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Big Data and AI for Healthcare Sector

Akhil Kumar By Akhil Kumar | June 19, 2020
big data and ai for healthcare sector

Big data and AI in healthcare sector – an intelligent blend of new-age necessity and technology. The healthcare industry is booming at a faster rate and the dire need to attend and manage patients is also getting increased. 

To curb such a situation, more number of newer technologies are required and need to be implemented. The minimalist issue that arises here is storing and analyzing the humongous data of the patients. 

Big data in healthcare sector here has the potential to take over the procedure keeping everything streamlined and handy. As per the report by International Data Corporation (IDC) found that big data is projected to grow way faster in the healthcare domain as compared to Manufacturing, financial services, media, and others. Apart from that, big data will experience a compound annual growth rate (CAGR) of 36% by 2025. 

When this one was about storing the data, the next-gen technology AI in healthcare simplifies the lives of doctors, hospital administrations along with patients, by digitally performing tasks that one requires manual assistance. Also, a fraction of seconds and the work is done. This makes it easy and less time consuming for the healthcare personnel to focus on major tasks too. 

Big data and AI in healthcare sector, with their features and mechanism, are making the healthcare domain extremely intelligent and quick. 

To understand their what and how- a few scrolls and you will get to know big data and AI in healthcare sector dominance. 

So, without further ado, let’s get started with Big Data and its core role in the healthcare domain first- 

What is Big Data in Healthcare Sector?

Big data analytics in healthcare carry a lot of importance offering life-saving outcomes. In a simplistic language, Big Data is the vast quantity of information created by the digitization of a system that further gets analyzed by specific technologies. 

When used in the healthcare industry, Big data solutions use health data of patients and help further to prevent epidemics, costings, and curing diseases, etc.

Using the pre-stored data, doctors can analyze and understand the signs of diseases, cause, and others before they actually arise in the human body. Thus, treating the disease at an early stage becomes simpler and a little less economic. This will also result in bringing a tailored made solution to the patients. 

Furthermore, the big data in healthcare sector extracted from the medical places is not just stored but also gets converted into relevant insights that can be further used for better solutions. 

Big data when doing that has made its stable position in the healthcare domain by offering lots of things. Let’s check them out now- 

Role of Big Data in Healthcare 

role of big data in healthcare sector

1.Patient Predictions

One of the major concerns of healthcare professionals is to make a balance between how many workers should be made available at the given point of time. 

Putting too many workers at a time can cost more labor costs whereas too few workers can come up with poor customer service. The latter can be fatal to the patient’s life in the healthcare industry. 

Here, big data analytics in healthcare helps in solving such issues. The technology uses a variety of sources to gain predictions of how many patients are expected to come up to the hospitals. The analysis allows researchers to understand relevant patterns in patients’ admission rates. Once done with the analysis, the next moment, machine learning makes an entrance for finding the accurate algorithms for future admission trends. 

2.Electronic Health Records

Big data analytics in healthcare consists of Electronic health records- acknowledged as the second most widespread application of big data made into the healthcare domain. Each and every patient has their own digital records that include medical history, test results, past diagnosis, demographics, and so on. These records are then shared via a secure information system that is made available to both the providers. 

Here the role of big data in healthcare is to make records that are composed of the modifiable file that makes doctors implement changes to eliminate the need for paperwork and no data replication requirements.

Apart from that, EHRs offer reminders and warnings whenever a patient opts for a new lab test or tracks prescriptions. This helps in gaining an understanding of whether a patient is following the doctor’s prescriptions or not. 

A McKinsey report on big data healthcare states that “The integrated system has improved outcomes in cardiovascular disease and achieved an estimated $1 billion in savings from reduced office visits and lab tests.”

3.Real-time Alerts

One of the best advantages of big data analytics in healthcare is timely real-time alerts. Clinical Decision Support (CDS) software intelligently analyzed medical reports on the given point of time and then forward it to the healthcare practitioners in order to let them make prescriptive decisions. 

Wearable technology trends are the best way that can easily collect patients’ health data accordingly and then send that data to the cloud storage. Additional information can also be accessed to the database stored helping doctors to compare the healthcare data on the basis of socioeconomic content. The data can be further modified for delivery strategies. 

For instance, if a patient’s blood pressure increases suddenly, the system will send alerts in real-time to the patient’s doctor. Once done with the alert, the following action takes place to reach the patient for measuring the pressure. 

