extraction form, and the content of selected studies was analysed with respect to key registry processes, including case finding, data gathering, data abstracting, data quality control, reporting and patient follow-up.
Results: A total of 17,604 studies were identified in the search, 55 of which were relevant studies that addressed the 21 registries and were selected for the analysis. Results showed that the most common resources for case finding included admission and discharge documents, physician's reports and screening results. Patient follow-up was mainly performed through direct visits or via telephone calls. The key attributes used for checking the data quality included data accuracy, completeness and definition.
Conclusion: CAD registries aim to facilitate the assessment of health services provided to patients. Putting the key registry processes in place is crucial for developing and implementing the CAD registry. The data quality control, as a CAD registry process, requires developing standard tools and applying appropriate data quality attributes.
Implications: The findings of the current study could lay the foundation for successful design and development of CAD registries based on the key registry processes for effective data management.