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Bernardi FA, Alves D, Crepaldi N, Yamada DB, Lima VC, Rijo R. Data Quality in Health Research: Integrative Literature Review. J Med Internet Res 2023; 25:e41446. [PMID: 37906223 PMCID: PMC10646672 DOI: 10.2196/41446] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/18/2022] [Revised: 04/18/2023] [Accepted: 07/14/2023] [Indexed: 11/02/2023] Open
Abstract
BACKGROUND Decision-making and strategies to improve service delivery must be supported by reliable health data to generate consistent evidence on health status. The data quality management process must ensure the reliability of collected data. Consequently, various methodologies to improve the quality of services are applied in the health field. At the same time, scientific research is constantly evolving to improve data quality through better reproducibility and empowerment of researchers and offers patient groups tools for secured data sharing and privacy compliance. OBJECTIVE Through an integrative literature review, the aim of this work was to identify and evaluate digital health technology interventions designed to support the conducting of health research based on data quality. METHODS A search was conducted in 6 electronic scientific databases in January 2022: PubMed, SCOPUS, Web of Science, Institute of Electrical and Electronics Engineers Digital Library, Cumulative Index of Nursing and Allied Health Literature, and Latin American and Caribbean Health Sciences Literature. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses checklist and flowchart were used to visualize the search strategy results in the databases. RESULTS After analyzing and extracting the outcomes of interest, 33 papers were included in the review. The studies covered the period of 2017-2021 and were conducted in 22 countries. Key findings revealed variability and a lack of consensus in assessing data quality domains and metrics. Data quality factors included the research environment, application time, and development steps. Strategies for improving data quality involved using business intelligence models, statistical analyses, data mining techniques, and qualitative approaches. CONCLUSIONS The main barriers to health data quality are technical, motivational, economical, political, legal, ethical, organizational, human resources, and methodological. The data quality process and techniques, from precollection to gathering, postcollection, and analysis, are critical for the final result of a study or the quality of processes and decision-making in a health care organization. The findings highlight the need for standardized practices and collaborative efforts to enhance data quality in health research. Finally, context guides decisions regarding data quality strategies and techniques. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID) RR2-10.1101/2022.05.31.22275804.
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Affiliation(s)
| | - Domingos Alves
- Ribeirão Preto School of Medicine, University of Sao Paulo, Ribeirão Preto, Brazil
| | - Nathalia Crepaldi
- Ribeirão Preto School of Medicine, University of Sao Paulo, Ribeirão Preto, Brazil
| | - Diego Bettiol Yamada
- Ribeirão Preto School of Medicine, University of Sao Paulo, Ribeirão Preto, Brazil
| | - Vinícius Costa Lima
- Ribeirão Preto School of Medicine, University of Sao Paulo, Ribeirão Preto, Brazil
| | - Rui Rijo
- Ribeirão Preto School of Medicine, University of Sao Paulo, Ribeirão Preto, Brazil
- Polytechnic Institute of Leiria, Leiria, Portugal
- Institute for Systems and Computers Engineering, Coimbra, Portugal
- Center for Research in Health Technologies and Services, Porto, Portugal
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Kamminga NCW, Wakkee M, De Bruin RJ, van der Veldt AAM, Joosse A, Reeder SWI, Plaisier PW, Nijsten T, Lugtenberg M. Oncological healthcare providers' perspectives on appropriate melanoma survivorship care: a qualitative focus group study. BMC Cancer 2023; 23:278. [PMID: 36973713 PMCID: PMC10042579 DOI: 10.1186/s12885-023-10759-9] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/03/2022] [Accepted: 03/21/2023] [Indexed: 03/29/2023] Open
Abstract
BACKGROUND The increasing group of melanoma survivors reports multiple unmet needs regarding survivorship care (SSC). To optimise melanoma SSC, it is crucial to take into account the perspectives of oncological healthcare providers (HCPs) in addition to those of patients. The aim of this study is to gain an in-depth understanding of HCPs' perspectives on appropriate melanoma SSC. METHODS Four online focus groups were conducted with mixed samples of oncological HCPs (dermatologists, surgeons, oncologists, oncological nurse practitioners, support counsellors and general practitioners) (total n = 23). A topic guide was used to structure the discussions, focusing on perspectives on both SSC and survivorship care plans (SCPs). All focus groups were recorded, transcribed verbatim, and subjected to an elaborate thematic content analysis. RESULTS Regarding SSC, HCPs considered the current offer minimal and stressed the need for broader personalised SSC from diagnosis onwards. Although hardly anyone was familiar with SCPs, they perceived various potential benefits of SCPs, such as an increase in the patients' self-management and providing HCPs with an up-to-date overview of the patient's situation. Perceived preconditions for successful implementation included adequate personalisation, integration in the electronic health record and ensuring adequate funding to activate and provide timely updates. CONCLUSIONS According to HCPs there is considerable room for improvement in terms of melanoma SSC. SCPs can assist in offering personalised and broader i.e., including psychosocial SSC. Aside from personalisation, efforts should be focused on SCPs' integration in clinical practice, and their long-term maintenance.
