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Developing predictive models using electronic medical records: challenges and pitfalls
2013
AMIA Annual Symposium Proceedings
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While Electronic Medical Records (EMR) contain detailed records of the patient-clinician encounter - vital signs, laboratory tests, symptoms, caregivers' notes, interventions prescribed and outcomes - ...
In this paper, we discuss key issues and subtle pitfalls specific to building predictive models from EMR. ...
Conclusions Electronic Medical Records are becoming an increasingly valuable resource for developing predictive models for improving patient management. ...
pmid:24551396
pmcid:PMC3900132
fatcat:e3nzxrhd3bekbmzqougr2givma
FRAMR-EMR: Framework for Prognostic Predictive Model Development Using Electronic Medical Record Data with a Case Study in Osteoarthritis Risk
[article]
2017
arXiv
pre-print
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Electronic medical record, EMR, data can be used for the construction of these models. ...
Objectives- To provide a framework for those seeking to develop prognostic predictive models using EMR data, and to illustrate these steps using osteoarthritis risk estimation as an example. ...
Electronic medical record (EMR) data can be used for the construction of these models. ...
arXiv:1705.09563v2
fatcat:mu57mxvqizhzldv2vup7gpd7gm
Clinical Trials in Neurovirology: Successes, Challenges, and Pitfalls
2016
Neurotherapeutics
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This review aims to highlight these methodological challenges and pitfalls in designing and executing clinical neurovirology trials, as well as to outline innovative trial designs, which could be useful ...
in addressing common challenges. ...
and unpredictable, challenging medical staff, infrastructure, and policy-makers and the media. ...
doi:10.1007/s13311-016-0440-8
pmid:27194073
pmcid:PMC4965408
fatcat:la5yaw6fpvevnejzubu43hatdy
Pay for Performance for Salaried Health Care Providers: Methodology, Challenges, and Pitfalls
2014
The Permanente Journal
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Accurate recording, extraction, and analysis of data together with careful selection and measurement of indicators of performance are crucial for meaningful assessment. ...
If appropriate methodology is not used, much time, effort, and money may be expended gathering data that may be potentially misleading or even useless, with the possibility that good performance may go ...
to extract from electronic medical records (EMRs). ...
doi:10.7812/tpp/13-087
pmid:24626075
pmcid:PMC3951034
fatcat:tg4dydzxobbgjgf2qrntkmsn7u
SP-0215: Clinical application of auto-contouring systems: Challenges and pitfalls
2013
Radiotherapy and Oncology
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Multi-layer ionization chambers (MLIC) can effectively measure and verify the range of a large number of beam energies and can be used for routine QA. ...
The electronic read-out of such devices can be very advantageous since it allows on-line analysis of the data just measured. ...
Clinical application of auto-contouring systems: Challenges and pitfalls P. Voet 1 , M. Dirkx 1 , D. Teguh 1 , A. Al Mamgami 2 , P. Levendag 2 , M. Hoogeman 1 , B. ...
doi:10.1016/s0167-8140(15)32521-4
fatcat:rtdnaoxdbnbypejnjh2yfvenym
Research in progress—electronic patient records: a new era
2014
Thorax
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In 2006, we set up a program to develop electronic patient records (EPR) for chronic disease using Cystic Fibrosis (CF) as our initial model. ...
Clinical information systems and electronic records are starting to appear in secondary care and herald new potentials for improving health provision and capturing high quality data. ...
CHALLENGES AND PITFALLS Developing EPR in 2007 proved difficult due to the absence of appropriate hardware and hospital infrastructure. ...
doi:10.1136/thoraxjnl-2014-206573
pmid:25504824
fatcat:74fmalzng5frljhxvdd5rymevi
From Medical Records to Clinical Science
2012
The Permanente Journal
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Medical records contain an abundance of information, very little of which is extracted and put to clinical use. ...
Increasing the flow of information from medical records to clinical practice requires methods of analysis that are appropriate for large nonintervention studies. ...
Clinical Perspective: Propensity Scoring and Matched Comparison Groups On the basis of electronic medical record (EMR) data, it is possible to predict whether a patient will be assigned a certain treatment ...
doi:10.7812/tpp/12-047
pmid:23251122
pmcid:PMC3523940
fatcat:eogysfh3gbggrljpa34oudnuwa
Adoption of clinical risk prediction tools is limited by a lack of integration with electronic health records
2021
BMJ Health & Care Informatics
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Adoption of clinical risk prediction tools is limited by a lack of integration with electronic health records. ...
