The medical device industry has noticed this factor and uses it to save lives. Artificial intelligence (AI) in the life sciences industry is capable of more than one could imagine and it’s changing the future. For example, one organization is creating AI-based voice robot technology, which, according to an article in Management Matters Network, will deliver custom prescriptive advice to managers using strengths and performance data to help better coach and engage employees.
According to the same article, workers are fearful of the future because of potential job loss. However, in terms of quality and safety, it is unlikely this will be the case. In fact, it can create the best- performing companies. In terms of audit management, production, and efficiency, companies have successfully managed audits internally and externally with automated technology for years.
Automated audit management has served as a great source of information to delve deeper into data with predictive intelligence regarding safety and compliance. Leading safety metrics provide:
- Total number of noncompliances
- Number of near-misses enabling investigation to prevent potential incidents
- The time it takes to complete post-audit corrective and preventive actions
- Easy-to-view previous findings for corrective action launches and findings
- Automated audit management software that centralizes all risk items and allows users to automatically assess them and generate reports quickly to pinpoint high-risk gaps that may otherwise go unnoticed
The same goes for automated employee training tools, which create:
- Integration of employee data
- Creation and linking of requirements
- Integration with document control
- Automated testing
- Integration with adverse events, reporting, and change management
Employee training software helps ensure the first step is laid out for proper training. Processes are made intuitive and automatic when integrated with the Quality Management system (QMS), facilitating getting straight to the point without missing crucial details.
Such automated tools allow managers more proactivity in delivering their work, continually making improvements as the organization’s processes and systems grow. Delivering better performance and more reliable end products is the goal of technology as a viable automated tool.
Artificial Intelligence and the Latest Developments
The U.S. Food and Drug Administration (FDA) is creating a new committee solely dedicated to digital health. Policy Advisor Bakul Patel is organizing a team of 13 engineers, software developers, AI experts, and cloud computing specialists to predict and develop regulatory needs for machine-led healthcare.
Life science professionals are excited about the possible future of AI in medical devices. Devices powered by AI have the potential to reduce cost as well as increase diagnostic accuracy. In one example of AI, a computer was able to spot 52 percent of breast cancer cases up to a year before women were officially diagnosed. In terms of early detection and treatment of cancers and diseases, this tool could make a world of difference for patients.
The increased accuracy could also minimize the risk of false diagnosis or intra-operative complications. That way, doctors can focus on developing targeted treatment plans that go above and beyond diagnoses and operations.
Paramedics and hospitals, according to the LNS Research Spotlight, “Leveraging the IoT to Improve Product Quality: What You Need to Know,” are armed with intelligent defibrillators that use biphasics, impedance compensation, and synchronized cardioversion to guide and calculate shock delivery in life-threatening situations. Regarding that bit of information LNS stated that it’s not difficult to picture the smart connected defibrillator feeding back data, along with usage statistics, readiness state, battery life, and other valuable performance metrics both outside and potentially during actual operation. In fact, the spotlight further stated, “using data from hundreds of thousands of devices to derive reliability insight and quality performance information is an example of how applying IoT can improve Design for Quality (DFQ) initiatives.” Usage statistics could even impact healthcare operational and deployment decisions, demonstrating the cross-industry opportunities IoT-driven data can yield.
LNS said, “For the quality management professional, IoT is the gateway to decision driving intelligence in performance, reliability and all manners of in-field product data that was once unique to organizations like space agencies communicating with their assets. This latest technology wave is the engineered product equivalent, based on enabling engineering and development, design-in quality and reliability based on current field data.”
Recently, many forms of rapidly emerging technologies have surfaced that contribute to furthering communication with machines, computers, or other objects. Transforming the way humans track usage and managing anything from road traffic and street lighting to product quality and customer outcomes, the Internet of Things (IoT) is becoming a sure way of making more informed decisions. (“IoT” refers to a network of devices tracking data for an entire host of purposes.)
It is impossible to predict how far healthcare can advance because of AI’s endless possibilities within the IoT. IoT technologies potentially enable billions of everyday devices to become more self-aware and intelligent, negotiating communication with each other via public and private internets in order to create new ways of collaborating, working, and living together.
