Predictive Analytics and Data Mining Reduce Healthcare Costs and Improve Outcomes

October 15, 2017
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Predictive analytics and data mining technology is changing the future of healthcare in unprecedented ways. Healthcare providers around the world are praising these solutions for emerging when they are needed the most.

Predictive Analytics and Big Data Technology Could Stave Growing Healthcare Challenges

Healthcare providers around the world are under immense pressure to reduce healthcare costs and improve outcomes. According to the OECD, the United States has the most expensive healthcare system in the world, while delivering fair outcomes at best. Their research shows that the United States spent 16.4% of its GDP on healthcare in 2013, compared to the OECD average of 8.9%. The new healthcare law has tried to address rising healthcare costs by forcing healthcare providers to focus on improving outcomes and reducing readmission rates.

The United States isn’t alone in this quandary, even though it is in the worst shape. Healthcare costs in Germany have spiked in recent years, so they had to start charging out-of-pocket fees to patients.

Unfortunately, penalizing providers and introducing cost-sharing mechanisms can only do so much. Fortunately, healthcare providers have discovered a newer and more innovative ways to deal with these challenges. One of their best options is using predictive analytics and data mining solutions.

Here are some ways that predictive analytics and big data technology could be the solution healthcare providers need.

Identifying Thousands of Risk Factors

As our understanding of medical knowledge grows, healthcare providers are finally beginning to grasp how little they truly know about the human body. They have, however, identified tens of thousands of factors that play a role in various diseases.

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It is difficult for doctors to make accurate diagnoses and risk assessments during one or even several clinical visits. As human beings, they can’t even comprehend all the data they need to process at once. This assumes they even would know everything they needed. Since physicians are highly specialized these days, they may be unaware of comorbid factors that fall outside the realm of their every narrower specialty,

Predictive analytics technology has made it infinitely easier for doctors to conduct analyses and identify patient risk factors.

Perform Better Preventive Care

Preventive care is key to most successful healthcare systems. Resources that are invested in treating healthcare problems at their onset can dramatically improve patient outcomes.

Improve Actuarial Healthcare Models

In order to provide healthcare to patients, insurers, providers and employers must understand the cost structure. Regardless of the nature of the healthcare system, they need to accurately estimate costs, so they can set premiums, implement the right tax policy and budget for future epidemics.

This is where healthcare predictive analytics models become most useful at a large scale. The largest governments in the world will depend on them to set their healthcare policy.

What is the Catch?

Most experts agree that predictive analytics can play a crucial role in driving down healthcare costs and improving outcomes. However, Dr. David Crocket, Sr. Director of Health Catalyst, states that it is only effective if the right infrastructure is in place.

“The buzzword fever around predictive analytics will likely continue to rise and fall. Unfortunately, lacking the proper infrastructure, staffing and resource to act when something is predicted with high certainty to happen, we fall short of the full potential of harnessing historic trends and patterns in patient data. In other words, without the willpower for clinical intervention, any predictor – no matter how good – is not fully utilized.”

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Healthcare providers must understand these challenges and invest in the resources they need to get them off the ground.