Predicting the Risk of Severe Hypoglycemic and Hyperglycemic Events in Adults with Diabetes

预测成人糖尿病患者发生严重低血糖和高血糖事件的风险

• 批准号: 9369218
• 负责人: Rozalina Grubina McCoy
• 金额: $ 17.05万
• 依托单位: MAYO CLINIC ROCHESTER
• 依托单位国家: 美国
• 财政年份: 2017
• 资助国家: 美国
• 起止时间: 2017-08-15 至 2022-08-14
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9369218
• 关键词: Accident and Emergency department; Address; Adult; Affect; Algorithms; Big Data; Calibration; California; Caring; Chronic; Clinic; Clinical; Clinical Trials; Clinical Trials Design; Communication; Computing Methodologies; Data; Data Analytics; Data Science; Data Set; Data Sources; Databases; Decision Making; Development; Development Plans; Diabetes Mellitus; Discrimination; Economic Burden; Endocrinologist; Epidemiology; Event; Evidence Based Medicine; Face; Foundations; Frequencies; Goals; Guidelines; Health; Health Services Research; Healthcare; Heterogeneity; Hospitalization; Hyperglycemia; Hypoglycemia; Impairment; Individual; Interdisciplinary Study; Interview; Knowledge; Lead; Leadership; Learning; Machine Learning; Mentored Patient-Oriented Research Career Development Award; Mentors; Methodology; Modeling; Morbidity - disease rate; Outcome; Outcomes Research; Patient Care; Patient risk; Patients; Pattern; Physicians; Primary Care Physician; Productivity; Qualitative Methods; Qualitative Research; Quality of life; Recording of previous events; Regimen; Registries; Research; Research Infrastructure; Research Personnel; Research Proposals; Research Training; Risk; Risk Estimate; Risk Factors; Science; Scientist; Self Care; Specific qualifier value; Time; Training; Treatment Protocols; United States; Validation; Work; analytical method; base; career; career development; clinical care; data integration; data registry; diabetes management; disease phenotype; economic cost; education research; experience; glycemic control; health care delivery; health data; high risk; improved; individual patient; individualized medicine; innovation; insight; member; multidisciplinary; novel; patient oriented; point of care; predictive modeling; prevent; prospective; psychologic; psychological distress; shared decision making; skills; social; statistics; support tools; tool

PROJECT SUMMARY/ABSTRACT Dr. McCoy is an endocrinologist and primary care physician specializing in the care for patients with diabetes and other chronic health conditions. Her long-term goal is to become an independent researcher and leader in evaluating, improving, and individualizing diabetes care through effective use of big data completed by qualitative insights from patients and those involved in their care. The short-term training goals of this proposal are to acquire: 1) proficiency in statistics and data science; 2) experience in qualitative research; 3) skills in clinical trial design; and 4) communication and leadership skills to lead multi-disciplinary research. The proposal's research will be conducted at Mayo Clinic, which has a strong history of training physician scientists and a well-developed infrastructure for education and research. Dr. McCoy has access to an ideal set of data assets, the OptumLabs Data Warehouse and the Kaiser Permanente Northern California Diabetes Registry, and the support of an exceptional team of mentors and advisors who are national leaders in diabetes outcomes and health care delivery research, shared decision-making, qualitative research, and data science. Optimization of glycemic control, while avoiding severe hypoglycemia and hyperglycemia, is the cornerstone of diabetes management. Severe hypoglycemia and hyperglycemia are often preventable, yet continue to incur substantial morbidity, psychological distress, impaired quality of life, and economic burden. There are no validated tools to predict these events and as a result clinicians lack a practical and reliable means to identify high risk patients. The goal of Dr. McCoy's work is to address this critical gap in diabetes management. In Aim 1, she will use large database analysis and novel analytic methods to characterize the patterns of severe hypoglycemia and hyperglycemia among adults with diabetes in the U.S. In Aim 2, she will build on Aim 1 to develop and validate computationally efficient concurrent risk prediction models for severe hypoglycemia and hyperglycemia that could be used in clinical encounters. In Aim 3, she will directly engage patients and their clinicians in conversation about severe hypoglycemia /hyperglycemia risk in order to better understand how information about severe hypoglycemia/ hyperglycemia risk is perceived, interpreted, and used. These studies will serve as foundation for two R01 applications to be submitted during Years 4 and 5, and will advance the science and practice of personalized diabetes care through integration of data science and qualitative methods for the purpose of understanding, predicting, and ultimately preventing severe hypoglycemic/hyperglycemic events. Dr. McCoy has a proven track record of scientific productivity and innovation, and a strong foundation in using secondary data for health services and outcomes research in diabetes. In summary, the training, mentoring, and research proposed here are essential for Dr. McCoy's career development as she develops research independence and expertise in the crucial interface between patients and their clinical teams, evidence-based medicine, and big data.

项目总结/摘要 博士麦考伊是一名内分泌学家和初级保健医生，专门从事糖尿病患者的护理， 其他慢性健康问题。她的长期目标是成为一名独立的研究人员和领导者， 通过有效利用大数据，改善和个性化糖尿病护理， 患者和参与其护理的人员。本方案的短期培训目标是：1）熟练掌握 统计学和数据科学; 2）定性研究经验; 3）临床试验设计技能;以及4） 领导多学科研究的沟通和领导技能。该提案的研究将在 在马约诊所，它有一个强大的历史，培训医生科学家和发达的基础设施， 教育和研究。麦考伊博士可以访问一组理想的数据资产，OptumLabs数据仓库和 Kaiser Permanente北方加州糖尿病登记处，以及杰出导师团队的支持， 顾问谁是糖尿病的结果和卫生保健提供研究，共同决策， 定性研究和数据科学。 优化血糖控制，同时避免严重的低血糖和高血糖，是 糖尿病管理严重的低血糖和高血糖通常是可以预防的，但仍会导致 严重的发病率、心理困扰、生活质量受损和经济负担。没有经过验证的 预测这些事件的工具，因此临床医生缺乏实用可靠的方法来识别高风险 患者麦考伊博士的工作目标是解决糖尿病管理中的这一关键差距。在目标1中，她将使用 大型数据库分析和新的分析方法来表征严重低血糖的模式， 在目标2中，她将在目标1的基础上开发和验证 严重低血糖和高血糖的计算有效并发风险预测模型， 用于临床治疗。在目标3中，她将直接与患者及其临床医生进行对话， 严重低血糖/高血糖风险，以便更好地了解有关严重低血糖/高血糖的信息 高血糖风险被感知、解释和使用。这些研究将作为两个R 01的基础 申请将在第4年和第5年提交，并将推进个性化糖尿病的科学和实践 通过数据科学和定性方法的整合，以了解，预测和 最终预防严重的低血糖/高血糖事件。麦考伊博士有着良好的科研记录 生产力和创新，以及使用二级数据进行卫生服务和成果的坚实基础 糖尿病的研究总之，这里提出的培训、指导和研究对麦考伊博士的 职业发展，因为她在患者之间的关键界面上发展了研究独立性和专业知识 及其临床团队、循证医学和大数据。