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MAV-clic: management, analysis, and visualization of clinical data
OBJECTIVES: Develop a multifunctional analytics platform for efficient management and analysis of healthcare data. MATERIALS AND METHODS: Management, Analysis, and Visualization of Clinical Data (MAV-clic) is a Health Insurance Portability and Accountability Act of 1996 (HIPAA)-compliant framework b...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6951942/ https://www.ncbi.nlm.nih.gov/pubmed/31984341 http://dx.doi.org/10.1093/jamiaopen/ooy052 |
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author | Ahmed, Zeeshan Kim, Minjung Liang, Bruce T |
author_facet | Ahmed, Zeeshan Kim, Minjung Liang, Bruce T |
author_sort | Ahmed, Zeeshan |
collection | PubMed |
description | OBJECTIVES: Develop a multifunctional analytics platform for efficient management and analysis of healthcare data. MATERIALS AND METHODS: Management, Analysis, and Visualization of Clinical Data (MAV-clic) is a Health Insurance Portability and Accountability Act of 1996 (HIPAA)-compliant framework based on the Butterfly Model. MAV-clic extracts, cleanses, and encrypts data then restructures and aggregates data in a deidentified format. A graphical user interface allows query, analysis, and visualization of clinical data. RESULTS: MAV-clic manages healthcare data for over 800 000 subjects at UConn Health. Three analytic capabilities of MAV-clic include: creating cohorts based on specific criteria; performing measurement analysis of subjects with a specific diagnosis and medication; and calculating measure outcomes of subjects over time. DISCUSSION: MAV-clic supports clinicians and healthcare analysts by efficiently stratifying subjects to understand specific scenarios and optimize decision making. CONCLUSION: MAV-clic is founded on the scientific premise that to improve the quality and transition of healthcare, integrative platforms are necessary to analyze heterogeneous clinical, epidemiological, metabolomics, proteomics, and genomics data for precision medicine. |
format | Online Article Text |
id | pubmed-6951942 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-69519422020-01-24 MAV-clic: management, analysis, and visualization of clinical data Ahmed, Zeeshan Kim, Minjung Liang, Bruce T JAMIA Open Database Notes OBJECTIVES: Develop a multifunctional analytics platform for efficient management and analysis of healthcare data. MATERIALS AND METHODS: Management, Analysis, and Visualization of Clinical Data (MAV-clic) is a Health Insurance Portability and Accountability Act of 1996 (HIPAA)-compliant framework based on the Butterfly Model. MAV-clic extracts, cleanses, and encrypts data then restructures and aggregates data in a deidentified format. A graphical user interface allows query, analysis, and visualization of clinical data. RESULTS: MAV-clic manages healthcare data for over 800 000 subjects at UConn Health. Three analytic capabilities of MAV-clic include: creating cohorts based on specific criteria; performing measurement analysis of subjects with a specific diagnosis and medication; and calculating measure outcomes of subjects over time. DISCUSSION: MAV-clic supports clinicians and healthcare analysts by efficiently stratifying subjects to understand specific scenarios and optimize decision making. CONCLUSION: MAV-clic is founded on the scientific premise that to improve the quality and transition of healthcare, integrative platforms are necessary to analyze heterogeneous clinical, epidemiological, metabolomics, proteomics, and genomics data for precision medicine. Oxford University Press 2018-12-29 /pmc/articles/PMC6951942/ /pubmed/31984341 http://dx.doi.org/10.1093/jamiaopen/ooy052 Text en © The Author(s) 2018. Published by Oxford University Press on behalf of the American Medical Informatics Association. http://creativecommons.org/licenses/by-nc/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com |
spellingShingle | Database Notes Ahmed, Zeeshan Kim, Minjung Liang, Bruce T MAV-clic: management, analysis, and visualization of clinical data |
title | MAV-clic: management, analysis, and visualization of clinical data |
title_full | MAV-clic: management, analysis, and visualization of clinical data |
title_fullStr | MAV-clic: management, analysis, and visualization of clinical data |
title_full_unstemmed | MAV-clic: management, analysis, and visualization of clinical data |
title_short | MAV-clic: management, analysis, and visualization of clinical data |
title_sort | mav-clic: management, analysis, and visualization of clinical data |
topic | Database Notes |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6951942/ https://www.ncbi.nlm.nih.gov/pubmed/31984341 http://dx.doi.org/10.1093/jamiaopen/ooy052 |
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