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Affiliation(s)
- Nadia C W Kamminga
- Department of Dermatology, Erasmus MC Cancer Institute, University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - Marlies Wakkee
- Department of Dermatology, Erasmus MC Cancer Institute, University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - Rianne J De Bruin
- Department of Dermatology, Erasmus MC Cancer Institute, University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - Astrid A M van der Veldt
- Department of Medical Oncology, Erasmus MC Cancer Institute, University Medical Center Rotterdam, Rotterdam, The Netherlands
- Department of Radiology & Nuclear Medicine, Erasmus MC Cancer Institute, University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - Arjen Joosse
- Department of Medical Oncology, Erasmus MC Cancer Institute, University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - Suzan W I Reeder
- Department of Dermatology, Albert Schweitzer Hospital, Dordrecht, The Netherlands
| | - Peter W Plaisier
- Department of Surgical Oncology, Albert Schweitzer Hospital, Dordrecht, The Netherlands
| | - Tamar Nijsten
- Department of Dermatology, Erasmus MC Cancer Institute, University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - Marjolein Lugtenberg
- Department of Dermatology, Erasmus MC Cancer Institute, University Medical Center Rotterdam, Rotterdam, The Netherlands.
- Department Tranzo, Tilburg School of Social and Behavioral Sciences, Tilburg University, Tilburg, The Netherlands.
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Guo H, Scriney M, Liu K. An Ostensive Information Architecture to Enhance Semantic Interoperability for Healthcare Information Systems. INFORMATION SYSTEMS FRONTIERS : A JOURNAL OF RESEARCH AND INNOVATION 2023:1-24. [PMID: 37361885 PMCID: PMC9974391 DOI: 10.1007/s10796-023-10379-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Accepted: 02/13/2023] [Indexed: 06/28/2023]
Abstract
Semantic interoperability establishes intercommunications and enables data sharing across disparate systems. In this study, we propose an ostensive information architecture for healthcare information systems to decrease ambiguity caused by using signs in different contexts for different purposes. The ostensive information architecture adopts a consensus-based approach initiated from the perspective of information systems re-design and can be applied to other domains where information exchange is required between heterogeneous systems. Driven by the issues in FHIR (Fast Health Interoperability Resources) implementation, an ostensive approach that supplements the current lexical approach in semantic exchange is proposed. A Semantic Engine with an FHIR knowledge graph as the core is constructed using Neo4j to provide semantic interpretation and examples. The MIMIC III (Medical Information Mart for Intensive Care) datasets and diabetes datasets have been employed to demonstrate the effectiveness of the proposed information architecture. We further discuss the benefits of the separation of semantic interpretation and data storage from the perspective of information system design, and the semantic reasoning towards patient-centric care underpinned by the Semantic Engine.
