Forecasting and Predictive Analytics in Healthcare

Do you know Netflix awarded 1 million dollars to a team of scientists in 2009 for inventing an algorithm that has the potential to improve their recommendation ability? Remember, this 1 million dollar contest was much before the arrival of Big Data. So, there is a long history of forecasting and predictive analytics, and it is definitely not something new as you may be thinking right now.

Now, when we are talking about healthcare, we must know that much importance is given to forecasting and predictive analytics to curb healthcare costs, to optimize the clinical workflow, and so on. Now, let’s dig deeper.

What exactly is forecasting?

Forecasting is about finding what will happen based on an analysis of past events and the current events. For entrepreneurs, it is basically a planning tool. You are well aware of the term weather forecasting. So, forecasting is also there in healthcare because the future is unpredictable, and no one loves unforeseeable events. For example, the recent outbreak of COVID-19 is such an event that has caused a disastrous impact on the entire world population.

The need for forecasting in healthcare

The health environment is changing rapidly. Over the last few years, the cost of care, a shift in the cultural mindset of people and demographics of healthcare professionals, illness trends, and change in healthcare policies has dramatically changed the healthcare environment.

Various forecasting tools are now used to combat events that will happen in the future, such as the evolving demand for healthcare services or health strategies. In short, forecasting is essential in the healthcare system because of some of these primary reasons:

  • To enhance services of preventive health care
  • To create alerts for patient overflow management
  • To reduce overall healthcare cost
  • To decrease redundancy in healthcare staff

Here, it must be remembered that forecasting outcomes are not always perfect. So for accuracy in forecasting results, the key decision-makers in the healthcare industry are blending their accumulated experience and judgment.

Impact of forecasting on healthcare sector

There is no denying the fact that forecasting is making baby steps in the healthcare sector. Due to technological advancement, it is evolving at a gradual pace to have a profound impact. To understand how it impacts, let’s have a look at the COPD health forecasting used by the United Kingdom Meteorological Office for several years.

The aim of the forecasting service that was launched in 2012 was to help the patients in managing their Chronic Obstructive Pulmonary Disease (COPD) in a better way, especially in the long periods of cold. This service that was named Healthy Outlook® use to send health alerts not only to just people with this disease but also to health service providers by an automated call system.

What is the need for predictive analysis?

We all have visited a clinical setting at one point in our lives. We all may have suffered from some kind of illness at some time or another. Each time, we assume that the doctors or medical professionals always make informed decisions because they have all the knowledge they need to make any decision for their patients.

Unfortunately, this is not the truth. Even if these medical professionals have access to massive data, they need time to analyze and compare it with the past treatment outcomes before arriving at any decision. However, neither they have time, nor the expertise to perform this type of analysis.

So, here predictive analytics comes into the picture. It is used to search through a large amount of information and do an analysis of the same to predict treatment outcomes for patients. Many times, this vast information also includes the latest research published in various medical journals.

It is here vital to understand that there are actually two kinds of predictive analytics-Automated Predictive Analytics and Manual/Traditional Predictive Analytics.

Healthcare settings are at present using various predictive analytics tools for some of these reasons:

  • To identify high-risk patients who can have chronic diseases
  • To create personalized treatments for those who are at such risk
  • To reduce patient’s waiting time during appointments
  • To optimize staff in emergency rooms
  • To improve cost-cutting in a healthcare setting

Apart from these, predictive analytics has now also found its use in health insurance companies to identify claims that suddenly become a reason for incurring high-cost losses.

How predictive analytics impacts the healthcare industry?

Predictive analytics has impacted the healthcare industry in profound ways. Now authorities use predictive models to analyze historical and real-time data to comprehend the scale of an outbreak in different regions or even continents.

You may be surprised to know that the COVID-19 outbreak was accurately predicted by an AI-powered tool named Blue Dot well before the official warning issued by the Chinese Government.

Physicians in plenty of healthcare settings across the world are now using predictive algorithms or models to make an accurate diagnosis and more target treatments than ever before. Hospitals are effectively using predictive analytics to prevent no shows during a doctor’s appointment that saves the valuable time of doctors and helps in the effective management of the patient flow throughout the hospital.

According to Peter Sondergaard, “Information is the oil of the 21st century, and analytics is the combustion engine.” The former executive vice-president of Gartner Research was absolutely right when he said this several years back.

Predictive analytics is now even used in identifying the maintenance needs of medical equipment by pooling and analyzing technical data from the sensors of such equipment. While this impact may seem to you insignificant, such a prediction helps a lot in minimizing workflow disruptions due to failure in equipment.

Predictive analytics is nowadays also used to combine data from several sources like electronic medical records of hospitals, fall detection sensors in wearable devices, medical alert services, and so on to accurately identify seniors who may need emergency transport within a month. For example, CareSage-a predictive analytics engine developed by Philips is successfully doing the same since 2015.

While the tool immensely helps seniors who are at risk, it also prevents hospital readmissions by early intervention and solves the problem of shortage of beds in a hospital setting. This also eliminates the unnecessary transportation costs to the hospital.

Wrap up

Indeed, forecasting and predictive analytics have vast potential in revolutionizing the healthcare sector. Patients are now better informed, and hospital admissions are becoming more meaningful.

Yes, initially, maybe there will be a loss of revenue in healthcare centers due to fewer unnecessary hospitalizations, but with more specialized offerings, lower need for medical equipment maintenance, and minimized workflow disruptions, overall revenue will increase gradually.

May be with forecasting and predictive analytics in healthcare, the day is not far when you will get a note from your physician that will say that you are at risk of getting a heart attack in the next 5 years! Don’t worry because you will be able to make necessary adjustments in your current lifestyle to mitigate any such risk.



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