Defining and measuring completeness of electronic health records for secondary use
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TLDR
It is found that according to any definition, the number of complete records in the clinical database is far lower than the nominal total, and it is concluded that the concept of completeness in EHR is contextual.About:
This article is published in Journal of Biomedical Informatics.The article was published on 2013-10-01 and is currently open access. It has received 290 citations till now. The article focuses on the topics: Data quality & Completeness (statistics).read more
Citations
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Journal ArticleDOI
Deep Patient: An Unsupervised Representation to Predict the Future of Patients from the Electronic Health Records
TL;DR: The findings indicate that deep learning applied to EHRs can derive patient representations that offer improved clinical predictions, and could provide a machine learning framework for augmenting clinical decision systems.
Journal ArticleDOI
The National COVID Cohort Collaborative (N3C): Rationale, Design, Infrastructure, and Deployment.
Melissa A. Haendel,Melissa A. Haendel,Christopher G. Chute,Tellen D. Bennett,David Eichmann,Justin Guinney,Warren A. Kibbe,Philip R. O. Payne,Emily R. Pfaff,Peter N. Robinson,Joel H. Saltz,Heidi Spratt,Christine Suver,John Wilbanks,Adam B. Wilcox,Andrew E. Williams,Chunlei Wu,Clair Blacketer,Robert L. Bradford,James J. Cimino,Marshall Clark,Evan W Colmenares,Patricia A Francis,Davera Gabriel,Alexis Graves,Raju Hemadri,Stephanie S Hong,George Hripscak,Dazhi Jiao,Jeffrey G. Klann,Kristin Kostka,Adam M Lee,Harold P Lehmann,Lora Lingrey,Robert T. Miller,Michele I. Morris,Shawn N. Murphy,Karthik Natarajan,Matvey B. Palchuk,Usman Sheikh,Harold R. Solbrig,Shyam Visweswaran,Anita Walden,Anita Walden,Kellie M Walters,Griffin M. Weber,Xiaohan Tanner Zhang,Richard L Zhu,Benjamin Amor,Andrew T Girvin,Amin Manna,Nabeel Qureshi,Michael G. Kurilla,Sam Michael,Lili M Portilla,Joni L Rutter,Christopher P. Austin,Ken R Gersing +57 more
TL;DR: The N3C has demonstrated that a multisite collaborative learning health network can overcome barriers to rapidly build a scalable infrastructure incorporating multiorganizational clinical data for COVID-19 analytics.
Journal ArticleDOI
A Harmonized Data Quality Assessment Terminology and Framework for the Secondary Use of Electronic Health Record Data
Michael G. Kahn,Tiffany J. Callahan,Juliana Barnard,Alan Bauck,Jeffrey S. Brown,Bruce N. Davidson,Hossein Estiri,Carsten Goerg,Erin Holve,Steven G. Johnson,Siaw-Teng Liaw,Marianne Hamilton-Lopez,Daniella Meeker,Toan C. Ong,Patrick B. Ryan,Ning Shang,Nicole G. Weiskopf,Chunhua Weng,Meredith N. Zozus,Lisa M. Schilling +19 more
TL;DR: A consistent, common DQ terminology, organized into a logical framework, is an initial step in enabling data owners and users, patients, and policy makers to evaluate and communicate data quality findings in a well-defined manner with a shared vocabulary.
Posted Content
DeepCare: A Deep Dynamic Memory Model for Predictive Medicine
TL;DR: DeepCare as discussed by the authors is an end-to-end deep dynamic neural network that reads medical records, stores previous illness history, infers current illness states and predicts future medical outcomes.
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"Big data" and the electronic health record.
TL;DR: In reviewing the literature for the past three years, this work focuses on "big data" in the context of EHR systems and reports on some examples of how secondary use of data has been put into practice.
References
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Journal ArticleDOI
Inference and missing data
TL;DR: In this paper, it was shown that ignoring the process that causes missing data when making sampling distribution inferences about the parameter of the data, θ, is generally appropriate if and only if the missing data are missing at random and the observed data are observed at random, and then such inferences are generally conditional on the observed pattern of missing data.
Book
Juran's Quality Control Handbook
TL;DR: The third edition of the book has been updated to give managers the know-how they need to manage for quality through the next decade as discussed by the authors, which is the finest book on quality ever written.
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