One of the examples is Asthmapolis that has started to make use of inhalers with GPS-Enabled Trackers for identifying asthma trends. 

4.Patient Engagement

Starting from healthcare professionals to the patients, everyone’s interest has started for smart devices. Smart devices can record every step, heart rates, health monitoring, sleeping habits, walking distance, etc on a daily basis.

The information can be circulated with other trackable data in order to identify potential health risks. This way, a patient is involved in the monitoring of his/her own health and health monitoring. Wearables trends here have taken the major role here along with tracking specific health trends and relying on top cloud technology trends in order to let physicians monitor the health parameters. 

5.Informed Strategic Planning

Just like Iot in healthcare, Big data in healthcare allows strategic planning in order to gain insights into the patient’s health and motivations. Using the insights of patient’s health check-up results residing in different demographic groups, it becomes easy for healthcare professionals to understand what’s discouraging people from taking up treatments. 

One such example of big data in healthcare sector is the University of Florida who made use of Google Maps and free public health data for preparing heat maps. These heat maps are then targeted at multiple issues like population growth and chronic diseases. 

Using big data trends and informed strategic planning makes it streamline to understand what arises as an issue for the patient. Once gaining such insights, figuring out solutions and ways becomes less challenging. 

6.Reduction in Cost

Big data in healthcare sector is the best way to save a few bucks on hospitals when it comes to over or under book staff members. With the help of predictive analysis, getting a prediction of admission rates will help staffing allocations. 

The right allocation of staff members will reduce the rate of investment incurred by the hospitals and can utilize the secure amount of some other investment projects. By developing wearables and health trackers can make patients eliminate frequent visits to the hospital. Through trackers, it can save the time of both patients and doctors to curb any issues related to staff and beds availability. 

Predictive analytics makes it easy to reduce the cost of hospital readmissions. 

As per the report by the Society of Actuaries, 47% of healthcare organizations are using Predictive analytics. Around 57% of healthcare sectors believe that Predictive analytics can save up to 25% of the company’s annual costs.

McKinsey & Company report states that after 20 years of steady increases, healthcare expenses now represent 17.6% of GDP, ie. nearly $600 billion more than the expected benchmark for the U.S. size and wealth.

7.Medical Human Errors

The next application of big data analytics in healthcare is medical errors. Humans are prone to numerous errors and a lot of times, it has been noticed that healthcare professionals unintentionally prescribe wrong medicine or dispatch different medicines. 

The impact of big data in healthcare helps in reducing human errors by analyzing user data along with scanning their patient’s medical records and identifying potential errors. Once done with this. Prescribed medication is then placed. This will result in zero human errors and better medical solutions. 

Check out- how mobile app healthcare advantages are serving patients and doctors. 

The Centers for Medicare and Medicaid Services saved over $210.7 million in healthcare fraud in one year using predictive analytics. 

8.Fraud and Enhance Security

The Healthcare industry is prone to 200% of data breaches experiences than any other domain. But this situation can be prevented by big data analytics in healthcare. The analytics can prevent security threats by correctly identifying changes in network traffic and other cybersecurity issues. 

The Centers for Medicare and Medicaid Services said they saved over $210.7 million in fraud in just a year.

9.Telemedicine

Telemedicine is available in the market for over 40 years until now. The arrival of online video conferences, wireless devices, smartphones, and wearables devices which has made telemedicine bloom. 

Role of big data in healthcare is vividly used for primary consultations and initial diagnosis, medical education for professionals, remote patient monitoring, and others. Some of the best use of this technology is telesurgery. Telesurgery allows doctors to perform operations using robots and high-speed real-time data delivery without being physically available.  

Know also- Impact on telemedicines apps amid COVID-19

On the other hand, Clinicians use telemedicine for offering personalized treatment plans while preventing hospitalization or re-admission. Also, telemedicine predicts actual medical events prior to the actual occurrence while preventing deterioration of the patient’s conditions.

Also, telemedicine can help in reducing costs along with improving the quality of service too. 

10.Big Data for Medical Imaging

Over 600 million imaging procedures take place in the US every year. Now, analyzing and storing this much of images is both- expensive and time-consuming. Carestream explains how big data analytics can change the way images are read. The algorithms developed can analyze thousands of images identifying patterns in the form of pixels and then convert them into a number for easing the work processes of healthcare professionals. 

