Wk 3, MHA 507: DR 1

APA format

175 – 265 words

Cite at least one (1) peer-reviewed reference

Further the conversation and respond to the following:


Taj Rossi

4/24/23, 10:17 PM NEW

Hello Class,

One example of the use of predictive analytics in healthcare is the application of machine learning algorithms in predicting hospital readmissions. A study conducted by the University of Chicago Medical Center developed a predictive model that uses electronic health records (EHR) data to forecast readmissions within 30 days of discharge. The algorithm was developed using a large dataset of de-identified EHRs and trained to identify high-risk patients based on factors such as age, comorbidities, and previous hospitalizations. The model was able to accurately predict readmissions with a 77% accuracy rate, allowing physicians to proactively intervene to prevent readmissions and improve patient outcomes.

The benefits of predictive analytics in healthcare are significant, including improved patient outcomes, reduced healthcare costs, and better resource allocation. However, there are also potential drawbacks to consider, such as the potential for bias and discrimination in algorithms, as well as concerns around data privacy and security.

While the use of genomics in predictive analytics has the potential to lead to biased and discriminatory outcomes, there is no evidence to suggest that the use of predictive analytics itself is inherently racist, sexist, homophobic, or discriminatory. Rather, the potential for bias and discrimination arises from the data and algorithms used to develop the models. As such, it is important to ensure that the data used is representative and that the algorithms are designed to be fair and unbiased.

As a healthcare administrative professional, the greatest organizational benefit of using predictive analytics in patient care is the ability to proactively identify high-risk patients and intervene early to prevent adverse outcomes, such as hospital readmissions. This can lead to improved patient outcomes, reduced healthcare costs, and better resource allocation, ultimately benefiting both patients and healthcare organizations.


Zachariah, P., & Phansalkar, S. (2019). Predictive analytics in healthcare. Journal of Hospital Administration, 8(3), 36-42. https://doi.org/10.5430/jha.v8n3p36

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