Using Routine Care Electronic Medical Record Data and Artificial Intelligence to Develop a Passive Digital Marker to Predict Postoperative Delirium

使用常规护理电子病历数据和人工智能开发被动数字标记来预测术后谵妄

• 批准号: 10449523
• 负责人: Sanjay Mohanty
• 金额: $ 12.61万
• 依托单位: INDIANA UNIV-PURDUE UNIV AT INDIANAPOLIS
• 依托单位国家: 美国
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-09-01 至 2027-06-30
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10449523
• 关键词: Active Learning; Acute; Age; Aging; Alzheimer' s Disease; Alzheimer' s disease model; American; Artificial Intelligence; Attention; Award; Cardiopulmonary; Cardiovascular system; Clinical Sciences; Cognition; Cognitive; Computerized Medical Record; Data; Databases; Delirium; Dementia; Detection; Development; Development Plans; Diagnosis; Disease; Dropout; Elderly; Electronic Health Record; Enrollment; Environment; Funding; Future; Goals; Health; Health system; Healthcare; Hospitals; Impaired cognition; Indiana; Informed Consent; Institutes; International; Intervention; K-Series Research Career Programs; Length of Stay; Machine Learning; Medical Informatics; Mentors; Methods; Modeling; Operative Surgical Procedures; Outcome; Patient Care; Patients; Performance; Perioperative; Physiological; Polypharmacy; Postoperative Period; Preparation; Prevention; Process; Psychiatric Diagnosis; Randomized Clinical Trials; Randomized Controlled Clinical Trials; Randomized Controlled Trials; Recovery of Function; Reproducibility; Research; Research Personnel; Research Project Grants; Risk; Risk Factors; Senior Scientist; Structure; Surgical complication; Survivors; Syndrome; System; Techniques; Testing; Text; Time; Translational Research; United States National Institutes of Health; Universities; acceptability and feasibility; advanced analytics; brain health; career; career development; clinical decision support; cognitive disability; cognitive enhancement; cognitive recovery; cohort; comorbidity; cost; design; digital; digital models; efficacy evaluation; efficacy trial; feasibility testing; frailty; functional decline; functional disability; functional status; health data; high risk; implementation science; improved; machine learning algorithm; mortality; multi-component intervention; multidisciplinary; nutrition; older patient; patient oriented; postoperative delirium; predictive modeling; prevent; prospective; research study; risk prediction; risk stratification; routine care; screening; support tools; usability

PROJECT SUMMARY Postoperative delirium is among the most common complications following elective surgery. Delirium is associated with prolonged lengths of stay, functional decline, cognitive impairment, higher costs, and higher mortality. This proposal describes a career development plan that will transform Dr. Mohanty into a patient- oriented investigator focused on improving the perioperative brain health of every older American undergoing major surgery. Dr. Mohanty’s proposed project will involve merging the data of more than 35000 patients who underwent major surgery in a statewide health system with electronic health record (EHR) data from the Indiana Network for Patient Care (INPC), a Regional Health Information Exchange. Using this merged database, the candidate will develop and test a passive predictive model (“digital marker”) for postoperative delirium risk using routine care EHR data, including unstructured, free text notes, and a machine learning algorithm. This “digital marker” will then be tested in a pilot randomized clinical trial in preparation for a large efficacy trial which will evaluate the impact of this scalable “digital marker” on short and long-term cognitive outcomes. The proposed career development plan integrates: close mentoring from a multidisciplinary team of senior scientists; coursework and structured didactics in medical informatics, including advanced analytics, artificial intelligence, and clinical decision support; implementation science; experiential learning via the conduct of the proposed research project; and a supportive research environment. This environment includes an internationally recognized NIH-funded delirium study group, the distinguished Indiana University Center for Aging Research, the NIA-funded Indiana Alzheimer’s Disease Center, and the NIH-funded Indiana Clinical and Translational Sciences Institute (CTSI). This career development award will guarantee protected time that will be necessary to advance the candidate’s career in perioperative brain health. In addition, the award will provide critical support to collect data for a future R01 efficacy randomized controlled trial.

项目摘要 术后del妄是最常见的综合性。 与长时间的住院时间，功能下降，认知障碍，更高的成本和更高的相关 死亡率。 注重的研究人员致力于改善围手术期的大脑健康，美国老年人正在进行 Mohanty博士的主要手术将涉及更多 通过您的电子健康记录（EHR）数据进行了全州卫生系统的大手术 印第安纳州患者护理网络（INPC），区域健康信息交换。 数据库，候选人将开发和测试术后的被动预测模型（“数字标记”） 使用常规护理EHR数据的ir妄风险，包括非结构化的免费文本注释和机器学习 算法。 功效试验将评估这种可扩展的“数字标记”对短期和长期认知的影响 结果。 支撑的职业发展计划集成：高级多学科团队的密切指导 科学家; 智能和临床决策支持； 支撑研究和支持性研究环境 国际公认的NIH资助的ir妄研究小组，杰出的印第安纳大学中心 老化研究，NIA资助的印第安纳州阿尔茨海默氏病中心和NIH资助的印第安纳州临床 转化科学研究所（CTSI）。 还必须在围手术期的大脑健康方面提高候选人的职业。 提供关键的支持，以收集未来R01功效随机对照试验的数据。