As digital healthcare expands, ecosystems prioritizing patient safety and well-being will become important. Data security, thus, becomes critical for the information management of sensitive medical records. 

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AI is getting better at doing human work, and it keeps improving all the time. Artificial intelligence and robotics have enormous potential to enhance medical care. The healthcare ecosystem is becoming more and more like our everyday one with the addition of AI and robotics.

Overview

While AI technology is growing fast in today’s business world, it’s also penetrating the medical field. Administrators and caregivers can use it in daily work as it can improve many processes. AI technology is useful in many industries, and healthcare facilities can use it too. 

While research suggests that AI may outperform humans in areas such as disease diagnosis, it will take time before it replaces humans.

With that said, here are the possible questions you might be asking yourself. Is AI already being used in healthcare, and if so, how? To what extent can artificial intelligence (AI) help the healthcare industry? Will it eventually be able to replace humans in emergencies and hospitals?

This article will examine a few AI sub-fields and their role in the healthcare sector.

What Is Artificial Intelligence?

Artificial intelligence is when programmed machines in computer systems mimic human behavior. Natural language processing(NLP), speech recognition, expert systems, and machine vision are ways AI can exist.

The best thing about AI is that it can think and act in ways that increase the possibility of succeeding in a given task. It processes data to find patterns and correlations and then uses these to predict what will happen in the future. 

A chatbot with fed examples of text chats can learn to make lifelike exchanges with people. On the other hand, image recognition software can learn to recognize and describe things in photos by looking at millions of examples.

Functionalities of Artificial Intelligence

There is no limitation to how one can put AI to use. Many fields and industries can benefit from this technology. The healthcare business is actively testing and implementing AI applications, such as medicine dosing, treatment distribution, and surgical procedure assistance.

Other AI-equipped gadgets include chess-playing computers and autonomous vehicles. Any decision made by one of these machines will affect the final product, so it must think things through carefully. For instance, the ultimate goal of a chess game is to emerge victorious. 

The computer system must process all information for self-driving cars to avoid crashing.

A bank’s fraud department can enjoy using AI because the technology can find and flag suspicious financial activities like using a debit card for big purchases or depositing large amounts of money.

Artificial intelligence (AI) applications are also utilized to simplify and improve trade processes. That is achieved by lowering the bar for estimating securities’ supply, demand, and price.

Use of Artificial Intelligence in Healthcare

Artificial intelligence is utilized to aid with diagnosis in the healthcare industry. It is good at triangulating diagnoses based on a patient’s symptoms and vital signs, and it is great at finding even the smallest problems in scans. 

AI is also used to sort patients into different groups, keep track of medical records, and process health insurance claims. In the future of healthcare, there may be virtual doctors, AI-assisted robotic surgery, and shared clinical decision-making.

The Importance of Artificial Intelligence in Healthcare

The following are ways in which AI is helping medical professionals improve the standard of care and the lives of their patients. They include:

• Medical Diagnosis

Deep neural networks do better than radiologists figuring out if someone has pneumonia from a chest X-ray. AI can help radiologists process many imaging volumes more efficiently and accurately. Further, it provides the means to integrate whole-genome and other patient data for use by machine learning algorithms. 

That enables more accurate early detection, diagnosis, differential diagnosis, subclassification, and outcome prediction.

IBM has an AI tool that helps healthcare providers to unlock massive amounts of health data and boost diagnosis. It can process more medical data, including medical publications and treatment case studies.

DeepMind Health at Google works with practitioners to answer important healthcare questions. This technology uses machine learning and systems neuroscience to make artificial neural networks that function like the human brain.

• Decision-Making

Clinical decisions can benefit from predictive analytics, which can rank administrative chores. That is important for improving treatment because it matches health data with the right decisions at the right time.

Pattern recognition is another area where AI is becoming more popular in healthcare. It is used to identify people at risk of contracting a disease because of their lifestyle, environment, genetics, or other factors.

Everything from hearing aids to fitness trackers is now considered wearables. Machine learning and artificial intelligence technologies turn the data from these devices into useful user insights. 

These wearables are significant in the following ways:

• They use data obtained from the motions of a person to help the visually impaired navigate their environments.
• Based on these trends, they can warn epileptic patients before they suffer a seizure.

