Adoption of novel biomarker test parameters with machine learning-based algorithms for the early detection of sepsis in hospital practice.

AIMS: We aim (i) to redesign sepsis's clinical pathway and fit the organizational requirements of a novel machine-learning algorithm incorporating a novel biomarker test and (ii) to assess adoption drivers of the new combined technology. BACKGROUND: There is an urgent need to achieve sepsis' early detection and diagnostic excellence. METHODS: A qualitative study based on semi-structured interviews conducted at the target site and across other Italian hospitals. A content analysis was undertaken, emergent themes were selected and categorized, and interviews were conducted until saturation was reached. RESULTS: Sixteen nurses (10 at the target site and six across other hospitals) and nine non-nursing professionals (seven at the target site and two across other hospitals) were interviewed. An organizational redesign was identified as the primary adoption driver. Even though nurses perceived workload increase related to the machine-learning component, technology acceptability was relatively high, as the standardization of tasks was perceived as crucial to improving professional satisfaction. CONCLUSIONS: A novel business-oriented solution based on machine learning requires interprofessional integration, new professional roles, infrastructure improvement, and data integration to be effectively implemented. IMPLICATIONS FOR NURSING MANAGEMENT: Lessons learned from this study suggest the need to involve nurses in the early stages of the design of new machine-learning technologies and the importance of training nurses on sepsis management through the support of disruptive technological innovation.

A Design Method of Tele-Rehabilitation Platforms for Post-Stroke Patients Based on Consumer Technology.

BACKGROUND: Telerehabilitation represents a new cutting-edge method in the treatment of patients suffering from motor and cognitive disorders caused by stroke. Even if there exist dedicated devices able to track patients' movements to evaluate the performed rehabilitation exercises, they require specific settings necessary for a correct and simple use at the patient's home. If we consider the recent pandemic situation and the lockdown condition, which made difficult the access to these products, post stroke patients may be not able to perform home rehabilitation. OBJECTIVES: the goal of this work is the design of a specific method to develop a tele-rehabilitation platform for post-stroke patients using consumer technologies without involving ad-hoc devices. METHOD: Open-source tools have been investigated for speeding up the development starting with the medical knowledge. RESULTS: a group of four healthcare technologies engineering students with no specific skills about computer science has developed a platform in four months using the design method. CONCLUSION: the presented method allowed the development of a clinical knowledge-based web platform for post-stroke patients totally based on consumer technology.