And there are more advantages of Big data in the field of healthcare helping both patients and healthcare professionals. Using big data, many medical professional firms are using it wholeheartedly.

Let’s have a look at big data healthcare companies- 

Who is using Big Data in Healthcare?

Flatiron Health

One of the first big data examples in healthcare is Flatiron Health. It uses billions of data points from cancer patients in order to gain new insights for research purposes. Here, the platform connects everyone, from oncologists, academics, hospitals, researchers, and others to learn from each patient.

Digital Reasoning Systems

The next application of big data analytics in healthcare is Digital Reasoning Systems that offers hospitals deep analytics and natural language in order to understand solutions that can further assist with repetitive and routine tasks.

Pieces Technologies

A cloud-based software company Pieces Technologies collects data from the patient’s healthcare journey for improving quality and care costs. Its flagship product- Pieces Decision Sciences offers recommendations and makes decisions on a variety of data like lab results, structured or unstructured data. 

Amitech

Last but not the least big data examples in healthcare is Amitech. From healthcare analytics to modern data management, Amitech is utilized for population health management solutions. The solutions are then presented by combining physical and behavioral health data for identifying risks and also engaging patients with their own healthcare tracking. 

When using the latest technology for great solutions, the technology itself comes with its own set of challenges.

Let’s have a look at the challenges too- 

What are the challenges with Big Data in Healthcare?

  1. Storage

One of the biggest challenges of big data in healthcare is storage. Storing enormous data on an everyday basis is nothing less than a challenge. Though, big data is also filled with a plethora of advantages in terms of control over security, up-time, access, and more. However,  an on-site server network is expensive to scale and difficult to maintain as well. 

To put a stop to storage issues, using big data that is supported by cloud infrastructure can be the best option as cloud storage offers lower up-front costs, nimble disaster recovery, and easier expansion. 

2.Cleaning

For accuracy in results, correctness, relevancy, consistency, and purity, the big data in healthcare sector is also required to be cleansed. This is the next challenge that is required to be curbed using either an automated process or through manual cleaning approach. Using sophisticated and precise tools help in reducing time and expenses. 

3.Unified Format

A vast amount of patient’s data is produced every day and it is not easy to store data using the traditional EHR approach. The tasks become more challenging when it comes to managing big data from billing purposes, clinical analytics, claims, and so on. 

Hence, medical coding systems like the International Classification of Diseases (ICD) code and Current Procedural Terminology (CPT) sets were developed for representing core clinical concepts. 

4.Data Accuracy

There are many chances when the data recorded from EMRs or EHRs often doesn’t carry accurate information. The reason can be complexity in workflows. Such reasons can become an issue for big data in healthcare sector. As everything is stored in big data, a minor miss in the data accuracy can present different results. Due to differences in automated results, further processes will also get affected. 

5.Image Pre-Processing

The role of big data in healthcare can be seen as Physical factors can alter data quality and misinterpretations from previous medical records. Similarly, medical images often suffer from technical errors like artifacts and types of noise. Other than that, the wrong handling of images can also cause tampered images. 

This altered process goes straight to the big data and presents faulty results. 

6.Meta-Data

Meta-data is information composed of various things like time of creation, the person responsible for the data, purpose, previous usages, etc. These are required by researchers and big data analytics in healthcare for various purposes. Hence, accurate and up-to-date metadata is also important.

When offered the right and exact meta-data information, it increases the usefulness of data while preventing data of low or no use. 

7.Data Sharing

The next difference between big data and AI in healthcare sector is that the former one is known for offering healthcare to multiple locations which can be a little challenging. If rendering the service, sharing data with the other healthcare organizations is also essential. But if the data is not interoperable, then in such a situation information sharing between organizations could be lowered. The fault can occur due to technical and organizational barriers. 

This will make healthcare professionals challenge themselves to come up with accurate and right solutions. In such a situation, solutions like CommonWell (a not-for-profit trade association) and Carequality (a consensus-built, common interoperability framework), Fast Healthcare Interoperability Resource (FHIR), and public APIs are making data interoperability easier and secure. 

Attending to the core functionality and role of big data in healthcare, let us now move on to the role of artificial intelligence in healthcare. 

What is AI in Healthcare?

Artificial intelligence is what a human can do, perform, and say. When it comes to artificial intelligence in the healthcare domain, technology can simplify the tasks of both the patient and the doctors by performing various different tasks. 

