ABSTRACT
BACKGROUND: There has been a surge in academic and business interest in software as a medical device (SaMD). SaMD enables medical professionals to streamline existing medical practices and make innovative medical processes such as digital therapeutics a reality. Furthermore, SaMD is a billion-dollar market. However, SaMD is not clearly understood as a technological change and emerging industry. OBJECTIVE: This study aims to review the landscape of SaMD in response to increasing interest in SaMD within health systems and regulation. The objectives of the study are to (1) clarify the innovation process of SaMD, (2) identify the prevailing typology of such innovation, and (3) elucidate the underlying mechanisms driving the SaMD innovation process. METHODS: We collected product information on 581 US Food and Drug Administration-approved SaMDs from the OpenFDA website and 268 company profiles of the corresponding manufacturers from Crunchbase, Bloomberg, PichBook.com, and other company websites. In addition to assessing the metadata of SaMD, we used correspondence and business process analysis to assess the distribution of intended use and how SaMDs interact with other devices in the medical process. RESULTS: The current SaMD industry is highly concentrated in medical image processing and radiological analysis. Incumbents in the medical device industry currently lead the market and focus on incremental innovation, whereas new entrants, particularly startups, produce more disruptive innovation. We found that hardware medical device functions as a complementary asset for SaMD, whereas how SaMD interacts with the complementary asset differs according to its intended use. Based on these findings, we propose a regime map that illustrates the SaMD innovation process. CONCLUSIONS: SaMD, as an industry, is nascent and dominated by incremental innovation. The innovation process of the present SaMD industry is shaped by data accessibility, which is key to building disruptive innovation.
Subject(s)
Commerce , Software , Humans , United States , United States Food and Drug AdministrationABSTRACT
Waste management workers experience high stress and physical strain in their work environment, but very little empirical evidence supports effective health management practices for waste management workers. Hence, this study investigated the effects of worker characteristics and biometric indices on workers' physical and psychological loads during waste-handling operations. A biometric measurement system was installed in an industrial waste management facility in Japan to understand the actual working conditions of 29 workers in the facility. It comprised sensing wear for data collection and biometric sensors to measure heart rate (HR) and physical activity (PA) based on electrocardiogram signals. Multiple regression analysis was performed to evaluate significant relationships between the parameters. Although stress level is indicated by the ratio of low frequency (LF) to high frequency (HF) or high LF power in HR, the results showed that compared with workers who did not handle waste, those who did had lower PA and body surface temperature, higher stress, and lower HR variability parameters associated with higher psychological load. There were no significant differences in HR, heart rate interval (RRI), and workload. The psychological load of workers dealing directly with waste was high, regardless of their PA, whereas others had a low psychological load even with high PA. These findings suggest the need to promote sustainable work relationships and a quantitative understanding of harsh working conditions to improve work quality and reduce health hazards.