Patient-centered decision support based on device evidence (I DECIDE)

基于设备证据的以患者为中心的决策支持（I DECIDE）

• 批准号: 8822571
• 负责人: MARIA ADELA GRANDO
• 金额: $ 20.48万
• 依托单位: ARIZONA STATE UNIVERSITY-TEMPE CAMPUS
• 依托单位国家: 美国
• 财政年份: 2014
• 资助国家: 美国
• 起止时间: 2014-09-15 至 2016-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8822571
• 关键词: Accounting; Achievement; Address; Adherence; Adopted; Adult; Affect; Age; Alcohol consumption; Alcohols; American; Area; Arizona; Behavior Therapy; Blood Glucose Self-Monitoring; Blood Pressure; Bolus Infusion; Carbohydrates; Caring; Chronic; Clinic; Clinical; Collection; Complex; Comprehension; Data; Decision Aid; Decision Making; Development; Devices; Diabetes Mellitus; Disadvantaged; Disease; Disease Management; Dose; Exercise; Feasibility Studies; Foundations; Future; Glucose; Goals; Guidelines; Health; Health Status; Health behavior; Heart failure; Human; Individual; Injection of therapeutic agent; Insulin; Insulin Infusion Systems; Insulin-Dependent Diabetes Mellitus; Interview; Knowledge; Lead; Learning; Life Style; Literature; Logic; Lung diseases; Measurement; Methods; Monitor; Morphologic artifacts; Ontology; Outcome; Outpatients; Patient Preferences; Patients; Personal Satisfaction; Phase; Psychosocial Factor; Recommendation; Research; Resources; Review Literature; Self Management; Solutions; Source Code; Suggestion; Surveys; System; Techniques; Testing; Time; To specify; Weight; alcohol content; base; blood glucose regulation; design; dosage; empowered; evidence base; flexibility; improved; information organization; knowledge base; knowledge of results; mathematical algorithm; mobile application; monitoring device; non-compliance; open source; patient oriented; preference; programs; respiratory; satisfaction; treatment planning; usability; user centered design

DESCRIPTION (provided by applicant): Some chronic conditions require patient self-management and behavior modification based on the regular collection of health status data from monitoring devices. Given the high complexity of potential solutions, we focus on a particular use case. Because we will adopt portable, reusable, and extensible ontology-based knowledge representation and reasoning techniques we expect to build foundations for the future development of patient-centered decision aids. To demonstrate the proposed disease self-management decision aid we will implement and evaluate a patient- centered decision system for adult type 1 diabetes outpatients who are using insulin pumps to support the daily task of adjusting pre-meal insulin dosage. As the abundant literature about noncompliance indicates, predetermined self-management care programs are not effective in diabetes care, as they are not tailored to patient priorities, goals, psychosocial factors, and lifestyle. Our hypothesis is that incorporating patient preferences, glycemic and well-being goals, and adherence to health-behavior recommendations will improve decision-making and postprandial glucose levels for individuals with T1D. Our first aim is to learn about diabetes patient preferences and goals by interviewing patients and through bibliographic surveys. Our second aim is to capture in an ontology the knowledge gained from first aim, and build on top of it an argumentation-logic decision aid that suggests treatments that are tailored to patient's clinical state and preferences, in order to achieve active clinical goals. When more than one treatment is available to achieve the clinical goals, the argumentation system compares and ranks options by presenting human-like arguments for and against the proposed treatments. Our third aim is to deploy and evaluate the decision aid. I DECIDE will be deployed as a smartphone application. It will ask patients at the time of the pre-meal insulin dosage their preferences on carbohydrate and alcohol intake, planned after-meal exercise, and provide them suggestions to help them achieve tailored clinical goals. Recommendations will be supported with lay-based explanations to help patients learn how daily choices affect their overall well-being and goals achievement. The decision system will be evaluated with a feasibility study involving adult T1D outpatients in terms of evidence-based compliance, accuracy and comprehension.

描述（由申请人提供）：一些慢性疾病需要患者自我管理和行为改变，基于从监测设备定期收集的健康状态数据。考虑到潜在解决方案的高度复杂性，我们专注于特定的用例。因为我们将采用可移植的，可重用的，可扩展的基于本体的知识表示和推理技术，我们希望建立以病人为中心的决策辅助工具的未来发展的基础。 为了证明所提出的疾病自我管理决策辅助，我们将实施和评估一个以患者为中心的决策系统，用于使用胰岛素泵的成人1型糖尿病门诊患者，以支持调整餐前胰岛素剂量的日常任务。正如大量关于不依从性的文献所表明的那样，预定的自我管理护理程序在糖尿病护理中是无效的，因为它们不适合患者的优先事项、目标、心理社会因素和治疗方法。 因素和生活方式。我们的假设是，将患者的偏好，血糖和幸福的目标，并遵守健康行为的建议，将改善决策和餐后血糖水平的个人与T1D。我们的第一个目标是通过采访患者和文献调查来了解糖尿病患者的偏好和目标。我们的第二个目标是在本体中捕获从第一个目标获得的知识，并在此基础上建立一个论证逻辑决策辅助工具，该工具建议根据患者的临床状态和偏好定制治疗方法，以实现积极的临床目标。当有一种以上的治疗方法可用于实现临床目标时，论证系统通过提出支持和反对所提出的治疗方法的类似人类的论点来比较和排名选项。我们的第三个目标是部署和评估决策辅助。I DECIDE将被部署为智能手机应用程序。它将在餐前胰岛素剂量时询问患者对碳水化合物和酒精摄入的偏好，计划的餐后运动，并为他们提供建议，以帮助他们实现定制的临床目标。建议将得到基于外行的解释的支持，以帮助患者了解日常选择如何影响他们的整体健康和目标实现。将通过一项涉及成人T1D门诊患者的可行性研究，在循证依从性、准确性和理解性方面对决策系统进行评价。