Advancing Patient Call Light Systems to Achieve Better Outcomes

描述(由申请人提供)：患者提供者通信将基于从密歇根大学护理学院进行的针对特定目标和假设的研究获得的数据来开发EloquenceTM。该项目扩展了研究团队的初步发现，即开发技术，使用患者设计的通信板来改善与危重患者的沟通，以及呼叫灯的使用与跌倒反应时间和患者满意度的关系。缺乏管理呼叫灯请求的系统方法是一个患者安全问题，需要设计呼叫灯技术以使呼叫系统更高效和有效。EloquenceTM是一种先进的患者呼叫灯系统，它将使用触摸屏让患者向护理人员传递特定的信息，然后这些信息将被分配给最合适的护理人员。EloquenceTM将生成患者通信指标，这将为前所未有的安全、质量和性能改进计划提供一种手段。很少有研究描述这样一个先进的患者呼叫灯系统中应该包括什么使用内容，或者应该如何组织这些内容，以及哪些护理人员应该是最初负责响应每个患者需求的接受者。该项目的长期目标是开发EloquenceTM并将其商业化。这项拟议的第一阶段研究的具体目标是：(1)确定EloquenceTM最有用和最有效的使用内容，以及b)这些内容将如何为患者组织(例如通过图标)，并根据患者请求的类型针对持证护理人员和辅助护理人员；以及(2)开发EloquenceTM的交互模拟模型，并检查EloquenceTM在急性住院非危重护理病房中的有用性、有效性和适宜性。这项研究的研究地点是来自密歇根大学卫生系统(UMHS；913张床位)的6个成人住院病房。这项研究将利用焦点小组和产品开发研讨会来实现具体目标。对焦点小组问题的回应将被用来检验假设：EloquenceTM可以在患者和护理人员的指导和反馈下开发，他们将共同评价这种呼叫灯系统比研究医院目前的患者呼叫灯系统更有用、更有效和更合适。这项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EloquenceTM的功能模型，并在学术或社区医院选定的成人内外科病房的患者和护理人员中进行测试，以改善患者的安全性(例如，减少跌倒)、反应时间和护理实践中的效率。根据第二阶段的结果，EloquenceTM有可能被评为最智能的呼叫灯系统，为医院和熟练的护理设施简化患者护理。 与公共卫生相关：尽管取得了一些小的进步，但患者呼叫灯系统仍然无法识别患者呼叫灯请求的最佳接受者，并且无法使护理人员能够优先处理呼叫灯请求；所有这些都是导致患者摔倒的风险因素，也是护理交付效率低下的指标。住院患者跌倒一直是医院报告的最大一类意外伤害，这可能是护理交付效率低下的结果。因此，这项第一阶段研究将确定开发EloquenceTM的可行性，这是一种先进的患者呼叫灯系统，旨在通过呼叫灯的使用来提高效率，改善护理人员的响应能力，并最终减少住院护理环境中的患者跌倒。

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.