There is an increased need to foster effective and improved dynamics between people, processes, knowledge and technology to generate an output of safety. “Nudges,” which can help optimize choices by encouraging safer and healthier behaviors, are a promising option.
Life sciences companies have a lot of factors to consider when it comes to labeling. Understanding the global labeling regulations for patient safety and how enterprise labeling solutions can help companies achieve compliance while assuring speed to market, and labeling system validation and auditability, can save resources and reduce costly errors.
Including figures and images in clinical research enables researchers to illustrate their findings in a clear, effective and engaging way. Yet, it can be difficult to manually check images for accuracy, introducing the risk of integrity issues. Following we look at best practices and new tools developed to ensure image integrity in clinical research.
The deeper insights provided by a single source of truth help regulatory teams pinpoint and address gaps in data collection during each trial phase. By mitigating potential risks earlier in the process, teams generate more robust evidence and stronger submissions, which often means a shorter approval process.
Inspecting for quality after a process is completed is reactive and outdated. Instead, the future lies in predicting quality and quality issues. For medical device manufacturers, the advantages in predictive quality are so great they simply cannot be ignored.
Connected medical devices have many advantages but require a higher level of security. If the medical industry doesn’t improve its cybersecurity posture, it could endanger patient privacy and lives.
Artificial intelligence has numerous practical applications in diagnostic imaging; the key to making them work for clinicians and patients lies in developing and embracing integrated workflow networks.
Medtech and Biotech companies that prioritize professional development and career growth can reduce turnover and attract new talent. Here is how one company is standing out in a highly competitive employment market.
Remote care in the home relies both on the quality of patient monitoring and on the insights provided to the care team. There is a real danger that data overload and alert fatigue will undermine otherwise well-designed remote patient monitoring (RPM) and Hospital at Home programs. The software platform and algorithms tasked with integrating and evaluating data must identify the data that matters, when it matters.
The key priority for any healthcare system should be the well-being of patients. At present, the U.S. healthcare system is failing to target low-hanging fruit that could help drive better results for patients, and—by catching illnesses earlier—ultimately lower the cost of our healthcare system.
