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Computable Declarative Representation of Clinical Assessment Scales in EHRs

Mercedes Arguello Casteleiro, Nicolas Matentzoglu, Bijan Parsia, Sebastian Brandt
2014 2014 IEEE 27th International Symposium on Computer-Based Medical Systems  
Clinical assessment scales, such as the Glasgow coma scale, are a core part of Electronic Health Records (EHRs).  ...  To solve this problem, we propose to separate the representation of the structure and content of an assessment scale from its enactment with the former being captured in OWL 2 and the latter being determined  ...  Figure 3 isolates the computation of the scale from the representation of the scale.  ... 
doi:10.1109/cbms.2014.80 dblp:conf/cbms/CasteleiroMPB14 fatcat:y7sgqpjzvjh4ziqbo5gkecyocm

Application of an Ontology for Characterizing Data Quality for a Secondary Use of EHR Data

Stuart Speedie, Gyorgy Simon, Vipin Kumar, Bonnie Westra, Steven Johnson
2016 Applied Clinical Informatics  
SummaryThe goal of this study is to apply an ontology based assessment process to electronic health record (EHR) data and determine its usefulness in characterizing data quality for calculating an example  ...  Automating the data quality assessment process using this method can enable sharing of data quality metrics that may aid in making research results that use EHR data more transparent and reproducible.  ...  Clinical and Translational Science Institute (CTSI).  ... 
doi:10.4338/aci-2015-08-ra-0107 pmid:27081408 pmcid:PMC4817336 fatcat:npystizupbdsbmgjiwkgaj7fle

Deep representation learning of electronic health records to unlock patient stratification at scale

Isotta Landi, Benjamin S. Glicksberg, Hao-Chih Lee, Sarah Cherng, Giulia Landi, Matteo Danieletto, Joel T. Dudley, Cesare Furlanello, Riccardo Miotto
2020 npj Digital Medicine  
We considered EHRs of 1,608,741 patients from a diverse hospital cohort comprising a total of 57,464 clinical concepts.  ...  However, challenges in summarizing and representing patient data prevent widespread practice of scalable EHR-based stratification analysis.  ...  DISCUSSION This study proposes a computational framework to disentangle the heterogeneity of complex disorders in large-scale EHRs through the identification of data-driven clinical patterns with machine  ... 
doi:10.1038/s41746-020-0301-z pmid:32699826 pmcid:PMC7367859 fatcat:ddt7xa36jvbzzdkpirhdslxnty

Phe2vec: Automated Disease Phenotyping based on Unsupervised Embeddings from Electronic Health Records [article]

Jessica K De Freitas, Kipp W Johnson, Eddye Golden, Girish N Nadkarni, Joel T Dudley, Erwin P Bottinger, Benjamin S Glicksberg, Riccardo Miotto
2020 medRxiv   pre-print
Materials and Methods: Phe2vec is based on pre computing embeddings of medical concepts and patients' longitudinal clinical history.  ...  We evaluated Phe2vec using 49,234 medical concepts from structured EHRs and clinical notes from 1,908,741 patients in the Mount Sinai Health System.  ...  This result highlights the scalability of Phe2vec and reinforces the initial assumption of deriving a model that can automatically compute phenotype representations from EHR data in a seamless and robust  ... 
doi:10.1101/2020.11.14.20231894 fatcat:hcdjknsc3jfnhn2wjy3nuwboui

Selected articles from the BioCreative/OHNLP challenge 2018

Sijia Liu, Yanshan Wang, Hongfang Liu
2019 BMC Medical Informatics and Decision Making  
Acknowledgements Publication of this supplement was funded by National Institute of Health, National Institute of General Medical Sciences R01-GM102282, National Library of Medicine R01LM11934 and National  ...  The guest editors would like to acknowledge all the authors, anonymous reviewers and the journal of BMC Medical Informatics and Decision Making for their contributions to this supplement.  ...  One technique for automatically reducing redundancy in free text EHRs is to compute semantic similarity between clinical text snippets and remove highly similar snippets.  ... 
doi:10.1186/s12911-019-0994-6 pmid:31882003 pmcid:PMC6933636 fatcat:llxmntq4xbdahahctajal5uqjq

Transitive Sequencing Medical Records for Mining Predictive and Interpretable Temporal Representations

