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Predictive Healthcare Can Dramatically Improve Patient Outcomes & Drive Greater Efficiency

3 minute read, posted on 07/10/2024, by VXI Marketing

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Predictive analytics, powered by artificial intelligence (AI) and machine learning, has been applied across several industries for various solutions where companies want to use the data they have in order to predict the next action a customer might take. Retailers use it to predict what customers may purchase next, banks and payment companies use it to spot fraud and unusual transactions, and Netflix will recommend a show based on their prediction of what you are likely to watch. 

But one area where predictive analytics could be transformational is in healthcare. Instead of just trying to predict what a customer may want to buy, in healthcare, we could be saving their life. 

A doctor usually has to diagnose a condition when a patient is already sick. Even where they have access to the complete medical history of the patient, it may be too much information to process quickly. This is where an AI algorithm can absorb all the data to support a doctor within seconds. 

The algorithm can analyze vast amounts of patient data, including medical history, genetic information, lifestyle factors, and real-time health metrics, to identify patterns and predict potential health issues before they become critical. For instance, AI can predict the likelihood of chronic diseases such as diabetes, heart disease, and cancer, enabling early intervention and personalized treatment plans.  

This allows healthcare providers to intervene with suggested actions to prevent a serious illness from developing further. For example, a health insurance company could inform a patient that after their recent health checkup it appears that they are at risk of a specific illness. The healthcare provider can advise on preventative wellness measures. 

Medicine can also be more personalized when AI can advise how a patient may respond to different types of treatment or drugs. This allows healthcare providers to design personalized treatment plans that are more effective and have fewer side effects. For example, in oncology, AI can predict which cancer treatments will be most effective for a particular patient based on their genetic makeup and the specific characteristics of their cancer.  

Many medical processes are trial and error – this can reduce the cost of that process and help patients recover faster. 

Wearable devices also allow medical professionals to monitor ongoing patient health in real time. A patient at risk of heart disease can regularly wear a monitor to constantly check vital signs and physical activity. Devices like this can identify abnormal heart rhythms, detect early symptoms of respiratory issues, or monitor glucose levels in diabetic patients.  

When a potential health issue is detected, the patient and their healthcare provider can both be alerted so they can manage the situation before it becomes an emergency. 

Predictive analytics can even help hospital managers to organize their resources more effectively by predicting patient numbers and medical staff requirements. This ensures that the right medical supplies are always available and staffing levels are optimized. 

Healthcare providers really have a wide array of options. Predictive analytics using AI has many applications that can improve health outcomes and allow healthcare companies to enhance their operational efficiency. 

To summarize, AI can help healthcare providers to offer better care to patients, more consistently high quality and personalized care, and it can help to improve operational efficiency. 

Predictive healthcare and risk management is one of those rare examples where a business can improve their service and find efficiencies simultaneously. Our team has case studies and more information if you want to explore this in detail. 

For more information on our purpose-driven approach to healthcare outsourcing at VXI please click here. 

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