An Infrastructure Framework for Remote Patient Monitoring Interventions and Research.

Remote patient monitoring (RPM) enables clinicians to maintain and adjust their patients' plan of care by using remotely gathered data, such as vital signs, to proactively make medical decisions about a patient's care. RPM interventions have been touted as a means to improve patient care and well-being while reducing costs and resource needs within the health care ecosystem. However, multiple interworking components must be successfully implemented for an RPM intervention to yield the desired outcomes, and the design and key driver of each component can vary depending on the medical context. This viewpoint and perspective paper presents a 4-component RPM infrastructure framework based on a synthesis of existing literature and practice related to RPM. Specifically, these components are identified and considered: (1) data collection, (2) data transmission and storage, (3) data analysis, and (4) information presentation. Interaction points to consider between components include transmission, interoperability, accessibility, workflow integration, and transparency. Within each of the 4 components, questions affecting research and practice emerge that can affect the outcomes of RPM interventions. This framework provides a holistic perspective of the technologies involved in RPM interventions and how these core elements interact to provide an appropriate infrastructure for deploying RPM in health systems. Further, it provides a common vocabulary to compare and contrast RPM solutions across health contexts and may stimulate new research and intervention opportunities.

Evaluating the success of an emergency response medical information system.

OBJECTIVE: STATPack™ is an information system used to aid in the diagnosis of pathogens in hospitals and state public health laboratories. STATPack™ is used as a communication and telemedicine diagnosis tool during emergencies. This paper explores the success of this emergency response medical information system (ERMIS) using a well-known framework of information systems success developed by DeLone and McLean. METHOD: Using an online survey, the entire population of STATPack™ users evaluated the success of the information system by considering system quality, information quality, system use, intention to use, user satisfaction, individual impact, and organizational impact. RESULTS: The results indicate that the overall quality of this ERMIS (i.e., system quality, information quality, and service quality) has a positive impact on both user satisfaction and intention to use the system. However, given the nature of ERMIS, overall quality does not necessarily predict use of the system. Moreover, the user's satisfaction with the information system positively affected the intention to use the system. User satisfaction, intention to use, and system use had a positive influence on the system's impact on the individual. Finally, the organizational impacts of the system were positively influenced by use of the system and the system's individual impact on the user. CONCLUSIONS: The results of the study demonstrate how to evaluate the success of an ERMIS as well as introduce potential changes in how one applies the DeLone and McLean success model in an emergency response medical information system context.