Patient Provider Communications will develop EloquenceTM based on data acquired from research conducted by the University of Michigan School of Nursing addressing the specific aims and hypothesis. This project extends the research team's preliminary findings on the development of technology to improve communication with critically ill patients using patient designed communication boards, and the relationship of call light usage with response time to falls and patient satisfaction. The lack of a systematic method for managing call light requests is a patient safety issue and the design of call light technology to make call systems more efficient and effective is needed. EloquenceTM is an advanced patient call light system that will use a touch screen for patients to deliver a specific message to nursing personnel, which will then be directed with an assigned priority ranking to the most appropriate nursing personnel. EloquenceTM will generate patient communication metrics, which will provide a means for safety, quality, and performance improvement initiatives that are unprecedented. Little research has described what use content should be included within such an advanced patient call light system or how that content should be organized, and which nursing personnel should be the initial recipient accountable to respond to each patient need. The long term goal of this project is to develop and commercialize EloquenceTM.
The specific aims of this proposed Phase I study are: (1) To determine a) the most useful and effective use content for EloquenceTM and b) how this content will be organized for patients (e.g. via icons) and directed to licensed versus assistive nursing personnel according to the type of patient request;and (2) To develop an interactive simulation model of EloquenceTM and to examine the usefulness, effectiveness and appropriateness of EloquenceTM in acute inpatient noncritical care units. The sites for this study are 6 adult inpatient units from the University of Michigan Health System (UMHS;913 beds). This study will use focus groups and product development workshops to achieve the specific aims. Responses to focus group questions will be used to test the hypothesis: EloquenceTM can be developed with guidance and feedback from patients and nursing staff who will collectively rate this call light system as being more useful, effective and appropriate as compared with the current patient call light system in the study hospital. This Phase I study will deliver a first-generation model and examine the usefulness, effectiveness, and appropriateness of EloquenceTM. In Phase II, a functional model of EloquenceTM will be developed and tested with patients and nursing personnel in selected adult medical-surgical units in an academic or community hospital for improvements in patient safety (e.g. fall reduction), response time, and improved efficiencies in nursing practice. Depending on outcomes in Phase II, EloquenceTM has the potential to be ranked as the most intelligent call light system, streamlining patient care for hospitals and skilled nursing facilities.
Despite some minor advances, patient call light systems still fail to identify the best recipient of a patient call light request and fail to enable nursing personnel to prioritize their response to call light requests;all of which serve as risk factors contributing to patient falls and indicators of inefficiencies in nursing care deliveries. Inpatient falls consistently comprise the largest single category of reported accidental injuries in hospitals, which may be a consequence of inefficiencies in nursing care deliveries. Consequently, this Phase I study will determine the feasibility of developing EloquenceTM, an advanced patient call light system that seeks to create efficiencies with call light usage, to improve nursing staff responsiveness, and eventually to reduce inpatient falls in inpatient care settings.
|Galinato, Jose; Montie, Mary; Patak, Lance et al. (2015) Perspectives of Nurses and Patients on Call Light Technology. Comput Inform Nurs 33:359-67|