Predictive Modeling: The Future of Personalized Healthcare

Predictive analytics has always been in the news and the marketplace has been echoing with a buzz that claims to turn your dreams into reality. True to its promise, predictive modeling technique delivers a proven solution that has the power, nearly limitless, to be able to quickly and accurately predict things for you. Now, isn’t that something?

In this blog, let me put some things in perspective that exists in relation to Prime’s prospective solution offerings for companies looking to dramatically ramp up their business performance, with a view to reduce costs and continuous quality improvements. With Prime’s analytics solutions, you can do three things all at the same time these are: Analyze the past, understand the present and change the future. Almost infinite potential to do things your way across the continuum, a solution that is based on historic data. Mind if I say that I am a permanent enthusiast in the field of predictive modeling.

Understanding Predictive Modeling

Predictive modeling is the practice of iterative, methodically exploring the patterns present in various datasets of an organization with emphasis on statistical techniques. It is used by companies to drive the data and use it for decision making, to detect or predict trends with the help of the mined data. That’s being put in a simple way. Now let’s look at the core of it.

Predictive modeling is basically a smart approach that takes particular datasets and uses them to anticipate future patterns and trends. Especially, in healthcare business settings, this has become one of the most important tools available for care managers—through personalized care—aiming for the triple benefits of improved quality, cost reduction, and most definitely better patient outcomes. This kind of modeling is now prevalent in numerous aspects of collaborative and coordinated medical business, and is applied as a regular part of our everyday lives, even though we don't really realize it. Just to give you an example: Organizations use predictive modeling to decide when is the best time to run a commercial for their product/item on the TV. This is helped by the power of predictive modeling that considers their target demographics.

Not to be left behind, even insurance firms use predictive modeling to consider an individual’s age, community data, census data, and lifestyle to actually figure out what his/her premium should be, depending on the data gathered from such a powerful modeling technique that the market has to offer. And based on our current actions plans, we even utilize predictive modeling ourselves day in, day out foreseeing future outcomes/results, and making into record what past results those activities/actions have yielded. Without doubt, it’s an exciting field of interest for us.

Understanding the Present Healthcare Markets

Statewide reform initiative ObamaCare (Patient Protection & Affordable Care Act (PPACA in short)) has made many Americans sign up for medical coverage, in other words, health insurance plans, taking onboard the aging population, offering them various new rights, consumer protection benefits, and protection securities concerning their healthcare. The insurance companies are increasingly dependent on the PBMs to process and pay doctor prescribed medication claims at reduced costs for policyholders. The networked PBMs, as we know, act as third party administrators and negotiators and address certain critical areas in healthcare, are crucial to facilitating transactions between the moving parts of the healthcare industry.

A couple of years ago, in 2014, the specialty drugs market in the US grew by 27% valued at $85 billion and by 2018 it is expected to rise to 50%, expected to grow tremendously at a rate of around 18% during 2015-2019. And now, according to The Pew Charitable Trusts, an independent not for profit trust, the US specialty drugs market will total $400 billion by 2020.

Prescription drug costs continue to be a major component in a plan sponsor’s overall healthcare budget. Current trends show specialty equaling 50% of drug spends by 2018.

Use Predictive Modeling to Make Better Decisions

By connecting all the dots you can draw an obvious conclusion from the bid data sets. It is by developing crucial insights that the care management teams at the hospitals can empower themselves to make the right decisions that are crucial to their business success. And better still, timely decisions will be the harbinger of making the ultimate difference in bringing enhanced patient care results to the care continuum, not to mention a more elevated level of proficiency in patient care is established. Having a clearer future view through this predictive modeling technique will speak for an important strategic advantage for any hospital leader.

Now let’s have a look at the implications of the market trends I have cited above from the benefits angle of an excellent predictive modeling.

• Predict future events.
• Establishes trust and goodwill with consumers for customer retention.
• Reduces fiscal pressures on healthcare.
• Identifies and gives a holistic viewpoint, wherein the risk of patient’s long-term medical non-adherence is prevented and initiates interventions.
• Most useful for drug utilization reviews.
• Helps insurance companies for integrated gaps in care programs.
• Helps in patient awareness and education programs.
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Prime Technology Group, LLC is a global, technology services company with innovation at the core of our business engagements. For more Information visit http://www.PrimeTGI.com