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Consumer Health Vocabulary

Ans Rensen, Margo M van Mol, Ilse Menheere, Marjan D Nijkamp, Ellen Verhoogt, Bea Maris, Willeke Manders, Lilian Vloet, Lisbeth Verharen
BACKGROUND: The quality standards of the Dutch Society of Intensive Care require monitoring of the satisfaction of patient's relatives with respect to care. Currently, no suitable instrument is available in the Netherlands to measure this. This study describes the development and psychometric evaluation of the questionnaire-based Consumer Quality Index 'Relatives in Intensive Care Unit' (CQI 'R-ICU'). The CQI 'R-ICU' measures the perceived quality of care from the perspective of patients' relatives, and identifies aspects of care that need improvement...
January 24, 2017: BMC Health Services Research
Jinying Chen, Jiaping Zheng, Hong Yu
BACKGROUND: Many health organizations allow patients to access their own electronic health record (EHR) notes through online patient portals as a way to enhance patient-centered care. However, EHR notes are typically long and contain abundant medical jargon that can be difficult for patients to understand. In addition, many medical terms in patients' notes are not directly related to their health care needs. One way to help patients better comprehend their own notes is to reduce information overload and help them focus on medical terms that matter most to them...
November 30, 2016: JMIR Medical Informatics
Min Sook Park, Zhe He, Zhiwei Chen, Sanghee Oh, Jiang Bian
BACKGROUND: The widely known terminology gap between health professionals and health consumers hinders effective information seeking for consumers. OBJECTIVE: The aim of this study was to better understand consumers' usage of medical concepts by evaluating the coverage of concepts and semantic types of the Unified Medical Language System (UMLS) on diabetes-related postings in 2 types of social media: blogs and social question and answer (Q&A). METHODS: We collected 2 types of social media data: (1) a total of 3711 blogs tagged with "diabetes" on Tumblr posted between February and October 2015; and (2) a total of 58,422 questions and associated answers posted between 2009 and 2014 in the diabetes category of Yahoo! Answers...
November 24, 2016: JMIR Medical Informatics
Danielle L Mowery, Brett R South, Lee Christensen, Jianwei Leng, Laura-Maria Peltonen, Sanna Salanterä, Hanna Suominen, David Martinez, Sumithra Velupillai, Noémie Elhadad, Guergana Savova, Sameer Pradhan, Wendy W Chapman
BACKGROUND: The ShARe/CLEF eHealth challenge lab aims to stimulate development of natural language processing and information retrieval technologies to aid patients in understanding their clinical reports. In clinical text, acronyms and abbreviations, also referenced as short forms, can be difficult for patients to understand. For one of three shared tasks in 2013 (Task 2), we generated a reference standard of clinical short forms normalized to the Unified Medical Language System. This reference standard can be used to improve patient understanding by linking to web sources with lay descriptions of annotated short forms or by substituting short forms with a more simplified, lay term...
2016: Journal of Biomedical Semantics
Shi-Heng Wang, Yijun Ding, Weizhong Zhao, Yung-Hsiang Huang, Roger Perkins, Wen Zou, James J Chen
BACKGROUND: Both adolescent substance use and adolescent depression are major public health problems, and have the tendency to co-occur. Thousands of articles on adolescent substance use or depression have been published. It is labor intensive and time consuming to extract huge amounts of information from the cumulated collections. Topic modeling offers a computational tool to find relevant topics by capturing meaningful structure among collections of documents. METHODS: In this study, a total of 17,723 abstracts from PubMed published from 2000 to 2014 on adolescent substance use and depression were downloaded as objects, and Latent Dirichlet allocation (LDA) was applied to perform text mining on the dataset...
March 19, 2016: BMC Public Health
Cui Tao, Yongqun He, Sivaram Arabandi
The "Vaccine and Drug Ontology Studies" (VDOS) international workshop series focuses on vaccine- and drug-related ontology modeling and applications. Drugs and vaccines have been critical to prevent and treat human and animal diseases. Work in both (drugs and vaccines) areas is closely related - from preclinical research and development to manufacturing, clinical trials, government approval and regulation, and post-licensure usage surveillance and monitoring. Over the last decade, tremendous efforts have been made in the biomedical ontology community to ontologically represent various areas associated with vaccines and drugs - extending existing clinical terminology systems such as SNOMED, RxNorm, NDF-RT, and MedDRA, developing new models such as the Vaccine Ontology (VO) and Ontology of Adverse Events (OAE), vernacular medical terminologies such as the Consumer Health Vocabulary (CHV)...
