Analysis and visualization of longitudinal assessments of clinical, functional and psychosocial state of AD patients from the Massachusetts home care program

对马萨诸塞州家庭护理项目 AD 患者的临床、功能和心理社会状态的纵向评估进行分析和可视化

• 批准号: 10756631
• 负责人: Niteesh K Choudhry
• 金额: $ 29.91万
• 依托单位: UNIVERSITY OF MASSACHUSETTS AMHERST
• 依托单位国家: 美国
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-09-30 至 2026-05-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10756631
• 关键词: Age; Aging; American; Caring; Case Manager; Clinical; Cognitive; Collaborations; Contracts; Data; Dementia; Elderly; Goals; Home; Home visitation; Intervention; Machine Learning; Massachusetts; Patients; Policies; Predictive Factor; Registered nurse; Research; Research Personnel; Research Project Summaries; Services; Visualization; cost effective; data cleaning; machine learning model; patient home care; programs; psychosocial; research clinical testing

Project summary This research will support MassAITC investigators in a collaboration with the Commonwealth of Massachusetts Executive Office of Elder Affairs (EOEA), which administers state home care programs in Massachusetts. EOEA support a network of 27 regional field agencies administering the Massachusetts state home care program. EOEA has contracted with Aging Service Access Points (ASAPs) to ensure that all consumers receive a comprehensive clinical evaluation in an appropriate and cost-effective manner. To this end, a Care Manager and/or Registered Nurse who is part of the program completes an extensive patient record with each home visit. MassAITC is proposing to use these unique data to develop machine learning models for several different tasks that will help to understand the factors that predict early termination. Our eventual goal is to identify modifiable predictors that could lead to interventions, and as a first step towards that goal, this project begins by cleaning the data to make it ready for machine learning analysis and explore the prediction problems for which sufficient data is present.

项目摘要 这项研究将支持MassAITC研究人员与 马萨诸塞州老年事务执行办公室（EOEA）， 负责管理马萨诸塞州的家庭护理项目。EOEA支持27个网络 管理马萨诸塞州家庭护理计划的地区性现场机构。EOEA 已与老龄服务接入点（ASAP）签订合同，以确保所有消费者 以适当和具有成本效益的方式接受全面的临床评价。 为此，参与该计划的护理经理和/或注册护士 每次家访都要完成大量的患者记录。MassAITC建议 使用这些独特的数据为几个不同的任务开发机器学习模型， 将有助于了解预测提前终止妊娠的因素。我们的最终目标是 确定可导致干预措施的可修改的预测因素，并作为 为了实现这一目标，该项目首先清理数据，使其为机器学习做好准备。 分析和探索有足够数据的预测问题。