Promise and challenges of big data analytics in healthcare

2^nd International Conference on Health Informatics and Technology

July 27-29, 2015 Valencia, Spain

Anjali Shah and Dinesh Mital

Posters-Accepted Abstracts: J Health Med Informat

Abstract :

Healthcare industry has traditionally been data intensive driven by record keeping needs for patient care, provider reimbursement, regulatory and compliance requirements. Although much of the data has existed in paper form, last decade has seen a major transformation leading to rapid digitization of records. Government health reforms are pushing for adoption of interoperable electronic health records to make stored data exchangeable, usable, searchable, and actionable by the healthcare sector as a whole. Major sources of healthcare data include clinical and administrative data from EHRs, data from registries, monitoring tools, wearable devices, social media, news feeds, and articles from medical journals among others. These massive amounts of electronic health data sets, referred to as �??big data�?� in healthcare are complex, fragmented and difficult (or impossible) to manage effectively with traditional data analysis techniques and tools. By harnessing the power of big data analytical methods, there is tremendous potential to take advantage of the data explosion to deliver more effective patient care and reduce costs. Big data analytical methods leverage modern age computing horsepower, distributed processing and advanced visualization for processing real-time transactional, structured and unstructured data to discover associations, identify trends and patterns within the data to make better informed decisions and predictions. However, it is still an emerging healthcare field and several challenges must be addressed to accelerate its maturity and widespread adoption. These challenges include addressing privacy, security, and quality assurance concerns using available opensource platforms, addressing issues of data ownership, lack of standardization, and need for data governance.

Biography :

Anjali Shah received her PhD in Biomedical Informatics from Rutgers University. She has served as Assistant Professor and Program Director in the department of Health Information Management at Temple University. She is currently a Visiting Scholar in the School of Health Related Professions at Rutgers University. She has over ten years of experience in software development in different industries including telecommunications, finance and health care. She has led and delivered several projects, including electronic health record (EHR) system at Rutgers School of Dental Medicine.