2016: Journal of Biomedical Semantics
Chaitanya Shivade, Pranav Malewadkar, Eric Fosler-Lussier, Albert M Lai
The second track of the 2014 i2b2 challenge asked participants to automatically identify risk factors for heart disease among diabetic patients using natural language processing techniques for clinical notes. This paper describes a rule-based system developed using a combination of regular expressions, concepts from the Unified Medical Language System (UMLS), and freely-available resources from the community. With a performance (F1=90.7) that is significantly higher than the median (F1=87.20) and close to the top performing system (F1=92...
December 2015: Journal of Biomedical Informatics
Yueping Sun, Zhen Hou, Li Hou, Jiao Li
Different groups of audiences in health care: health professionals and health consumers, each have different information needs. Health monographs targeting different audiences are created by leveraging readers' background knowledge. The NCI's Physician Data Query (PDQ®) Cancer Information Summaries provide parallel cancer information and education resources with different target audiences. In this paper, we used targeted audience-specific cancer information PDQs to measure characteristic differences on the element level between audiences...
2015: Studies in Health Technology and Informatics
Josceli Maria Tenório, Ivan Torres Pisa
Studies show a gap between the expressions commonly used by health consumers and health professionals. To bridge this gap, consumer health vocabularies are presented as a solution. The aim of this paper is to describe an on-going project to create a consumer health vocabulary (CHV) in the Brazilian Portuguese language. This project will be developed in three phases: terms extraction and connection to compose a CHV graph structure, human validation, and computacional application development. We expect to make a CHV beta version (including approximately 5,000 valid consumer terms stored in a database graph) available...
2015: Studies in Health Technology and Informatics
Majid Rastegar-Mojarad, Zhan Ye, Daniel Wall, Narayana Murali, Simon Lin
BACKGROUND: Social Media, such as Yelp, provides rich information of consumer experience. Previous studies suggest that Yelp can serve as a new source to study patient experience. However, the lack of a corpus of patient reviews causes a major bottleneck for applying computational techniques. OBJECTIVE: The objective of this study is to create a corpus of patient experience (COPE) and report descriptive statistics to characterize COPE. METHODS: Yelp reviews about health care-related businesses were extracted from the Yelp Academic Dataset...
2015: JMIR Research Protocols
Hugo Leroux, Laurent Lefort
BACKGROUND: There is an increasing recognition of the need for the data capture phase of clinical studies to be improved and for more effective sharing of clinical data. The Health Care and Life Sciences community has embraced semantic technologies to facilitate the integration of health data from electronic health records, clinical studies and pharmaceutical research. This paper explores the integration of clinical study data exchange standards and semantic statistic vocabularies to deliver clinical data as linked data in a format that is easier to enrich with links to complementary data sources and consume by a broad user base...
2015: Journal of Biomedical Semantics
V G Vinod Vydiswaran, Qiaozhu Mei, David A Hanauer, Kai Zheng
Community-generated text corpora can be a valuable resource to extract consumer health vocabulary (CHV) and link them to professional terminologies and alternative variants. In this research, we propose a pattern-based text-mining approach to identify pairs of CHV and professional terms from Wikipedia, a large text corpus created and maintained by the community. A novel measure, leveraging the ratio of frequency of occurrence, was used to differentiate consumer terms from professional terms. We empirically evaluated the applicability of this approach using a large data sample consisting of MedLine abstracts and all posts from an online health forum, MedHelp...
2014: AMIA ... Annual Symposium Proceedings
Carlos Marcos, Arturo González-Ferrer, Mor Peleg, Carlos Cavero
OBJECTIVE: We show how the HL7 Virtual Medical Record (vMR) standard can be used to design and implement a data integrator (DI) component that collects patient information from heterogeneous sources and stores it into a personal health record, from which it can then retrieve data. Our working hypothesis is that the HL7 vMR standard in its release 1 version can properly capture the semantics needed to drive evidence-based clinical decision support systems. MATERIALS AND METHODS: To achieve seamless communication between the personal health record and heterogeneous data consumers, we used a three-pronged approach...
