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Informatics approaches to assessing patient frailty in surgical care

评估外科护理中患者虚弱程度的信息学方法

基本信息

批准号：
10652340
负责人：
Elizabeth Marjorie Cespedes Feliciano
金额：
$ 58.85万
依托单位：
KAISER FOUNDATION RESEARCH INSTITUTE
依托单位国家：
美国
项目类别：
财政年份：
2020
资助国家：
美国
起止时间：
2020-09-01 至 2025-05-31
项目状态：
未结题

来源：
https://reporter.nih.gov/project-details/10652340
关键词：
Abdomen Acute Address Age Aging Algorithms American Biological Caring Chronic Disease Chronology Clinical Code Complex Computer software Consumption Counseling Data Data Set Decision Making Diagnostic Elderly Electronic Health Record Electronics Exhibits Future Goals Hospital Costs Hospital Mortality Hospitals Infiltration Informatics Intervention Laboratories Length of Stay Manuals Measures Methodology Modeling Morbidity - disease rate Muscle Muscular Atrophy National Institute on Aging Operative Surgical Procedures Pathway interactions Patient-Focused Outcomes Patients Performance Perioperative Perioperative Care Physical Function Physiological Population Population Heterogeneity Postoperative Period Predictive Value Process Research Risk Risk Factors Scanning Severity of illness Skeletal Muscle Standardization Surgical complication Technology Time Validation X-Ray Computed Tomography adverse outcome clinical care computer science cost digital electronic data frailty functional status high risk hospital readmission improved innovation inpatient surgery mortality muscle form older patient patient response performance tests postoperative recovery predictive modeling profiles in patients programs prospective risk stratification sarcopenia secondary analysis shared decision making stressor surgery outcome surgical risk tool

项目摘要

ABSTRACT Surgical complications are common, costly, and deadly. Older patients are at high risk of adverse surgical outcomes, especially when they exhibit frailty. Frailty is a state of decreased physiologic reserve and loss of capacity to adapt to stressors. Over the past decade, while frailty has been increasingly recognized as an important risk factor for poor surgical outcomes, integration of a standardized frailty metric into clinical care has not been achieved. A key barrier is that existing frailty assessments are not standardized, objective, or widely available, limiting their routine application in surgical decision-making. With the long-term goal of improving surgical care for older adults, we will evaluate two “e-frailty” metrics that can be automatically derived from electronic or digital data that are already collected as part of routine clinical care. These e-frailty metrics include, first, granular patient profiles of electronic health record (EHR) data (risk scores based on claims data or on physiologic and laboratory values), and second, muscle loss assessed from pre-surgical computed tomography (CT) scans (low skeletal muscle mass, known as sarcopenia, and fatty infiltration into muscle indicative of reduced physical function, known as myosteatosis). In Aim 1, we will calculate these two e-frailty metrics among a diverse population of over 41,000 abdominal surgical patients; characterize the overlap between patients designated as frail by the two e-frailty metrics; and evaluate their associations with 30-day readmission and other adverse surgical outcomes (30-day and 1-year mortality, complications, non-home discharge, and length of stay >7 days). In Aim 2, we will compare the performance of e-frailty metrics for predicting 30-day readmission and other adverse surgical outcomes to that of standard risk stratification tools (acute and chronic illness severity metrics) already embedded in EHRs today using cross-validation and an independent validation dataset of over 14,000 more recent abdominal surgeries. In Aim 3, we will examine whether e-frailty metrics modify the benefits that patients derive from achieving postoperative targets -including early and sustained mobilization- in one of the largest Enhanced Recovery After Surgery (ERAS) programs in the nation. We will examine e-frailty metrics as salient indicators of biologic age for predicting morbidity and mortality. In sum, e-frailty metrics show great promise for identifying high-risk patients in the surgical domain, but they need to be integrated within clinical workflows to be scalable and sustainable. This proposal will compute standardized e-frailty metrics automatically derived from EHR data and provide new information regarding the potential value of these e-frailty metrics for improving surgical care for older adults. This study will also lay the groundwork for future prospective interventions integrating e-frailty metrics into clinical care to improve risk stratification and counseling of patients considering surgery and enhance perioperative care for frail surgical patients.

摘要