Hossein Estiri, Zachary H. Strasser, Jeffery G. Klann, Thomas H. McCoy, Kavishwar B. Wagholikar, Sebastien Vasey, Victor M. Castro, MaryKate E. Murphy, Shawn N. Murphy
2020 Patterns  
Using clinical data from a cohort of patients with congestive heart failure, we mined temporal representations by transitive sequencing of EHR medication and diagnosis records for classification and prediction  ...  when clinical data are treated independently of the patient's history.  ...  The silver-standard labels were not verified by human experts but are crucial for scaling up ML training on large-scale clinical data.  ... 
doi:10.1016/j.patter.2020.100051 pmid:32835307 pmcid:PMC7301790 fatcat:julqjonrpbgwjkpkm5nrexgpmu

Risk Assessment Tools and Data-Driven Approaches for Predicting and Preventing Suicidal Behavior

Sumithra Velupillai, Gergö Hadlaczky, Enrique Baca-Garcia, Genevieve M. Gorrell, Nomi Werbeloff, Dong Nguyen, Rashmi Patel, Daniel Leightley, Johnny Downs, Matthew Hotopf, Rina Dutta
2019 Frontiers in Psychiatry  
In the last 50 years a large number of tools have been designed for suicide risk assessment, and tested in a wide variety of populations, but studies show that these tools suffer from low positive predictive  ...  We provide a perspective on the strengths and weaknesses of these applications to mental health-related data, and suggest research directions to enable improvement in clinical practice.  ...  SV incorporated edits of the other authors. All authors approved the final version.  ... 
doi:10.3389/fpsyt.2019.00036 pmid:30814958 pmcid:PMC6381841 fatcat:jkf63z33xbhh3ckgvpe6ozu7sy

Leveraging the EHR4CR platform to support patient inclusion in academic studies: challenges and lessons learned

Yannick Girardeau, Justin Doods, Eric Zapletal, Gilles Chatellier, Christel Daniel, Anita Burgun, Martin Dugas, Bastien Rance
2017 BMC Medical Research Methodology  
The development of Electronic Health Records (EHRs) in hospitals offers the ability to reuse data from patient care activities for clinical research.  ...  We also defined metrics to assess each of the steps (including criteria complexity, normalization quality, and data completeness of EHRs).  ...  Juliette Djadi-Prat for their help in preparing this study. We would like to thank all people who contribute to the the development of the EHR4CR platform. Funding  ... 
doi:10.1186/s12874-017-0299-3 pmid:28241798 pmcid:PMC5329914 fatcat:2q4jxjryureazo4rhnzd6utkei

Perceived Burden of EHRs on Physicians at Different Stages of Their Career

Gary Burke, Heather Archambault, Todd Schwartz, James Larson, Raj Ratwani, Saif Khairat
2018 Applied Clinical Informatics  
This study investigated key EHR usability barriers in the ED particularly, the assess frustration levels among physicians based on experience, and identifying factors impacting those levels of frustrations  ...  Physicians were asked to complete six patient scenarios in the EHR, and then participants filled two surveys to assess the perceived workload and satisfaction with the EHR interface.  ...  may approve of EHRs in concept and appreciate the ability to provide care remotely at a variety of locations; however, in an assessment of physicians' opinions of EHR technologies in practice, the American  ... 
doi:10.1055/s-0038-1648222 pmid:29768634 pmcid:PMC5955717 fatcat:p6wr5vpmx5hqpp4oywtit4foci

The value of structured data elements from electronic health records for identifying subjects for primary care clinical trials

Mohammad B. Ateya, Brendan C. Delaney, Stuart M. Speedie
2015 BMC Medical Informatics and Decision Making  
An increasing number of clinical trials are conducted in primary care settings.  ...  Conclusions: Electronic health records readily contain much of the data needed to assess patients' eligibility for clinical trials enrollment.  ...  However none of these require standard or computable representations of eligibility criteria.  ... 
doi:10.1186/s12911-016-0239-x pmid:26754574 pmcid:PMC4709934 fatcat:aknth2tbbvcbfbicfpoy3qrzka

Deep Representation Learning of Electronic Health Records to Unlock Patient Stratification at Scale [article]

