Mobile Decision Support System for Nurse Management of Neuromodulation Therapy

神经调节治疗护士管理移动决策支持系统

• 批准号: 8816815
• 负责人: CHRISTOPHER R BUTSON
• 金额: $ 62.27万
• 依托单位: UNIVERSITY OF UTAH
• 依托单位国家: 美国
• 财政年份: 2015
• 资助国家: 美国
• 起止时间: 2015-02-11 至 2020-01-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8816815
• 关键词: Academic Medical Centers; Address; Alzheimer' s Disease; Applications Grants; Blinded; Caregiver Burden; Caregivers; Caring; Chronic Disease; Clinic; Clinical; Clinical Decision Support Systems; Clinical Informatics; Computer Simulation; Data; Decision Support Systems; Deep Brain Stimulation; Devices; Disease; Dystonia; Electrodes; Enrollment; Essential Tremor; Expert Systems; Family; Family Caregiver; Frequencies; Future; Geographic Locations; Gilles de la Tourette syndrome; Goals; Health Personnel; Home environment; Hour; Implant; Individual; Informatics; Knowledge; Measures; Medical; Mental Depression; Mission; Modeling; Movement Disorders; Neuroanatomy; Nurses; Obsessive-Compulsive Disorder; Online Systems; Operative Surgical Procedures; Outcome; Parkinson Disease; Patients; Physicians; Physiologic pulse; Pilot Projects; Postoperative Period; Process; Public Health; Quality of life; Randomized; Reporting; Research; Research Infrastructure; Savings; Support System; System; Testing; Time; Training; Traumatic Brain Injury; Travel; Visit; Visiting Nurse; Width; Work; base; clinical care; cost; effectiveness measure; experience; improved; innovation; man; nervous system disorder; neuroregulation; nurse performance; primary outcome; programs; public health relevance; secondary outcome; standard care; symptom management; tool; voltage

 DESCRIPTION (provided by applicant): Deep brain stimulation (DBS) has tremendous potential to improve the lives of patients with a wide range of chronic illnesses. Good outcomes from DBS for Parkinson's disease (PD) are strongly correlated to accurate electrode placement and to careful post-operative selection of stimulation parameters (voltage, pulse width, frequency, active electrode contact(s), among others). Although DBS is beneficial for a variety of disorders, a persistent problem has been extensive, costly programming time after the electrode leads are implanted. This is largely because there are very few tools available to assist clinicians in this process, and as a result DBS programming can require a significant degree of experience and expertise, as well as a substantial amount of time for the clinician to search for optimal device settings. Over the last few years computational models have been developed to predict and visualize the effects of DBS based on the neuroanatomy of individual patients. Recently these models have shown promise for improving the efficiency of DBS programming, and have been incorporated into a clinical decision support system. The long-term goal of this research is to improve the lives of patients with neurological disease that are treated with DBS. The objective of this application is to prospec- tively test the use of DBS clinical decision support tool in post-operative clinical care. The central hypothesis is that the use of a DBS clinical decision support system for individual patient management will enable consider- able time savings and reduced burden on patients and caregivers. This hypothesis has been formulated from pilot studies that have shown dramatic decreases in DBS programming time compared to standard care for clinicians who used an iPad-based decision support system (99% time savings from over 4 hours to 2 minutes). The rationale for the proposed research is that computational models, clinical informatics, and mobile computing devices can be used to enable DBS management in a way that has never before been possible. Guided by strong preliminary data, this hypothesis will be tested in two specific aims: 1) Measure the effective- ness of DBS decision support system in an established PD clinic; 2) Measure the effectiveness of DBS deci- sion support system by home health nurses. Under the first aim we will compare programming time and clinical outcomes for patients managed using the clinical decision support system compared to standard care. Under the second aim we will assess the effects of the system on patient and caregiver strain when used by home health nurses. This approach is innovative because it provides an iPad-based clinical decision support applica- tion (app) to enable nurses and physicians to quickly focus on stimulation settings that are likely to be most effective. The proposed research is significant because it will provide powerful tools to the health care provid- ers who will be able to provide the greatest benefit for DBS patients. The knowledge gained could enable a future model for DBS management where care is provided in both clinical and home settings by skilled nurses who use expert systems for guidance.

 描述(申请人提供)：脑深部刺激(DBS)具有巨大的潜力，可以改善各种慢性病患者的生活。DBS治疗帕金森病(PD)的良好结果与准确的电极放置和术后刺激参数(电压、脉冲宽度、频率、主动电极接触等)的仔细选择密切相关(S等)。虽然DBS对多种疾病有益，但在电极导线植入后，一个持续存在的问题是广泛而昂贵的编程时间。这在很大程度上是因为在这一过程中可用于帮助临床医生的工具非常少，因此DBS编程可能需要大量的经验和专业知识，以及临床医生搜索最佳设备设置的大量时间。在过去的几年里，基于单个患者的神经解剖学，已经开发了计算模型来预测和可视化DBS的效果。最近，这些模型已经显示出提高DBS编程效率的前景，并已被纳入临床决策支持系统。这项研究的长期目标是改善接受DBS治疗的神经疾病患者的生活。本应用的目的是前瞻性地测试DBS临床决策支持工具在术后临床护理中的应用。中心假设是，使用DBS临床决策支持系统进行个体患者管理将能够节省可考虑的时间，并减轻患者和照顾者的负担。这一假设是根据试点研究得出的，这些研究表明，与使用基于iPad的决策支持系统的临床医生的标准护理相比，DBS编程时间大幅减少(从4小时以上节省99%的时间到2分钟)。这项拟议研究的基本原理是，可以使用计算模型、临床信息学和移动计算设备以一种前所未有的方式实现DBS管理。在强大的初步数据指导下，这一假设将在两个具体目标上进行检验：1)在已建立的PD诊所测量DBS决策支持系统的有效性；2)测量家庭健康护士对DBS决策支持系统的有效性。在第一个目标下，我们将比较使用临床决策支持系统管理的患者的规划时间和临床结果与标准护理相比。在第二个目标下，我们将评估该系统在家庭健康护士使用时对患者和照顾者压力的影响。这种方法是创新的，因为它提供了基于iPad的临床决策支持应用程序(APP)，使护士和医生能够快速专注于可能最有效的刺激设置。这项拟议的研究具有重要意义，因为它将为能够为DBS患者提供最大利益的卫生保健提供者提供强大的工具。所获得的知识可以使未来的DBS管理模式成为可能，在这种模式下，临床和家庭环境都由熟练的护士提供护理，他们使用专家系统进行指导。