Real-World Evidence of COVID-19 Patients’ Data Quality in the Electronic Health Records
Samar Binkheder,Mohammed Ahmed Asiri,Khaled Waleed Altowayan,Turki Mohammed Alshehri,Mashhour Faleh Alzarie,Raniah N. Aldekhyyel,Ibrahim A. Almaghlouth,Jwaher A. Almulhem +7 more
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TLDR
In this article, the quality of COVID-19 patients' records and their readiness for secondary use was evaluated using ICD-10 codes and case definition guidelines, and the accuracy of the COVID19 case identification was higher in laboratory tests than in ICD10 codes.About:
This article is published in Healthcare.The article was published on 2021-11-28 and is currently open access. It has received 2 citations till now. The article focuses on the topics: Patient safety & Data quality.read more
Citations
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Health Informatics: The Foundations of Public Health
Tian-Shyug Lee,Chi-Jie Lu +1 more
TL;DR: In this article , the authors describe how vast amounts of diverse digital data are becoming more easily generated and collected and how they can be easily collected and used to improve the quality of data.
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Electronic health record data quality assessment and tools: a systematic review.
Abbie Lewis,Nicole G. Weiskopf,Zachary B. Abrams,Randi E. Foraker,Albert Lai,Philip R. O. Payne,Aditi Gupta +6 more
TL;DR: The most common dimensions of EHR data quality were completeness, correctness, concordance, plausibility, and currency, followed by conformance and bias as 2 additional dimensions of data quality and structural agreement as an additional methodology as mentioned in this paper .
References
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Review of the Clinical Characteristics of Coronavirus Disease 2019 (COVID-19)
TL;DR: The purpose of this brief review is to summarize published studies as of late February 2020 on the clinical features, symptoms, complications, and treatments of COVID-19 and help provide guidance for frontline medical staff in the clinical management of this outbreak.
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Methods and dimensions of electronic health record data quality assessment: enabling reuse for clinical research.
Nicole G. Weiskopf,Chunhua Weng +1 more
TL;DR: Researchers interested in the reuse of EHR data for clinical research are recommended to consider the adoption of a consistent taxonomy of E HR data quality, to remain aware of the task-dependence of dataquality, and to integrate work on data quality assessment from other fields.
Journal ArticleDOI
Diagnosis and treatment recommendations for pediatric respiratory infection caused by the 2019 novel coronavirus.
Zhimin Chen,Jun Fen Fu,Qiang Shu,Ying Hu Chen,Chun Zhen Hua,Fu Bang Li,Ru Lin,Lan Fang Tang,Tianlin Wang,Wei Wang,Ying Shuo Wang,Wei Ze Xu,Zi Hao Yang,Sheng Ye,Tian Ming Yuan,Chen Mei Zhang,Yuanyuan Zhang +16 more
TL;DR: Recommendations for the diagnosis and treatment of respiratory infection caused by 2019-nCoV for children were drafted by the National Clinical Research Center for Child Health, the National Children’s Regional Medical Center, Children's Hospital, Zhejiang University School of Medicine to further standardize the protocol.
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Large-Scale Multi-omic Analysis of COVID-19 Severity.
Katherine A. Overmyer,Evgenia Shishkova,Ian J. Miller,Joseph Balnis,Matthew N. Bernstein,Trenton M. Peters-Clarke,Jesse G. Meyer,Qiuwen Quan,Laura K. Muehlbauer,Edna A. Trujillo,Yuchen He,Amit Chopra,Hau Chieng,Anupama Tiwari,Marc A. Judson,Brett Paulson,Dain R. Brademan,Yunyun Zhu,Lia R. Serrano,Vanessa Linke,Lisa A. Drake,Alejandro P. Adam,Bradford S Schwartz,Harold A. Singer,Scott Swanson,Deane F. Mosher,Ron Stewart,Joshua J. Coon,Ariel Jaitovich +28 more
TL;DR: A web-based tool (covid-omics.app) is presented enabling interactive exploration of the compendium and its utility through a machine learning approach for prediction of COVID-19 severity is illustrated.
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Validation of Electronic Medical Record-Based Phenotyping Algorithms: Results and Lessons Learned From the eMERGE Network
Katherine M. Newton,Peggy L. Peissig,Abel N. Kho,Suzette J. Bielinski,Richard L. Berg,Vidhu Choudhary,Melissa A. Basford,Christopher G. Chute,Iftikhar J. Kullo,Rongling Li,Jennifer A. Pacheco,Luke V. Rasmussen,Leslie Spangler,Joshua C. Denny +13 more
TL;DR: Validation is a worthwhile process that not only measures phenotype performance but also strengthens phenotype algorithm definitions and enhances their inter-institutional sharing.