Machine learning- a subset of AI has the potential to offer data-driven clinical decision support to healthcare professionals and physicians. The technology can also identify patterns, algorithms, and data for more precise automated insights to healthcare professionals. 

According to Ron Moody, Accenture’s chief medical officer stated “Artificial intelligence (AI) is poised to revolutionize healthcare operations, health research, the delivery of medical care and how patients are supported to maintain health. It is and will be a critical part of long-term healthcare solutions.”

With it, let’s get started with the role of artificial intelligence in healthcare.

Role of AI in Healthcare Sector

role of ai in healthcare sector
  1. Unifying Minds

Computers are not just a means of communication but also a way to create direct interfaces between technology & the human mind eliminating the need for keywords, monitors. 

Moving to Traumas and neurological disorders- something that can take patients’ ability to move, speak, or interact properly with their surroundings. Thankfully, brain-computer interfaces (BCIs) made with the help of AI have the potential to restore the fundamental experiences. 

2.Next-Gen Radiology Tools

MRI machines, CT scanners, X-rays offer non-invasive visibility into the workings of the human body and these images are the form of radiological images. And on the other hand, the use of tissue samples also takes place that forms the risk of infections. 

As per experts, the use of artificial intelligence in healthcare can enable the next generation of radiology tools- detailed and accurate can replace the need for tissue samples in many cases. 

This way clinicians can take a look at how tumors behave rather than dependent upon treatment decisions. Also, defining the aggressiveness of cancers and targeted treatment can also be made through AI. 

3.Expanding Access to the Region

Healthcare is something that works 24*7 and shortages of doctors can cause a severe threat to the life of people. Now, when it comes to ultrasound technicians and radiologist limitations, it is a great threat.  

Luckily, the role of ai in healthcare  can mitigate the impacts of deficiency of qualified staff by performing diagnostic duties. Diagnostic duties that are meant to be done by humans only. 

Take for example- an AI imaging tool can screen chest X rays for finding the signs of tuberculosis. The process can be done with the help of mobile applications aiding the shortage of diagnostic radiologists. 

Check out- why to invest in AI app development

4.Electronic Health Records

Just like the role of artificial intelligence in retail industry, AI is considered the best asset for healthcare too. It’s EHRs are considered the best known for playing a great role in the healthcare industry. But it does come up with its own set of issues. 

To curb any kind of related issue, using AI ML development, EHR developers are using AI for creating more intuitive interfaces in order to automate repetitive and routine tasks. 

This will not only save the time of healthcare professionals but also the time of users. Users majorly spend their time on tasks like clinical documentation, order entry. This can further aid by voice recognition, dictations, and NLP.  

Read also- A beginners guide to Natural Language Processing 

5.Risks of Antibiotic Resistance

Antibiotics are important and antibiotics resistance can be a threat to the people as treatment will no longer affect the superbugs. The more drug-resistant capability, the more are the chances of failed treatments. 

By leveraging machine learning, and use of artificial intelligence in healthcare and tools and the use of EHR can help in identifying infection patterns and can also help in enhancing the accuracy and faster alerts. 

Know more- A beginner’s guide to machine learning.

6.Precise Analytics

Pathologists provide significant sources of diagnostics data for further processes. The right pathology report can greatly help in a more accurate diagnosis. And integrating AI in healthcare into the pathological process can greatly help in delivering way more accurate and precise results. 

Things and nuances that might escape by the human eye can be caught by Artificial intelligence.

So, yes AI in healthcare does have the power to ease the manual work by creating faster reports and data. 

7.Medical Devices and Machines

Smart devices are capable of offering various things to users like real-time video, videos of healthcare services, and others. When it comes to the core mechanism of medical services, smart devices can greatly help in monitoring patients in the ICU or somewhere else. And integration of AI in healthcare into the devices can altogether enhance the ability to identify the deteriorating stage too. 

The overall mechanism will help hospitals to save costs along with escaping from severe penalties too. Furthermore, the pressure on healthcare professionals will also be reduced and patient care can also be done without too much manual interference. 

8.Risk Predictor

EHRs are the tool that can store the humongous amount of patient data but at the same time extracting, analyzing them in an accurate, reliable, and timely manner is a task for both the providers and developers. 