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Affiliation(s)
- Hua Guo
- School of Electronic Engineering and Computer Science, Queen Mary University of London, London, UK
- Insight Centre for Data Analytics, School of Computing, Dublin City University, Dublin, Ireland
- Informatics Research Centre, University of Reading, Reading, UK
| | - Michael Scriney
- School of Electronic Engineering and Computer Science, Queen Mary University of London, London, UK
- Insight Centre for Data Analytics, School of Computing, Dublin City University, Dublin, Ireland
- Informatics Research Centre, University of Reading, Reading, UK
| | - Kecheng Liu
- School of Electronic Engineering and Computer Science, Queen Mary University of London, London, UK
- Insight Centre for Data Analytics, School of Computing, Dublin City University, Dublin, Ireland
- Informatics Research Centre, University of Reading, Reading, UK
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Entity linking and API resource-based matchmaking for Web APIs composition. SERVICE ORIENTED COMPUTING AND APPLICATIONS 2022. [DOI: 10.1007/s11761-022-00353-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/13/2022]
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Shen L, Shi W, Cai L, An J, Ling Q. Discuss the Application of Data Services in Data Health Management of High-Risk Pregnant and Lying-In Women in Smart Medical Care. SCANNING 2022; 2022:5957697. [PMID: 36082174 PMCID: PMC9436624 DOI: 10.1155/2022/5957697] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 07/05/2022] [Revised: 08/06/2022] [Accepted: 08/16/2022] [Indexed: 06/15/2023]
Abstract
Objective In order to improve the refined management of hospitals, promote the scientific development of smart hospitals in medical institutions, and solve the problem of data filling and reporting that is increasing year by year in the country, province, and city. Methods A total of 84 high-risk pregnant women admitted to our hospital from January 2020 to October 2021 were selected and screened for high-risk pregnant women. Risk pregnant women were divided into a routine intervention group and a DS medical group, with 42 cases in each group. High-risk pregnant women in the routine intervention group received routine intervention, and the DS medical group applied data to serve smart medical services on the basis of routine intervention. The scores of self-care, anxiety, and depression were compared between the two groups, the coping styles were analyzed, the satisfaction rate and incidence of adverse conditions of the high-risk puerperae were recorded, and the delivery methods of the two groups were compared. Results After the intervention, the activities of daily living, follow-up, fetal monitoring, and self-protection behaviors in the DS medical group were higher than those in the routine intervention group, and the difference was statistically significant (P < 0.05). The scores of anxiety and depression in the group were lower, with statistical significance (P < 0.05); after the intervention, the scores of negative coping styles in the DS medical group were lower than those in the conventional intervention group, while the scores for positive coping styles were higher than those in the conventional intervention group; the DS medical group had higher risk. The satisfaction of pregnant women was significantly higher than that of the routine intervention group, and the difference was statistically significant (P < 0.05); the overall incidence of adverse maternal outcomes among high-risk pregnant women in the DS medical group was lower than that of the routine intervention group, and the difference was not statistically significant (P > 0.05). Compared with the routine group, the DS medical group had a higher number of vaginal deliveries and a lower number of cesarean deliveries, and the difference was statistically significant (P < 0.05). Conclusion The application of data services in a smart medical high-risk maternity-related data management platform enables the promotion of high-risk pregnant women's self-care behaviors and improves negative emotions, enables them to cooperate in delivery with positive behaviors, and reduces the number of cases of cesarean delivery.
