Developing, Validating, and Implementing a CKD Predictive Model (DELVECKD)

开发、验证和实施 CKD 预测模型 (DELVECKD)

• 批准号: 8301548
• 负责人: Khaled A Abdel-Kader
• 金额: $ 17.23万
• 依托单位: UNIVERSITY OF PITTSBURGH AT PITTSBURGH
• 依托单位国家: 美国
• 财政年份: 2011
• 资助国家: 美国
• 起止时间: 2011-08-01 至 2013-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8301548
• 关键词: Accounting; Address; Adult; Advocate; Affect; Area; Award; Behavior; Biometry; Blood; Cardiovascular system; Caring; Cessation of life; Characteristics; Charities; Chemistry; Cholesterol; Chronic; Chronic Kidney Failure; Classification; Clinic; Clinical; Clinical Decision Support Systems; Clinical Investigator; Clinical Research; Clinical Sciences; Clinical Trials; Clinical Trials Design; Cognitive; Comorbidity; Complement; Computerized Medical Record; Coupled; Creatinine; Data; Databases; Decision Analysis; Decision Trees; Development; Diagnosis; Disease; Disease Outcome; Disease model; Education; Educational Intervention; Educational process of instructing; Educational workshop; Elements; Ensure; Environment; Epidemiologic Studies; Epidemiology; Evaluation; Foundations; Funding; Goals; Guidelines; Health; Health Policy; Health Services; Health Services Research; Hemoglobin; Hospitalization; Individual; Institutes; Internal Medicine; Intervention; K-Series Research Career Programs; Knowledge; Leadership; Learning; Logistic Regressions; Medical Education; Medical Errors; Medical Informatics; Medical center; Mentors; Mentorship; Methods; Modeling; Nephrology; Outcome; Outpatients; Patient Care; Patients; Performance; Pharmaceutical Preparations; Phase; Physicians; Population; Postdoctoral Fellow; Prevalence; Primary Care Physician; Process; Provider; Public Health; Public Health Schools; Qualifying; Randomized; Randomized Controlled Trials; Recommendation; Research; Research Design; Research Infrastructure; Research Personnel; Research Project Grants; Research Proposals; Resources; Risk; Risk Assessment; Risk Factors; Sampling; Screening procedure; Sensitivity and Specificity; Serum; Staging; Testing; Time; Training; Translational Research; United States; Universities; Urine; Validation; Work; advanced disease; age related; base; biomedical informatics; care delivery; career; computer program; cost; data mining; demographics; disease diagnosis; disorder risk; experience; high risk; improved; interest; multidisciplinary; novel; novel strategies; predictive modeling; primary care setting; skills; sound; theories; treatment as usual; trend

DESCRIPTION (provided by applicant): Dr. Khaled Abdel-Kader has completed prior training in nephrology and a master's in medical education with formal training in adult learning, medical errors, and cognitive theory as well as introductory coursework in clinical research and biostatistics. His primary research interest is characterizing and addressing chronic kidney disease (CKD) care deficiencies in the primary care setting. He has received individual post-doctoral funding to support his work in this area. His career goal is to become an expert in CKD epidemiology and an independent clinical investigator studying electronic medical record (EMR)-based interventions to improve CKD care and outcomes. In this career development award (CDA), he focuses on improving primary care physician (PCP) screening for CKD. This award provides him with mentorship, formal coursework, and hands-on experience in epidemiology, research design, medical informatics, decision analysis, health services research, and biostatistics. He has assembled a group of highly skilled mentors who will guide him and help him develop into an independent clinical investigator. A supportive research environment that has already cultivated the development of numerous successful independent clinical investigators complements these individual mentors. In addition, unique institutional resources including a well-developed EMR, EMR research infrastructure, and large patient base make the local environment an ideal setting for the candidate and his research. Dr. Abdel- Kader will use these research experiences, coursework, mentorship, and institutional resources and commitment to continue his progression to becoming an independently funded clinical researcher. An important element of the