• Administrative Tasks

A variety of healthcare administration tasks lend themselves well to using artificial intelligence. Compared to patient care, the impact of AI on the healthcare industry has been muted so far. However, AI has the potential to improve administrative procedures in healthcare facilities. Clinical documentation, claims processing, revenue cycle management, and medical records administration are a few areas where AI has improved.

Machine learning is another that matches data across healthcare claims and payment administration databases. The millions of claims submitted daily must be checked for accuracy by insurers and providers. Finding and fixing coding errors and false claims is a win-win for everyone involved.

• Early Detection of Diseases

AI has contributed to the early detection and precise diagnosis of diseases like cancer. The American Cancer Society reports that 50% of mammograms have inaccurate results, leading to cancer diagnosis in healthy women. Artificial intelligence reviews them faster with 99% accuracy, reducing needless biopsies.

Many AI-enabled consumer wearables and other medical devices are also used to track patients with early-stage cardiac disease. That allows doctors and caregivers to catch fatal episodes at an earlier, more curable stage.

• Treatment

AI can help clinicians approach disease management from a wider angle. That includes coordinating care plans and assisting patients in following their treatment programs.

More than 30 years ago, robots began making their way into the medical field. They might be somewhat basic, like those used in a lab, or advanced, like those designed to work with or even replace a human surgeon. They perform various purposes, from laboratory work to surgery, rehabilitation, and physical therapy.

• Training

A basic computer-driven algorithm cannot give trainees the same level of realism as AI. With the development of AI’s natural language processing, the answer to a trainee’s questions, decisions, or suggestions can be harder than it would be for a human. 

In addition, the training program can adapt the difficulty of the exercises based on the student’s answers to them in the past.

And with the power of AI built into a smartphone, you may train after a particularly challenging case at the clinic or on the road.

• Research

Getting a new treatment from the lab to the patient is expensive and time-consuming. The California Biomedical Research Association cites it takes about 12 years to get a new medicine. One in every thousand medications that enter preclinical testing makes it to human testing. Of those, only about one in twenty gets approved for human use.

One of AI’s more recent uses in healthcare is searching for new drugs. If AI technology gets applied to drug development, the time and money required to bring new medications to market could reduce.

Conclusion

Due to rapid growth, the healthcare sector is in for some massive shakeup in the next couple of years. With AI and ML, healthcare providers will improve service and diagnose better. They should embrace change and figure out how to use these disruptive technologies. healthcare is based on data, and a security breach can hurt trust and put health and lives at risk. Businesses need a comprehensive plan to fight the growing risks of cybercrime. When developing privacy safeguards, it is important to consider regulatory requirements. Here is an overview of the threat to healthcare data, the most common compliance standards, and how to protect against it.

Overview

Cybercriminals keep attacking the healthcare industry because patient health information (PHI) is valuable. The average cost of a privacy breach in healthcare was $9.23 million in 2021, and about 714 breaches involved over 500 records. As such, we cannot overstate the significance of safekeeping medical records.

Cybercriminals do not discriminate against their targets. Small healthcare facilities are also susceptible to cyberattacks like large healthcare networks.

The need for consumerization in IT has even reached today’s medical clinics and hospitals. Patients expect efficiency from booking appointments and getting reminders to having video sessions. Modern practice management and patient experience software is becoming popular, which is good in some ways. However, if medical facilities don’t take steps to protect patients’ personal information, they could be in trouble.

This article will discuss keeping healthcare information safe and suggest ways to make the space safer.

Potential Threats to Healthcare Data

Cybercriminals can be very patient and attack your data in various sophisticated ways. Never underestimate their abilities. Here are some of the methods that they use while conducting their operations.

• DDoS Attacks

A distributed denial of service (DDoS) attack attempts to bring down a service, server, or network by overloading it or the infrastructure that supports it. 

DDoS assaults are effective because they draw traffic from many different infected computers. It can take advantage of PCs and other networked resources like the Internet of Things. At a high level, a DDoS assault is like an unforeseen traffic jam that blocks off a highway, making it impossible for ordinary traffic to get through.

