With technological advancements in the healthcare sector, predictive analysis tools also can take a step forward in better analysis and diagnosis of autoimmune diseases reducing the cost involved in the process and providing better results.
FREMONT, CA: Nowadays, hospitals and healthcare system providers have started the use of predictive data analytics to provide patients with better, detailed, and more effective health management services, moving towards value-based care models. The need to move towards predictive analytics will be critical as hospitals seek to improve their capabilities to forecast, detect, and monitor autoimmune diseases. Technology can be a boon in providing healthcare benefits and also helps to avoid excessive expenditure.
In America, around 15 percent of the population suffers from an autoimmune disease. The overall expenses in the treatment process are too high, which in return leaves fewer funds for research on other conditions.
Hospital and Health Systems Game-Changer
Predictive analysis of data can bring transformative information to healthcare providers. With the use of artificial intelligence and machine learning tools, the analytics platform can analyze millions of healthcare claims and electronic medical records. Predictive models can confirm existing diagnoses and identify patients who were left undetected or misdiagnosed.
How Analytics will Detect Patients with Autoimmune Disease?
It can be life-changing to discover and predict an autoimmune disease through data analysis. As the symptoms are difficult to detect, confirming autoimmune diseases is difficult. Patients with an autoimmune disease had to wait for their symptoms to show clearly before a proper diagnosis could be made and begin the treatment.
It can take approximately 3 to 5 years to diagnose autoimmune diseases like multiple sclerosis (MS) using traditional methods such as MRIs, spinal taps, and some other testing. During the process, there is a chance of misdiagnosis and misleading results, which may lead to the wrong diagnosis. The cost of offering medical care for patients with an autoimmune disease tends to increase before a definitive diagnosis and then grows more if patients experience an adverse reaction. Predictive analysis tools can facilitate an early diagnosis so that the treatment plan can be put in place to improve the patient's health and reduce costs.
Healthcare industry is at its peak to exploit the power and promise of predictive analysis tools. These tools can derive meaningful information from data to monitor patients and provide new ways of collecting, processing, and analyzing data. New technologies will help in better data analysis and providing quick and effective results. These technologies will include enhanced information analytics systems capable of evaluating various datasets, including billions of information points capable of uncovering trends and helping to forecast outcomes.