In the fast-changing and increasingly complex medical device industry, manufacturers are turning to digital tools to ensure their production practices and products meet the highest quality and safety standards. With an increased demand for personalized care and a rising elderly population, the medical device industry is expected to grow at a compound annual rate of 4.5% through 2023. Increasingly, those devices will feature more of the latest embedded technologies. Predictive analytics, apps that integrate with personalized medical devices via Bluetooth, and magnetic stimulation devices are just a few of the innovations the industry sees on the horizon. However, the increased complexity that comes with such innovation threatens to exacerbate the challenges companies face achieving the strict quality standards the industry demands.
The Crippling Cost of Poor Quality
Because quality in medical devices often directly affects patient safety, the risks go beyond financial concerns. Quality manufacturing issues can cost a company, on average, up to $300 million a year, should they face a recall or other quality-related challenges. The amount includes spending to ensure good quality and the direct cost of poor quality. Worse, dysfunctional medical devices reportedly have caused more than 1.7 million injuries and nearly 83,000 deaths since 2008.
Quality lapses arise in a variety of areas. Inaccurate or incomplete medical device records; cyberattacks on networked devices; and uncaptured, lost or expired charges make up most of the cost of poor quality in the industry. In total, estimates indicate that the industry is losing anywhere from $17 billion to $26 billion per year on average as a direct result of devices that don’t meet quality standards.
Improving Quality in the Medical Device Industry
Many—if not most—medical device industry quality issues result from mistakes that occur somewhere along the supply chain or during design, testing, or manufacturing processes. Fortunately, that’s where the latest digital manufacturing technologies can make the most significant impact. To ensure quality, manufacturers must automatically track medical devices through every stage of production and, increasingly, once they’re in use by a patient. Among the most effective technologies are the following:
Intelligent automation: With intelligent automation systems, companies can implement more robust process and product controls. Such automation provides continuous visibility into factory operations and processes, which drives improvements in productivity and quality.
Intelligent systems also automate the all-important tracking and tracing capability necessary to meet ever-stringent medical regulatory requirements, as well as monitor production processes. Instead of using time-consuming manual methods, manufacturers use new systems to record data from every step in the process automatically. With electronic records, companies can more efficiently deliver requested materials to auditors. More importantly, they can more quickly trace any sign of a potential quality issue to its root-cause and address it before product quality is affected.
Data analytics: With data automatically collected from connected intelligent production systems, companies can deploy predictive analytics to improve production processes and product quality. Predictive analytics monitors every machine in the production process in real time, predicting outcomes, and preventing medical device defects. The system alerts operators when predetermined Key Performance Indicators (KPIs) begin to slip out of spec. With early warning and prompt action, manufacturers ensure that no devices are produced by machines that are not in acceptable condition. Also, operators can use predictive analytics to make better decisions.
Artificial Intelligence (AI) and Machine Learning (ML): When predictive analytics is powered by AI and ML, the system continuously learns and optimizes production processes. By implementing AI- and ML-powered predictive analytics, manufacturers can eliminate a great deal of human error in record-keeping, and in-the-moment production decisions. It can also improve patient outcomes and the quality of their care, as predictive models assess resource use and patient risk.
Remote Device Monitoring: Once in use by a patient, a medical device generates massive amounts of data. With a big data and predictive analytics software, manufacturers can capture and analyze this data with unprecedented speed, leading to powerful, actionable conclusions. Device data can be used by the manufacturer to improve device quality and, in partnership with physicians, to personalize the device based on patient vital signs, lifestyle, and other information.
A Higher Standard of Quality is Good for Everybody
Fixing the medical device industry’s quality manufacturing issues isn’t a simple fix. It requires effort on multiple fronts, such as improving record-keeping, optimizing production, and managing complexity. However, the latest digital technologies offer manufacturers a robust, comprehensive solution. By adopting them, they’ll increase operational efficiency, reduce device malfunctions and recalls, and more effectively meet regulatory requirements—even as they become able to offer more innovative and more useful products. They’ll save potentially billions in lost revenue, capture market share, and grow profits. More importantly, however, they’ll reduce—or eliminate—the injuries and death caused by poor-quality devices.