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Using Predictive Analytics to Minimize Emergency Room Claims for Payers

Are you dealing with a medical condition that may be critical - a heart attack, a stroke, or a serious injury? This is certainly not the time to seek a doctor’s appointment or waiting in line at a clinic. Instead, you should immediately go to the emergency room (ER), where immediate medical care is guaranteed.

By its very nature, ER must provide initial treatment for a broad spectrum of illnesses and injuries. Some of the most common cases that an emergency room treats include injuries, trauma, heart attack, stroke, breathlessness, seizure, among others. Though injuries and trauma eventually get transferred to their respective specialised units, the initial aid is given in the ER.

Sky high costs

Due to the need to diagnose and treat a wide range of conditions, an ER staff come highly trained and specialised. Also, ERs are 24x7 facilities. These factors contribute to an ER’s exorbitant costs.

Obviously, a visit to the ER translates to a burden on the pocket - either of the individual or the payer. One way to ease this burden is to avoid ER altogether, if possible.

Little can be done about expenses incurred due to injuries and trauma because they happen without notice. But what about expenses arising from other medical conditions and causes? Can they be minimised? If there is enough warning, one can take the necessary action before the condition turns into an emergency and avoid ER altogether.

Numbers and statistics

A staggering number of ER admissions are due to chronic illnesses, and about a third of them are unnecessary. Major savings could be achieved annually if patients with non-urgent medical problems were to take advantage of alternative healthcare options. These are huge advantages, if only the problems are predictable.

Of the chronically ill patients admitted to the emergency ward, a huge majority survive the first spell. Of these, a small percent of people get re-admitted twice or thrice in less than a year. It does seem that addressing chronic conditions can prove to be a big saving, particularly for the insurance industry.

But what are chronic conditions? Are they predictable?

Chronic illnesses and their influencers

Conditions that last at least a year, require ongoing medical attention, and limit activities of daily living fall into the chronic illness category. A few examples include asthma, chronic obstructive pulmonary disease (COPD), epilepsy, hypertension, diabetes, and high blood cholesterol.

Almost all these conditions are brought on by dietary and lifestyle factors.

So, chronic conditions help build analytical models when fed with the right data.

The competence of analytics

Advanced analytics is pivotal in potential loss minimisation for chronic illnesses. By using various factors like social determinants of health, affluence, claim history, and past medical records of a patient, analytics models are capable of predicting, fairly accurately, a possible emergency. This is almost akin to how a sentient organism behaves.*

Healthcare facilities can benefit greatly from using data analytics to distinguish and apply new insights from data, both in the areas of business as well as value-based patient care.

Predictive analytics (especially for chronic diseases) is a remarkable development in healthcare technology. It can help detect early signs of deterioration, identify high-risk individuals, and help them manage risk-levels outside an ER - all contributing to reduced hospital admissions, thereby preventing downtime of medical equipment, and reducing costs.

Dr. Ethan Halm of UT Southwestern states that health records automatically help hospitals identify high-risk patients. They require readmission as early as their first admission to the hospital. When hospitals and individuals are both armed with this knowledge, it can help minimise ER costs.

Be forewarned, save costs

Apart from the suffering individual, healthcare and insurance sectors also bear the burden of a medical emergency. By using the combined power of information and big data analytics, a big leap towards proactively taking a course that minimises usage of hospital resources and emergency claims pay-offs is possible.

As Peter Sondergaard, Chairman of the Board, DecideAct, says “Information is the oil of the 21st century, and analytics is the combustion engine.”

* For organizations on the digital transformation journey, agility is key in responding to a rapidly changing technology and business landscape. Now more than ever, it is crucial to deliver and exceed on organizational expectations with a robust digital mindset backed by innovation. Enabling businesses to sense, learn, respond, and evolve like a living organism, will be imperative for business excellence going forward. A comprehensive, yet modular suite of services is doing exactly that. Equipping organizations with intuitive decision-making automatically at scale, actionable insights based on real-time solutions, anytime/anywhere experience, and in-depth data visibility across functions leading to hyper-productivity, Live Enterprise is building connected organizations that are innovating collaboratively for the future.

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