Big data in healthcare: management, analysis and future prospects
Open accessAbstract
‘Big data’ is massive amounts of information that can work wonders. It has become a topic of special interest for the past two decades because of a great potential that is hidden in it. Various public and private sector industries generate, store, and analyze big data with an aim to improve the services they provide. In the healthcare industry, various sources for big data include hospital records, medical records of patients, results of medical examinations, and devices that are a part of internet of things. Biomedical research also generates a significant portion of big data relevant to public healthcare. This data requires proper management and analysis in order to derive meaningful information. Otherwise, seeking solution by analyzing big data quickly becomes comparable to finding a needle in the haystack. There are various challenges associated with each step of handling big data which can only be surpassed by using high-end computing solutions for big data analysis. That is why, to provide relevant solutions for improving public health, healthcare providers are required to be fully equipped with appropriate infrastructure to systematically generate and analyze big data. An efficient management, analysis, and interpretation of big data can change the game by opening new avenues for modern healthcare. That is exactly why various industries, including the healthcare industry, are taking vigorous steps to convert this potential into better services and financial advantages. With a strong integration of biomedical and healthcare data, modern healthcare organizations can possibly revolutionize the medical therapies and personalized medicine.
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At present, annually, health care systems collect enormous amounts of patient care data that remain disparate and disconnected from one another.
“At present, annually, health care systems collect enormous amounts of patient care data that remain disparate and disconnected from one another [29].”
From Reimagining Core Entrustable Professional Activities for Undergraduate Medical Education in the Era of Artificial Intelligence (2023) · cites this paper as [29]
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- Authors
- Dash, S., Shakyawar, S. K., Sharma, M., & Kaushik, S.
- Affiliations
- Weill Cornell Medicine (US)
- SilicoLife (Portugal) (PT)
- Jagiellonian University (PL)
- 3B's Research Group (PT)
- Corresponding author
- Kaushik, Sandeep
- Venue
- Journal of Big Data
- Published
- 2019-06-19
- Volume
- 6
- Issue
- 1
- ISSN
- 2196-1115 (ISSN-L)
- OpenAlex
- W2951635356
- Cited by
- 1,747
- References
- 47
- Citations by year
- 2026: 129 · 2025: 301 · 2024: 399 · 2023: 409 · 2022: 252 · 2021: 188 · 2020: 66 · 2019: 3
- FWCI
- 150.93
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Locations
- Journal Of Big Data (publishedVersion, cc-by)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Portuguese National Funding Agency for Science, Research and Technology (RCAAP Project by FCT) (submittedVersion, cc-by)
- Portuguese National Funding Agency for Science, Research and Technology (RCAAP Project by FCT) (submittedVersion, cc-by-nc-nd)
- Topics
- Social Sciences › Decision Sciences › Information Systems and Management › Big Data Technologies and Applications
- Health Sciences › Health Professions › Health Information Management › Artificial Intelligence in Healthcare
- Health Sciences › Medicine › Health Informatics › Artificial Intelligence in Healthcare and Education
- Keywords
- big data in healthcare, health data management, big data analytics, medical records, hospital records, Internet of Things, biomedical research data, high-performance computing, health infrastructure, personalized medicine
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