The Revised Identification of Seniors At Risk screening tool predicts readmission in older hospitalized patients: a cohort study

Abstract

Abstract Background The Identification of Seniors at Risk (ISAR) screening tool is a widely-used risk stratification tool for older adults in the emergency department (ED). Few studies have investigated the use of ISAR to predict outcomes of hospitalized patients. To improve usability a revised version of ISAR (ISAR-R), was developed in a quality improvement project. The ISAR-R is also widely used, although never formally validated. To address these two gaps in knowledge, we aimed to assess the ability of the ISAR-R to predict readmission in a cohort of older adults who were hospitalized (admitted from the ED) and discharged home. Methods This was a secondary analysis of data collected in a pre-post evaluation of a patient discharge education tool. Participants were patients aged 65 and older, admitted to hospital via the ED of two general community hospitals, and discharged home from the medical and geriatric units of these hospitals. Patients (or family caregivers for patients with mental or physical impairment) were recruited during their admission. The ISAR-R was administered as part of a short in-hospital interview. Providers were blinded to ISAR-R scores. Among patients discharged home, 90-day readmissions were extracted from hospital administrative data. The primary metrics of interest were sensitivity and negative predictive value. The Area Under the Curve (AUC) was also computed as an overall measure of performance. Results Of 711 attempted recruitments, 496 accepted, and ISAR-R was completed for 485. Of these 386 patients were discharged home with a complete ISAR-R, the 90-day readmission rate was 24.9%; the AUC was 0.63 (95% CI 0.57,0.69). Sensitivity and negative predictive value at the recommended cut-point of 2 + were 81% and 87%, respectively. Specificity was low (40%). Conclusions The ISAR-R tool is a potentially useful risk stratification tool to predict patients at increased risk of readmission. Its high values of sensitivity and negative predictive value at a cut-point of 2 + make it suitable for rapid screening of patients to identify those suitable for assessment by a clinical geriatric team, who can identify those with geriatric problems requiring further treatment, education, and follow-up to reduce the risk of readmission.

Keywords

• Older adults
• Hospital
• Readmission
• Risk stratification
• Discharge planning