How Health Insurance Uses Predictive Analytics

Predictive analytics is a growing phenomenon in the world of business. From hospitals to boardrooms, combing through historical data and decision tree analytics to build algorithm approaches to large scale problems has become the new norm. Big data is here to stay as social media and digital communications channels continue to grow in prominence in the modern world.

You may be asking, what is predictive analytics, and perhaps more importantly, how does predictive analytics work? With a catchy, buzz-word title, predictive analytics and its closely related cousin, predictive modelling, offer the future of machine learning, data mining, analytics, and fusion. Predictive analytics is the foundation of decision-making in the modern world, and businesses are taking notice while implementing new artificial intelligence and machine learning facets of their strategy divisions.

The Health Insurance Industry

Health care and health insurance coverage acts as an actuarial nightmare. The business isn’t exactly favorable to the individual policyholder, as profit is derived from non-use of the benefits. This remains true in all facets of the insurance industry, yet on the surface, this conundrum can, in fact, benefit the average user. We all require car insurance to drive on the roads, and both drivers and their insurers pray for a long string of uneventful coverage years with no accidents, claims, or general issues.

The same relationship exists within the health care industry. People in the United States, Australia, and beyond require high quality health care coverage to ensure that they’ll be taken care of in the event of an illness, terminal diagnosis, or accident on the job, road, or ball field—among a bevy of other accident-prone spaces in which the messy business of life takes place. A private health insurance comparison site is often the greatest ally that an individual can take advantage of while looking for high quality coverage for themselves and their family members.

While a wide variety of coverage options and providers exist, the choice is often difficult to quantify, as pricing can range across a wide scope. This is where predictive analytics makes its greatest mark as business becomes more and more data driven.

Predictive Analytics and Private Insurers

Private insurance options give the greatest flexibility when it comes to selecting health insurance coverage that will stand up to your rigorous needs. Private insurance companies also employ the big data insights that predictive analytics offers up for the greatest possible profits over the long term. By utilizing these insights, private insurers are able to predict how often you’ll need health services, the types of injuries and illnesses that you’re most likely to encounter, and offer a stunningly accurate picture of the total cost of these needs. All this factors into the quote you’ll ultimately receive from private insurer options.

However, there are a few ways you can tip this landscape of predictive analytics-driven datasets in your favor. We all know that smoking, drinking, and poor exercise can lead to greater long term health risks. This isn’t a hard and fast rule, but in the world of predictive analysis, the current data models lean heavily on the aggregate total of society. This means that quitting smoking, committing to a healthier eating regime and exercising—even once or twice per week—can dramatically change the data surrounding your specific case. This is a great weapon that individuals can leverage in an effort to lower their overall private insurance costs while also boosting their own quality of life in the process.

Predictive analytics is the way of the future in the health care marketplace, as well as in a variety of other business processes and ventures in the United States and all around the world. Take advantage of this trend, and alter the current data that informs your own personal dataset.