Does new always equal better?

“New” and “improved” have been marketing buzzwords ever since the early days of Madison Avenue. A newer version of a car or airplane or charcoal grill usually is the culmination of years of use and lessons learned from failures. It’s logical to believe that the newest version of something represents the best that technology and human ambition have to offer. But do they always mean the same thing? And how does this relate to medical devices?

The 510k process requires a predicate device

More than eight out of every 10 medical devices that made it to market in 2018 were cleared through the 510k submission process. This is also required when an existing device has significant changes or modifications to design, components, methods of manufacture, or intended uses. The route to the market for these Class II medical devices includes comparisons to a previous device. This is called a predicate. The choice of a predicate device resolves a number of complexities in the approval process. An existing device is assumed to be safe and effective and serves as physical proof that the device is appropriate for medical use. By comparing a new device to this, it creates a standard that the FDA can use to determine the efficacy of the new device.

The issue is that some predicate devices are more than 10 years old. This is an indication that the devices aren’t undergoing significant improvements.

What happens when new doesn’t equal better?

Many Class II medical devices have been recalled or taken out of the market because they were not as good as their predicates. If a device that was cleared is found to not perform as well as the predicate device, it is possible for a manufacturer to use the newer device as a predicate for another device. This would be done to avoid comparisons to an older device that performs better leading to a deterioration of the standard. When new advances in technology are compared to older technology that has successfully been used as a predicate, the new technology may be prevented from reaching the patient.

The FDA is working to streamline the process

It is comforting to think that all medical devices get better with new advancements in technology and by knowledge gained through clinical trials and actual use. The FDA regulations are there to make sure the process evaluates new devices against advances in technology. This new 510k clearance pathway will allow a medical device manufacturer to compare the performance of some new devices to FDA-identified criteria rather than measuring them against predicates. This final guidance is planned to be released by the FDA in 2019. The hope is that these guidelines will be a more logical way to validate new devices, be a quicker pathway to acceptance and use, and eventually supplant predicate device comparisons.

Healthcare has always depended on technology to provide the best care to patients and AI is no exception.

Cutting-edge technology is a wealth of opportunity and nowhere is this more advantageous as healthcare. The world is going through a technological revolution and artificial intelligence is permeating all kinds of industries making processes simpler, quicker, and safer. One area where AI is being deployed is healthcare.

 

From initial hurdles to widespread acceptance

As the use of AI grows, it still has a long way to go to reach mainstream acceptance. Technology is intimidating, especially to people who are used to tried-and-true methods of doing things. To healthcare organizations, we are predisposed to be even more cautious as we deal with matters of life-and-death.

Artificial intelligence and machine learning are going to be game changers to the healthcare industry. Instead of a disruption, stakeholders across the entire healthcare spectrum from doctors to hospital administrators to medical researchers will use this technology in various ways to improve care and bring better patient outcomes.

Managing medical records

The ability to compile and analyze data is critical in healthcare. Data management is a common and obvious use of digital automation. This is especially relevant since medical data can exist in so many different formats. Because of this wide range of data, and the need to accurately, and quickly recall and analyze it, AI allows this process to be manageable and streamlined.

Providing better diagnoses

Diagnostic errors play a role in hospital complications and even patient deaths. The human mind, no matter how educated and experienced, will make mistakes. Artificial intelligence systems can analyze thousands of sources of data, notes, and reports from a patient’s file, external research, healthcare data, clinical knowledge, and case studies to arrive at suggested ways to treat a patient. AI may not be able to be the sole provider of a medical diagnosis, but a hybrid of human problem solving and computer interpretations will result in more precise decisions when it comes to treatments.

Health monitoring

Smartphones and wearable health trackers from companies like Fitbit, Apple, and Garmin can gather an extraordinary amount of medical and fitness data about a patient. This can be used to supply data about patient habits that will help doctors better satisfy their needs.

Drug creation

Clinical trials can take more than a decade to complete and they cost billions of dollars from start to finish. Medical researchers have a difficult task of finding effective and responsible ways of making this process faster. Artificial intelligence is a quicker way to analyze the effectiveness of a drug and measure its ability to treat or cure a condition. Making this process quicker and cheaper can bring life-saving drugs to patients faster and save countless lives.

Doing repetitive tasks

Many medical staffs get caught up in time-consuming, yet important tasks such as analyzing tests, x-rays, and CT scans that can easily be done by AI. This frees staff to concentrate more on patient outcomes rather than following long and tedious processes.

This is only the beginning

Artificial intelligence will continue to have an impact on our daily lives. Data science and medical analytics will influence AI development play a critical role in curing diseases and helping patients live longer, more fulfilling lives. As AI technology continues to grow, healthcare providers like Remington will use it to reduce costs, save time, and allow healthcare providers to provide as accurate a diagnosis as possible.