AI and IoT cooperation accomplishes a new form of communication within organizations. By creating a quality-driven method of assurance that minimizes risk, industry professionals can quickly streamline results that potentially pose harm if gone unnoticed. Users could then be granted the appropriate amount of time to monitor and control the outcome.
According to Waqaas Al-Siddiq, CEO of Biotricity, “Its propensity for automation, machine intelligence, and refined celerity in analyzing disproportionately large and variegated types of data is ideal for transforming the utility of medical device technologies, empowering both patients and healthcare providers alike. AI’s utility for these technologies is predicated on a number of current developments that, once fully matured in the coming years, will enable medical devices to personalize care for individuals from initial diagnosis to ongoing treatments.”
Although some are concerned about loss of jobs due to artificial intelligence, there is also a sufficient amount of information predicting machine intelligence will perfect and improve a variety of outcomes. AI is centered around dynamic algorithms learning from previous data-based experience, like automated audit management and employee training, and is expected to achieve better outcomes as it can, according to Al-Siddiq, “detect anomalies, identify specific medical conditions, or even issue alerts on such information.”
The current developments of AI are disrupting the world of visual perception, speech recognition, decision-making, and translation between languages. There are hundreds of forms of AI and it continues to improve future enhancements in regular everyday devices (like Siri), in healthcare and medicine, and through the exploits of NASA’s Quantum Artificial Intelligence Laboratory.
There are many IBM Watson examples being used in life science fields to review data, complaints, or clinical studies to identify new trends and insights where AI can complete tasks in hours and days—compared to what would normally take weeks or months, or instances that would perhaps go entirely unnoticed. In another example, IBM Research focused on the eye’s retina and detecting abnormalities, potentially offering doctors earlier identification of patients at risk for eye diseases like glaucoma, a leading cause of blindness in the developed world. “Cognitive technology holds immense promise for confirming the accuracy, reproducibility, and efficiency of clinicians’ analyses during the diagnostic workflow,” Dr. Joanna Batstone, vice president and lab director at IBM Research Australia, said in a press release.
The IoT and AI are beginning to substantially impact quality management. By connecting sensors into increasing numbers of products, gadgets can now assess problems directly and quickly without mistakes. This equips quality managers and healthcare professionals with the tools to create and maintain a more proactive approach to their work.
AI technology promises to deliver improved, more reliable end results. Whether in the form of an everyday tool like Siri, a new product being delivered to market, or in healthcare to generate early diagnoses or more accurate results, AI is truly an advantage fostering healthy change.
Strong leadership is the key to building compliance. That said, an organization with the most effective methods for conducting processes will be able to create and ensure quality quicker than before. In any new product market, the time it takes to achieve results is a huge concern. With AI tools, it is becoming easier to achieve standardized testing with better decision-making skills that focus on continuously reducing risk. With that in mind, it is important to evaluate and leverage effective processes with an organization type so that the tools can accurately be used to streamline change.
Artificial intelligence by machine technology is creating 21st century advances in computer power, data and safety within the technology industry built on theoretical understanding. AI techniques have become a critical part of today and are on the brink of progressing our future. A 2017 report by PWC said 72 percent of business decision-makers believe AI will be the advantage of the future, providing a competitive edge on the business front. The report also highlighted trends in the use of AI with companies, for example: how AI can shift human tasks from menial to strategic; freeing up time for innovation and the broader, bigger-picture thinking leading to transformation; where AI provides the greatest business advantages and how it can be leveraged across an enterprise; the integration of AI into customer service roles; and where customers are most willing and sometimes eager to embrace AI.
Consumers believe AI will provide solutions to major issues they’re concerned with today like global health and well-being, economic growth, climate change, cybersecurity and privacy, cancer and diseases, clean energy, and more.
Emily Ysaguirre is a marketing content writer for ETQ . She is responsible for developing and writing content for EtQ, a leading enterprise quality and compliance management software vendor, as well as traqpath, EtQ’s compliance and event-tracking solution.