Challenges and Opportunities for the Future of Predictive Analytics in Healthcare

With any successful process, challenges are always a concern. Although technology can produce algorithms, human error is possible. Skill and knowledge to appropriately interpret and share data are essential to the implementation of changes in healthcare. Predictive analytics is based on past and present data but does not account for unpredictable changes that may affect outcomes.

In the world of technological advances, predictive analytics plays a significant role. Early disease detection, production of time and cost-saving processes, and enhancement of medical decision-making techniques are expected outcomes of predictive analytics. As problems are identified, predictive analytics can change the healthcare system to a preventative healthcare model.

References

Ataman, M. G., Sariyer, G., Saglam, C., Karagoz, A., & Unluer, E. E. (2023). Factors relating to decision delay in the Emergency Department: Effects of diagnostic tests and consultations. Open Access Emergency Medicine15, 119–131.

GovLoop. (2016, June 15). Defining data analytics. [Video]. YouTube. https://www.youtube.com/watch?v=RAw55JEcnEs

IDG TECHTalk. (2020, March 27). What is predictive analytics? Transforming data into future insights [Video]. YouTube. https://www.youtube.com/watch?v=cVibCHRSxB0

Mathur, G. (2023). IBM. Data science versus machine learning: What’s the difference? https://www.ibm.com/blog/data-science-vs-machine-learning-whats-the-difference/

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