5 AI Applications To Optimize Healthcare Data Management

Artificial intelligence (AI) has proven to have several benefits across different industries and businesses. One sector that has benefitted from the use of AI is the healthcare industry. This sector is always full of patient information, health records, and other important data crucial to patients and hospitals. 

Major problems facing healthcare data are cyberattacks, losing the information, and improper handling, leading to mixing up the records. These mistakes always have devastating effects on the healthcare sector as these medical procedures and other treatments are dependent on these data. In addition, there are other procedures outside the health industry that are dependent on these data. Therefore, properly managing healthcare data is fundamental in the healthcare industry.

The importance of these data has led to the adoption of AI in hospitals to help in the management. Here are some of the applications of AI in optimizing data management: 

• Convenient Data Transmission

Health records are constantly subjected to several transfers among patients, hospitals, remote workers, and other legally entitled parties. When transferring this data, there needs to be a convenient and streamlined way to reach all the desired recipients in time. For example, you may opt to use faxing services, like MyFax, and several others to send the faxes digitally without the need for printing and scanning. 

These modes of data transmission ensure that the records are sent faster and securely. This helps reduce cases of alterations or sending to wrong addresses. With AI, the sharing of information is simplified.

• Data Security 

Several cyberattacks are lodged on these records during these transfers as criminals try to steal or change the records. These attacks are a major concern for the healthcare sector. 

Moreover, even when being stored, patient information is always vulnerable to attacks from hackers. Covering all these attack points manually could be next to impossible, considering the amount of data being held by the information system. 

However, with the application of AI, securing health records against any cyberattacks is promising and fruitful. This is because AI can identify possible entry points for hackers and provide possible solutions for correcting them. Moreover, AI can diagnose the system to identify and correct bugs that would otherwise affect the data management system. 

• Automation Of Data Flow

When patients enter a medical facility, their records are always taken by the hospital from time to time. Each process of their treatment is dependent on the information from the previous step to avoid any cases of errors. The number of patients in the hospital could be challenging to handle if the data flow is done manually. Moreover, handling data manually can lead to confusion.

In contrast, AI automates the data flow from one point to the other, streamlining the whole process. Once the information is entered at the first stage, it becomes accessible for authorized personnel in the hospitals. These records are always entered against a patient's identity, which means very minimal cases of errors. It also becomes easy for return patients to continue their treatment as the complete information is already recorded in the system. 

• Optimizing Data Storage

Traditionally, health records could be stored in paper works and filed for future references. However, this storage has several disadvantages and limitations. 

First, once a record is added, deleting or changing is difficult unless new paperwork is filed. Secondly, paper is limited in storage, and very little information can be stored on a piece of paper. Finally, once you lost these records, it would be difficult to retrieve them due to a lack of backups.

Fortunately, AI changes all these and optimize data storage in many ways. For example, cloud storage can help hospitals store large quantities of data in only one system. In addition, these cloud services have data backup where you can retrieve any lost information. It's also possible to change any medical data without altering the other record elements when storing it in a system.

• Data Analysis And Decision Making 

Another important use of AI when handling health data, especially in big data, is analyzing and interpreting the data. With AI, it's possible to deduce important data points from health records, analyze them, and then present them to understand the chart. This can help in decision-making regarding medical procedures or genetic mapping for patients.

Conclusion 

The healthcare sector is crucial due to the information stored in the systems and their value. Therefore, there's the need to have an efficient data management system that can ensure information security and streamline any process that depends on these data. 

Manual handling of these data has some limitations, unlike AI, which has several applications in health data management. It can be used in automating data flow and aiding in crucial decision making among many others. It's safe to say that the application of AI in healthcare will improve.