Big data in digital healthcare: lessons learnt and recommendations for general practice.
Springer Science and Business Media LLC
MetadataShow full item record
Agrawal, R., & Prabakaran, S. (2020). Big data in digital healthcare: lessons learnt and recommendations for general practice.. Heredity (Edinb), 124 (4), 525-534. https://doi.org/10.1038/s41437-020-0303-2
Big Data will be an integral part of the next generation of technological developments-allowing us to gain new insights from the vast quantities of data being produced by modern life. There is significant potential for the application of Big Data to healthcare, but there are still some impediments to overcome, such as fragmentation, high costs, and questions around data ownership. Envisioning a future role for Big Data within the digital healthcare context means balancing the benefits of improving patient outcomes with the potential pitfalls of increasing physician burnout due to poor implementation leading to added complexity. Oncology, the field where Big Data collection and utilization got a heard start with programs like TCGA and the Cancer Moon Shot, provides an instructive example as we see different perspectives provided by the United States (US), the United Kingdom (UK) and other nations in the implementation of Big Data in patient care with regards to their centralization and regulatory approach to data. By drawing upon global approaches, we propose recommendations for guidelines and regulations of data use in healthcare centering on the creation of a unique global patient ID that can integrate data from a variety of healthcare providers. In addition, we expand upon the topic by discussing potential pitfalls to Big Data such as the lack of diversity in Big Data research, and the security and transparency risks posed by machine learning algorithms.
Humans, Delivery of Health Care, United States, General Practice, Machine Learning, United Kingdom, Big Data
External DOI: https://doi.org/10.1038/s41437-020-0303-2
This record's URL: https://www.repository.cam.ac.uk/handle/1810/303227
Attribution 4.0 International
Licence URL: https://creativecommons.org/licenses/by/4.0/