Pros and Cons of Predictive Analytics in Healthcare

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Click here to learn more about author Harsh Arora.

As part of the Fourth Industrial Revolution, predictive analytics is surely a hot buzz word and is something that most of industries, including healthcare, are implementing. Predictive analytics is the branch of analytics that recognize patterns and predict future trends from information extracted from existing data sets. Of course, it’s almost impossible to tell what will happen in the future due to the dynamic nature of almost everything. However, predictive analytics tries to forecast what might happen with an acceptable level of reliability.

A powerful tool like this does have its pros and can help businesses in many ways, but there are challenges as well.

Pros of Predictive Analytics

  • Early Diagnosis

This would be the primary usage of predictive analytics in healthcare – diagnosing and treating a disease before it causes larger problems. It’s understood that diagnosing a disease as early as possible can prevent it from becoming severe. A cliché associated with healthcare is that prevention is better than the cure and just like most clichés, this is certainly true.

An example of this technology being implemented would be through social media. A majority of severe diseases are caused by lifestyle-related issues, so the model would be to take data from an individual’s social account to predict if certain habits are a cause for concern.

  • Research

Predictive analytics also can be influential for medical research purposes. In drug trials, experiments are conducted on a small group of subjects to ensure that the drug will be successful when implemented on a larger scale. Researchers with access to the patient’s data can effectively study the impact of any specific treatment over patient populations. All this research is mostly done by collecting and then analysing large sets of data. The outcomes of these types of research can be improvement in treatment procedures.

  • Higher Quality Care

Now the basic principle of predictive analytics is that the more data, the better the predictions. Big data drawn from a number of sources gives us access to a lot more information than we ever have had in the past. These sources include pharmacy visits, previous doctor visits, social media, and other outside sources. With all this data comes the ability to customize treatments for patients and provide innovative healthcare solutions. It is certain that thanks to predictive analytics and similar technologies the quality of healthcare is bound to go up in the years to come.

  • Cost Savings

A recent report by the Society of Actuaries says that 47 percent of healthcare companies have already started using predictive analytics in their daily functions. It also states that predictive analytics will save organizations 25 percent or more in annual costs over the next five years. These two statements display the magnitude of the impact that will be seen due to this technology. The cost savings will be through a series of optimizations of processes like predicting admission rates.

  • Predicting No-Shows

Understandably, there are bound to be patients that are unable to show up for their appointments. This not only disrupts health provider   schedules but also has financial ramifications. using predictive analytics, providers can identify patients who are likely to skip an appointment without advance notice. They can cut down on losses, improve patient satisfaction, and offer open slots to other patients.

Now, as is the case with most things, there are also some cons associated with predictive analytics. Though it is true that the pros in this case certainly outweigh the cons and that this technology is certainly something that must be utilized, it is important to know what the drawbacks are.

Cons of Predictive Analytics  

  • Privacy

This is surely one of the biggest challenges being faced by the public today. Though there are laws and regulations in place, big corporations have been exploiting private data for years now. It is almost impossible to keep your privacy in today’s social age. In fact, some people believe that privacy might actually be the new celebrity. Ironically, as previously mentioned, for predictive analytics to reach its full potential, there needs to a be a large amount of data. In the case of healthcare, there will be a large amount of private data that will be shared with healthcare companies.

  • Replacing doctors

Though currently the purpose of AI is to assist real doctors, it won’t be long before machines can completely replace them. AI is able to process a diagnosis based on the information provided by the patient and is then able to offer further assistance in treatment. However, this may be an idea of the future because most humans today prefer to interact with a human when it comes to healthcare. However, with the next generations, this will surely fade away.

Market research has shown that the global big data spend in healthcare is expected to grow at a CAGR of 22.07%, reaching $34.27 billion by 2022. These are serious numbers There is a huge amount of investment flowing into this area and it won’t be long before you will start seeing these technologies used in daily life. We have just seen the tip of the iceberg and there is still so much potential that is yet to be explored. However, the intention of the technology is to make the world a better and safer place and it is surely doing so. As previously mentioned, the pros do outweigh the cons and predictive analytics is certainly a technology that will shape the future of healthcare across the world.

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