Healthcare & TechnologyWhat Are the Benefits of Predictive Analytics in the Healthcare Industry?

Over the past decade, technology and the healthcare industry have become inextricably linked. Although healthcare is a field where innovation takes time, because there are so many factors to consider when people’s lives are at stake, it’s also the industry where tech can make the biggest impact. AI, the Internet of Medical Things, telemedicine, robotics, all of these things have become integrated into the medical field in one way or another, and they’re slowly but surely transforming the industry and taking it to the next level. 

Predictive analytics is another tool, or concept, that can lead to better patient outcomes and ease the workflow of healthcare professionals and represents an extremely important technological progress for the future of healthcare. By leveraging the power of data, healthcare professionals and their patients can benefit in many different ways, both in the short-term and in the long term.  

The main benefits of predictive analytics in healthcare 

Predictive analytics uses artificial intelligence and big data to paint a real-time picture of administrative information, healthcare processes, patient information, and so much more. It can use all of this crucial historical data to predict and prevent diseases and aid medical professionals in crafting effective treatment plans for each patient, based on their medical, environmental, psychological, and economic history. Below we list some of the ways in which predictive analytics can streamline processes and help medical professionals do their job effectively.  

Improving patient care and patient outcomes  

The main benefit of predictive analytics for the healthcare industry is without a doubt improved patient care. By leveraging technology and AI tools to analyze and interpret massive amounts of patient data, medical professionals can obtain a clear, real-time, data-driven view of each individual patient. By combining this invaluable digital information with information regarding a patient’s environment, history, and socio-economic situation, doctors can better determine the best course of treatment that fits each patient’s unique needs. By having access to real-time patient information, healthcare professionals can be more effective in their decision-making process, and they can use this data to establish a diagnosis and craft the right treatment plan for the patient. 

One of the most important advantages of precision medicine is that it allows healthcare providers to identify individuals at high risk for specific conditions and diseases long before symptoms appear. By identifying these individuals early, healthcare providers can take proactive steps to prevent the progression of the condition or disease, leading to better patient outcomes.

Predictive analysis can detect changes in a patient’s health status and alert medical professionals that they might need to switch treatment plans, increase or decrease dosage, or reevaluate the patient’s condition and enables medical providers to determine which individuals might be at risk to develop chronic diseases or other medical issues.

By considering the patient’s history, their lifestyle choices and patterns, their environment and economic status, providers can use the data to predict whether someone is at risk for developing high blood pressure, diabetes, kidney disease, obesity, or even cancer. By being able to identify at-risk patients, healthcare providers can intervene early and prevent potential health issues down the line. Predictive analytics provides them with that opportunity, and can lead to better patient outcomes and, consequently, better patient care.  

Streamlining workflows for healthcare professionals  

Healthcare providers spend a huge amount of time going through paperwork and analyzing patient information and other databases. With the help of AI-powered predictive analytics tools, providers can manage their patient information in a more timely and effective manner. As a result, they are able to free up time that can be devoted to research, patient care, courses and clinical trials, and more. Also, the impact that human errors could have on healthcare could be fatal. Thankfully, by providing real-time, accurate insights to guide medical professionals actions, data can help flag potential errors and prevent fatal mistakes.

Predictive analytics also helps providers identify whether a treatment plan is working for a patient or not before results can be visible in imaging scans or other tests. For instance, researchers at the University of Michigan Rogel Cancer Center are devising a blood test that can predict whether a certain treatment for HPV-positive throat cancer is working, months earlier than through standard imaging.  

Fueling innovation in the medical field  

Predictive analytics is a valuable tool that can be used to fuel innovation in the medical field by leveraging historical patient data, and it can help researchers identify, analyze, and prevent diseases from evolving. Researchers are using predictive analytics, AI, machine learning, and every other healthtech tool available today to develop new methods to combat viruses like Covid19. For such viruses, the severity of the symptoms varies from patient to patient, so determining how the virus will evolve is a tough challenge.

A recent JAMA study highlighted several risk factors that can lead to severe cases of Covid19, factors that were identified using predictive analytics and machine learning algorithms. Demographic characteristics and comorbidities were the risk factors identified as those with the highest impact on the evolution of Covid19 symptoms in patients.
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By analyzing both real-time and historical patient data, predictive analytics can streamline a wide range of healthcare processes, from administrative and financial tasks for healthcare institutions to patient care, diagnostics, and prevention. Predictive analytics methods can also identify trends and help with managing the spread of diseases like Covid19. These methods, combined with machine learning, AI, IoMT, and other emerging technologies, can transform the healthcare industry and bring significant improvements that benefit both providers and patients.  

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