Budget and time have always been concerns for clinicians and researchers; however, the overwhelming volume of big data is an emerging issue for those conducting clinical trials. Big data is a relatively new term that refers to extremely vast amounts of data sets or information accumulated for pattern and trend analysis. In other words, big data is exactly what it sounds like — a large amount of data. In this blog, we explore how big data is used currently by hospitals and practices, and how it ultimately benefits both doctors and patients.
Case Study: Cancer Medication Clinical Trials
Dr. Thomas is a physician interested in conducting clinical trials regarding a new, and potentially breakthrough, cancer medication. Dr. Thomas thinks the new medication possesses the capacity to revolutionize cancer therapy and help treat thousands of cancer patients across America. Moreover, Dr. Thomas believes the new medication can save lives. Dr. Thomas has worked with cancer patients for years and thinks that new medications are needed to improve patient care and outcomes. He has a strong commitment to the advancement of treatment options and understands that the future of cancer therapy, and healthcare in general, lies in clinical trials results and findings. With that in mind, Dr. Thomas is eager to begin clinical trials for his new cancer medication. However, Dr. Thomas has a few problems: budget, time, and the overwhelming volume of big data.
Analytics Trends and Big Data in Healthcare
Big data, as it relates to healthcare, is collected by hospitals, other healthcare facilities, and clinicians. Essentially, when a patient visits a clinician or is admitted to a hospital or other healthcare facility, his or her health-related data is collected and stored. The source of the health-related data can remain anonymous; however, the health-related data that are collected can include patient-specific information such as patient ages, heights, weights, blood types, blood pressures, heart rates, blood glucose levels, disease states, treatment outcomes, and more. All of the health-related data that is collected is then stored in massive databases, which can then be used by clinicians and researchers to gain valuable insight into patient populations, disease state patterns, and disease management outcomes. In essence, big data can provide clinicians and researchers with the key to unlocking a wealth of real-world data/information that possesses the potential to revolutionize healthcare and research.
However, one question remains to be answered: how can clinicians and researchers sift through the immense magnitude of the information held by big data to find exactly what they are looking for? The previously posed question brings Dr. Thomas’s problems back to the forefront: budget, time and the overwhelming volume of big data. With a limited budget and a limited amount of time, how can Dr. Thomas evaluate and use the valuable information found in big data to conduct his clinical trial? Dr. Thomas knows from his understanding of big data that the real-world information he needs to design a clinical trial protocol that can maximize his budget, time, outcomes, and clinical data integrity can be found within the stores of big data. However, Dr. Thomas is not exactly sure how to obtain the information he requires. Fortunately, there is a potential solution for Dr. Thomas and those like him in the form of artificial intelligence (AI).
AI-Based Analytics and Blockchain Analytics
AI has long been thought of as the future’s answer to big data questions by those interpreting analytic trends. Luckily, for all those hoping to use the vast quantity of information held by big data, the future is here. AI programs, coupled with what is referred to as blockchain data science and blockchain analysis software, may hold the secret to big data analysis. With that said, how can AI and blockchain data science help clinicians and researchers obtain the information they require from big data?
Basically, AI and blockchain analysis software can be programmed to master the volume of big data, the speed at which big data is generated, the array of big data sources, the variability of big data and the value of big data. In other words, AI and blockchain analysis software can be designed to create a customized, virtual net that can be used to collect and capture relevant information of value to individual parities. For example, if a researcher is interested in examining the infection rates of a specific community, an AI program can be developed and used to capture that data as it is generated. It can simultaneously filter out irrelevant information held within big data, allowing the researcher to efficiently obtain exactly what is required without wasting time, effort, energy and perhaps most importantly, money. By using AI and related programs, researchers can find the proverbial knowledge needle in the haystack of big data.
Blockchain Analysis Software
As previously mentioned, the knowledge obtained through AI-based analytics, blockchain analytics and related programs and software can be extremely valuable to clinicians and researchers. It can help them design protocols and gather real-world patient data on which to base their clinical trial design. Furthermore, AI technology can also be used during the trial to collect real-time data and observations from patients included in the trial. Through the use of wearable AI devices and sensors, researchers can gather consistent, objective data from patients in actual time, which can be used in clinical trial data analysis and the formulation of trial conclusions. Perhaps, for the first time in clinical trial history, researchers can use AI to track the progression of diseases and the impact of medications through biometric signals as they are generated, allowing them unprecedented access to patients, results and the potential for improved trial outcomes.
AI Trials and AI Trends
After some research, Dr. Thomas realizes the trends in clinical trials and the AI trends are changing and that he may not have any problems after all. Through the use of AI, Dr. Thomas breaks the enigma of big data and finds the information necessary for the success of his clinical trial. Like Dr. Thomas, clinicians and researchers are using AI to tap the seemingly limitless potential of big data to further their research and the progression of healthcare for the betterment of patients. After all, the key to healthcare has always been innovation and the attempts to close the gaps between therapy and the various diseases and conditions of patients. With the use of big data and AI in clinical trials, perhaps those gaps may finally be closed, allowing patients to receive the progressive treatment they require to transform their health and lives for the better.