Digital Health and Medical Analytics
The potential benefits to patients and healthcare works are coming into sharp focus as new digital technologies such as big data analytics, artificial intelligence (AI), and machine learning become more widely available.
Digital health, an interdisciplinary convergence of medicine, social science, and digitalisation, is transforming the healthcare landscape by creating a future ecosystem with responsibility, agility, inclusiveness, sustainability and efficiency for high quality of care.
Dr Yichuan Wang
The excitement surrounding the transformational potential of digital innovation in healthcare is growing. The potential benefits to patients and healthcare works are coming into sharp focus as new digital technologies such as big data analytics, artificial intelligence (AI), and machine learning become more widely available. These digital technologies could be effective tools to optimise clinical practices and operations and support public health management and medical research.
However, the adoption of digital technology in health care usually lags behind other industries, as some major technological and managerial obstacles still remain. Obstacles include the lack of healthcare system integration, and health data quality issues. At the same time, there are ethical issues that need to be addressed to protect patient health data. For instance, AI could trigger potential risks for care delivery by devaluing physicians’ skills, dissatisfying transparency standards, underestimating the biases of algorithms, and neglecting the fairness of clinical deployment. Such challenges, if not well addressed, not only can lead to a negative impact on patients but it may also hamper the healthcare organisations’ reputation.
The digital health and medical analytics research stream, led by Dr. Yichuan Wang with research collaboration from University of Bristol, Brandeis University (USA), Kyushu Institute of Technology (Japan), and the First Affiliated Hospital of Zhengzhou University (China), aims to:
- explore how to utilize digital health data to support evidence-based medicine using AI and analytics approaches
- understand how healthcare information systems can operate in a coordinated manner to deliver effective care to patients
- demonstrate how digital technologies can be applied to increase the economic, social, sustainable impact in health care
- address the governance, legal, ethical and privacy issues for the use of digital technology in health care
- Zhai, Y., Wang, Y., Zhang, M., Gittell, J. H., Jiang, S., Chen, B., ... & Wang, X. (2020). From isolation to coordination: How can telemedicine help combat the COVID-19 outbreak?. MedRxiv.
- Wang, Y., Kung, L., Gupta, S., & Ozdemir, S. (2019). Leveraging big data analytics to improve quality of care in healthcare organizations: A configurational perspective. British Journal of Management, 30(2), 362-388.
- Wang, Y., Kung, L., Wang, W. Y. C., & Cegielski, C. G. (2018). An integrated big data analytics-enabled transformation model: Application to health care. Information & Management, 55(1), 64-79.
- Wang, Y., Kung, L., & Byrd, T. A. (2018). Big data analytics: Understanding its capabilities and potential benefits for healthcare organizations. Technological Forecasting and Social Change, 126, 3-13.
- 1st International Conference on Digital Health and Medical Analytics (DHA 2019), 23 - 25 August 2019, Zhengzhou, China
- 2nd International Conference on Digital Health and Medical Analytics (DHA 2020), 24 - 25 July 2020, Beijing, China
- 3rd International Conference on Digital Health and Medical Analytics (DHA 2020), July 2021, United Kingdom