A patient-centered mobile intervention to promote self-management and improve patient outcomes in chronic heart failure

 描述(申请人提供)：在美国，心力衰竭(HF)是老年人最常见的出院诊断。大约40%的患者在第一次入院后一年内再次入院，住院费用约占心力衰竭治疗费用的70%。先前的研究表明，病例管理和电话支持在减少HF住院方面是有效的，但这些策略代价高昂。因此，对心力衰竭患者的管理正在从传统的面对面随访的模式演变为一种主动的实时技术模式，帮助患者在社区中进行监测和自我管理。虽然几项HF研究实施了技术驱动的疾病管理计划，但结果喜忧参半。这些系统在向医疗保健提供者提供监测数据和警报方面是有效的，但它们在提供和改变患者行为方面的有效性尚未经过测试。这代表着知识上的一个重大缺口，如果不填补这一缺口，将扼杀自我管理科学的进步。因此，迫切需要开发技术，毫不费力地增加由患者进行的自我监测(主动监测)和由外部设备进行的监测(被动监测)，识别不断恶化的心力衰竭的临床前和临床测量，并提供促进自我管理的行为干预措施，总体目标是减少心力衰竭住院。拟议的项目将确定自我监测移动应用程序对非卧床心力衰竭患者的自我管理、生活质量和入院的影响，确定被动的临床前测量在多大程度上预测心力衰竭临床恶化的症状，并为移动应用程序开发通知消息系统，以通过患者参与者的反馈改善心力衰竭的自我管理。这些数据将对进一步完善我们的干预措施(移动应用程序)至关重要，并将作为未来研究的基础，这些研究将测试移动应用程序，在更大的随机临床试验中，使用强大的推送通知系统与常规护理相比，这种技术方法在改善自我管理和降低疾病发病率方面具有积极意义。它还将促进引进一种新的工具和技术，有可能带来一种自我管理常见和令人衰弱的慢性健康状况的新范例。

 DESCRIPTION (provided by applicant): In the United States, heart failure (HF) is the most common hospital discharge diagnosis among older adults. About 40 percent of patients are readmitted within 1-year following their first admission for HF and hospitalization accounts for approximately 70 percent of the costs of HF management. Previous research shows that case management and telephonic support are effective in reducing HF hospitalizations, but these strategies are costly. As a result, the management of HF patients is evolving from the traditional model of face-to-face follow-up visits toward a proactive real-time technological model of assisting patients with monitoring and self- management while in the community. While several HF studies have implemented technologically-driven disease management programs, results have been mixed. These systems are effective for delivering the monitoring data and alerts to healthcare providers, but they have not been tested for their effectiveness in delivering and modifying patient behavior. This represents a significant gap in knowledge that unless filled will stifle the advancement of self-management science. Therefore, there is a critical need for the development of technologies that effortlessly increase self-monitoring performed by the patient (active monitoring) and monitoring done by external devices (passive monitoring), identify pre-clinical and clinical measurements of worsening HF, and deliver behavioral interventions that promote self-management with an overall goal of reducing HF hospitalizations. The proposed project will determine the impact of a self-monitoring mobile application on self-management, quality of life and hospital admission in ambulatory HF patients, determine the extent to which passive pre- clinical measurements predict symptoms of clinical worsening in HF and develop a notification message system for the mobile application to improve self-management of HF via patient participant feedback. These data will be crucial in further refining our intervention (the mobile application) and serve as the basis for future research that will test the mobile applicatio with a robust push notification system against the usual care in a larger randomized clinical trial This technological approach has positive implications in improving self-management and reducing disease morbidity. It will also foster the introduction of a novel tool and technology tha has the potential to bring about a new paradigm for self-management of common and debilitating chronic health conditions.