Understanding and Predicting High-Need, High-Cost Patients among Older Adults

了解和预测老年人中高需求、高费用的患者

• 批准号: 10606948
• 负责人: Yongkang Zhang
• 金额: $ 24.9万
• 依托单位: WEILL MEDICAL COLL OF CORNELL UNIV
• 依托单位国家: 美国
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-07-01 至 2024-04-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10606948
• 关键词: Adult; Applications Grants; Area; Award; Behavioral; Calibration; Caring; Characteristics; Chronic; Clinical; Complex; Data; Data Science; Data Set; Doctor of Philosophy; Elderly; Foundations; Funding; Geriatrics; Goals; Health Policy; Health system; Healthcare; Individual; Intervention; Knowledge; Light; Literature; Machine Learning; Medical; Medicare; Mentors; Methods; Modeling; National Institute on Aging; Neighborhoods; Outcome; Pathway interactions; Patient risk; Patients; Pattern; Performance; Pharmaceutical Preparations; Phase; Policy Research; Postdoctoral Fellow; Predictive Value; Process; Public Health; Public Health Informatics; Research; Research Personnel; Research Training; Resources; Risk; Risk Adjustment; Risk Factors; Safety; Sensitivity and Specificity; Social Conditions; Taxonomy; Testing; Time; Training; Work; base; behavioral health; care coordination; career; clinical decision-making; clinical risk; comorbidity; cost; distinguished professor; effective intervention; experience; frailty; gradient boosting; health care delivery; health care quality; health care service organization; health care service utilization; health data; improved; machine learning method; machine learning model; machine learning prediction; medical schools; mid-career faculty; multilayer perceptron; multiple chronic conditions; novel; patient oriented; performance tests; post-doctoral training; predictive modeling; professor; programs; random forest; risk prediction; social; social vulnerability; tool

PROJECT SUMMARY/ABSTRACT This is a K99/R00 Pathway to Independence Award submitted to the National Institute on Aging by Yongkang Zhang, a Research Associate in the Department of Healthcare Policy and Research at Weill Cornell Medical College (WCMC). Dr. Zhang’s career goal is to become an independent researcher on improving care for the elderly through developing and applying effective prediction tools to identify older adults with complex conditions and high healthcare needs. This K99/R00 application will provide Dr. Zhang with the necessary training 1) to understand the complexity and characteristics of high-need, high-cost (HNHC) older adults; 2) to develop a prediction model for HNHC adults using machine learning methods; and 3) to test the performance of the machine learning-based model with three commonly used, patient-risk prediction tools. Dr. Zhang has assembled a mentor team of accomplished researchers across multiple divisions and departments at Weill Cornell Medical College: Dr. Rainu Kaushal (primary mentor) who is the Nanette Laitman Distinguished Professor and an expert on the HNHC patients and health data science; Dr. Lawrence Casalino (co-mentor) who is the Livingston Farrand Professor of Public Health and an expert on characteristics of and healthcare delivery for HNHC patients; Dr. Mark Lachs (co-mentor) who is a Professor of Geriatrics and prac- ticing geriatrician and an expert on the complexity and healthcare needs of older adults; Dr. Yuhua Bao (co- mentor) who is an Associate Professor of Healthcare Policy and Research and expert on behavioral health conditions and prescription data; Dr. Fei Wang (co-mentor) who is an Associate Professor of Health Informat- ics and an expert on machine learning methods; and Dr. James Flory (consultant) who is an Assistant Profes- sor of Healthcare Policy and Research and practicing clinician and an expert on medication use. HNHC older adults are small group of patients representing a disproportionate share of healthcare utili- zation. These patients are more likely to experience preventable quality and safety problems due to their fre- quent interactions with health systems. Caring for HNHC older adults provides great potential benefits for qual- ity improvement and cost reduction. However, the benefits are unlikely to be realized unless these patients can be correctly identified and targeted. Building on his previous research and training on developing a claims data-based taxonomy for HNHC Medicare patients, Dr. Zhang’s research will understand the characteristics of HNHC older adults and develop predictors for these patients using clinical and prescription data (Aim 1), de- velop a machine learning-based prediction model for HNHC older adults (Aim 2), and compare the perfor- mance of the prediction model with three commonly used, patient risk prediction tools (Aim 3). This research will be the foundation for an R01 grant application that will incorporate this prediction model into healthcare de- livery process and identify the optimal ways to inform opportunities for improvement in healthcare delivery.

项目总结/摘要 这是K99/R00独立之路奖提交给国家老龄化研究所， 张永康，威尔康奈尔大学医疗保健政策与研究系副研究员 医学院（WCMC）。张博士的职业目标是成为一名独立的研究人员， 通过开发和应用有效的预测工具来识别老年人的复杂性， 条件和高医疗保健需求。此K99/R00应用程序将为张博士提供必要的 培训1）了解高需求，高成本（HNHC）老年人的复杂性和特点; 2） 使用机器学习方法为HNHC成人开发预测模型;以及3）测试性能 基于机器学习的模型与三种常用的患者风险预测工具。 张博士组建了一个由多个部门的优秀研究人员组成的导师团队， 威尔康奈尔医学院各部门：Rainu Kaushal博士（主要导师），Nanette Laitman 杰出教授和HNHC患者和健康数据科学专家; Lawrence卡萨利诺博士 （共同导师）谁是公共卫生的利文斯顿法兰德教授和专家的特点， 为HNHC患者提供医疗保健服务; Mark Lachs博士（共同导师）是老年医学和实践教授， 老年医学专家和老年人的复杂性和医疗保健需求的专家; Yuhua Bao博士（合作， 导师），他是医疗保健政策和研究的副教授，也是行为健康专家 条件和处方数据; Fei Wang博士（共同导师）是健康信息学副教授， ics和机器学习方法专家;以及James Flory博士（顾问），他是助理教授， 卫生保健政策和研究分类以及执业临床医生和药物使用专家。 HNHC老年人是一小群患者，占医疗保健利用的比例不成比例， zation.这些患者更有可能遇到可预防的质量和安全问题，因为他们的自由， 与卫生系统的互动。照顾HNHC老年人提供了巨大的潜在利益， 提高效率和降低成本。然而，除非这些患者能够 正确识别和定位。根据他以前的研究和培训， 基于HNHC医疗保险患者的数据分类，张博士的研究将了解 HNHC老年人，并使用临床和处方数据为这些患者开发预测因子（目的1）， 为HNHC老年人开发一个基于机器学习的预测模型（目标2），并比较其性能。 使用三种常用的患者风险预测工具（目标3）管理预测模型。本研究 将成为R01资助申请的基础，该资助申请将把该预测模型纳入医疗保健领域， 交付流程并确定最佳方式，以告知改善医疗保健服务的机会。