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Affiliation(s)
- Leifen Shen
- Maternity Group Healthcare Department, Huzhou Maternity & Child Health Care Hospital, Huzhou, Zhejiang 313000, China
| | - Weiqin Shi
- Healthcare Department, Huzhou Maternity & Child Health Care Hospital, Huzhou, Zhejiang 313000, China
| | - Liwen Cai
- Maternity Group Healthcare Department, Huzhou Maternity & Child Health Care Hospital, Huzhou, Zhejiang 313000, China
| | - Jing An
- Child Group Health Department, Huzhou Maternity & Child Health Care Hospital, Huzhou, Zhejiang 313000, China
| | - Qian Ling
- Obstetrics and Gynecology Department, Huzhou Maternity & Child Health Care Hospital, Huzhou, Zhejiang 313000, China
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Zhang H, Lyu T, Yin P, Bost S, He X, Guo Y, Prosperi M, Hogan WR, Bian J. A scoping review of semantic integration of health data and information. Int J Med Inform 2022; 165:104834. [PMID: 35863206 DOI: 10.1016/j.ijmedinf.2022.104834] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/21/2022] [Revised: 07/06/2022] [Accepted: 07/13/2022] [Indexed: 11/25/2022]
Abstract
OBJECTIVE We summarized a decade of new research focusing on semantic data integration (SDI) since 2009, and we aim to: (1) summarize the state-of-art approaches on integrating health data and information; and (2) identify the main gaps and challenges of integrating health data and information from multiple levels and domains. MATERIALS AND METHODS We used PubMed as our focus is applications of SDI in biomedical domains and followed the Preferred Reporting Items for Systematic Review and Meta-Analyses (PRISMA) to search and report for relevant studies published between January 1, 2009 and December 31, 2021. We used Covidence-a systematic review management system-to carry out this scoping review. RESULTS The initial search from PubMed resulted in 5,326 articles using the two sets of keywords. We then removed 44 duplicates and 5,282 articles were retained for abstract screening. After abstract screening, we included 246 articles for full-text screening, among which 87 articles were deemed eligible for full-text extraction. We summarized the 87 articles from four aspects: (1) methods for the global schema; (2) data integration strategies (i.e., federated system vs. data warehousing); (3) the sources of the data; and (4) downstream applications. CONCLUSION SDI approach can effectively resolve the semantic heterogeneities across different data sources. We identified two key gaps and challenges in existing SDI studies that (1) many of the existing SDI studies used data from only single-level data sources (e.g., integrating individual-level patient records from different hospital systems), and (2) documentation of the data integration processes is sparse, threatening the reproducibility of SDI studies.
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Affiliation(s)
- Hansi Zhang
- Health Outcomes & Biomedical Informatics, College of Medicine, University of Florida, Gainesville, FL, United States
| | - Tianchen Lyu
- Health Outcomes & Biomedical Informatics, College of Medicine, University of Florida, Gainesville, FL, United States
| | - Pengfei Yin
- Health Outcomes & Biomedical Informatics, College of Medicine, University of Florida, Gainesville, FL, United States
| | - Sarah Bost
- Health Outcomes & Biomedical Informatics, College of Medicine, University of Florida, Gainesville, FL, United States
| | - Xing He
- Health Outcomes & Biomedical Informatics, College of Medicine, University of Florida, Gainesville, FL, United States
| | - Yi Guo
- Health Outcomes & Biomedical Informatics, College of Medicine, University of Florida, Gainesville, FL, United States
| | - Mattia Prosperi
- Department of Epidemiology, College of Medicine, University of Florida, Gainesville, FL, United States
| | - Willian R Hogan
- Health Outcomes & Biomedical Informatics, College of Medicine, University of Florida, Gainesville, FL, United States
| | - Jiang Bian
- Health Outcomes & Biomedical Informatics, College of Medicine, University of Florida, Gainesville, FL, United States.
