5 Ways Data Analytics Improves Global Healthcare Services

Data analytics is a very important technological capability that has helped to improve all areas of our lives. In recent years, a lot has occurred in different walks of life where data analysis has improved business outcomes. Get to know vascular access and its benefits comparer to any other product in health care. One area that is beyond the normal walks of business outcomes is healthcare services. Healthcare services continue to evolve at a rapid pace, and data analytics is one of the most important aspects of the industry. It involves the participation of different types of professionals, customers, capabilities, or specialties like Allied Healthcare Specialities, and services.

For instance, the normal relationship would involve a patient, their family, insurance companies, medical loan facilitators, doctors and nurses, administrators, government regulators, logistics, transportation, emergency utilities, drugs and research, IT companies, and a host of other services that may or may not be directly involved in making healthcare very effective. In normal times, these groups of people, and the technologies that they use to streamline various processes perform in perfect sync.

But, when there is pressure due to situations such as a pandemic, things change very quickly and lead to rapid deterioration of the best of systems that for so long have been working so smoothly before the bad times strike. In such challenging times, the role of certified professionals from data analytics courses in Gurgaon is very important. In this article, we have mentioned the usefulness of data analysis in improving the condition of the global healthcare industry.

1 – Improve the reach and usefulness of Telehealth

By 2025, telehealth would be one of the biggest markets for data analysts passing out from the reputed data analytics courses in Gurgaon.

Let’s understand this development from the current context.

Today, millions of babies die due to negligence during childbirth. In countries where telehealth is available, the numbers come down by 500%! 

Telehealth is a very unique part of healthcare services. It is often seen as an urbanized extension of internet applications and mobile usage. In most parts of the world, patients use telehealth applications and mobile services to instantly contact physicians.

But, things are yet to come to the doorsteps of the rural patients and physicians stationed there. The use of data analytics is changing that for everyone—by providing better mobile services to patients, they are able to meet physicians during emergencies, and the physicians are able to utilize the data management and healthcare services facilities to provide an up to date medical consultancy to patients. This rapid data analysis facility has helped in the diagnosis of many critical ailments, reduce the time to diagnose epidemics, improve the fitness levels of the doctors and nurses, and overall improve the health condition of the citizens. 

2- RPM Market development

The remote patient monitoring or RPM market is one of the fastest growing markets for the data science applications. Currently, it taps the data science platforms for delivering both real time as well as predictive services using healthcare data. 

Currently, the RPM market is segmented into 6-7 domains, which include;

• Cardiac health monitoring systemsWeight tracking systems
• Respiratory health monitoring systems
• Fetal and neonatal / post-partum health management

By 2024, this RPM market will use $180 billion dollars to enhance the healthcare applications from various aspects such as mental fitness, employee safety, mobile blood pressure monitoring, eye tests, pregnancy detection, and much more. Big companies like Philips, Medtronic, Siemens, VitalConnect, VivaLNK, and others have already made huge investments in the RPM world through software development and AI innovations. These companies hire thousands of top grade data analysts from the data analytics courses in Gurgaon, Bangalore, and other parts of the world to improve RPM services.

3 – Healthcare fraud detection 

The US is the biggest target for healthcare fraud. It alone accounts for the 86% of the global healthcare related financial frauds.

Healthcare fraud costs the industry billions of dollars. It also brings disrepute to the whole ecosystem of service providers, financial institutions, and physicians who have recommended the use of these instruments to ease medical pressures. In general, medical frauds are mostly related to insurance claims, payment defaults, loan management, and auditing irregularities. In general, these affect the outcome of patient welfare management despite them having access to the best of healthcare platforms.

By using data analytics, financial services companies are mostly able to detect and penalize companies that support and promote financial irregularities in the healthcare segment. The use of neural networks, text analytics, and supervised support vector machines (SVMs) are widely accepted as the future of fraud detection in healthcare.

4 – Drug research and logistics support

Every year, millions of tons of drugs are wasted to poor inventory management. 90 percent of these cases could have been reversed had drug companies made a good use of the data analysis technologies for drug research, manufacturing, supply, and retention or recall. Because, the drug industry is highly time sensitive and recall value is almost nil, healthcare infrastructure has to rely on real time analytics to ensure there is 0% wastage or reverse logistics involved. 

By using predictive intelligence, many drug companies are able to improve distribution and materials management with superlative outcomes, directly proportional to the number of lives saved. This case is also mostly seen among patients who require an emergency transplant or surgical intervention procedures such as those during accidents, pregnancies, lungs, or heart transplants, and so on.

5- AI for autism

Autism, when detected early, can improve medical outcomes drastically. AI’s role in this regard is highly appreciated. Autism among children is a common disorder of the nervous system which results in speech slur, social inconvenience, and so on. By using AI, physicians and psychiatrists are able to quickly diagnose autism and help people who need support during their development. Data analysts and scientists are using AI for autism by calling in early signs. 

These are the top reasons to adapt to fast paced data science culture and include these in the modern healthcare systems. Companies can solve billions of dollars in cost and millions of lives by providing good quality service.