Jacques S Lee1, P Richard Verbeek1, Michael J Schull1, Lisa Calder2, Ian G Stiell2, John Trickett3, Laurie J Morrison4, Michael Nolan5, Brian H Rowe6, Sunil Sookram6, David Ryan7, Alex Kiss1, Gary Naglie8. 1. *Sunnybrook Research Institute,Toronto,ON. 2. ‡Department of Emergency Medicine,University of Ottawa,Ottawa,ON. 3. §The Ottawa Hospital Research Institute,Ottawa,ON. 4. †Division of Emergency Medicine,Department of Medicine,University of Toronto,Toronto,ON. 5. ǁCounty of Renfrew Paramedic Services,Pembroke,ON. 6. **Department of Emergency Medicine,University of Alberta,Edmonton,AB. 7. ‡‡Regional Geriatric Program of Toronto,Toronto,ON. 8. §§Department of Medicine and Rotman Research Institute,Baycrest Health Sciences,Toronto,ON.
Abstract
OBJECTIVES: We conducted a program of research to derive and test the reliability of a clinical prediction rule to identify high-risk older adults using paramedics' observations. METHODS: We developed the Paramedics assessing Elders at Risk of Independence Loss (PERIL) checklist of 43 yes or no questions, including the Identifying Seniors at Risk (ISAR) tool items. We trained 1,185 paramedics from three Ontario services to use this checklist, and assessed inter-observer reliability in a convenience sample. The primary outcome, return to the ED, hospitalization, or death within one month was assessed using provincial databases. We derived a prediction rule using multivariable logistic regression. RESULTS: We enrolled 1,065 subjects, of which 764 (71.7%) had complete data. Inter-observer reliability was good or excellent for 40/43 questions. We derived a four-item rule: 1) "Problems in the home contributing to adverse outcomes?" (OR 1.43); 2) "Called 911 in the last 30 days?" (OR 1.72); 3) male (OR 1.38) and 4) lacks social support (OR 1.4). The PERIL rule performed better than a proxy measure of clinical judgment (AUC 0.62 vs. 0.56, p=0.02) and adherence was better for PERIL than for ISAR. CONCLUSIONS: The four-item PERIL rule has good inter-observer reliability and adherence, and had advantages compared to a proxy measure of clinical judgment. The ISAR is an acceptable alternative, but adherence may be lower. If future research validates the PERIL rule, it could be used by emergency physicians and paramedic services to target preventative interventions for seniors identified as high-risk.
OBJECTIVES: We conducted a program of research to derive and test the reliability of a clinical prediction rule to identify high-risk older adults using paramedics' observations. METHODS: We developed the Paramedics assessing Elders at Risk of Independence Loss (PERIL) checklist of 43 yes or no questions, including the Identifying Seniors at Risk (ISAR) tool items. We trained 1,185 paramedics from three Ontario services to use this checklist, and assessed inter-observer reliability in a convenience sample. The primary outcome, return to the ED, hospitalization, or death within one month was assessed using provincial databases. We derived a prediction rule using multivariable logistic regression. RESULTS: We enrolled 1,065 subjects, of which 764 (71.7%) had complete data. Inter-observer reliability was good or excellent for 40/43 questions. We derived a four-item rule: 1) "Problems in the home contributing to adverse outcomes?" (OR 1.43); 2) "Called 911 in the last 30 days?" (OR 1.72); 3) male (OR 1.38) and 4) lacks social support (OR 1.4). The PERIL rule performed better than a proxy measure of clinical judgment (AUC 0.62 vs. 0.56, p=0.02) and adherence was better for PERIL than for ISAR. CONCLUSIONS: The four-item PERIL rule has good inter-observer reliability and adherence, and had advantages compared to a proxy measure of clinical judgment. The ISAR is an acceptable alternative, but adherence may be lower. If future research validates the PERIL rule, it could be used by emergency physicians and paramedic services to target preventative interventions for seniors identified as high-risk.
Authors: Matthew S Leyenaar; Brent McLeod; Aaron Jones; Audrey-Anne Brousseau; Eric Mercier; Ryan P Strum; Michael Nolan; Samir K Sinha; Gina Agarwal; Walter Tavares; Andrew P Costa Journal: CJEM Date: 2021-08-17 Impact factor: 2.410