Frailty Assessment in Hospitalized Older Adults Using the Electronic Health Record

被引:36
|
作者
Lekan, Deborah A. [1 ]
Wallace, Debra C. [1 ]
McCoy, Thomas P. [1 ]
Hu, Jie [2 ]
Silva, Susan G. [3 ]
Whitson, Heather E. [4 ,5 ,6 ]
机构
[1] Univ N Carolina, Sch Nursing, 409 Moore Nursing Bldg, Greensboro, NC 27402 USA
[2] Ohio State Univ, Coll Nursing, Columbus, OH 43210 USA
[3] Duke Univ, Sch Nursing, Durham, NC USA
[4] Duke Univ, Sch Med, Dept Med, Durham, NC 27706 USA
[5] Duke Univ, Sch Med, Dept Opthalmol, Durham, NC USA
[6] Durham VA Geriatr Res Educ & Clin Ctr GRECC, Durham, NC USA
关键词
frail elderly; hospitalization; electronic health record; biomarkers; risk assessment; C-REACTIVE PROTEIN; COMPREHENSIVE GERIATRIC ASSESSMENT; BLOOD-CELL COUNTS; ALLOSTATIC LOAD; COGNITIVE IMPAIRMENT; INFLAMMATORY MARKERS; RISK STRATIFICATION; ADVERSE OUTCOMES; CLINICAL FRAILTY; PROGNOSTIC VALUE;
D O I
10.1177/1099800416679730
中图分类号
R47 [护理学];
学科分类号
1011 ;
摘要
Introduction: Frailty, a clinical syndrome of decreased physiologic reserve and dysregulation in multiple physiologic systems, is associated with increased risk for adverse outcomes. Purpose: The aim of this retrospective, cross-sectional, correlational study was to characterize frailty in older adults admitted to a tertiary-care hospital using a biopsychosocial frailty assessment and to determine associations between frailty and time to in-hospital mortality and 30-day rehospitalization. Methods: The sample included 278 patients 55 years old admitted to medicine units. Frailty was determined using clinical data from the electronic health record (EHR) for symptoms, syndromes, and conditions and laboratory data for four serum biomarkers. A frailty risk score (FRS) was created from 16 risk factors, and relationships between the FRS and outcomes were examined. Results: The mean age of the sample was 70.2 years and mean FRS was 9.4 (SD, 2.2). Increased FRS was significantly associated with increased risk of death (hazard ratio = 1.77-2.27 for 3 days length of stay (LOS) 7 days), but depended upon LOS (p < .001). Frailty was marginally associated with rehospitalization for those who did not die in hospital (adjusted odds ratio = 1.18, p = .086, area under the curve [AUC] = 0.66, 95% confidence interval for AUC = [0.57, 0.76]). Discussion: Clinical data in the EHR can be used for frailty assessment. Informatics may facilitate data aggregation and decision support. Because frailty is potentially preventable and treatable, early detection is crucial to delivery of tailored interventions and optimal patient outcomes.
引用
收藏
页码:213 / 228
页数:16
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