Isotta Landi , Hao-Chih Lee, Matteo Danieletto, Cesare Furlanello (1 and 7), and Riccardo Miotto Bruno Kessler Foundation, Trento, Italy Hasso Plattner Institute for Digital Health at Mount Sinai, NY, Institute for Next Generation Healthcare, NY, Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, NY, Department of Mental Health and Pathological Addiction (+3 others)
2020 arXiv   pre-print
Materials and methods: We considered EHRs of 1,608,741 patients from a diverse hospital cohort comprising of a total of 57,464 clinical concepts.  ...  However, challenges in summarizing and representing patient data prevent widespread practice of scalable EHR-based stratification analysis.  ...  Discussion This study proposes a computational framework to disentangle the heterogeneity of complex disorders in large-scale EHRs through the identification of data-driven clinical patterns with machine  ... 
arXiv:2003.06516v1 fatcat:l2mg5ox6orbi3e7tnlhmbiuesu

Nutrition Information in Oncology - Extending the Electronic Patient-Record Data Set

Priscila A Maranhão, Ana Margarida Pereira, Conceição Calhau, Paula Ravasco, Federico Bozzetti, Alessandro Laviano, Liz Isenring, Elisa V Bandera, Maureen B Huhmann, Pedro Vieira-Marques, Ricardo J Cruz-Correia
2020 Journal of medical systems  
Future studies are needed to assess their applicability in other areas and their practical impact on data quality, system interoperability and, ultimately, on clinical practice and research.  ...  However, the oncology context presents a complex content that increases the difficulties of EHR application.  ...  The data are represented as knowledge artifacts that are structured, computable, and shareable representations of clinical knowledge [11] .  ... 
doi:10.1007/s10916-020-01649-9 pmid:32986139 pmcid:PMC7520877 fatcat:7utpoyicjncwhc3echbhf6dfi4

An Archetype-Based Solution for the Interoperability of Computerised Guidelines and Electronic Health Records [chapter]

Mar Marcos, Jose A. Maldonado, Begoña Martínez-Salvador, David Moner, Diego Boscá, Montserrat Robles
2011 Lecture Notes in Computer Science  
In this paper we present an archetype-based approach to solve the interoperability problems of guideline systems, as well as to enable guideline sharing.  ...  There is a wide consensus about the benefits of guidelines and about the fact that they should be deployed through clinical information systems, making them available during consultation time.  ...  scale used in the archetype.  ... 
doi:10.1007/978-3-642-22218-4_35 fatcat:m2gykgahs5c7ragk3sarea5r3e

Deep Multi-Modal Transfer Learning for Augmented Patient Acuity Assessment in the Intelligent ICU

Benjamin Shickel, Anis Davoudi, Tezcan Ozrazgat-Baslanti, Matthew Ruppert, Azra Bihorac, Parisa Rashidi
2021 Frontiers in Digital Health  
In this pilot study, we explore the benefits of augmenting existing EHR data with novel measurements from wrist-worn activity sensors as part of a clinical environment known as the Intelligent ICU.  ...  We overcome the challenge of small sample size in our prospective cohort by applying deep transfer learning using EHR data from a much larger cohort of traditional ICU patients.  ...  ACKNOWLEDGMENTS The authors acknowledge Gigi Lipori, MBA for assistance with data retrieval, and the University of Florida Integrated Data Repository (IDR) and the UF Health Office of the Chief Data Officer  ... 
doi:10.3389/fdgth.2021.640685 pmid:33718920 pmcid:PMC7954405 fatcat:g2siuwh3l5ertdopmglfvdystm

Provider perspectives on the integration of patient-reported outcomes in an electronic health record

Renwen Zhang, Eleanor R Burgess, Madhu C Reddy, Nan E Rothrock, Surabhi Bhatt, Luke V Rasmussen, Zeeshan Butt, Justin B Starren
2019 JAMIA Open  
This study examines how well an EHR-integrated PRO system fits clinical workflows and individual needs of different provider groups within 2 clinics.  ...  However, new system implementation in health-care institutions is often accompanied by a change in clinical workflow and organizational culture.  ...  Conflict of interest statement. None declared.  ... 
doi:10.1093/jamiaopen/ooz001 pmid:30976756 pmcid:PMC6447042 fatcat:xok7yv7gvbabzda6pbs6yq2oka
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