Big Data in Healthcare Example Paper

Big Data in Healthcare Example Paper

Big Data in Healthcare

There are many ways that “big data” is currently being used to positively impact population health. For example, The Cancer Genome Atlas Program has molecularly characterized tens of thousands of cancer samples which has led to improvements in the diagnosis, treatment, and prevention of various types of cancers (National Cancer Institute, 2021). One way that I use “big data” in my current position, is by collecting data on certain metrics, such as CLABSI and CAUTI, for presentation at the Nurse Practice Council.

Data has the potential to increase patient safety by predicting and preventing hospital-acquired infections (HAI). The most obvious way is by using HAI rates as a benchmark to evaluate nursing interventions, such as the incorporation of CHG baths or a new Foley catheter protocol. Another way is by using predictive analytics and AI to actually predict which patients are at the highest risk for developing a HAI. According to HHS, this type of predictive technology has saved hospitals more than $12 billion between 2010 and 2013 (Bresnick, J., 2018) Big Data in Healthcare Example Paper.


Risks of Big Data

Unfortunately, there are some unintended risks with the collection of big data. The one that usually comes to mind is the unintended release of data or data hacking. Personal identifiable information is important to keep private to most people. This information could be used maliciously to steal money, take out loans, etc. Although more safeguards are being produced to protect our information, vulnerabilities still exist. Strang, K.D. & Sun, Z. (2019) state “the nature of wireless transmissions is that even encrypted data could be easily intercepted and decoded with currently available software”. One way of combating this issue is by ensuring you are only accessing or sharing data on a secure network.


Bresnick, J. (2018). Using big data analytics for patient safety, hospital acquired conditions. Health IT Analytics

National Cancer Institute. (2021). The cancer genome atlas program.

Strang, K. D. & Sun, Z. (2019). Hidden big analytics issues in the healthcare industry. Health Informatics Journal, 26(2).

sample response post

I found your post to be informative, and I agree that security is the most significant risk associated with using and collecting big data.  Unfortunately, data breaches happen more frequently than people realize.  In 2020 alone, data breaches increased by 25% from 2019, and 176 data breaches of 500 healthcare records or more were reported every day (HIPPA Journal, 2021).  Surprisingly, Mitchell (2021) states that “the average cost per healthcare record breached increased from $429 in 2019 to $499 in 2020, costing healthcare organizations around $13.2 billion in 2020”.   Mitchell also points out that 37 out of the 50 states saw an increase in healthcare data breaches last year Big Data in Healthcare Example Paper.  The largest data breach in 2020 happened to Trinity Health, and it involved 3,320,726 people (Jercich, 2020).  Using the data above, a breach of that size would cost the organization 1,424,591,454 to 1,657,320,726 dollars.  A billion and a half dollars because of a data breach is unfathomable. Nevertheless, it shows that everyone needs to pay attention and ensure that everything is being done to prevent a breach.


Jercich, K. (2020, December 30). The biggest healthcare data breaches reported in 2020. Healthcare IT News.

Journal, H. (2021, March 3). 2020 Healthcare Data Breach Report: 25% Increase in Breaches in 2020. HIPAA Journal.

Mitchell, H. (2021, February 22). Healthcare data breaches up 55.1% in 2020, report finds. Becker’s Healthcare. Big Data in Healthcare Example Paper

sample response 2

Enjoyed reading your post.  As part of a clinical method, one of the main benefits of using big data is that it allows early detection of diseases at an early

stage. It is easy to treat and efficiently control diseases as they are identified only early. When diagnosed at an early stage, diseases such as cancer can

be fully treated and can be fatal in most cases if identified early. For example, ovarian cancer is a common condition for women and, with high

mortality rates, it ranks fourth among other cancers. The mortality rate from ovarian cancer is that most people were unaware of cancer before the

disease progressed to Stage III or Stage IV. The key to this problem is early detection to reduce the rate of death from ovarian cancer. The ethical issues

associated with big data are among the primary challenges facing the adoption and application of big data in the clinical system. The risk of a clash

between privacy and personal autonomy has emerged as a crucial problem that is a barrier to the adoption of big data. The use of large quantities of

data could, if accessed by unauthorized entities with malicious intent, reveal private information. The ethical problem of adopting big data can be

resolved by implementing appropriate policy initiatives and frameworks. The policy measure will direct data use and access and ensure that privacy

issues are addressed. The introduction of policy initiatives is a critical step to resolve Big Data-related privacy concerns in full Big Data in Healthcare Example Paper.


Mehta N. and Pandit A. (2018). Concurrence of big data analytics and healthcare: A systematic review. International journal of medical informatics, 114, 57-65.

Yasodha P. and Anathanarayanan N. R. (2015). Analyzing big data to build a knowledge-based system for early detection of ovarian cancer. Indian journal of science and technology. 8(14), 1-7.

Murdoch, T. B., & Detsky, A. S. (2013). The inevitable application of big data to health care. Jama, 309(13), 1351-1352 Big Data in Healthcare Example Paper.