• Phishing

Phishing is a social manipulation attack conducted by email, text messages, or any communication medium. Its goal is to get people to give away their credentials, download malicious software, or reveal other sensitive information. The attackers can use the information to get initial access to a healthcare system. That is the most frequent entry point for any attack.

• Ransomware

Ransomware is bad software that encrypts files and asks for money to decrypt them. It encrypts the most sensitive information of a user or company to prevent access to documents, databases, and programs. 

After that, attackers demand a ransom to unlock the features. Because ransomware is so common and can infect databases and file servers quickly, it can bring any business to its knees. It’s becoming more of a problem and costing businesses and governments billions of dollars yearly.

• Mobile Devices

In-patient use of mobile devices for charting and communication and outpatient use of gadgets to interact with patients are rising. Ensure that all patient-facing and internal clinic software complies with the requirements.

• Unauthorized Access or Disclosure

Information is vulnerable to attack from many different sources, not only criminals. Someone in the healthcare field could share private information by email, on paper, by accident, or on purpose. Failure to log out of a healthcare system open to the public could also lead to compliance problems.

Tips for Securing Healthcare Data

It is important to follow compliance requirements when making plans to secure healthcare data. The following are some of the most effective ways:

• Building Capacity Among Health Staff

An efficient way of improving security in the healthcare sector is to increase employee training on common weak points like phishing attacks and other social engineering techniques. It covers other common breach points, like emailing sensitive information or forgetting to log out of systems. Many courses are also available online at no cost.

If staff isn’t trained enough to deal with these problems, it could be a sign that the current healthcare software systems are slowing down workflow and making it take longer to provide care. A specialist in healthcare software may be useful in these situations.

• Safeguard Mobile Devices

Laptops, smartphones, and other portable devices have given people more ways to use Electronic Health Records (EHRs) away from desktops.

However, these possibilities also raise risks to data privacy and security. Although some of these dangers exist within the desktop environment, others are specific to mobile devices.

Whether a doctor uses a tablet to look up a patient’s medical history or a billing clerk submitting an insurance claim, healthcare professionals and covered organizations increasingly rely on mobile devices to get work done. 

The protection of mobile devices requires a wide range of techniques, such as:

• Controlling everything from devices to network settings.
• Providing a means to lock and delete data from a missing device remotely.
• Methods for encrypting application data
• Managing inboxes and attachments helps thwart malware intrusions and stolen information.
• Instructional measures for enhancing mobile device safety.
• Restricting software installation to only those that meet certain criteria.
• Ensure customers install the most recent versions of their apps and operating systems.
• Mandating the use of mobile device management systems and other forms of mobile security software

• Encrypt Patient’s Data

Encryption is a crucial part of healthcare’s big data security infrastructure. It is necessary to transfer and store sensitive data in healthcare institutions safely. Only the intended users and recipients should be able to read the data. If there is a data breach, the bad guys won’t be able to get to the encrypted files because they won’t have the keys to decrypt them. 

Healthcare providers may choose the required encryption methods based on their business operations.

• Conduct Risk Assessments

It’s important to keep an audit trail if something goes wrong, but it’s much more important to take precautions beforehand to avoid problems. Healthcare providers can prevent costly data breaches by building capacity among staff.

Regular risk assessments will identify any risks to the privacy and security of PHI before they lead to a costly data breach. Many businesses and software are available to aid with healthcare facility audit readiness.

The HIPAA Omnibus Rule states that third parties, like business associates and software vendors, must take part in risk assessments. That includes using any third-party service such as Google Docs or any other use or storage of PHI.

• Backup Data to a Safe Location

Protect the integrity of data by backing it up to a safe, offsite location. That will reduce the risk of ransomware, which can be very expensive. Also, ensure that you can always provide accurate patient data. No matter the size of your practice, it is imperative that you have a daily backup.

Think about how ransomware can lead to the disclosure of critical patient information. If data is not backed up, a healthcare company could face catastrophic losses in the event of a crisis, even if it only affects the data center. That’s why it’s important to make regular backups of your data in a safe place away from your computer. 

A backup of data kept in a safe place offsite is also an important part of any plan for dealing with a disaster.

Conclusion

Using Big Data Security in healthcare ensures that important patient data is safe from new threats. That’s because cyberattacks are getting more sophisticated, and privacy issues are worsening.