Data quality, unstructured inputs, mismatch details, incomplete records can be difficult to understand in order to gain meaningful insights, predictive analytics, and clinical decision. 

This will increase the difficulty level for doctors to get started with the treatment, or analysis procedures. But use of ai in healthcare into the system will make it easy to gain insights without errors or faults. 

9.Wearables and Personal Devices

A large number of audiences are using digital devices and sensors that can collect their health-related data. Wearables and trackers are the most obvious devices. 

These devices are quite useful and ai applications in healthcare used for the core functioning can extract more actionable information. 

10.Selfies into Tool

Images taken from smartphones and devices can generate clinical quality imaging especially in underserved populations or developing countries. 

Due to the quality of smartphone cameras increasing, producing images through AI algorithms can help healthcare professionals to gain valuable insights. 

For example- Researchers in the UK have developed a tool that can identify development diseases through a child’s face. The tool through the algorithm can detect discrete features like a child’s jawline, eye, nose placement, and many more.

11.Intelligent Robot-Assisted Surgery

Robotics surgery is in the market for many years like aid to human fatigue and exhaustion. Using AI visioned with computer software can achieve a new level of precision allowing robot surgeons to perform surgery properly. 

The numerous benefits of Artificial intelligence still got a few lags. Let’s check out the challenges associated with AI in healthcare sector. 

Challenges with AI In Healthcare Sector

1.Accuracy & Safety

One of the very first challenges of AI in healthcare sector is accuracy & safety. Though AI has the potential to provide more accurate and reliable information. As the healthcare documents consist of patient sensitive data, thus it has to be reliable enough to safeguard data. 

2.Risk in Cases

The right use of AI in healthcare requires to be accurate & safe along with providing instant information with the new health cases. For that matter, a program needs to be trained and developed in an intelligent manner. Also, feeding intelligence with constant updates is also important. 

3.Risk for Healthcare Professionals

Role of AI in healthcare is a boon for healthcare professionals but at the same time, it can never replace the importance of doctors and patients. Doctors can never rely fully on AI and still need to make decisions based on their knowledge and experience. 

On the other hand, Patients are also at higher risk by relying fully on artificial intelligence. If the program provides wrong or incorrect information, the technology can still become a threat to the user’s life. 

By bringing out the solution from challenges, AI still poses as a hero in the field of healthcare. To witness it, let’s have a look at firms or healthcare organizations using it. 

Companies using AI in Healthcare Sector

  1. Buoy Health

Buoy’s role of AI in Healthcare based Symptom and cure checker. It uses algorithms for diagnosing and treating expected illness. 

A chatbot integrated to the system can listen to the patient’s symptoms and other related concerns. Using it, the chatbot then further guides the patient for better diagnosis. 

For example- Harvard Medical School is one of the hospital and healthcare providers that is suing Buoy’s AI for diagnosing and treating patients. 

Know also- how chatbots providing COVID-19 Information

2.BioXcel Therapeutics

BioXcel Therapeutics is using AI for identifying and developing new medicines when it comes to immuno-oncology and neuroscience. The company’s drug re-innovation program uses AI for finding new applications for identifying new patients and also existing drugs. 

Also, it is named as the “Most Innovative Healthcare AI Developments of 2019.”

3.Olive

The AI platform designed for Olive is made to automate the repetitive tasks of the healthcare industry. It also helps in freeing up the administration’s tasks too. Olive’s AI platform also automates everything starting from eligibility checks to claims made and data migrations. This will make healthcare staffers provide better services to the patients. 

4.Tempus

Tempus uses AI for offering personalized healthcare treatments. Also, the firm is developing AI tools for collecting and analyzing data starting from image recognition to genetic sequencing offering better insights to healthcare professionals. 

The company is currently using AI-driven data to tackle cancer research and treatment.

These are a few names in the list of firms using artificial intelligence in healthcare and also for better medical services. 

Conclusion

Both big data and AI in healthcare sector are quite capable of transforming the whole healthcare domain into intelligent & automatic systems. In the coming years, with the advancement in technology & expertise, together the technologies will remain on the top. 

If you still have doubts, connect with our experts. 

Akhil Kumar
Akhil Kumar

Co-Founder & Managing Director of AppVenturez Mobitech. An entrepreneur who is tech-savvy and aims to build the largest software business through technological innovation, keen business strategist and a passionate technocrat. He firmly believes in learning and earning by planning and performing.

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