Improving the Provision of Healthcare ? the Big Data and AI
Medicine and IT had been two isolated arenas for centuries.
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Updated November 2026. This was first published on 9 July 2021. The idea is the same. Any number below is what the original piece said then. It is not a new count.
Key takeaways
- Medicine and IT had been two isolated arenas for centuries.
- They believed that they had nothing to offer one another.
- After all, their thought processes and manner of operations had been so drastically divergent from one another!
Medicine and IT had been two isolated arenas for centuries. They believed that they had nothing to offer one another. After all, their thought processes and manner of operations had been so drastically divergent from one another! It was only during the latter half of the 20th century that a ‘rethink? The medical fraternity began to feel that they could use computer technology for enhanced decision-making, processing literature on healthcare, etc. This was the beginning, and it set the foundation for a growing friendship between the healthcare and the technology industries. The bonding has only been getting stronger and stronger, over the years, prompting experts to comment upon the changing scenario.
?Only digital health can bring healthcare into the 21stcentury, and make patients the point-of-care. We prepare everyone in healthcare for the adoption of innovative, disruptive, and smart technologies, while keeping the human touch? Bertalan Mesko, MD (Director, The Medical Futurist Institute).
?Improving health outcomes through digital health became my obsession after witnessing the inefficiencies and unsafe practices that result from our reliance on a paper-based healthcare system? Louise Schaper, MD (CEO, Australasian Institute of Digital Health).
Two technological innovations that have caught on in a big way in the healthcare sector across the globe, are Big Data and Artificial Intelligence (AI).
Big Data Analytics #
Medical establishments, regardless of the kind of services they provide, must deal with humongous amounts of information, on a day-to-day basis. The information relates to the input that diverse patients provide about their diverse illnesses. This data is vital to medical practitioners, for they influence decision-making about the types of healthcare tasks they must undertake for each patient. The data proves equally vital for healthcare insurance agents, and medical research. So, every bit of information finds its way to huge databases, or storehouses of data. Since the quantity of information is vast, the IT industry refers to it as Big Data. Outlined below are the different applications of Big Data in the healthcare sector.
This refers to electronic health records. Many medical establishments enter personal and healthcare details of every patient, into a computer system. Often, there is sharing of information about certain patients amongst different healthcare providers. Thanks to Big Data, it becomes possible to create files that can undergo modification at any time. As a result, there is elimination of excessive paperwork. Then again, there is elimination of errors related to duplication/replication of records. EHRs also issue warnings and reminders regarding prescriptions and new diagnostic tests. So, EHR is a great boon for the healthcare industry. As per a report from McKinsey, ‘The integrated system has improved outcomes in cardiovascular disease, and achieved an estimated $1 billion in savings from reduced office visits and lab tests.?[1].
Human Errors #
Wrong medications prescribed to the wrong patients, can prove disastrous, or even life-threatening. But, this is a common error, amongst other errors, especially when administrators tackle everything manually. The entry of Big Data and predictive analysis has managed to majorly reduce the percentage of human errors. This is because it scans the computerized records, and even identifies possible errors.
Big Data Analytics has the capacity to recognize changes that may occur in network traffic. It can even identify problems with security. This is big relief for medical privacy breaches have always been a huge concern for the healthcare industry. Way back in 2015, CMS (Centers for Medicare and Medicaid Services) declared that predictive analysis had helped to save beyond $210.7 million in that year.[2]Predictive analysis uses four types of models ? anomaly, rules-based, predictive, and social networking ? to identify diverse types of medical frauds.
Medical Imaging #
It would be impossible to correctly predict how many imaging procedures take place in a single year! Storing the images safely for lengthy periods, is an expensive business. So, the only solution to this problem is to bring Big Data Analytics into play. IT experts can create algorithms for analyzing numerous images simultaneously. This would lead to the recognition of certain patterns, and ultimately, presenting them in a comprehensible format to healthcare professionals.
Making Predictions #
Predictive analysis suffices to decide about how many patients may visit medical establishments. In other words, this analysis can help medical researchers to reach relevant conclusions about admission rates. In turn, it becomes possible to predict the trend of future admissions. Such conclusions can help hospitals to create a sensible ratio between patients and hospital staff, at any given point in time. Having less staff may endanger the lives of patients. Having an excess of staff, tends to lead towards enhancement in labor expenses.