application is the candidate's research proposal. He will conduct his research project in 2 phases. In the first phase, he will leverage the local, well-developed EMR database and the University of Pittsburgh's large ambulatory patient base (>450,000 unique patients in the prior 2 years) to develop a decision tree predictive model to identify patients at high risk for CKD without the use of serum chemistries. He will compare the performance of the decision tree model to a prominent, recently developed logistic regression model of CKD risk. After identifying the model with the best performance, the candidate will conduct a randomized controlled trial of PCPs examining the effect of implementing the CKD predictive model in the EMR as a clinical alert versus usual care. The clinical alert will remind PCPs to screen high-risk patients for CKD if they have not already done so. This novel approach pairs machine modeling of CKD risk factors with an EMR clinical decision support system (CDSS) to provide real-time guidance to PCPs to improve the care delivered to patients with occult CKD. This project will provide the applicant with valuable experience in data mining, medical informatics, decision analysis, health services research, and clinical trial design and implementation. These experiences will be integral to his development into an independent clinical researcher. In addition to these direct experiences, the applicant will also benefit from the teaching and guidance provided by his team of proficient mentors and consultants. Dr. Mark Unruh, primary mentor for the proposal, is a well-funded, independent clinical investigator who brings expertise in epidemiology, clinical trials, and CKD. Dr. Mark Roberts, Chair of Health Policy and Management at the University of Pittsburgh's Graduate School of Public Health, brings a strong record of independent funding and well-established research interests in predictive modeling, decision tree analysis, and CKD. Dr. Shyam Visweswaran, an investigator in biomedical informatics, brings expertise in biomedical data mining, predictive modeling, and CDSS. Dr. Charity Moore is a highly skilled health services statistician with extensive experience in clinical trials. She will bring her expertise in research design, implementation, analysis, and interpretation to the project. Dr. Gary Fischer, director of the general internal medicine ambulatory clinic, has substantial experience in the integration of the EMR and CDSS with physician workflow. Dr. Douglas Landsittel, a statistician with an interest in the classification of disease outcomes using decision trees, has extensive experience in building and validating predictive models. This interdisciplinary team combines uniquely qualified investigators with the diversity of experience and expertise necessary for the successful completion of the proposed research and the candidate's training. To complement these hands-on experiences and mentorship activities, the candidate will undertake formal coursework through the University of Pittsburgh's Graduate School of Public Health, Department of Biomedical Informatics, and the Institute for Clinical Research Education (part of the university's Clinical and Translational Science Institute). These courses will include formal training in research design and clinical trial implementation, applied medical informatics and decision analysis, and methods in health services research and biostatistics. In addition, the medical center has numerous seminars, workshops, and leadership courses that the candidate will participate in to form collaborative relationships and enhance his skills. In summary, the candidate's research interest in improving the quality of CKD care delivery coupled with a sound background in medical education and early training in clinical research make him an ideal candidate to use this CDA to investigate EMR interventions that can broadly improve CKD screening by PCPs. The applicant's experienced, multidisciplinary mentorship team, strong institutional resources and support, and the formal training he will complete under this award will ensure that he continues to develop into a successful independent clinical investigator studying methods to improve PCP care delivery to CKD patients.

