The entry of big data and artificial intelligence is bringing a marvelous amount of value across the existing healthcare continuum. Big data has specifically helped to deliver the improved outcomes in the field of healthcare. Big data analytics in healthcare supports the new plans related to the value-based care. Therefore, the increased use of big data is helping the healthcare professionals as well as the healthcare institutes in the improvement of the overall quality of care that is being provided.
But, that’s not it, in fact, the use of big data is even paving a way for personalized medicines and precision medications. With the help of the big data and AI, the healthcare experts can steer personalization in the world of healthcare. The use of AI is expected to reach the $6.6 billion mark by the year 2021. In this article, we will focus on the use of big data analytics for personalized medication.
Let’s understand Personalized Medicines
All the patients are not the same, and the healthcare world has started to realize that. Therefore, now the medicines will be given based on the type of the patient. Every person’s medical history is very different. One patient’s social factors, background as well as the psychological factors may be different, therefore, the disease has to be treated differently as well. The factors hugely influence the healing process as well the response of the patient towards the cure. Also, the risk of the complications can be a less if the medicine is provided as per the personality of the patient.
Customization of the medications
The real meaning of personalized medication is the planning of the treatment process based on the person. The medical decisions of the patient are customized as per the patient specific details like the psychological health, social conditions, DNA, family history as well as the complete medical history. Basically, the main aim of personalizing the medication is to identify the most ideal approach for a patient. Most of the times, the treatment is quite economical as well.
Personalization is reducing the cost of the treatment, and at the same time, the treatment will be much more powerful and the experience will be improved. As per one of the surveys, 90% of the USA’s health spending is either on the mental health issues or the chronic illnesses. Thus, prevention will definitely save a lot of money. Also, personalization will reduce the time of treatment, therefore, it is surely beneficial for the patients.
Medicines driven by data
Real-world data is paving a way for the development of future treatments. At the same time, with the help of data, the healthcare experts are able to understand the present set of medicines more concisely. Additionally, with the help of data, you get to know what and how the medicines have to be taken for the best results. Most importantly, with the help of the data analytics, the healthcare experts would be able to understand the patients more clearly. And, that information will allow the healthcare institutes to boost the overall experience of the patients. Newer and newer medicines will be developed that will offer better outcomes. Data driven medication increasing the life expectancy of the patients. Also, it is making sure that the patients spend less for more.
Personalized medicine is revolutionizing the conventional medication
The conventional medicine mostly provides blanket suggestions and prescribes cure that is designed to for a certain category of patients. The medicines are made to cure a certain disease, but they may not work on you. However, personalized medications are curated specifically for you. Therefore, the chances of working on you would be higher. And, the overall impact of the medications is increased.
Role of big data in Precision Medicine
Precision Medication is the future of healthcare. The extensive patient histories and the study of immense amount of data is helping the healthcare professionals to deliver the best possible outcomes. Big data is the backbone of precision medications. As, precision medication is all about tailoring the delivery of care more effectively. The motive is to treat the patients without any flaws. Also, it is focused on the prevention of illnesses. Therefore, the healthcare experts require a huge amount of data to make precision medication strategies. A lot of data has been collected in the EHRs. The huge volume of complex data is being converted in the insights that will be helped to offer much better care.
Big data in personalized branding and marketing
Big data is playing a role in branding and marketing of the healthcare products as well. With the help of the data which is generated related to the patients, the healthcare businesses are able to make better products. Also, the marketing and branding of the products is much more personalized. Basically, big data analytics bring the patients and the healthcare experts closer, therefore, the healthcare experts are able to understand the patients. And, the insights are even used by the healthcare businesses to market their products better as the marketers are able to strike a chord and build a connection with the patients.
The world is becoming more and more advanced and therefore, the field of healthcare is evolving as well. As, there is an enhanced collaboration between the healthcare professionals, healthcare institutes and the scientists, hence, the scientific methods have been upgraded. And, the modern scientific inventions have been translated into better patient outcomes. One of the most talked about modern inventions is personalized medications and it is turning out to be pretty valuable for the world of healthcare. Big data analytics has a major role to play in the future of personalized medication. And, big data is only expected to get more powerful. Though, there are some challenged, but eventually, big data analytics will only benefit both the care provider and the care seeker. At the same time, there will be smaller margins for error. Big data analytics solutions will not just pave way for the personalization of medication, but it will allow the healthcare ecosystem to become more efficient.