MAV-clic: management, analysis, and visualization of clinical data

Author:

Ahmed Zeeshan1ORCID,Kim Minjung2,Liang Bruce T3

Affiliation:

1. Department of Genetics and Genome Sciences, Institute for Systems Genomics, School of Medicine, University of Connecticut Health Center, Farmington, Connecticut, USA

2. The Pat and Jim Calhoun Cardiology Center, School of Medicine, University of Connecticut Health Center, Farmington, Connecticut, USA

3. Ray Neag Distinguished Professor of Cardiovascular Biology and Medicine, Director Pat and Jim Calhoun Cardiology Center, Dean UConn School of Medicine, University of Connecticut Health Center, Farmington, Connecticut, USA

Abstract

AbstractObjectivesDevelop a multifunctional analytics platform for efficient management and analysis of healthcare data.Materials and MethodsManagement, 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.ResultsMAV-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.DiscussionMAV-clic supports clinicians and healthcare analysts by efficiently stratifying subjects to understand specific scenarios and optimize decision making.ConclusionMAV-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.

Funder

Ahmed lab, Genetics and Genome Sciences, School of Medicine, University of Connecticut Health Center

Publisher

Oxford University Press (OUP)

Subject

Health Informatics

Reference29 articles.

1. Big data analytics in healthcare: promise and potential;Raghupathi;Health Information Science and Systems,2014

2. From big data analysis to personalized medicine for all: challenges and opportunities;Alyass;BMC Med Genomics,2015

3. Criteria for the use of omics-based predictors in clinical trials: explanation and elaboration predictors in clinical trials: explanation and elaboration;Nature,2013

4. Computational solutions for omics data;Berger;Nat Rev Genet,2013

5. Problems with health information technology and their effects on care delivery and patient outcomes: a systematic review;Kim;J Am Med Inform Assoc,2017

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