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Zhang S, Bai G, Li H, Liu P, Zhang M, Li S. Multi-Source Knowledge Reasoning for Data-Driven IoT Security. SENSORS 2021; 21:s21227579. [PMID: 34833653 PMCID: PMC8623156 DOI: 10.3390/s21227579] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/30/2021] [Revised: 11/02/2021] [Accepted: 11/11/2021] [Indexed: 11/16/2022]
Abstract
Nowadays, there are different kinds of public knowledge bases for cyber security vulnerability and threat intelligence which can be used for IoT security threat analysis. However, the heterogeneity of these knowledge bases and the complexity of the IoT environments make network security situation awareness and threat assessment difficult. In this paper, we integrate vulnerabilities, weaknesses, affected platforms, tactics, attack techniques, and attack patterns into a coherent set of links. In addition, we propose an IoT security ontology model, namely, the IoT Security Threat Ontology (IoTSTO), to describe the elements of IoT security threats and design inference rules for threat analysis. This IoTSTO expands the current knowledge domain of cyber security ontology modeling. In the IoTSTO model, the proposed multi-source knowledge reasoning method can perform the following tasks: assess the threats of the IoT environment, automatically infer mitigations, and separate IoT nodes that are subject to specific threats. The method above provides support to security managers in their deployment of security solutions. This paper completes the association of current public knowledge bases for IoT security and solves the semantic heterogeneity of multi-source knowledge. In this paper, we reveal the scope of public knowledge bases and their interrelationships through the multi-source knowledge reasoning method for IoT security. In conclusion, the paper provides a unified, extensible, and reusable method for IoT security analysis and decision making.
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Affiliation(s)
- Shuqin Zhang
- School of Computer Science, Zhongyuan University of Technology, Zhengzhou 450007, China; (G.B.); (M.Z.)
- Correspondence:
| | - Guangyao Bai
- School of Computer Science, Zhongyuan University of Technology, Zhengzhou 450007, China; (G.B.); (M.Z.)
| | - Hong Li
- Institute of Information Engineering, Chinese Academy of Sciences, Beijing 100093, China; (H.L.); (P.L.)
| | - Peipei Liu
- Institute of Information Engineering, Chinese Academy of Sciences, Beijing 100093, China; (H.L.); (P.L.)
| | - Minzhi Zhang
- School of Computer Science, Zhongyuan University of Technology, Zhengzhou 450007, China; (G.B.); (M.Z.)
| | - Shujun Li
- School of Information Science and Technology, Yancheng Teachers University, Yancheng 224002, China;
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Calvillo-Arbizu J, Román-Martínez I, Reina-Tosina J. Internet of things in health: Requirements, issues, and gaps. COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE 2021; 208:106231. [PMID: 34186337 DOI: 10.1016/j.cmpb.2021.106231] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/14/2020] [Accepted: 06/02/2021] [Indexed: 06/13/2023]
Abstract
BACKGROUND AND OBJECTIVES The Internet of Things (IoT) paradigm has been extensively applied to several sectors in the last years, ranging from industry to smart cities. In the health domain, IoT makes possible new scenarios of healthcare delivery as well as collecting and processing health data in real time from sensors in order to make informed decisions. However, this domain is complex and presents several technological challenges. Despite the extensive literature about this topic, the application of IoT in healthcare scarcely covers requirements of this sector. METHODS A literature review from January 2010 to February 2021 was performed resulting in 12,108 articles. After filtering by title, abstract, and content, 86 were eligible and examined according to three requirement themes: data lifecycle; trust, security, and privacy; and human-related issues. RESULTS The analysis of the reviewed literature shows that most approaches consider IoT application in healthcare merely as in any other domain (industry, smart cities…), with no regard of the specific requirements of this domain. CONCLUSIONS Future efforts in this matter should be aligned with the specific requirements and needs of the health domain, so that exploiting the capabilities of the IoT paradigm may represent a meaningful step forward in the application of this technology in healthcare.
