Data Mining In Health Care

Data mining offers great potential to the health care industry in enabling the health systems to have a systemic use of data and analytics. This helps in the identification of inefficiencies and best practices that can help in the improvement of care and a reduction of costs. Currently, the health care industry lags in terms of technology, where it lags behind other sectors in the implementation of effective data mining and analytic strategies (Raghupathi, 2016). Data mining helps in extracting knowledge and also determining interesting and useful patter

An example of how data mining can help meet a current global challenge is addressing of pandemics such as the current Covid19 pandemic.  Mining of data can help health institution to collect, analyze and leverage information regarding a patient, his/her location, and underlying conditions that the patient may be suffering from.  It could be used to create a holistic view of the patients and the physicians and health caregivers, which will be vital in planning how to approach the patients’ conditions (Ţăranu, 2016).  The information collected can also help a health facility in making strategic decisions that will help with the processes of managing the number of patients in the facility and also the caregivers.

Through data mining, the current pandemic challenge can easily be managed by health instructions across the globe. This is by informing the physics relationship management by tracking referrals, physical references, and clinical appointments, a factor that could enable more efficiency in the treatment and care for the patients (Ray, 2018).  Data mining could also facilitate straight forward identification of the patients in the health outcomes, the growth of the hospital capability and ultimately ensure that there is patient satisfaction.


Raghupathi, W. (2016). Data mining in healthcare. Healthcare Informatics: Improving Efficiency through Technology, Analytics, and Management. 353-372.

Ray, R. (2018). Advances in Data Mining: Healthcare Applications. International Research Journal of Engineering and Technology (IRJET). 5(3), 3738-3742.

Ţăranu, I. (2016). Data mining in healthcare: decision making and precision. Database Systems Journal, 6(4), 33-40.

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