Advancing Patient Call Light Systems to Achieve Better Outcomes

描述（由申请人提供）：患者与提供者交流将根据密歇根大学护理学院针对特定目标和假设进行的研究获得的数据开发EloquenceTM。本项目扩展了研究小组的初步研究成果，即利用病人设计的通讯板，发展技术以改善与危重病人的沟通，以及呼叫灯的使用与跌倒反应时间和病人满意度的关系。缺乏一个系统的方法来管理呼叫灯的请求是一个病人的安全问题，呼叫灯技术的设计，使呼叫系统更加高效和有效是必要的。EloquenceTM是一种先进的患者呼叫灯系统，它将使用触摸屏为患者传递特定的信息给护理人员，然后该信息将按照指定的优先级顺序定向到最合适的护理人员。EloquenceTM将生成患者沟通指标，这将为前所未有的安全、质量和性能改进举措提供一种手段。很少有研究描述在这样一个先进的病人呼叫灯系统中应该包括哪些使用内容，或者这些内容应该如何组织，以及哪些护理人员应该是负责响应每个病人需求的初始接受者。该项目的长期目标是开发和商业化EloquenceTM。这项拟议的I期研究的具体目标是：(1)确定a) EloquenceTM最有用和最有效的使用内容，以及b)如何为患者组织这些内容（例如通过图标），并根据患者请求的类型将这些内容指导给有执照的护理人员和辅助护理人员；(2)建立一个EloquenceTM的交互式仿真模型，并检验EloquenceTM在急性住院非重症监护病房的有用性、有效性和适宜性。本研究的地点是密歇根大学卫生系统（UMHS； 913张床位）的6个成人住院病房。这项研究将使用焦点小组和产品开发研讨会来实现具体目标。焦点小组问题的回答将用于验证假设：EloquenceTM可以在患者和护理人员的指导和反馈下开发，他们将共同评价该呼叫灯系统比研究医院当前的患者呼叫灯系统更有用、更有效和更合适。第一阶段的研究将提供第一代模型，并检查EloquenceTM的有用性、有效性和适当性。在第二阶段，将开发一个EloquenceTM的功能模型，并在学术医院或社区医院选定的成人医疗外科单位的患者和护理人员中进行测试，以改善患者安全（例如减少跌倒）、响应时间和护理实践的效率。根据二期试验的结果，EloquenceTM有可能被评为最智能的呼叫灯系统，为医院和专业护理机构简化患者护理。

DESCRIPTION (provided by applicant): 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. PUBLIC HEALTH RELEVANCE: 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.