Application of Big Data in Australian Government, Department of Health

This presentation explores the application of Big Data in the Australian Government's Department of Health and its impact on the healthcare sector. It discusses the benefits, innovation examples, and future advancements in the use of Big Data in healthcare. The presentation also highlights the primary areas of focus and market trends of Big Data in the healthcare sector.

Application of Big Data in
Australian Government,
Department of Health
Name of the Student
Name of the University

Without data, you are just
another person with an opinion
-W.
Edwards Deming

Big Data
 Complex and large data sets that are difficult to
process without advanced technology (Groves et al.
2016)
 The technology finds insights based on
heterogeneous, voluminous and longitudinal data
 Aims for solving problems that were unanswered or
solve complex problems (Kim et al. 2014)

The Four V’s of Big Data
(Figure 1: The Four V’s of Big
Data)
(Source: Wyber et al. 2015)

Big Data in Healthcare Sector

Healthcare Analytics with Big Data
Old Ways: Data was small and inexpensive
EHR Era: Data is large and highly cheap
 Focuses over patient population
 Heterogeneous data
 Diverse scale
 Noisy data (Zhang et al. 2015)
 Longitudinal records

Big Data in Australian Government,
Department of Health
 The Department of Health of the Australian
Government makes a wide use of technology for
evaluating the health of patients (Health.gov.au 2019)
 Provide services based on advanced methodologies
 Big Data has paved the path of innovation within the
sector

The Primary Areas of Focus
(Figure 2: The Primary Areas of Focus)
(Source: Lee and Yoon 2017)

Innovation Examples
Initiatives by the Australian Healthcare Department:
 Innovative methods for diagnosis of healthcare factors
 New ways for curing diseases
 Penalizing of hospitals with failure rate among patient
treatment (Hilbert 2016)
 BRAIN Initiative

The Underlying Benefits
With the help of Big Data, the underlying benefits that
would be supported include:
 360-degree view and holistic view of patients and
physicians
 Improving efforts for physician relationship
management
 Identifying patterns in healthcare outcomes, hospital
organization and patient satisfaction

The Underlying Benefits
The other kind of benefits that are supported are:
 Optimizing the growth for efficiency in care,
personalization and effectiveness.
 Informing the patients about their preferences and
data referral (Ta, Liu and Nkabinde 2016)
 Analysing trends and benefiting research ideas to
positive health outcomes

Market Trends of Big Data
(Figure 3: Market Trends of Big Data)
(Source: Roski Bo-Linn and Andrews 2014)

Future Advancement and Implications
The different forms of future uses of Big Data in
healthcare sector:
 Engagement of patients could be further enhanced
 Tracking of patients could be improved
 Personal injuries could be resolved quickly

Future Advancement and Implications
The other applications of the future for the healthcare
sector are:
 Advancements in terms of monitoring abilities
 Providing personalized healthcare assistance (Belle et
al. 2015)
 Assessing high risks of patients

Applications of Healthcare Data
The different applications supported are:
 Predictive premiums
 Development of social communities
 Advanced payment modes
 Improvement of channels between patient and physician

Rise of Big Data
(Figure 4: Rise of Big Data)
(Source: Ta, Liu and Nkabinde 2016)

References
Belle, A., Thiagarajan, R., Soroushmehr, S.M., Navidi, F., Beard, D.A. and Najarian, K., 2015. Big data
analytics in healthcare. BioMed research international, 2015.
Groves, P., Kayyali, B., Knott, D. and Kuiken, S.V., 2016. The'big data'revolution in healthcare:
Accelerating value and innovation.
Health.gov.au. (2019). Department of Health | Welcome to the Department of Health. [online]
Available at: https://www.health.gov.au/ [Accessed 24 May 2019].
Hilbert, M., 2016. Big data for development: A review of promises and challenges. Development Policy
Review, 34(1), pp.135-174.
Kim, G.H., Trimi, S. and Chung, J.H., 2014. Big-data applications in the government
sector. Communications of the ACM, 57(3), pp.78-85.
Lee, C.H. and Yoon, H.J., 2017. Medical big data: promise and challenges. Kidney research and clinical
practice, 36(1), p.3.
Roski, J., Bo-Linn, G.W. and Andrews, T.A., 2014. Creating value in health care through big data:
opportunities and policy implications. Health affairs, 33(7), pp.1115-1122.
Ta, V.D., Liu, C.M. and Nkabinde, G.W., 2016, July. Big data stream computing in healthcare real-time
analytics. In 2016 IEEE International Conference on Cloud Computing and Big Data Analysis
(ICCCBDA) (pp. 37-42). IEEE.
Wyber, R., Vaillancourt, S., Perry, W., Mannava, P., Folaranmi, T. and Celi, L.A., 2015. Big data in global
health: improving health in low-and middle-income countries. Bulletin of the World Health
Organization, 93, pp.203-208.
Zhang, Y., Qiu, M., Tsai, C.W., Hassan, M.M. and Alamri, A., 2015. Health-CPS: Healthcare cyber-
physical system assisted by cloud and big data. IEEE Systems Journal, 11(1), pp.88-95.

Thank You