May 2015: Journal of the American Medical Informatics Association: JAMIA
Altug Akay, Andrei Dragomir, Björn-Erik Erlandsson
A novel data mining method was developed to gauge the experience of the drug Sitagliptin (trade name Januvia) by patients with diabetes mellitus type 2. To this goal, we devised a two-step analysis framework. Initial exploratory analysis using self-organizing maps was performed to determine structures based on user opinions among the forum posts. The results were a compilation of user's clusters and their correlated (positive or negative) opinion of the drug. Subsequent modeling using network analysis methods was used to determine influential users among the forum members...
January 2015: IEEE Journal of Biomedical and Health Informatics
Alexander S Fiksdal, Ashok Kumbamu, Ashutosh S Jadhav, Cristian Cocos, Laurie A Nelsen, Jyotishman Pathak, Jennifer B McCormick
BACKGROUND: The Internet is a common resource that patients and consumers use to access health-related information. Multiple practical, cultural, and socioeconomic factors influence why, when, and how people utilize this tool. Improving the delivery of health-related information necessitates a thorough understanding of users' searching-related needs, preferences, and experiences. Although a wide body of quantitative research examining search behavior exists, qualitative approaches have been under-utilized and provide unique perspectives that may prove useful in improving the delivery of health information over the Internet...
2014: Journal of Medical Internet Research
Ashutosh Jadhav, Stephen Wu, Amit Sheth, Jyotishman Pathak
The objective of this study is to understand the types of health information (health topics) that users search online for Cardiovascular Diseases, by performing categorization of health search queries (from using UMLS Metamap based on UMLS concepts and semantic types.
2014: Studies in Health Technology and Informatics
Till Plumbaum, Sascha Narr, Elif Eryilmaz, Frank Hopfgartner, Funda Klein-Ellinghaus, Anna Reese, Sahin Albayrak
Finding health-related content is not an easy task. People have to know what to search for, which medical terms to use, and where to find accurate information. This task becomes even harder when people such as immigrants wish to find information in their country of residence and do not speak the national language very well. In this paper, we present a new health information system that allows users to search for health information using natural language queries composed of multiple languages. We present the technical details of the system and outline the results of a preliminary user study to demonstrate the usability of the system...
2014: Studies in Health Technology and Informatics
Fabrizio Pecoraro, Daniela Luzi, Fabrizio L Ricci
This paper proposes a conceptual framework to design a dimensional model based on the HL7 Clinical Document Architecture (CDA) standard. The adoption of this framework can represent a possible solution to facilitate the integration of heterogeneous information systems in a clinical data warehouse. This can simplify the Extract, Transform and Load (ETL) procedures that are considered the most time-consuming and expensive part of the data warehouse development process. The paper describes the main activities to be carried out to design the dimensional model outlining the main advantages in the application of the proposed framework...
2014: Studies in Health Technology and Informatics
Altug Akay, Andrei Dragomir, Bjorn-Erik Erlandsson
Intelligently extracting knowledge from social media has recently attracted great interest from the Biomedical and Health Informatics community to simultaneously improve healthcare outcomes and reduce costs using consumer-generated opinion. We propose a two-step analysis framework that focuses on positive and negative sentiment, as well as the side effects of treatment, in users' forum posts, and identifies user communities (modules) and influential users for the purpose of ascertaining user opinion of cancer treatment...
January 2015: IEEE Journal of Biomedical and Health Informatics
Tae-Min Song, Hyeoun-Ae Park, Dal-Lae Jin
OBJECTIVES: The aim of the study was to develop a metadata and ontology-based health information search engine ensuring semantic interoperability to collect and provide health information using different application programs. METHODS: Health information metadata ontology was developed using a distributed semantic Web content publishing model based on vocabularies used to index the contents generated by the information producers as well as those used to search the contents by the users...
April 2014: Healthcare Informatics Research
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