H. K. Weiss1, B. Cook2, B. W. Stocker1, N. Weingarten1, K. E. Engelhardt3, J. Posluszny2 1Feinberg School Of Medicine – Northwestern University,Chicago, IL, USA 2Northwestern University,Department Of Surgery,Chicago, IL, USA 3The Medical University Of South Carolina,Department Of Surgery,Charleston, SC, USA
Introduction: Screening patients for frailty is traditionally done at the bedside. This process includes screening for comorbidities, physical activity, emotional health, and nutrition. However, recent studies have attempted to identify frailty using non-bedside, electronic medical record (EMR)-based, and primarily comorbidity-focused frailty assessments. Our objective is to determine how the bedside Trauma and Emergency General Surgery (TEGS) frailty index (FI) compares to non-bedside frailty assessments in uniformity of detecting patients.
Methods: We retrospectively reviewed our quality improvement (QI) project database consisting of geriatric ( ≥65 year old ) TEGS patients. Patients were screened with the TEGS FI, a literature validated, 15-question assessment performed at the bedside, including comorbidities, physical activity, emotional health, and nutrition. We reviewed the EMR to calculate non-bedside frailty scores: the Enterprise Data Warehouse (EDW) Frailty Assessment score, a 6-point score from an EMR-based database, the NSQIP mFI-11, and the NSQIP mFI-5 (see Table 1). Based on 31% of the patients being frail as defined by the TEGS FI, a score ≥ 3 on the mFI-11 and ≥ 2 on the mFI-5 was considered frail. We compared overlap of frailty diagnoses between the four different frail groups. We then compared illness and disease severity among groups (Charlson Age-Comorbidity Index (CCI), ASA, SOFA, APACHE II, and P-POSSUM).
Results: 71 geriatric TEGS patients were included, of which 22 (31%) were frail on the TEGS FI, 24 (33%) on the EDW FI, 25 (35.2%) on the mFI-11, and 29 (40.8%) on the mFI-5. Of the patients identified as frail on the TEGS FI, only 13 patients (59%) were frail on the EDW FI, 13 patients (59%) on the mFI-11, and 15 patients (68%) on the mFI-5. Only 7 (32%) patients of the 22 frail patients identified by the bedside TEGS FI were frail by all 4 frailty assessments. When compared to the TEGS FI, illness severity scores did not differ amongst groups (ex. CCI: TEGS, 5.4; EDW, 5.1 (p=0.55); mFI-11, 5.8 (p=0.41); mFI-5, 5.6 (p=0.67)).
Conclusion: There was minimal overlap between the bedside TEGS FI and the non-bedside FIs, suggesting these various frailty scoring systems are identifying different cohorts of patients. There was no difference in traditional illness-severity scores between frail patients identified on the bedside and non-bedside FIs, suggesting no difference in disease or comorbidity between groups. The bedside and non-beside frailty assessments are both assessing for frailty, yet they are resulting in markedly differing patient populations. Larger sample size and further study analyzing clinical outcomes will help to demonstrate if there is a superior approach to identifying frailty.