描述（由申请人提供）：Khaled Abdel-Kader博士完成了肾脏学的前期培训，并获得了医学教育硕士学位，其中包括成人学习、医疗差错、认知理论以及临床研究和生物统计学的入门课程。他的主要研究兴趣是在初级保健环境中描述和解决慢性肾脏疾病（CKD）护理缺陷。他获得了个人博士后资助，以支持他在这一领域的工作。他的职业目标是成为一名CKD流行病学专家和一名独立的临床研究者，研究基于电子病历（EMR）的干预措施，以改善CKD的护理和预后。在这个职业发展奖（CDA）中，他专注于改善初级保健医生（PCP）对CKD的筛查。该奖项为他提供了在流行病学、研究设计、医学信息学、决策分析、卫生服务研究和生物统计学方面的指导、正式课程和实践经验。他已经召集了一群高技能的导师，他们将指导他并帮助他发展成为一名独立的临床研究者。一个支持性的研究环境已经培养了许多成功的独立临床研究人员的发展，补充了这些个人导师。此外，独特的机构资源，包括发达的电子病历、电子病历研究基础设施和庞大的患者基础，使当地环境成为候选人和他的研究的理想环境。Abdel- Kader博士将利用这些研究经验、课程、指导、机构资源和承诺继续他的进步，成为一名独立资助的临床研究员。申请的一个重要内容是候选人的研究计划。他的研究项目将分两个阶段进行。在第一阶段，他将利用当地发达的EMR数据库和匹兹堡大学庞大的门诊患者基础（前2年有45万名独特患者），开发一种决策树预测模型，在不使用血清化学的情况下识别CKD高风险患者。他将把决策树模型的性能与最近开发的CKD风险的逻辑回归模型进行比较。在确定表现最佳的模型后，候选人将进行pcp的随机对照试验，检查在EMR中实施CKD预测模型作为临床警报与常规护理的效果。临床警报将提醒pcp筛查CKD高危患者，如果他们还没有这样做的话。这种新颖的方法将CKD危险因素的机器建模与EMR临床决策支持系统（CDSS）相结合，为pcp提供实时指导，以改善对隐匿性CKD患者的护理。本项目将为申请人提供在数据挖掘、医学信息学、决策分析、卫生服务研究、临床试验设计与实施等方面的宝贵经验。这些经历将是他发展成为一名独立临床研究人员不可或缺的一部分。除了这些直接的经验外，申请人还将受益于他的专业导师和顾问团队提供的教学和指导。该提案的主要导师Mark Unruh博士是一位资金充足的独立临床研究者，他在流行病学、临床试验和慢性肾病方面拥有专业知识。Mark Roberts博士是匹兹堡大学公共卫生研究生院卫生政策与管理系主任，他在预测建模、决策树分析和慢性肾病方面有着强大的独立资助记录和成熟的研究兴趣。Shyam Visweswaran博士是生物医学信息学研究者，他在生物医学数据挖掘、预测建模和CDSS方面拥有专业知识。查丽蒂·摩尔博士是一位技术高超的卫生服务统计学家，在临床试验方面拥有丰富的经验。她将把她在研究设计、实施、分析和解释方面的专业知识带到项目中。普通内科门诊主任Gary Fischer博士在EMR和CDSS与医生工作流程的整合方面拥有丰富的经验。Douglas Landsittel博士是一位统计学家，对使用决策树对疾病结果进行分类感兴趣，在建立和验证预测模型方面拥有丰富的经验。这个跨学科的团队结合了独特的合格的研究人员与成功完成拟议的研究和候选人的培训所必需的经验和专业知识的多样性。为了补充这些实践经验和指导活动，候选人将在匹兹堡大学公共卫生研究生院、生物医学信息系和临床研究教育研究所（该大学临床和转化科学研究所的一部分）学习正式课程。这些课程将包括研究设计和临床试验实施、应用医学信息学和决策分析以及卫生服务研究和生物统计学方法方面的正式培训。此外，医疗中心有许多研讨会、讲习班和领导力课程，候选人将参加这些课程，以建立合作关系并提高他的技能。综上所述，候选人对提高CKD护理质量的研究兴趣，加上良好的医学教育背景和早期临床研究培训，使他成为使用该CDA研究EMR干预措施的理想人选，这些干预措施可以广泛改善pcp对CKD的筛查。申请人经验丰富的多学科指导团队，强大的机构资源和支持，以及他将在该奖项下完成的正式培训，将确保他继续发展成为一名成功的独立临床研究者，研究改善慢性肾病患者PCP护理的方法。