What are Predictive Analytics in Health Care

What are Predictive Analytics?

Predictive analytics is a branch of advanced analytics which uses techniques such as gathering statistics, modeling, artificial intelligence, and data mining to predict the outcomes of unknown future events.  When asking the question, “What are Predictive Analytics in Health Care?”  the answer would be utilizing the techniques mentioned above to predict trends in healthcare and better be able to plan for health care technologies and innovations that will benefit patients and medical facilities in the future.

What are the Benefits of Predictive Analytics in Healthcare?

There are many benefits to utilizing predictive analytics in a healthcare setting.  Some of the advantages include:

Increasing the Accuracy of Diagnosis: When a patient enters an emergency room, there is often limited information on what may be going on as well as what their prognosis may be if they were to be sent home versus being admitted.  Most of this unpredictability is because a patient’s medical history is not always readily available.  With the use of predictive analytics, the ER physician could enter the information into an algorithm that would, in turn, give them the most likely predictable outcome of the patient’s release.

Providing employers and Hospitals with Predicted Insurance Costs: Employers, along with medical facilities and insurance providers, could share data on the characteristics of their workforce to help develop a model that can estimate future medical costs and other predictive information, such as the average number of visits employees will make to their primary care physician within a year.  Not only will this help companies to estimate costs more accurately it will also contribute to building more accurate models for health care plans that are available.

Allowing Researchers to Develop Information Based on Prediction Instead of Relying on Large Amounts of Case Studies: The medical research community will often use significant amounts of case studies to provide them with their primary data.  This can take years to compile due to sampling methods.  With predictive analytics, the researchers would be able to draw predictions quicker from fewer case studies and add to the data as case studies continue to verify the accuracy and develop more predictions.

Patients Have Potential for Better Healthcare Outcomes Using Predictions: With the data that can be gained from predictive analytics in health care, along with increased technology in gathering data such as monitoring devices, patients have a chance at a better quality of life by learning about necessary lifestyle changes to prevent patterns that can lead to adverse health.  Additionally, it is possible that with more predictive models, patients will be able to be better treated for their specific needs, such as medications.  For example, analytics may help to find medications that can work well for the patient and not just work for most of the population.

Pharmaceutical Companies can Better Predict Need of Patients and Medical Facilities: Predictive analytics can help pharmaceutical companies develop medications to be used in smaller groups through the use of projections models.  With the data gained there will be less of a trial and error method to determine which medications will work for which patient.  This can lead to a significant reduction in wasted medication by ensuring the best possible treatment is utilized the first time.  Predictive analytics can also give pharmaceutical companies the data to determine where the need is for medication in the future.

Utilizing predictive analytics in healthcare can not only help patients to get better treatment and provide them with better health care information, but it also can help medical facilities with diagnostics, research, and better overall patient treatment.  While predictive analytics should not be relied on solely for research and diagnosis, it can be a helpful tool for predicting trends and patterns in the various areas of healthcare.