Empirical study of Data Completeness in Electronic Health Records in China

IF 2.4 Q2 INFORMATION SCIENCE & LIBRARY SCIENCE Pacific Asia Journal of the Association for Information Systems Pub Date : 2020-06-01 DOI:10.17705/1PAIS.12204

Caihua Liu, D. Zowghi, A. Talaei-Khoei, Zhi Jin

{"title":"Empirical study of Data Completeness in Electronic Health Records in China","authors":"Caihua Liu, D. Zowghi, A. Talaei-Khoei, Zhi Jin","doi":"10.17705/1PAIS.12204","DOIUrl":null,"url":null,"abstract":"Abstract Background: As a dimension of data quality in electronic health records (EHR), data completeness plays an important role in improving quality of care. Although many studies of data management focus on constructing the factors that influence data quality for the purpose of quality improvement, the constructs that are developed for interpreting factors influencing data completeness in the EHR context have received limited attention. Methods: Based on related studies, we constructed the factors influencing EHR data completeness in a conceptual model. We then examined the proposed model by surveying clinical practitioners in China. Results: Our results show that the data quality management literature can serve as a starting point to derive a conceptual model of factors influencing data completeness in the EHR context. This study also demonstrates that “resources” should be added as a factor that influences data completeness in EHR. Conclusion: Our resulting conceptual model shows a substantial explanation of data completeness in EHR assessed in this study. Although the proposed relationships between the included factors were previously supported in the literature, our work provides the beginning empirical evidence that some relationships may not be always significantly supported. The possible explanation of these differences has been discussed in the present research. This study thus benefits decision makers and EHR program managers in implementing EHR as well as EHR vendors in the EHR integration by addressing data completeness issues. Available at: https://aisel.aisnet.org/pajais/vol12/iss2/4/ Recommended Citation Liu, Caihua; Zowghi, Didar; Talaei-Khoei, Amir; and Jin, Zhi (2020) \"Empirical study of Data Completeness in Electronic Health Records in China,\" Pacific Asia Journal of the Association for Information Systems: Vol. 12: Iss. 2, Article 4. DOI: 10.17705/1pais.12204 Available at: https://aisel.aisnet.org/pajais/vol12/iss2/4","PeriodicalId":43480,"journal":{"name":"Pacific Asia Journal of the Association for Information Systems","volume":"65 1","pages":"4"},"PeriodicalIF":2.4000,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Pacific Asia Journal of the Association for Information Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.17705/1PAIS.12204","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"INFORMATION SCIENCE & LIBRARY SCIENCE","Score":null,"Total":0}

引用次数: 2

Abstract

Abstract Background: As a dimension of data quality in electronic health records (EHR), data completeness plays an important role in improving quality of care. Although many studies of data management focus on constructing the factors that influence data quality for the purpose of quality improvement, the constructs that are developed for interpreting factors influencing data completeness in the EHR context have received limited attention. Methods: Based on related studies, we constructed the factors influencing EHR data completeness in a conceptual model. We then examined the proposed model by surveying clinical practitioners in China. Results: Our results show that the data quality management literature can serve as a starting point to derive a conceptual model of factors influencing data completeness in the EHR context. This study also demonstrates that “resources” should be added as a factor that influences data completeness in EHR. Conclusion: Our resulting conceptual model shows a substantial explanation of data completeness in EHR assessed in this study. Although the proposed relationships between the included factors were previously supported in the literature, our work provides the beginning empirical evidence that some relationships may not be always significantly supported. The possible explanation of these differences has been discussed in the present research. This study thus benefits decision makers and EHR program managers in implementing EHR as well as EHR vendors in the EHR integration by addressing data completeness issues. Available at: https://aisel.aisnet.org/pajais/vol12/iss2/4/ Recommended Citation Liu, Caihua; Zowghi, Didar; Talaei-Khoei, Amir; and Jin, Zhi (2020) "Empirical study of Data Completeness in Electronic Health Records in China," Pacific Asia Journal of the Association for Information Systems: Vol. 12: Iss. 2, Article 4. DOI: 10.17705/1pais.12204 Available at: https://aisel.aisnet.org/pajais/vol12/iss2/4

查看原文

微信好友朋友圈 QQ好友复制链接

本刊更多论文

中国电子病历数据完整性的实证研究

背景:数据完整性作为电子健康档案(EHR)数据质量的一个维度，对提高医疗质量起着重要作用。尽管许多数据管理研究着眼于构建影响数据质量的因素，以提高质量，但为解释电子病历背景下影响数据完整性的因素而开发的结构受到的关注有限。方法:在相关研究的基础上，构建影响电子病历数据完整性的因素概念模型。然后，我们通过调查中国的临床从业人员来检验所提出的模型。结果:我们的研究结果表明，数据质量管理文献可以作为一个起点，推导出影响电子病历背景下数据完整性因素的概念模型。本研究还表明，在电子病历中应增加“资源”作为影响数据完整性的因素。结论:我们的概念模型显示了本研究中评估的电子病历数据完整性的实质性解释。虽然所提出的包括因素之间的关系在以前的文献中得到了支持，但我们的工作提供了初步的经验证据，表明一些关系可能并不总是得到显著支持。本研究对这些差异的可能解释进行了讨论。因此，本研究通过解决数据完整性问题，有利于决策者和EHR项目经理实施EHR，也有利于EHR供应商整合EHR。查阅网址:https://aisel.aisnet.org/pajais/vol12/iss2/4/Zowghi Didar;Talaei-Khoei,阿米尔;金智(2020)“中国电子健康档案数据完整性的实证研究”，《亚太信息系统协会杂志》，第12卷，第2期，第4条。pais.12204 DOI: 10.17705/1可在:https://aisel.aisnet.org/pajais/vol12/iss2/4

本文章由计算机程序翻译，如有差异，请以英文原文为准。

求助全文

约1分钟内获得全文去求助

来源期刊

Pacific Asia Journal of the Association for Information Systems INFORMATION SCIENCE & LIBRARY SCIENCE-

CiteScore

4.10

自引率

33.30%

发文量