Telemedicine and Telesurgery #
Thanks to the innovative wearables arriving at the medical marketplace, healthcare professionals are now able to monitor patients from afar. They may initiate phone calls, or video conferences, for consultations, primary diagnosis, etc. Even healthcare professionals can come together to undergo training, initiate discussions, etc., due to Big Data. Finally, robots are coming into play, for performing surgeries with the aid of real-time delivery of essential data.
Artificial Intelligence (AI) #
AI and Machine Learning (ML) go together, for the latter is a subset of the former.
AI simulates all that the actions that a human being can initiate and perform, as well as human speech. So, it can simplify the tasks undertaken by both, healthcare providers, and patients.
ML aids healthcare professionals in decision-making by bringing relevant data into each patient’s picture. It also has the capacity to recognize different algorithms, data, and patterns, thereby presenting highly precise and automated insights. Here is how AI and ML can improve healthcare worldwide.
Radiology Tools #
Currently, X-Rays, MRI machines, and CT scanners are popular tools for scanning the human body. They display radiological pictures for the healthcare professional’s perusal. Apart from this, healthcare technicians take samples of various tissues too. The technicians are extremely careful in initiating hygienic practices. Regardless, the risk of the appearance of infections remains.
In such a scenario, IT experts are ready to create innovative radiology tools via AI, such that they offer accurate and detailed diagnoses. This should prove highly useful in identifying aggressive tumors/cancers, and bringing about better decisions regarding treatment.
People suffering from neurological disorders, traumas, etc., prefer to communicate with human beings, and not machines/systems. But, AI can help in the creation of BCIs (brain-computer interfaces). can speak, move, and interact with such patients, in an extremely realistic way. This ensures that the mental health of a patient remains undisturbed.
If a patient’s body is highly resistant to certain drugs/antibiotics, the healthcare provider finds it difficult to treat him/her appropriately. But, AI and ML have the capacity to recognize various patterns of infection. They suffice to provide real-time, and accurate reports, to the concerned healthcare professional.
Robot Surgeons #
The combination of AI and other computer software suffices to initiate extremely precise and appropriate surgical practices.
Electronic Health Records #
AI is splendid for bringing greatly intuitive interfaces into play for automation. As a result, the administrative department, which oversees creating electronic health records (EHR), will be able to let go off routine and repetitive tasks. The machine will handle the entries of orders, clinical documentation, etc. If the AI developers can introduce automatic dictations, voice recognition, etc., the department will save plenty of time.
Recognition of Risks #
As mentioned earlier, every medical establishment must perforce store vast quantities of patient information in its database. It is a time-consuming task to extract any kind of data, as well as analyze it in an accurate manner. The task is even more difficult, if time is less. But, with AI as an assistant, it becomes possible for healthcare professionals to have comprehensive insights into the concerned patient’s problems, and make beneficial decisions for the same. Thus, AI is a wonderful predictor of risks and errors.
Devices, Machines, Tools #
The integration of AI into smart devices and machines, is perfect for monitoring people requiring critical care. They keep track of the patient’s progress, and prognosis. It serves to prevent healthcare providers from committing errors in advanced diagnosis and overall treatment. Since the devices record everything, they help the healthcare professionals to save on time, and the clinics/hospitals to save on expenses. Above all, the pressure on these professionals to perform beyond their capacities, lessens. Patients are also happy to have reduced manual interactions.
Patients may use them, as well as trackers, for recording the workings of their own bodies. These devices possess sensors, which record even the most sensitive of information. Patients can then convey this data to their primary healthcare providers.
Patients can take selfies, and forward the images to their respective doctors. They must just ensure that their Smartphones have the requisite AI algorithms.
Imaging tools integrated with AI, can help in diagnosing acute/chronic/life-threatening diseases. These tools can become part of mobile applications too. As a result, the shortage of staff, or rather, diagnostic radiologists, should not matter. Even pathological processes can benefit via AI. In short, AI has the capacity to provide data and reports, much faster, and more accurately, than humans do.
Bertalan Mesko declares, ‘AI will not end the era of art in medicine, it will start it as soon as we understand how AI operates. AI will not replace physicians, but those physicians who have AI, will replace those who do not.
To conclude, Big Data Analytics and Artificial Intelligence are becoming vital to the future of the healthcare industry. In fact, they have become even more necessary in the current COVID-19 scenario. Through them, the healthcare industry is looking towards the creation of automated, expert, intelligent systems. They should serve to provide healthcare to people living in the remotest corners of the earth.
Questions and answers #
What is the main point? #
Medicine and IT had been two isolated arenas for centuries.
What else did the original piece say? #
They believed that they had nothing to offer one another.