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Affiliation(s)
- Jorge Calvillo-Arbizu
- Grupo de Ingeniería Biomédica, Universidad de Sevilla, Sevilla 41092, Spain; Departamento de Ingeniería Telemática, Universidad de Sevilla, Spain.
| | | | - Javier Reina-Tosina
- Grupo de Ingeniería Biomédica, Universidad de Sevilla, Sevilla 41092, Spain; Departamento de Teoría de la Señal y las Comunicaciones, Universidad de Sevilla, Spain
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Smart City Ontologies and Their Applications: A Systematic Literature Review. SUSTAINABILITY 2021. [DOI: 10.3390/su13105578] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/25/2022]
Abstract
The increasing interconnections of city services, the explosion of available urban data, and the need for multidisciplinary analysis and decision making for city sustainability require new technological solutions to cope with such complexity. Ontologies have become viable and effective tools to practitioners for developing applications requiring data and process interoperability, big data management, and automated reasoning on knowledge. We investigate how and to what extent ontologies have been used to support smart city services and we provide a comprehensive reference on what problems have been addressed and what has been achieved so far with ontology-based applications. To this purpose, we conducted a systematic literature review finalized to presenting the ontologies, and the methods and technological systems where ontologies play a relevant role in shaping current smart cities. Based on the result of the review process, we also propose a classification of the sub-domains of the city addressed by the ontologies we found, and the research issues that have been considered so far by the scientific community. We highlight those for which semantic technologies have been mostly demonstrated to be effective to enhance the smart city concept and, finally, discuss in more details about some open problems.
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10
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Knott CE, Gomori S, Ngyuen M, Pedrazzani S, Sattaluri S, Mierzwa F, Chantala K. Connecting and linking neurocognitive, digital phenotyping, physiologic, psychophysical, neuroimaging, genomic, & sensor data with survey data. EPJ DATA SCIENCE 2021; 10:9. [PMID: 33614392 PMCID: PMC7880216 DOI: 10.1140/epjds/s13688-021-00264-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 09/10/2020] [Accepted: 02/02/2021] [Indexed: 06/12/2023]
Abstract
Combining survey data with alternative data sources (e.g., wearable technology, apps, physiological, ecological monitoring, genomic, neurocognitive assessments, brain imaging, and psychophysical data) to paint a complete biobehavioral picture of trauma patients comes with many complex system challenges and solutions. Starting in emergency departments and incorporating these diverse, broad, and separate data streams presents technical, operational, and logistical challenges but allows for a greater scientific understanding of the long-term effects of trauma. Our manuscript describes incorporating and prospectively linking these multi-dimensional big data elements into a clinical, observational study at US emergency departments with the goal to understand, prevent, and predict adverse posttraumatic neuropsychiatric sequelae (APNS) that affects over 40 million Americans annually. We outline key data-driven system challenges and solutions and investigate eligibility considerations, compliance, and response rate outcomes incorporating these diverse "big data" measures using integrated data-driven cross-discipline system architecture.
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Affiliation(s)
- Charles E. Knott
- Social, Statistical, and Environmental Sciences, RTI International, Research Triangle Park, NC USA
| | - Stephen Gomori
- Social, Statistical, and Environmental Sciences, RTI International, Research Triangle Park, NC USA
| | - Mai Ngyuen
- Social, Statistical, and Environmental Sciences, RTI International, Research Triangle Park, NC USA
| | - Susan Pedrazzani
- Social, Statistical, and Environmental Sciences, RTI International, Research Triangle Park, NC USA
| | - Sridevi Sattaluri
- Social, Statistical, and Environmental Sciences, RTI International, Research Triangle Park, NC USA
| | - Frank Mierzwa
- Social, Statistical, and Environmental Sciences, RTI International, Research Triangle Park, NC USA
| | - Kim Chantala
- Social, Statistical, and Environmental Sciences, RTI International, Research Triangle Park, NC USA
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Tiwari S, Abraham A. Semantic assessment of smart healthcare ontology. INTERNATIONAL JOURNAL OF WEB INFORMATION SYSTEMS 2020. [DOI: 10.1108/ijwis-05-2020-0027] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
Abstract
PurposeHealth-care ontologies and their terminologies play a vital role in knowledge representation and data integration for health information. In health-care systems, Internet of Technology (IoT) technologies provide data exchange among various entities and ontologies offer a formal description to present the knowledge of health-care domains. These ontologies are advised to assure the quality of their adoption and applicability in the real world.Design/methodology/approachOntology assessment is an integral part of ontology construction and maintenance. It is always performed to identify inconsistencies and modeling errors by the experts during the ontology development. A smart health-care ontology (SHCO) has been designed to deal with health-care information and IoT devices. In this paper, an integrated approach has been proposed to assess the SHCO on different assessment tools such as Themis, Test-Driven Development (TDD)onto, Protégé and OOPs! Several test cases are framed to assess the ontology on these tools, in this research, Themis and TDDonto tools provide the verification for the test cases while Protégé and OOPs! provides validation of modeled knowledge in the ontology.FindingsAs of the best knowledge, no other study has been presented earlier to conduct the integrated assessment on different tools. All test cases are successfully analyzed on these tools and results are drawn and compared with other ontologies.Originality/valueThe developed ontology is analyzed on different verification and validation tools to assure the quality of ontologies.