ORCID iD Videha Sharma http:// orcid. org/ 0000-0001-7640-1239 Figure 1 1 Current and proposed use of risk prediction tools. EHRs, electronic health records. on July 9, 2021 by guest. ...
on the development of risk prediction models, the evidence of successful clinical adoption and impact on care outcomes is largely absent. 11 Risk prediction models are primarily developed using routinely ...
doi:10.1136/bmjhci-2020-100253
pmid:33608259
pmcid:PMC7898839
fatcat:75p6bk5nv5fznh56layvafm4o4
Privacy, Confidentiality, and Electronic Medical Records
1996
JAMIA Journal of the American Medical Informatics Association
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One purpose of electronic medical records (EMRs) is to increase the accessibility and sharing of health records among authorized individuals. ...
It is argued that with guiding policy and current technology, an electronic medical record may offer better security than a traditional paper record. n JAMIA. 1996;3:i39-148. ...
A major challenge will be that of enticing developers, who are eager for working medical computer applications, to make the financial and time investments in designing and building adequate security features ...
doi:10.1136/jamia.1996.96236282
pmid:8653450
pmcid:PMC116296
fatcat:uug65a5r2jhlzas5jomdrp6lfq
Pre‐Recorded Symposia
2021
Bipolar Disorders
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Aims: Cognitive heterogeneity in schizophrenia spectrum disorders (SSD) and bipolar disorder (BD) has been explored using clustering analyses. ...
Aims: The Room-Light pilot study investigated the feasibility of a newly developed dynamic built-in LED light system in psychiatric hospital ward rooms. ...
We used logistic regression to determine whether baseline fMRI findings predicted psychopathology or resilience from developing any psychiatric symptoms. ...
doi:10.1111/bdi.13086
fatcat:f3gydcxvmjfadapb3laovjkzrm
Opportunities and challenges in developing risk prediction models with electronic health records data: a systematic review
2016
JAMIA Journal of the American Medical Informatics Association
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Objective: Electronic health records (EHRs) are an increasingly common data source for clinical risk prediction, presenting both unique analytic opportunities and challenges. ...
Methods: We searched PubMed for articles that reported on the use of an EHR to develop a risk prediction model from 2009 to 2014. ...
To limit the search to EHRbased studies we added the search terms: "((Electronic Health Record*) OR (Electronic Medical Record*) OR EHR OR EHRs OR EMR OR EMRs))." ...
doi:10.1093/jamia/ocw042
pmid:27189013
pmcid:PMC5201180
fatcat:wcaufkj2c5f27owhdmsxb2bmge
A Review of Automatic Phenotyping Approaches using Electronic Health Records
2019
Electronics
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Electronic Health Records (EHR) are a rich repository of valuable clinical information that exist in primary and secondary care databases. ...
Articles published on PubMed and Google scholar between 2013 and 2017 have been reviewed, using search terms derived from Medical Subject Headings (MeSH). ...
Acknowledgments: We would like to thank the jointly with the NICS group at School of Science and Technology, Nottingham Trent University, United Kingdom and College of Engineering, IT and Environment, ...
doi:10.3390/electronics8111235
fatcat:6wygemixhvgoxkhjqrmmjs3ynq
Readmission prediction using deep learning on electronic health records
2019
Journal of Biomedical Informatics
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This study targets key elements of an Electronic Health Record (EHR) driven prediction model in a single framework: using both expert and machine derived features, incorporating sequential patterns and ...
Here, using real data from over 7500 CHF patients hospitalized between 2012 and 2016 in Sweden, we built and tested a deep learning framework to predict 30-day unscheduled readmission. ...
Funding: The authors thank the European Regional Development Fund (ERDF), Health Technology Center and CAISR at Halmstad University and Hallands Hospital for financing the research work under the project ...
doi:10.1016/j.jbi.2019.103256
pmid:31351136
fatcat:cca7q63ifbe3likssiz7wxwhaa
Making The Case for a P2P Personal Health Record
2020
Information
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However, current Electronic Health Records (EHR) tend to be institution-centric, often leaving the medical information of the patient fragmented and more importantly inaccessible to the patient for sharing ...
and (3) promote integration with advanced third-party services (e.g., risk prediction for chronic diseases) that require access to the patient's health data. ...
The development of the hypertension prediction model is performed in two steps: training and testing. This study used panels 17, 18, and 19, which were conducted from 2012 to 2015. ...
doi:10.3390/info11110512
fatcat:33ofmp6t7bcqfm3hro36jjxztu
Public standards and patients' control: how to keep electronic medical records accessible but private Commentary: Open approaches to electronic patient records Commentary: A patient's viewpoint
2001
BMJ (Clinical Research Edition)
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We describe how such systems could be developed and used clinically. ...
A patient's medical records are generally fragmented across multiple treatment sites, posing an obstacle to clinical care, research, and public health efforts. 1 Electronic medical records and the internet ...
), local retail pharmacies, attorneys, and others. 6
Doctrines for developing electronic medical records We propose two doctrines to guide the development of electronic medical records: firstly, that ...
doi:10.1136/bmj.322.7281.283
pmid:11157533
pmcid:PMC1119527
fatcat:y7fcdqin5racji6i37ds7277wq
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