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Popul Health Manag ; 23(5): 350-360, 2020 10.
Article in English | MEDLINE | ID: mdl-32897820

ABSTRACT

Given the severe and rapid impact of COVID-19, the pace of information sharing has been accelerated. However, traditional methods of disseminating and digesting medical information can be time-consuming and cumbersome. In a pilot study, the authors used social listening to quickly extract information from social media channels to explore what people with COVID-19 are talking about regarding symptoms and disease progression. The goal was to determine whether, by amplifying patient voices, new information could be identified that might have been missed through other sources. Two data sets from social media groups of people with or presumed to have COVID-19 were analyzed: a Facebook group poll, and conversation data from a Reddit group including detailed disease natural history-like posts. Content analysis and a customized analytics engine that incorporates machine learning and natural language processing were used to quickly identify symptoms mentioned. Key findings include more than 20 symptoms in the data sets that were not listed in online lists of symptoms from 4 respected medical information sources. The disease natural history-like posts revealed that people can experience symptoms for many weeks and that some symptoms change over time. This study demonstrates that social media can offer novel insights into patient experiences as a source of real-world data. This inductive research approach can quickly generate descriptive information that can be used to develop hypotheses and new research questions. Also, the method allows rapid assessments of large numbers of social media conversations that could be applied to monitor public health for emerging and rapidly spreading diseases such as COVID-19.


Subject(s)
Coronavirus Infections/physiopathology , Disease Progression , Information Dissemination/methods , Medical Informatics/statistics & numerical data , Pandemics/statistics & numerical data , Pneumonia, Viral/physiopathology , Social Media/statistics & numerical data , COVID-19 , Coronavirus Infections/epidemiology , Data Analysis , Female , Humans , Male , Pilot Projects , Pneumonia, Viral/epidemiology , Public Health , Severity of Illness Index , United States
3.
Am J Med Genet A ; 182(1): 257-267, 2020 01.
Article in English | MEDLINE | ID: mdl-31769173

ABSTRACT

"An International Meeting on Wolf-Hirschhorn Syndrome (WHS)" was held at The University Hospital La Paz in Madrid, Spain (October 13-14, 2017). One hundred and twenty-five people, including physicians, scientists and affected families, attended the meeting. Parent and patient advocates from the Spanish Association of WHS opened the meeting with a panel discussion to set the stage regarding their hopes and expectations for therapeutic advances. In keeping with the theme on therapeutic development, the sessions followed a progression from description of the phenotype and definition of therapeutic endpoints, to definition of genomic changes. These proceedings will review the major points of discussion.


Subject(s)
Chromosomes, Human, Pair 4/immunology , Developmental Disabilities/genetics , Seizures/genetics , Wolf-Hirschhorn Syndrome/genetics , Chromosome Deletion , Chromosomes, Human, Pair 4/genetics , Developmental Disabilities/epidemiology , Developmental Disabilities/pathology , Female , Humans , Phenotype , Seizures/epidemiology , Seizures/therapy , Spain/epidemiology , Wolf-Hirschhorn Syndrome/epidemiology , Wolf-Hirschhorn Syndrome/therapy
4.
Mol Genet Genomic Med ; 7(7): e00551, 2019 07.
Article in English | MEDLINE | ID: mdl-31115190

ABSTRACT

PURPOSE: To assess clinical chromosomal microarray (CMA) genomic testing reports for the following: (a) usage of reporting elements consistent with 2011 ACMG guidelines and other elements identified in the primary literature, (b) information quality, and (c) readability. METHODS: We retrospectively analyzed genomic testing reports from 2011 to 2016 provided to, or by our laboratory to aid in clinical detection and interpretation of copy number variants. Analysis was restricted to the following sections: interpretation, recommendations, limitations, and citations. Analysis included descriptive characteristics, reporting elements, reading difficulty using the Simple Measure of Gobbledygook (SMOG), and quality ratings using a subset of questions adapted from the DISCERN-Genetics questionnaire. RESULTS: The analysis included 44 unique reports from 26 laboratories comprising four groups: specialty laboratories (SL; N = 9), reference laboratories (RL; N = 12), hospital laboratories (HL; N = 10), and university-based laboratories (UL; N = 13). There were 23 abnormal/pathogenic reports and 21 of uncertain/unknown significance. Nine laboratories did not include one or more pieces of information based on ACMG guidelines; only one of ten laboratories reported condition-specific management/treatment information when available and relevant. Average quality ratings and readability scores were not significantly different between laboratory types or result classification. CONCLUSIONS: Reporting practices for most report elements varied widely; however, readability and quality did not differ significantly between laboratory types. Management and treatment information, even for well-known conditions, are rarely included. Effectively communicating test results may be improved if certain reporting elements are incorporated. Recommendations to improve laboratory reports are provided.


Subject(s)
Genetic Testing , Laboratories/standards , DNA Copy Number Variations , Guidelines as Topic , Humans , Retrospective Studies
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