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A Review of Internet of Things Technologies for Ambient Assisted Living Environments. FUTURE INTERNET 2019. [DOI: 10.3390/fi11120259] [Citation(s) in RCA: 60] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023] Open
Abstract
The internet of things (IoT) aims to extend the internet to real-world objects, connecting smart and sensing devices into a global network infrastructure by connecting physical and virtual objects. The IoT has the potential to increase the quality of life of inhabitants and users of intelligent ambient assisted living (AAL) environments. The paper overviews and discusses the IoT technologies and their foreseen impacts and challenges for the AAL domain. The results of this review are summarized as the IoT based gerontechnology acceptance model for the assisted living domain. The model focuses on the acceptance of new technologies by older people and underscores the need for the adoption of the IoT for the AAL domain.
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Trakadas P, Nomikos N, Michailidis ET, Zahariadis T, Facca FM, Breitgand D, Rizou S, Masip X, Gkonis P. Hybrid Clouds for Data-Intensive, 5G-Enabled IoT Applications: An Overview, Key Issues and Relevant Architecture. SENSORS 2019; 19:s19163591. [PMID: 31426555 PMCID: PMC6721067 DOI: 10.3390/s19163591] [Citation(s) in RCA: 26] [Impact Index Per Article: 5.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/29/2019] [Revised: 08/07/2019] [Accepted: 08/12/2019] [Indexed: 02/05/2023]
Abstract
Hybrid cloud multi-access edge computing (MEC) deployments have been proposed as efficient means to support Internet of Things (IoT) applications, relying on a plethora of nodes and data. In this paper, an overview on the area of hybrid clouds considering relevant research areas is given, providing technologies and mechanisms for the formation of such MEC deployments, as well as emphasizing several key issues that should be tackled by novel approaches, especially under the 5G paradigm. Furthermore, a decentralized hybrid cloud MEC architecture, resulting in a Platform-as-a-Service (PaaS) is proposed and its main building blocks and layers are thoroughly described. Aiming to offer a broad perspective on the business potential of such a platform, the stakeholder ecosystem is also analyzed. Finally, two use cases in the context of smart cities and mobile health are presented, aimed at showing how the proposed PaaS enables the development of respective IoT applications.
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Affiliation(s)
- Panagiotis Trakadas
- General Department, National and Kapodistrian University of Athens, Psahna 34400, Greece.
| | - Nikolaos Nomikos
- Department of Information and Communication Systems Engineering, University of the Aegean, Samos 83200, Greece
| | - Emmanouel T Michailidis
- Department of Electrical and Electronic Engineering, University of West Attica, Aigaleo 12244, Greece
| | - Theodore Zahariadis
- General Department, National and Kapodistrian University of Athens, Psahna 34400, Greece
| | | | - David Breitgand
- IBM Israel, Science and Technology Ltd, Haifa 3498825, Israel
| | | | - Xavi Masip
- CRAAX, Universitat Politecnica de Catalunya, 08800 Vilanova i la Geltru, Spain
| | - Panagiotis Gkonis
- General Department, National and Kapodistrian University of Athens, Psahna 34400, Greece
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