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Use Frailty Status to Predict Postoperative Outcomes in Elderly Patient

利用虚弱状态预测老年患者的术后结果

基本信息

批准号：
9354376
负责人：
Bruce Earl Bray
金额：
$ 61.62万
依托单位：
GEORGE WASHINGTON UNIVERSITY
依托单位国家：
美国
项目类别：
财政年份：
2016
资助国家：
美国
起止时间：
2016-09-30 至 2018-08-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/9354376
关键词：
Address Affect American Atrial Fibrillation Benefits and Risks Cardiac Cardiac Surgery procedures Cardiovascular Diseases Caregivers Cessation of life Clinical Clinical Research Clinical Trials Collection Comorbidity Critical Care Data Data Sources Databases Decision Making Devices Dimensions Disease Documentation Elderly Electronic Health Record Equilibrium Fatigue Goals Health Heart failure Hospitalization Implantable Defibrillators Informatics Intervention Investigation Life Life Expectancy Malnutrition Measurement Measures Mechanics Metabolic Methods Modeling Natural Language Processing Ontology Operative Surgical Procedures Outcome Pain Patient Care Patient Selection Patient-Centered Care Patient-Focused Outcomes Patients Perioperative Population Postoperative Period Procedures Provider Quality of life Records Research Personnel Risk Technology Veterans base clinical decision-making cohort comparative effectiveness exercise capacity frailty functional status hospital readmission indexing individualized medicine interest mortality novel strategies older patient outcome forecast outcome prediction patient population predictive modeling prospective treatment choice treatment planning trend

项目摘要

Frailty is increasingly recognized as a leading indicator of poor health outcomes, even death, as well as a barometer of how well patients respond to treatment. To truly provide patient-centered care, providers should be aware of each patient's frailty status and incorporate it into clinical decision making. Providers can now offer a number of invasive and aggressive procedures for cardiovascular disease, which involve risk, and can be painful. The treatment intensity need to match the expected patient outcome, yet providers do not have a reliable method to estimate prognosis for frail patients. In the study proposed here, we will use a novel approach that leverages the electronic health record (EHR) in identifying patient frailty status, with the goal of supporting retrospective clinical studies and prospective clinical decision making. Our preliminary studies have demonstrated the availability of frailty-related findings in EHR, the feasibility of extracting frailty findings, and the feasibility of using EHR-extracted frailty for outcome prediction. The specific aims of the project are to 1) Create a frailty ontology building on existing functional status and quality of life measurements; 2) Develop ontology guided, natural language processing (NLP) methods for extracting frailty descriptions and measurements; 3) Develop a model to aggregate NLP-extracted frailty findings to generate a patient-level frailty score; 4) Examine the all-cause mortality and all-cause hospital readmission one year after major cardiac procedures in heart failure patients with different frailty scores and assess the impact of this information on surgical decision making.

虚弱越来越被认为是健康状况不佳，甚至死亡的主要指标